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Speaker 1: You're listening to a podcast from News Talk zed B.

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Speaker 1: Follow this and our wide range of podcasts now on iHeartRadio.

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Speaker 2: Hello you, great New Zealanders. Welcome to Matt and Tyler

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Speaker 2: Full Show Podcast number one two nine for Wednesday, the

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Speaker 2: twenty first of May twenty twenty five. Fantastic show. At

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Speaker 2: one point some guy called Josh got angry because something

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Speaker 2: to do with the edmund of how we're running our show.

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Speaker 2: But apart from that, it was a very pleasant after noon.

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Speaker 2: He was I think he'd been drinking yep. But we

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Speaker 2: had some fantastic chats about AI and people sticking up

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Speaker 2: for their jobs and people that are worried about what

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Speaker 2: was happening with AI.

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Speaker 3: Very interesting, very.

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Speaker 2: Interesting stuff about farms, and yeah, that chat went really

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Speaker 2: well around around the guy yelling abuse at Winston Peter's

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Speaker 2: tell you what, there was fifty to fifty down the middle,

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Speaker 2: but some great calls on that as well. So I

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Speaker 2: really enjoyed the show today and I hope you do

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Speaker 2: as well.

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Speaker 3: Exactly, And of course Mark Vitti the animal behaviorist, and

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Speaker 3: we talked a lot about octopi.

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Speaker 2: Yeah, oh boy, we learned more about octopi or octopus

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Speaker 2: or Octopussy.

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Speaker 4: Then you're likely to learn anywhere else today.

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Speaker 3: So look out for that download, subscribe, give us a review.

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Speaker 3: All that good stuff and we will see you soon.

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Speaker 1: The big stories, the legal issues, the big trends, and

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Speaker 1: everything in between. Matt Heath and Tyler Adams Afternoons news

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Speaker 1: Talk said, be.

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Speaker 3: Good afternoon. Welcome into the show, you good people. Hope

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Speaker 3: you're having a great day. Happy Wednesday.

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Speaker 2: Get a map, get a Tyler gooda all your great

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Speaker 2: New Zealanders. We've cobbled together a half decent show for

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Speaker 2: you over the next three hours. I believe some good topics.

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Speaker 2: But first, Tyler, Yeah, a few weeks ago on all

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Speaker 2: products were brought up. Yeah, and I mentioned the greatest

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Speaker 2: socks of all time. You did, and for winter, I

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Speaker 2: absolutely recommend these socks. So I went off and ordered

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Speaker 2: like six pairs of these socks. Yeah, norsewhere people from

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Speaker 2: where I come from in the South will know all

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Speaker 2: about norsewere So I ordered some Norseware socks.

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Speaker 4: They've arrived.

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Speaker 2: I got someone now and I'm so happy that the

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Speaker 2: socks are just so comfortable, that comfortable they fill me

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Speaker 2: with joy. So I got you a pair of socks, Tyler.

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Speaker 3: Oh, mates, and they washed them. Oh they're still in

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Speaker 3: their packaging.

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Speaker 2: Okay, it's good, yep, And I assume what what have

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Speaker 2: you got size six feet?

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Speaker 3: I'm sure, I'm sure we could find someone with size

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Speaker 3: six feet those in the morning.

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Speaker 2: I got you a pair of large norsewear socks, very

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Speaker 2: much mate, as a present.

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Speaker 3: He's just thrown them across the room people, but let

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Speaker 3: me just grab them.

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Speaker 2: Yeah, so this I mean like Norse. We aren't giving

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Speaker 2: us any money for this, or me any money for this.

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Speaker 2: I'm just such a fan of those socks. Is just

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Speaker 2: when you pull them on in the morning, they just

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Speaker 2: fill you full of joy because they're not they're soft,

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Speaker 2: but they're also real. So there's there's just a tiny

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Speaker 2: just the tiny, it's most satisfying little bit.

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Speaker 3: Of Scott great heel on a really nice petted heeled.

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Speaker 4: Quality full wall socks.

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Speaker 3: That is a quality sock. Yeah, thank you very much, mate,

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Speaker 3: And thank you to the company as well.

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Speaker 2: If you're listening, well, we don't think the company I

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Speaker 2: paid for them, then I thank you to the company.

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Speaker 3: Thinking the designer.

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Speaker 2: You know, this is thank the company for their fantastic

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Speaker 2: product and their attention to quality.

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Speaker 4: Fan bas but I paid.

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Speaker 3: For them, and if you are listening and you want

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Speaker 3: to give us some more socks, we're not going to

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Speaker 3: say no to that, you know. I think we've made

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Speaker 3: it pretty clear on the show that we will take

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Speaker 3: free things from good companies.

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Speaker 4: Well, there you go. Well, I'll look forward to your

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Speaker 4: review of those socks have given you.

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Speaker 3: Thank you very much. 'll put them on very short.

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Speaker 2: Of course, you've just moved up from South Island, so

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Speaker 2: you're probably going through that phase where you think it's

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Speaker 2: really really warm even though it's getting into winter and.

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Speaker 3: Auckland it did feel nippy today actually at thirteen degrees.

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Speaker 3: Well I've changed, man, I've changed right on to today's show.

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Speaker 3: After three o'clock, How long could you go without the Internet?

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Speaker 3: Many people freaking out last night after thousands lost internet

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Speaker 3: and what appeared to be quite a large outage up

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Speaker 3: and down the country.

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Speaker 2: Are you doing internet detoxes in your house to make

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Speaker 2: sure that you can operate as a household without the

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Speaker 2: internet and that your kids aren't so addicted to the

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Speaker 2: Internet that they'll go completely insane without it in two hours?

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Speaker 5: Yep?

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Speaker 3: Have you ever done it yourself? Just switched off the

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Speaker 3: old router yeah, yep.

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Speaker 2: Yep, No, I'll come off and off the internet. I'm

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Speaker 2: not a weak person. I'm powerful. And when I say

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Speaker 2: I'm off and off. I was on a TV show

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Speaker 2: called Traitors where we were taken away to a mens

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Speaker 2: and we had our phones taken off us. I'll tell

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Speaker 2: you what when that happened to me. When I had

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Speaker 2: those away in the mansion shooting this reality show, I

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Speaker 2: quickly got over my phone and actually enjoyed it. The

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Speaker 2: only thing is I couldn't contact my kids, so there

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Speaker 2: was a bit weird having no contact with my kids.

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Speaker 3: That would be a big thing.

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Speaker 2: Yeah, but I felt so good and I felt that

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Speaker 2: everything getting better in my life. But then when I

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Speaker 2: got back in the car and I was being driven

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Speaker 2: back to Auckland, I opened my phone.

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Speaker 4: It just started going bing bing bing bing bing bing

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Speaker 4: bing bing bing bing. Men, I was right back in there.

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Speaker 3: Yeah, there's going to be a good chet. That's after

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Speaker 3: three I've done it again. I forgot about three thirty.

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Speaker 3: A very special guest asked the experts, because it is

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Speaker 3: a Wednesday, and Mark Vetti will be back with us

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Speaker 3: animal behaviorist and he is incredible at what he does.

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Speaker 3: So if you've got a problem with your pet he

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Speaker 3: is the man to chat to after three point thirty

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Speaker 3: after two o'clock. What power does your employer have over

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Speaker 3: you when it comes to in this case, heckling politicians.

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Speaker 2: Yeah, you've all seen the footage of a person that

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Speaker 2: seems to me like they're spending too much time on

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Speaker 2: the internet and have been distorted and flipped around and

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Speaker 2: driven crazy by the algorithm. By the way, this man

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Speaker 2: was screaming at Winston Peters in quite a crazy way.

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Speaker 2: He lost the he lost the interaction with Winston Peter's

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Speaker 2: got absolutely owned because you know, Winston Peter's is.

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Speaker 4: Very very sharp.

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Speaker 2: But his employee employer Tonkin and Taylor have apologized for

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Speaker 2: him and they're doing an investigation into it. So the

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Speaker 2: question is, should you be allowed to express your opinions

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Speaker 2: offensively outside work?

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Speaker 4: And you know, how much does your job own your

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Speaker 4: expression or should it?

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Speaker 2: I mean, you probably have signed most of us have

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Speaker 2: signed a content that we won't bring our workplaces into disrepute.

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Speaker 2: And should we be campaigning for this guy to lose

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Speaker 2: his job as some people are, or is that just

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Speaker 2: lame and let him act like that in public? And

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Speaker 2: that's up to Tonkin and Taylor if they think he's

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Speaker 2: a cool guy to be working around the office.

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Speaker 3: Yeah, nice, he said. That's after two o'clock. But right now,

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Speaker 3: let's have a chat about artificial intelligence and whether you

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Speaker 3: have concerns it will take your job. Do you think

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Speaker 3: your job can or can't be replaced by artificial intelligence?

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Speaker 3: Bill Gates said in a recent article that he thinks

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Speaker 3: AI will replace pretty much every job and every industry

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Speaker 3: from apart from three different fields.

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Speaker 4: Yeah, that's right.

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Speaker 2: So he thinks that doctors and teachers are under threat.

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Speaker 2: On hangeman, have I got this wrong? Doctors and teachers

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Speaker 2: among professions most vulnerable to AI replacement, according to Bill Gates, Yeah,

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Speaker 2: I did get it right, because the only reason why

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Speaker 2: I question is because it seemed crazy, Because I think

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Speaker 2: teachers are very valuable, not just in teaching people facts

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Speaker 2: and you know the education, you know, maths or English

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Speaker 2: or whatever, but the social teaching that they do and

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Speaker 2: the interaction they have with human especially in primary school

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Speaker 2: and an intermediate school. And I would say even in

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Speaker 2: you know, the first few years of high school as well.

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Speaker 2: Your primary role of socializing humans to be members of society. Right, Yeah,

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Speaker 2: So I think it's very odd that he's picked out

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Speaker 2: teachers specifically, And I'd also say the same thing for doctors,

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Speaker 2: and that you can you know, you can find the prescription.

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Speaker 2: Maybe AO can do that, but there's a lot of

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Speaker 2: sort of low key counseling that a doctor does when

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Speaker 2: you go and see the doctor. There's an empathy that's

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Speaker 2: needed in that case.

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Speaker 3: I would agree. I think that's the only advantage that

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Speaker 3: we've got over AI at the moment, and increasingly so

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Speaker 3: as the technology develops, is that human connection and empathy

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Speaker 3: and EQ those things you talked about. But the three

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Speaker 3: jobs he mentioned was biologist, so the study of biology.

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Speaker 3: He doesn't think AI can take over that. He said

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Speaker 3: energy experts, which I thought was a strange one, but

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Speaker 3: he thinks you still need the human capacity to analyze

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Speaker 3: energy needs and what to next. He thinks that's beyond

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Speaker 3: the scope of AI at the stage. And then developers,

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Speaker 3: so people that actually make AI in the first place.

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Speaker 1: Yeah.

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Speaker 2: Look, Bill Gates is basically an evil AI himself, So

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Speaker 2: I wonder he doesn't think teachers and doctors do anything

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Speaker 2: more than teach and prescribe. You know, I wouldn't trace

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Speaker 2: trust Bill Gates with too much, but it is interesting

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Speaker 2: and look, we are seeing it now.

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Speaker 6: You know.

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Speaker 4: You look at Spark and there were claims just yesterday

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Speaker 4: that Spark were outsourcing some of their jobs and a

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Speaker 4: source claimed that two hundred jobs could be lost and

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Speaker 4: replaced by AI and overseas workers.

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Speaker 3: Yeah, I mean it is happening very fast, isn't it.

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Speaker 3: And a lot of experts that you listen to in

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Speaker 3: the realm of AI are saying that many, many jobs

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Speaker 3: will go and they'll go pretty fast.

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Speaker 7: Yeah.

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Speaker 2: Well, one hundred and eighty ten. Do you feel like

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Speaker 2: your job is safe? Is this something that you do

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Speaker 2: that you do not believe AI can do? And or

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Speaker 2: is your job under threat from AI? Or have you

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Speaker 2: already lost your job to AI? Eight hundred and eighty

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Speaker 2: ten eighty.

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Speaker 3: Let's get into what it is. Fourteen past one you're

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Speaker 3: listening to Matt and Tyler back very shortly.

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Speaker 2: Hi, guys, I seend my son in Perth, norsewear socks

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Speaker 2: every year and he loves them.

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Speaker 4: From Anna Bless Go norsewere.

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Speaker 1: The big stories, the big issues, the big trends, and

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Speaker 1: everything in between. Matt Heath and Taylor Adams afternoons used

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Speaker 1: talks that'd be very good afternoon, Jude seventeen past one.

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Speaker 3: Do you think AI can take your job or can't

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Speaker 3: take your job? Love to hear from you on OZ

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Speaker 3: one hundred and eighty ten eighty This.

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Speaker 2: Texas is radio talkback hosts under serious AI replacement threat.

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Speaker 2: Host and callers will be AI. That's an interesting idea,

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Speaker 2: and people do point out that seems to be happening

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Speaker 2: quite a lot on social media. When you drill down

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Speaker 2: on what's going off on it's off an AI arguing

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Speaker 2: with itself.

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Speaker 3: Yeah.

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Speaker 2: Bots that designed to respond to certain cues, and so

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Speaker 2: they just go back and forth, back and forth, back

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Speaker 2: and forth, and you can have there has been, you know,

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Speaker 2: part of the dead Internet theory that people have found

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Speaker 2: conversations and arguments that have been going for years just

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Speaker 2: between AI bots humans have long since left.

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Speaker 3: Yeah, yeah, exactly.

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Speaker 4: Oh.

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Speaker 3: One hundred and eighty ten eighty is the number to call. Georgie. Hello,

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Speaker 3: nice to chat with you. So you don't think your

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Speaker 3: job could be replaced by artificial intelligence?

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Speaker 4: What is your job, Georgie?

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Speaker 8: I am an embarna Ah, I love the deceased.

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Speaker 4: Wow. So you work for a funeral home? Yes, wow, Yeah,

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Speaker 4: I'm just trying to think. Yeah, no, not at this

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Speaker 4: stage your spot on.

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Speaker 3: Actually, I mean that is obviously a job that requires physicality,

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Speaker 3: but also a fear, well a lot of empathy as well.

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Speaker 8: Yeah, like because I'm mostly in the moltary side of things,

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Speaker 8: Like it's very spone anatomy chemistry.

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Speaker 4: Yeah.

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Speaker 9: Yeah.

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Speaker 2: So do you do you have any client facing part

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Speaker 2: of it? Do you talk to the families at all?

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Speaker 9: No?

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Speaker 8: No, not at all.

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Speaker 2: Yeah. So just to get to some of the details

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Speaker 2: of your job. So when you say embalming, where does

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Speaker 2: that start and how far.

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Speaker 4: Does it go?

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Speaker 8: As in what we do basically my way are sanitizing

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Speaker 8: and preserving the bodies or families if it makes any

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Speaker 8: sense to be viewable. And it's just I can't see

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Speaker 8: AI taking over doing that, yeah, because it's a lot

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Speaker 8: of work.

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Speaker 4: Yeah, But I mean, you know, they're saying there's some

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Speaker 4: people that say that open heart surgery will be able

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Speaker 4: to be done by doctors by within the next five years,

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Speaker 4: are unassisted by a human you know, some people are

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Speaker 4: claiming that. People claim all kinds of things, But I

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Speaker 4: guess the variation of what you're doing, You've got to

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Speaker 4: make a whole lot of a whole lot of decisions,

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Speaker 4: and the decisions on you know, esthetic decisions, aren't they

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Speaker 4: what looks right?

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Speaker 8: Yeah, Like it's just every single person is different as well,

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Speaker 8: like when they come in, like there is may be

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Speaker 8: someone that's got jaunder, the maybe someone with ADMA, like

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Speaker 8: and it's just every single case is always different what

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Speaker 8: we have to deal with. So it's like, I don't

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Speaker 8: know AI can play pick that up straight.

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Speaker 2: Away, And I wonder if families would want that to

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Speaker 2: be done by AI and robots not at all for me,

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Speaker 2: I would you know, imagine, Yeah, I'd like to imagine

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Speaker 2: that a human's doing that, And.

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Speaker 3: Yeah, I agree, that would be the big thing for me, Georgia.

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Speaker 3: You know, whether there would ever be technology that could

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Speaker 3: come into play and do that job. The very fact

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Speaker 3: that I wouldn't want artificial intelligence to do it to

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Speaker 3: me would say that your job it's safe for a

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Speaker 3: long long time hopefully.

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Speaker 9: Yeah, for sure.

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Speaker 8: I mean, like I wouldn't want my own family and

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Speaker 8: artificial intelligence. It's just so disconnected.

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Speaker 2: Yeah, how that begs a question, Georgie, would you embalm

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Speaker 2: members of your family?

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Speaker 4: Are you allowed to do that? Is there any ethical

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Speaker 4: side to it? And that in that realm, No, we are.

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Speaker 8: Allowed to Like for me personally, I can't do it. Yeah,

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Speaker 8: and I've never done it and I've been doing it

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Speaker 8: for like twelve years.

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Speaker 4: Yeah right, And is it rewarding work.

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Speaker 8: I'm still doing that, yeah.

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Speaker 2: Yeah, and it's not How what sort of reaction do

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Speaker 2: you get to that when you bring up around I

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Speaker 2: don't know, a dinner table or you know, a dinner party.

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Speaker 4: What you do?

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Speaker 1: What?

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Speaker 9: What?

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Speaker 4: What sort of reaction do you get?

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Speaker 8: Well, strangers, they're like.

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Speaker 9: Hey, for the how I look.

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Speaker 3: It must be very specialized Georgie.

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Speaker 9: Yeah.

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Speaker 2: Yeah, So how long's the training for the for to

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Speaker 2: become an Obama?

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Speaker 8: And like people have helped train in the past, that

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Speaker 8: takes a few months before they're up and running on

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Speaker 8: their own. But I mean it's all comes with time,

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Speaker 8: the experience.

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Speaker 4: Yeah, as well. Is there a course that you do?

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Speaker 4: Is there a degree or anything?

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Speaker 1: Yeah?

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Speaker 8: I'm just about finishing and am I doing my diploma

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Speaker 8: in it?

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Speaker 10: All right?

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Speaker 2: And you've been been working professionally in the business for

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Speaker 2: twelve years.

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Speaker 8: Yeah, But they got rid of the PLOTMA for a

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Speaker 8: while and then just coming up in the last two years. Okay,

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Speaker 8: I'm going to finally do this.

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Speaker 4: Is there decent pain in being in Obama? You just

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Speaker 4: gotta love what you do nicely see, well, thank you.

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Speaker 4: So there you go.

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Speaker 2: Georgie thinks that she will not be replaced by AI,

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Speaker 2: and I'm trying to picture that. But then again, you

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Speaker 2: could argue a lot and that there would have been

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Speaker 2: a time in.

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Speaker 4: The fifties where they thought that a car wash I know,

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Speaker 4: it's kind of different. I'm just trying to think of it.

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Speaker 2: Example, you go, there's no way that washing a car

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Speaker 2: could be replaced by robots. But we get you know, yeah,

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Speaker 2: it happens every day now.

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Speaker 3: But there's some jobs that I'm happy to pay a

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Speaker 3: little bit more for because you know, in embalming would

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Speaker 3: probably be right up there. You know that even if

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Speaker 3: I can get it cheaper, even a AI do it.

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Speaker 3: I just I don't know this.

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Speaker 2: Texas says, try a placing my job as a gardener

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Speaker 2: with AI. Good luck gates your knob.

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Speaker 3: Yeah yeah, well I don't know, Like, you know, could

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Speaker 3: you get in the near future a robot to come

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Speaker 3: and pull your weeds? I think that's definitely feasible.

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Speaker 2: Well no, but I think the thing is there's a

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Speaker 2: lot of decisions that need to be made esthetically. I mean,

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Speaker 2: it's very hard for us to get our heads around

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Speaker 2: what AI can do and what it can't do. So

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Speaker 2: you're bringing in, you know, the large language models. You've

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Speaker 2: got that part of it as well. But then there's

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Speaker 2: a physical part of it. You know, there's the robotic

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Speaker 2: part of it. And now you know you're looking at

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Speaker 2: you know, Boston Dynamics, and you're looking at those new.

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Speaker 4: Tesla pots and stuff. And I've seen some of the

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Speaker 4: footage of the chef.

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Speaker 2: Yeah, and you know, they're getting more and more delicate

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Speaker 2: with their fingers and their ability to interact with the

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Speaker 2: world is getting better and better. So you know, sometimes

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Speaker 2: can it just scan a garden and go a garden

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Speaker 2: should look like this, and then make it look like

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Speaker 2: what they think it should look.

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Speaker 3: Like a oh, one hundred and eighty ten to eighty.

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Speaker 3: Are you concerned that artificial intelligence may take your job?

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Speaker 3: Or if you've been in a position we've been let

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Speaker 3: go because the company has decided to go with AI,

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Speaker 3: we're really keen to have a chat with you. Spark

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Speaker 3: very earlier this week has made that exact call. Sources

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Speaker 3: have told The Herald that up to two hundred jobs

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Speaker 3: could be replaced by workers in India and artificial intelligence.

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Speaker 3: That is a massive change for that company.

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Speaker 4: This text from Jordan's is interesting.

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Speaker 2: I think a robot could prepare a body almost with

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Speaker 2: less ethical problems than a human being. We keep hearing

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Speaker 2: of these horror stories of people abusing the bodies and

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Speaker 2: being disrespectful or tipping them in a hole later to

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Speaker 2: score cash. Weird stuff happening. Yeah, I mean where there

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Speaker 2: is humans.

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Speaker 4: There is a possibility for weird stuff to go down.

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Speaker 3: Yeah, very true. Oh, e one hundred and eighty ten

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Speaker 3: eighty is the number to call. It's twenty five past one.

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Speaker 1: Putting the tough questions to the news speakers, the mic Hosking, Breakfast.

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Speaker 11: Winston Peters as well as My understanding is the Golden

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Speaker 11: visas working in the is interest. The Prime Minister told

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Speaker 11: us on Monday that you had discussions and they came

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Speaker 11: up to five or six million dollars next to no

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Speaker 11: houses in this country as sold at five or six

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Speaker 11: million dollars. Let them buy a place, invest in the

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Speaker 11: country and get.

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Speaker 4: On with it.

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Speaker 12: We have not got that rigid view and the Prime

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Speaker 12: Minister should not be discussing our negotiations with you.

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Speaker 11: Well, all I did was asking a question as to

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Speaker 11: what the hold up? And you set the hold up

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Speaker 11: to you and you're having a negotiation. I just don't

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Speaker 11: understand the logic. I get your logic around say two million.

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Speaker 11: I understand that I have time to run a radio

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Speaker 11: program in the country, for God's sake. But this seems

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Speaker 11: to me that you're not far apart. Why can't you

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Speaker 11: sort it and just get on with it? Back tomorrow

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Speaker 11: at six am the Mic Hosking Breakfast with the Rain

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Speaker 11: drove of Alame News talk z B.

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Speaker 3: Very good afternoon to you, and we're talking about artificial

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Speaker 3: intelligence and do you think AI can do your job?

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Speaker 3: And if you don't think it can do your job,

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Speaker 3: would love to hear from you. I would love to

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Speaker 3: hear from you on both sides one hundred eighty eight.

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Speaker 3: But if you if you don't think it can take

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Speaker 3: your job?

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Speaker 2: Why, yeah, all right, let's go to eleanor you're a midwife.

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Speaker 13: Yes, I'm a midwife and electation consultant. I can't see

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Speaker 13: any woman wanting AI to deliver their baby. Yeah, I

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Speaker 13: do think they can make the rapid decisions and intubate

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Speaker 13: and give emergency drugs and future and bung a canular

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Speaker 13: in quickly. For an IV it's very complex sometimes. And

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Speaker 13: then for breastfeeding, I mean, who would want what.

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Speaker 14: Would it be?

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Speaker 13: What's sitting on telling you what to do when you

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Speaker 13: don't know what to do? And handling, I mean we

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Speaker 13: examine babies and we we work out what's going on

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Speaker 13: with them by very detailed physical examination, handling them, feeling

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Speaker 13: their toe, checking their reflexes, things like that.

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Speaker 4: Very comic.

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Speaker 13: Ever see anything like that being done by AI. Well

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Speaker 13: it might have all the intelligence, all the all the

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Speaker 13: answers to everything, but can it ask the right questions?

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Speaker 2: Well, the thing is, you know, and you know, maybe

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Speaker 2: it can be there as another tool for a midwife

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Speaker 2: to so so you know, it's that, you know, the

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Speaker 2: midwife's asking questions of AI and pumping and the information.

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Speaker 4: That they see.

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Speaker 2: Would do you find that more people are looking at

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Speaker 2: having home births now eleanor than was in the past,

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Speaker 2: Because I was thinking that it seems to me, you know,

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Speaker 2: maybe this is just the circles. I'm maybe it's just

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Speaker 2: the circles, i'mond but seems that seems to be a

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Speaker 2: move away from from the high tech berths.

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Speaker 9: Not in my area.

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Speaker 13: I'm sort of up on a high Discus Coast and

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Speaker 13: we've got I'd see people regularly who've had a home birth.

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Speaker 13: I had home birth myself or one of mines. There

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Speaker 13: are little pockets where there's very high rates of home birth. Well,

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Speaker 13: Heky Island still has plenty, and West Coast on the

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Speaker 13: South Island on mainland.

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Speaker 2: And well why do people have part of my ignorance,

444
00:20:27,493 --> 00:20:31,013
Speaker 2: but why do people have home births? When you know

445
00:20:31,053 --> 00:20:34,173
Speaker 2: in a hospital, if something goes wrong, everything is there.

446
00:20:34,453 --> 00:20:36,493
Speaker 2: And I remember one of my when one of my

447
00:20:36,573 --> 00:20:39,293
Speaker 2: children was being born, everything went wrong, and I was

448
00:20:39,333 --> 00:20:41,813
Speaker 2: just so pleased to be somewhere where they could just

449
00:20:41,933 --> 00:20:44,253
Speaker 2: the hospital could bring so many resources, and it looked

450
00:20:44,253 --> 00:20:46,853
Speaker 2: like they deployed what loocked to me like ten million

451
00:20:46,893 --> 00:20:50,413
Speaker 2: dollars worth of equipment onto my son and and I

452
00:20:50,493 --> 00:20:51,653
Speaker 2: was so grateful for it.

453
00:20:51,813 --> 00:20:53,773
Speaker 4: So what what the advantage?

454
00:20:53,813 --> 00:20:58,853
Speaker 13: And the advantage is the woman feels a lot more comfortable,

455
00:20:58,893 --> 00:21:03,693
Speaker 13: they're tendto labor faster and I feel less pain. But

456
00:21:03,973 --> 00:21:06,853
Speaker 13: we've screened them very carefully. If somebody is low risk,

457
00:21:06,973 --> 00:21:09,093
Speaker 13: then they could be offered a home birth. But if

458
00:21:09,093 --> 00:21:12,293
Speaker 13: you've got any problems. If you'ren't going to labor naturally spontaneously,

459
00:21:12,293 --> 00:21:15,893
Speaker 13: you're not going to be a candidate anyway. And women

460
00:21:16,053 --> 00:21:19,213
Speaker 13: sort of have an innate feeling whether they want to

461
00:21:19,453 --> 00:21:22,933
Speaker 13: birth at home or not. I think, I mean, certainly,

462
00:21:23,053 --> 00:21:25,893
Speaker 13: there was a huge study done National Women's when it

463
00:21:25,933 --> 00:21:30,773
Speaker 13: was National Women's Auckland private Hospital now over a twenty

464
00:21:30,813 --> 00:21:33,693
Speaker 13: five year period which actually the outcome showed that home

465
00:21:33,733 --> 00:21:36,733
Speaker 13: birth was safer than hospital birth. But that's looking at

466
00:21:36,893 --> 00:21:40,573
Speaker 13: a low risk population. We're choosing to birth at home

467
00:21:40,773 --> 00:21:43,413
Speaker 13: with a low risk population who are choosing to birth

468
00:21:43,453 --> 00:21:45,693
Speaker 13: in hospital, and the ones to birth in the hospital

469
00:21:45,693 --> 00:21:47,813
Speaker 13: didn't have as good as outcomes as those at home.

470
00:21:48,653 --> 00:21:52,133
Speaker 2: Interesting, have you seen some of the latest developments in

471
00:21:52,413 --> 00:21:55,813
Speaker 2: you know, humanoid style robots at all?

472
00:21:55,853 --> 00:21:56,533
Speaker 4: Eleanor no.

473
00:21:56,933 --> 00:21:58,253
Speaker 13: No, they're not in.

474
00:21:58,173 --> 00:21:59,573
Speaker 9: My area at all.

475
00:22:01,973 --> 00:22:06,053
Speaker 4: Yeah, because in other areas of medicine.

476
00:22:05,933 --> 00:22:10,933
Speaker 13: Be deployed in some areas in healthcare sort of, I

477
00:22:10,973 --> 00:22:14,453
Speaker 13: can see a robot trundling around dispensing drugs. Well, it's

478
00:22:14,493 --> 00:22:17,853
Speaker 13: been programmed, I mean that that would be well, then

479
00:22:17,893 --> 00:22:20,093
Speaker 13: how do you check the person's really taken it?

480
00:22:20,573 --> 00:22:22,493
Speaker 4: Well? So a lot of surgery is now being done

481
00:22:22,573 --> 00:22:26,773
Speaker 4: by robots, mostly done remotely with the doctors.

482
00:22:27,093 --> 00:22:28,773
Speaker 13: Which is very very good, but you still need a

483
00:22:28,813 --> 00:22:30,453
Speaker 13: doctor their waggling stick at the moment.

484
00:22:30,693 --> 00:22:32,613
Speaker 2: Yeah, well, you don't want a robot coming at you

485
00:22:32,653 --> 00:22:34,013
Speaker 2: with a pair of calipers and trying to pull the

486
00:22:34,013 --> 00:22:37,573
Speaker 2: baby out, do you know? That would be And it's

487
00:22:37,613 --> 00:22:39,613
Speaker 2: kind of what Eleanor points out as well as there's

488
00:22:39,893 --> 00:22:43,013
Speaker 2: an emotional aspect of something like childbirth where the mother

489
00:22:43,133 --> 00:22:46,893
Speaker 2: needs to feel comfortable and if she's surrounded by non

490
00:22:47,013 --> 00:22:49,973
Speaker 2: humans then you know, and that's the reason why people

491
00:22:49,973 --> 00:22:51,853
Speaker 2: are having home births as opposed to the hospital because

492
00:22:51,853 --> 00:22:55,373
Speaker 2: they feel uncomfortable, they feel, you know, that the the

493
00:22:55,733 --> 00:22:59,653
Speaker 2: environment isn't right for them. Then you know robots an't

494
00:22:59,653 --> 00:23:00,373
Speaker 2: going to help that, aren't they.

495
00:23:00,453 --> 00:23:00,572
Speaker 5: No?

496
00:23:00,653 --> 00:23:02,653
Speaker 3: Exactly oh one hundred and eighty teen eighty is the

497
00:23:02,733 --> 00:23:05,053
Speaker 3: number to call. Do you think your job is safe

498
00:23:05,133 --> 00:23:06,813
Speaker 3: from artificial intelligence?

499
00:23:07,253 --> 00:23:11,292
Speaker 2: Warwick asks, any AI can catch and treat fly Boy

500
00:23:11,373 --> 00:23:11,733
Speaker 2: and Sheep.

501
00:23:11,813 --> 00:23:13,133
Speaker 4: I don't think so, not at.

502
00:23:13,093 --> 00:23:16,693
Speaker 3: The stage anyway. It's a fairpoint, Warwick. It is twenty

503
00:23:16,693 --> 00:23:20,373
Speaker 3: seven two US talks.

504
00:23:20,413 --> 00:23:24,133
Speaker 15: There'd be headlines with blue bubble taxis. It's no trouble

505
00:23:24,213 --> 00:23:27,373
Speaker 15: with a blue bubble. A tax expert claim scramping the

506
00:23:27,453 --> 00:23:31,413
Speaker 15: Digital Services tax, which would have imposed three percent on

507
00:23:31,533 --> 00:23:35,053
Speaker 15: Kiwi revenue for platforms like Google and Facebook, was the

508
00:23:35,093 --> 00:23:39,813
Speaker 15: only realistic move because of the risk of retaliation. Associate

509
00:23:39,893 --> 00:23:43,613
Speaker 15: Health Minister David Seymour's told a Health Select Committee speeding

510
00:23:43,613 --> 00:23:49,013
Speaker 15: access to drugs already approved overseas could improve safeguards a

511
00:23:49,053 --> 00:23:51,933
Speaker 15: group with a goal of ending sexual harm as warning

512
00:23:52,013 --> 00:23:56,613
Speaker 15: expertise could be lost. Is acc paus's national rollout of

513
00:23:56,653 --> 00:24:01,893
Speaker 15: its hiccatea program after reviewing funding and outputs. A Darnedin

514
00:24:01,933 --> 00:24:04,813
Speaker 15: police officers suffered an asthma attack when a man being

515
00:24:04,893 --> 00:24:08,853
Speaker 15: arrested sprayed deodorant in her face this morning. Man's stew

516
00:24:08,893 --> 00:24:12,893
Speaker 15: in court next week. Fruitful harvests and more Contain a

517
00:24:12,933 --> 00:24:16,133
Speaker 15: cargo through a napier port has brought strong earnings for

518
00:24:16,173 --> 00:24:19,133
Speaker 15: the six months ending March at twenty point two million

519
00:24:19,173 --> 00:24:23,853
Speaker 15: dollars after tax, and World Travel and Tourism Council Research

520
00:24:24,213 --> 00:24:27,373
Speaker 15: is forecasting the sector will pump fifty seven billion dollars

521
00:24:27,373 --> 00:24:32,293
Speaker 15: into the economy across the year. AI disruptors meet the

522
00:24:32,333 --> 00:24:35,373
Speaker 15: kiwis using new tech to boost their businesses and lead

523
00:24:35,453 --> 00:24:38,733
Speaker 15: the way see the story at Nzen Herald Premium back

524
00:24:38,733 --> 00:24:40,213
Speaker 15: to matt Ethan Tyler Adams.

525
00:24:40,213 --> 00:24:42,173
Speaker 3: Thank you very much, Ray Lean and we are, funnily

526
00:24:42,253 --> 00:24:45,973
Speaker 3: enough talking about AI. Are you concerned about AI taking

527
00:24:46,253 --> 00:24:49,493
Speaker 3: your job? It comes as Spark confirmed job cuts as

528
00:24:49,613 --> 00:24:52,933
Speaker 3: outsources to AI. A source told The Herald in this

529
00:24:53,053 --> 00:24:55,853
Speaker 3: article that it could result in two hundred jobs going

530
00:24:55,893 --> 00:24:58,133
Speaker 3: from Spark. That is a significant number, but they're not

531
00:24:58,133 --> 00:25:00,413
Speaker 3: the only ones. There's been many, many companies that have

532
00:25:00,453 --> 00:25:03,973
Speaker 3: been outsourcing particular jobs to AI for the last few years.

533
00:25:04,053 --> 00:25:05,733
Speaker 2: Yeah, so I one hundred and eighty ten eighty do

534
00:25:05,773 --> 00:25:08,493
Speaker 2: you think your job is it danger from AI? Where

535
00:25:08,493 --> 00:25:11,293
Speaker 2: do you think it's impervious to the invasion of AI?

536
00:25:11,613 --> 00:25:13,453
Speaker 2: Bill Gates a person that.

537
00:25:13,413 --> 00:25:15,733
Speaker 4: I have no time for it all. Generally speaking, he

538
00:25:15,773 --> 00:25:16,333
Speaker 4: really annoys me.

539
00:25:16,453 --> 00:25:19,413
Speaker 3: Where As you said before, highly likely he's AI himself.

540
00:25:19,493 --> 00:25:22,973
Speaker 2: Yeah, Oh, hugely likely. He's certainly got no empathy. But

541
00:25:23,493 --> 00:25:26,613
Speaker 2: he was saying that teachers and doctors too, that he

542
00:25:26,693 --> 00:25:29,893
Speaker 2: sees an immediate threat. I think that's on. I think

543
00:25:29,973 --> 00:25:32,293
Speaker 2: teachers will be around with us for a very long time.

544
00:25:32,333 --> 00:25:34,413
Speaker 2: Although we've had a few teachers texts in and say

545
00:25:34,413 --> 00:25:39,292
Speaker 2: we're definitely under threat. From AI This Texas, says Gaday Fellas.

546
00:25:39,373 --> 00:25:42,373
Speaker 2: I'm a vet. Most animal mortalities on farms occur during

547
00:25:42,413 --> 00:25:45,453
Speaker 2: spring ae carving, lambing. My vet colleagues know what can

548
00:25:45,493 --> 00:25:48,973
Speaker 2: go wrong, and most of us we're more than happy

549
00:25:49,173 --> 00:25:52,333
Speaker 2: for children to be born in the hospital, right, Yeah,

550
00:25:52,453 --> 00:25:55,213
Speaker 2: that's going back to the midwif three before.

551
00:25:55,453 --> 00:25:59,093
Speaker 3: Yeah, and guys, I'm fifty to fifty as a client

552
00:25:59,173 --> 00:26:03,893
Speaker 3: relationships manager. It's all about people that said AI evolved.

553
00:26:03,933 --> 00:26:08,133
Speaker 3: I think people still want human interactions, but I fear

554
00:26:08,173 --> 00:26:10,333
Speaker 3: that may changes the technology gets better.

555
00:26:10,653 --> 00:26:10,853
Speaker 4: Yeah.

556
00:26:10,893 --> 00:26:13,413
Speaker 2: I mean, if you were guaranteed that the baby was

557
00:26:13,493 --> 00:26:18,773
Speaker 2: going to be safer with AI and with some kind

558
00:26:18,813 --> 00:26:23,093
Speaker 2: of birthing bot, then your love of humans would have

559
00:26:23,093 --> 00:26:25,893
Speaker 2: to be huge to get over that. If it could

560
00:26:25,893 --> 00:26:28,373
Speaker 2: be shown that it was a just one hundred percent

561
00:26:28,413 --> 00:26:30,893
Speaker 2: safe and there was no chance of any problem happening

562
00:26:31,213 --> 00:26:34,293
Speaker 2: with the bot as opposed to some chance with the human,

563
00:26:34,333 --> 00:26:36,213
Speaker 2: then what are you going to do? But as I

564
00:26:36,213 --> 00:26:39,173
Speaker 2: said before, it gets confusing because you need the mother

565
00:26:39,213 --> 00:26:42,052
Speaker 2: to feel comfortable, and the mother it might just skew

566
00:26:42,133 --> 00:26:44,253
Speaker 2: things if it's a robot there and not another human being.

567
00:26:44,293 --> 00:26:45,413
Speaker 4: Still to it's an interesting one.

568
00:26:45,453 --> 00:26:48,013
Speaker 2: A lot of people been texting through saying that gardeners

569
00:26:48,093 --> 00:26:51,453
Speaker 2: and landscape gardeners and trades will be fine. But justin

570
00:26:51,853 --> 00:26:54,613
Speaker 2: your daughter has been working on a robot gardener.

571
00:26:55,773 --> 00:26:59,213
Speaker 12: Yes, so part of an internship for the end of

572
00:26:59,253 --> 00:27:06,773
Speaker 12: your Indian integree. The last years that you see, they

573
00:27:07,013 --> 00:27:13,013
Speaker 12: developed a in relation to drinking and university. I don't

574
00:27:13,173 --> 00:27:17,333
Speaker 12: drop names, but I think agg research. But anyway, it

575
00:27:17,373 --> 00:27:21,133
Speaker 12: would go through lines and crops and identify weeds and

576
00:27:21,253 --> 00:27:28,813
Speaker 12: with a small we very well uh pinpointed injection injected

577
00:27:28,893 --> 00:27:32,693
Speaker 12: with wiz wow, so it could actually go through entire crop.

578
00:27:32,453 --> 00:27:34,853
Speaker 4: Lines wow and fast.

579
00:27:36,173 --> 00:27:41,733
Speaker 12: Oh wow, than probably But yeah, we'll just just go

580
00:27:41,813 --> 00:27:44,453
Speaker 12: down and just down the lines and records and forwards

581
00:27:44,493 --> 00:27:49,173
Speaker 12: and take get the grand if you like, and identify

582
00:27:49,173 --> 00:27:56,812
Speaker 12: a weed for a assume effectively Google per se figuring

583
00:27:56,853 --> 00:27:57,573
Speaker 12: out that that's a weed.

584
00:27:57,613 --> 00:27:58,333
Speaker 16: So I'll get rid of that.

585
00:27:58,333 --> 00:28:00,093
Speaker 12: Well, that wasn't put us away. That plant is not

586
00:28:00,093 --> 00:28:01,413
Speaker 12: supposed to be there, killer.

587
00:28:02,013 --> 00:28:03,973
Speaker 2: Yeah right, And so because people think about this and

588
00:28:03,973 --> 00:28:06,173
Speaker 2: they think about robots, so they think of AI in

589
00:28:06,333 --> 00:28:08,453
Speaker 2: terms of the large language morals that we have have

590
00:28:08,493 --> 00:28:11,573
Speaker 2: on the internet like chat, GPT, but you could have

591
00:28:11,733 --> 00:28:14,493
Speaker 2: a system like that justin where the robot's you know,

592
00:28:14,653 --> 00:28:18,253
Speaker 2: been called behind a tractor and this.

593
00:28:18,293 --> 00:28:20,573
Speaker 12: One was self driven. I actually saw the video of

594
00:28:20,613 --> 00:28:23,453
Speaker 12: it and once it we're human my daughters from Yeah,

595
00:28:25,373 --> 00:28:28,573
Speaker 12: because the solar panels that.

596
00:28:28,613 --> 00:28:31,293
Speaker 2: Could be scanning at an insane rate, and you know

597
00:28:31,413 --> 00:28:33,973
Speaker 2: have a number. You know, it's not just a robot

598
00:28:33,973 --> 00:28:37,853
Speaker 2: with two hands. It's like, you know, hundreds of little

599
00:28:37,853 --> 00:28:39,333
Speaker 2: pokey things injecting stuff.

600
00:28:39,413 --> 00:28:41,213
Speaker 3: Well, why you guys have been having a chat. I've

601
00:28:41,213 --> 00:28:44,733
Speaker 3: just had a week. Look and if you google robot gardener,

602
00:28:44,853 --> 00:28:47,893
Speaker 3: what comes up is farm bot technology out of the US,

603
00:28:48,133 --> 00:28:49,933
Speaker 3: and it is effectively, I mean very similar to what

604
00:28:49,973 --> 00:28:52,173
Speaker 3: you're saying justin your what your daughter's doing, I think

605
00:28:52,253 --> 00:28:54,973
Speaker 3: is a little bit more advanced and flexible. But this

606
00:28:55,053 --> 00:28:58,493
Speaker 3: is effectively a robot that will grow vegetables for you

607
00:28:58,613 --> 00:29:00,653
Speaker 3: in your garden on a particular block and do it

608
00:29:00,653 --> 00:29:02,573
Speaker 3: all for you. Once you set it up, it's set

609
00:29:02,613 --> 00:29:05,133
Speaker 3: and forget, and it will make sure your vegetables are perfect.

610
00:29:05,213 --> 00:29:08,133
Speaker 3: It's watered, it's looked after, making sure it gets enough sun.

611
00:29:08,373 --> 00:29:10,813
Speaker 3: Everything is taken care of by the spot so you

612
00:29:10,813 --> 00:29:11,733
Speaker 3: don't have to do anything.

613
00:29:11,893 --> 00:29:15,293
Speaker 12: I mean, it has all the senses in the groundlight

614
00:29:15,493 --> 00:29:18,013
Speaker 12: for example, we're too much lime or too much salt

615
00:29:18,093 --> 00:29:23,373
Speaker 12: or too much water. So it can they will. Technology

616
00:29:23,453 --> 00:29:23,813
Speaker 12: is there, But.

617
00:29:24,293 --> 00:29:27,533
Speaker 7: As the midwife would say, is is.

618
00:29:27,533 --> 00:29:29,293
Speaker 12: There any money in that? So I don't can't. I

619
00:29:29,373 --> 00:29:33,093
Speaker 12: can't see why make a robot that doesn't mean roo free,

620
00:29:33,093 --> 00:29:35,053
Speaker 12: because what's the point of that with the money?

621
00:29:35,213 --> 00:29:36,093
Speaker 9: What's the point?

622
00:29:36,693 --> 00:29:38,853
Speaker 12: As on the same subly, my sparky. So I think

623
00:29:38,893 --> 00:29:44,653
Speaker 12: I'm pretty okay for the sell future, yeah, but forgetting.

624
00:29:45,293 --> 00:29:47,853
Speaker 12: I think if you were to give a robot scan

625
00:29:48,013 --> 00:29:50,853
Speaker 12: of what you wanted, it will be most likely a

626
00:29:51,453 --> 00:29:54,373
Speaker 12: robot probably even today that you go, oh you want this,

627
00:29:54,653 --> 00:29:56,093
Speaker 12: scan it in here, I'll make it happen.

628
00:29:56,293 --> 00:29:57,573
Speaker 4: Yeah, I think if you called justin.

629
00:29:57,653 --> 00:30:01,533
Speaker 2: I mean, that's an interesting idea, like a farm just

630
00:30:01,613 --> 00:30:04,413
Speaker 2: being run by robots but tending to the crops, so

631
00:30:04,493 --> 00:30:07,933
Speaker 2: the crops are being constantly monitored twenty four to seven,

632
00:30:08,373 --> 00:30:13,133
Speaker 2: any changes are being made, you know, analysis constantly done,

633
00:30:13,373 --> 00:30:16,933
Speaker 2: the perfect yield, soil acidity, all those all those things,

634
00:30:18,013 --> 00:30:21,653
Speaker 2: and then calling in the harvester. Yeah, when it's ready

635
00:30:21,693 --> 00:30:23,973
Speaker 2: to go, I mean, and then just you can just

636
00:30:24,013 --> 00:30:28,653
Speaker 2: imagine huge, huge swallows of the country just with robots

637
00:30:28,733 --> 00:30:31,933
Speaker 2: quietly working away, holding them together, and then we're just

638
00:30:31,973 --> 00:30:33,973
Speaker 2: sitting in the city is getting fatter and fatter like

639
00:30:34,013 --> 00:30:35,933
Speaker 2: the humans on Walley.

640
00:30:36,093 --> 00:30:38,813
Speaker 3: It is terrifying. Oh, one hundred eighty eighty is the

641
00:30:38,893 --> 00:30:42,413
Speaker 3: number to call. Do you think AI could replace your job?

642
00:30:42,493 --> 00:30:44,493
Speaker 3: Love to hear from you nine two nine too if

643
00:30:44,493 --> 00:30:46,493
Speaker 3: you want to seend the text as well.

644
00:30:46,933 --> 00:30:49,093
Speaker 2: It's as simple as this. If your job can be

645
00:30:49,133 --> 00:30:53,213
Speaker 2: converted to an algorithm, you're in a legacy occupation. GP

646
00:30:53,333 --> 00:30:56,813
Speaker 2: positions out of here. Accounting is gone, Burger, so on

647
00:30:56,893 --> 00:30:59,573
Speaker 2: and so on. But you know, humans are just running

648
00:30:59,573 --> 00:31:03,933
Speaker 2: an algorithm. I mean, if you read novel, you have novel?

649
00:31:04,253 --> 00:31:07,773
Speaker 2: Yeah you val Noah hurrara y you v ou know?

650
00:31:07,813 --> 00:31:11,213
Speaker 2: Harawis sapiens. He talks a lot about the algorithm that

651
00:31:11,253 --> 00:31:13,973
Speaker 2: we're running. We think we're so advanced and we're making

652
00:31:14,013 --> 00:31:17,373
Speaker 2: all these decisions, but you know, he argues, we're just

653
00:31:17,453 --> 00:31:21,173
Speaker 2: running an algorithm. So you know, it's a complex one.

654
00:31:21,573 --> 00:31:24,213
Speaker 2: But if A is getting more and more complex.

655
00:31:23,853 --> 00:31:25,413
Speaker 4: Then they might be able to run our algorithm. You

656
00:31:25,413 --> 00:31:25,653
Speaker 4: never know.

657
00:31:25,893 --> 00:31:27,413
Speaker 3: But let me throw this at you. Because we talked

658
00:31:27,413 --> 00:31:32,213
Speaker 3: about GPS and health and if they could guarantee that

659
00:31:32,293 --> 00:31:34,773
Speaker 3: your baby was delivered and it was going to be

660
00:31:34,813 --> 00:31:37,813
Speaker 3: perfectly healthy, or you had something going on and they

661
00:31:37,813 --> 00:31:39,693
Speaker 3: could guarantee it was going to be better than a human.

662
00:31:40,053 --> 00:31:42,213
Speaker 3: But I think, yeah, so so those jobs I think

663
00:31:42,253 --> 00:31:46,973
Speaker 3: are in danger. But I think there's still humans, like

664
00:31:47,733 --> 00:31:50,893
Speaker 3: for some reason, the flaws of other humans. You know,

665
00:31:50,973 --> 00:31:54,853
Speaker 3: that fallibility of humankind will still play a part. That

666
00:31:54,933 --> 00:31:57,973
Speaker 3: we don't want perfection in every single job. We want

667
00:31:58,053 --> 00:32:00,093
Speaker 3: humans making similar mistakes.

668
00:32:00,733 --> 00:32:04,893
Speaker 2: We want perfection and accounting. Yeah, okay, that's connection that's gone.

669
00:32:05,133 --> 00:32:07,013
Speaker 2: Wouldn't it be good if we had political perfection?

670
00:32:07,333 --> 00:32:09,013
Speaker 3: Yep? We see later, politician.

671
00:32:09,053 --> 00:32:10,253
Speaker 4: If you if the budget that.

672
00:32:10,293 --> 00:32:16,453
Speaker 2: Was coming out tomorrow was absolutely perfect to produce the

673
00:32:16,493 --> 00:32:20,933
Speaker 2: most possible productivity out of our country as possible. Yeah,

674
00:32:20,973 --> 00:32:23,373
Speaker 2: and you know, maybe throwing a little bit of happiness

675
00:32:23,413 --> 00:32:26,533
Speaker 2: for the for the flesh sacks walking.

676
00:32:26,333 --> 00:32:27,133
Speaker 4: Around as well.

677
00:32:27,173 --> 00:32:28,053
Speaker 3: Yeah, yeah, good point.

678
00:32:28,213 --> 00:32:28,333
Speaker 1: Yea.

679
00:32:28,653 --> 00:32:30,093
Speaker 3: I love to hear from you, though. Oh eight hundred

680
00:32:30,133 --> 00:32:31,333
Speaker 3: eighty ten eighty. It is quarter to.

681
00:32:31,373 --> 00:32:37,453
Speaker 1: Two your home of afternoon talk, Mad Heathen Taylor Adams

682
00:32:37,533 --> 00:32:41,253
Speaker 1: afternoons call, Oh eight hundred eighty ten eighty us talk.

683
00:32:41,093 --> 00:32:44,213
Speaker 3: Said, be very good afternoon, and we aren't talking about

684
00:32:44,253 --> 00:32:47,133
Speaker 3: artificial intelligence, how you're worried it could take your job,

685
00:32:47,173 --> 00:32:49,333
Speaker 3: and if you're not worried, we can hear from you.

686
00:32:49,333 --> 00:32:50,893
Speaker 3: Oh eight one hundred eighty teen eighty what do you

687
00:32:50,893 --> 00:32:52,493
Speaker 3: do that you think is AI proof?

688
00:32:52,973 --> 00:32:55,853
Speaker 2: That's interesting the amount of people are texting through saying

689
00:32:55,853 --> 00:32:58,213
Speaker 2: I'm a truck driver. They'll never take my job. Too dangerous.

690
00:32:58,213 --> 00:33:00,013
Speaker 2: No way, I'm a truck driver. I'm a driver.

691
00:33:00,293 --> 00:33:00,893
Speaker 1: No way.

692
00:33:01,013 --> 00:33:03,373
Speaker 2: This textas says my son just got back from the USA.

693
00:33:04,093 --> 00:33:07,133
Speaker 2: She got and my son just got back from the USA.

694
00:33:07,253 --> 00:33:10,413
Speaker 2: She got an UBER. I'm not going to delve into that.

695
00:33:10,933 --> 00:33:14,053
Speaker 2: Only she got an uber. I need to find out

696
00:33:14,053 --> 00:33:17,693
Speaker 2: there was no driver driverless car spooky, Yeah.

697
00:33:17,813 --> 00:33:19,333
Speaker 4: I mean yeah, boy boy.

698
00:33:19,373 --> 00:33:23,893
Speaker 2: The recent upgrade in the Tesla software typical that you

699
00:33:24,253 --> 00:33:26,213
Speaker 2: have to pay a subscription for it, but that that.

700
00:33:26,573 --> 00:33:30,853
Speaker 3: Would transport transported as for some serious disruption over the

701
00:33:30,893 --> 00:33:35,613
Speaker 3: next couple of years, that's for sure. Peter, You've got

702
00:33:35,933 --> 00:33:37,693
Speaker 3: a couple of jobs you don't think can be replaced

703
00:33:37,693 --> 00:33:38,133
Speaker 3: by AI.

704
00:33:39,253 --> 00:33:43,573
Speaker 16: Yeah, well the next twenty years. Butchery may be replaced.

705
00:33:43,613 --> 00:33:46,133
Speaker 16: But then I'll just go on to exotic dancing. Then

706
00:33:46,493 --> 00:33:50,293
Speaker 16: I should be fine until retirement.

707
00:33:50,573 --> 00:33:54,053
Speaker 2: Okay, so your butcher now, and you're going to hold

708
00:33:54,053 --> 00:33:56,253
Speaker 2: on as long as you can and then you straight

709
00:33:56,293 --> 00:33:57,853
Speaker 2: on the pole when that disappears.

710
00:33:58,693 --> 00:34:00,653
Speaker 16: Oh yeah, well he does have to be a pole mate,

711
00:34:02,573 --> 00:34:03,653
Speaker 16: gentleman dancing.

712
00:34:03,733 --> 00:34:08,053
Speaker 3: You can use anything you have done, your research strategized.

713
00:34:09,613 --> 00:34:12,013
Speaker 16: But I think but is almost to die and that

714
00:34:13,453 --> 00:34:16,172
Speaker 16: throughout new zell them it's just harder and harder to

715
00:34:16,213 --> 00:34:18,893
Speaker 16: get them. And yeah, you can break things down to

716
00:34:18,973 --> 00:34:23,053
Speaker 16: a primal three machine, but it's still that little intricate

717
00:34:23,653 --> 00:34:28,533
Speaker 16: pieces of cuts that you get that that AI can't

718
00:34:28,573 --> 00:34:31,613
Speaker 16: do now. But it's not too far away. But there's

719
00:34:31,613 --> 00:34:32,693
Speaker 16: something that broken.

720
00:34:33,293 --> 00:34:36,373
Speaker 2: There's something about going to your butcher though, Like you know,

721
00:34:36,453 --> 00:34:39,293
Speaker 2: I love going in and you know, talking to the

722
00:34:39,293 --> 00:34:43,173
Speaker 2: butcher about whatever interesting sausages they've tried to they've invented,

723
00:34:43,653 --> 00:34:46,093
Speaker 2: so that interactions, that interaction is pretty cool.

724
00:34:46,333 --> 00:34:47,812
Speaker 3: Yeah, it's not just about the meat.

725
00:34:48,853 --> 00:34:52,413
Speaker 16: Yeah, fairsuck of the salve mat, but you know it's.

726
00:34:52,733 --> 00:34:54,172
Speaker 2: You used to get the free You used to get

727
00:34:54,173 --> 00:34:55,693
Speaker 2: the free suck of the salve, didn't you when you

728
00:34:55,733 --> 00:34:58,173
Speaker 2: went in there used to get.

729
00:34:59,093 --> 00:35:02,373
Speaker 16: You can you can talk to a butcher on other

730
00:35:02,493 --> 00:35:06,573
Speaker 16: things other than small goods. We do a wide variety,

731
00:35:07,053 --> 00:35:10,893
Speaker 16: So it's me to please share, right cool?

732
00:35:11,213 --> 00:35:13,453
Speaker 2: Yeah, well, well, if it all, if it all sort

733
00:35:13,453 --> 00:35:15,853
Speaker 2: of ends up and you n up in his Exotic Dancer,

734
00:35:15,893 --> 00:35:17,373
Speaker 2: give me a yell. I'll try and see if I

735
00:35:17,413 --> 00:35:19,453
Speaker 2: can find you work on a few hen parties that

736
00:35:19,493 --> 00:35:21,773
Speaker 2: go through. You know, if you especially if you go

737
00:35:21,853 --> 00:35:23,933
Speaker 2: for the butcher motif, if you turn up in the

738
00:35:24,853 --> 00:35:27,773
Speaker 2: in the apron look at it, I think high demand

739
00:35:27,853 --> 00:35:31,093
Speaker 2: for with with the cleaver people.

740
00:35:30,933 --> 00:35:31,133
Speaker 17: Like that.

741
00:35:32,973 --> 00:35:36,893
Speaker 16: Pouts and the just a spring sawdust drown.

742
00:35:36,973 --> 00:35:37,813
Speaker 4: In the sausage.

743
00:35:38,093 --> 00:35:40,933
Speaker 3: Yeah, yep, thank you for your call, Peter, Thank you

744
00:35:41,093 --> 00:35:45,133
Speaker 3: very much. Oh eight one hundred eighty ten eighty A

745
00:35:45,213 --> 00:35:46,493
Speaker 3: couple of teaps coming through.

746
00:35:46,773 --> 00:35:50,172
Speaker 2: Guys, can't wait till AI will replace all the bureaucrats

747
00:35:50,213 --> 00:35:52,173
Speaker 2: in public and the public sector would save us a

748
00:35:52,213 --> 00:35:54,053
Speaker 2: lot of money. How many times do you call them

749
00:35:54,093 --> 00:35:57,013
Speaker 2: and speak to a useless person who's got no idea

750
00:35:57,093 --> 00:36:00,133
Speaker 2: how to do their job and get passed around? Hurry up,

751
00:36:00,173 --> 00:36:04,413
Speaker 2: I say, bring on our robot overlords. Okay, Yeah, that's

752
00:36:04,493 --> 00:36:05,173
Speaker 2: huge though, isn't it.

753
00:36:05,173 --> 00:36:08,293
Speaker 3: Bureaucrats or anyone who's just imputting data into a system

754
00:36:09,093 --> 00:36:10,293
Speaker 3: the the Goldburger.

755
00:36:11,613 --> 00:36:14,133
Speaker 2: Yeah, well, It's interesting though, if you look at it

756
00:36:14,173 --> 00:36:15,693
Speaker 2: before a lot of people talking about farm work and

757
00:36:15,733 --> 00:36:17,413
Speaker 2: we're talking about the farm robots. I mean, there's a

758
00:36:17,493 --> 00:36:19,213
Speaker 2: huge problem we've got now is getting people that are

759
00:36:19,253 --> 00:36:19,973
Speaker 2: willing to do the.

760
00:36:19,973 --> 00:36:21,813
Speaker 4: Hard work of working on a farm.

761
00:36:21,893 --> 00:36:22,213
Speaker 3: Yeah.

762
00:36:22,293 --> 00:36:24,533
Speaker 2: I mean, there is no one works harder than farmers,

763
00:36:24,893 --> 00:36:27,933
Speaker 2: and you know it's the hugest part of our economy.

764
00:36:28,253 --> 00:36:32,293
Speaker 2: But so many, so many, you know, families get to

765
00:36:32,293 --> 00:36:33,692
Speaker 2: the point when none of the kids want to do it.

766
00:36:34,413 --> 00:36:36,453
Speaker 2: You know, if dad gets to just hand it over

767
00:36:36,493 --> 00:36:38,373
Speaker 2: to some bots, then maybe they'll be.

768
00:36:38,373 --> 00:36:40,133
Speaker 3: Good than Sarah own fault. We've been too lazy. Oh

769
00:36:40,213 --> 00:36:42,293
Speaker 3: eight hundred eighty ten eighty is the number to call

770
00:36:42,333 --> 00:36:44,172
Speaker 3: back very shortly. It is nine to two.

771
00:36:47,413 --> 00:36:50,652
Speaker 1: Matt Heath, Taylor Adams taking your calls on Oh, eight

772
00:36:50,693 --> 00:36:55,093
Speaker 1: hundred eighty ten eighty. It's mad Heath and Taylor Adams afternoons.

773
00:36:54,493 --> 00:36:57,772
Speaker 3: News Talks B News Talks there B it is six

774
00:36:57,933 --> 00:37:00,732
Speaker 3: two two oh eight hundred eighty ten eighty. We're talking

775
00:37:00,733 --> 00:37:02,933
Speaker 3: about AI and whether your job is at risk?

776
00:37:04,053 --> 00:37:06,293
Speaker 4: John, you think this is yeah.

777
00:37:06,133 --> 00:37:10,453
Speaker 9: How I am find a clinical dental technician and yes,

778
00:37:11,213 --> 00:37:13,373
Speaker 9: there are going to be changes in my industry very soon.

779
00:37:14,533 --> 00:37:18,493
Speaker 9: I've won a computer program called three shape and it

780
00:37:18,613 --> 00:37:23,893
Speaker 9: scans the models of your mouth. And we used to

781
00:37:23,933 --> 00:37:29,813
Speaker 9: make metal benches or dnches by hand and now you

782
00:37:30,013 --> 00:37:34,093
Speaker 9: design on a computer stream. But I'm going after the

783
00:37:34,693 --> 00:37:39,333
Speaker 9: conference in Sydney, Australia about AI and happening in an

784
00:37:39,373 --> 00:37:42,653
Speaker 9: industry where you will basically take a scan of the

785
00:37:42,693 --> 00:37:46,453
Speaker 9: person's head and a cone being scan and then send

786
00:37:46,493 --> 00:37:48,853
Speaker 9: it off to the AI and it'll do all the design.

787
00:37:48,613 --> 00:37:49,053
Speaker 4: Work for you.

788
00:37:49,133 --> 00:37:51,773
Speaker 9: And it's scan seen and sent to a printer and

789
00:37:51,813 --> 00:37:53,933
Speaker 9: printed out either a metal or a plastic.

790
00:37:54,133 --> 00:37:57,213
Speaker 2: Well, that's interestanable. My son recently he got those in

791
00:37:57,333 --> 00:37:58,973
Speaker 2: visiline braces.

792
00:37:59,013 --> 00:38:01,053
Speaker 9: And that's exactly that's classic.

793
00:38:01,293 --> 00:38:02,293
Speaker 4: And the way they did it.

794
00:38:02,693 --> 00:38:05,493
Speaker 2: I watched how they took the camera, created the exact honestly,

795
00:38:05,493 --> 00:38:07,652
Speaker 2: how they're getting the exact proportions right, because it ended

796
00:38:07,693 --> 00:38:10,053
Speaker 2: up being the exact site just by taking a bunch

797
00:38:10,053 --> 00:38:12,133
Speaker 2: of photos and scanning around his teeth and then they

798
00:38:12,173 --> 00:38:14,213
Speaker 2: made the exact image and then send it off and

799
00:38:14,573 --> 00:38:16,573
Speaker 2: all these ones came back and they fit perfectly and

800
00:38:16,613 --> 00:38:17,093
Speaker 2: did the jobs.

801
00:38:17,093 --> 00:38:17,773
Speaker 4: Teeth look amazing.

802
00:38:17,813 --> 00:38:22,013
Speaker 9: Now Yah called it into all scanner and that it

803
00:38:22,253 --> 00:38:24,493
Speaker 9: changes it into what we call an STL final, which

804
00:38:24,533 --> 00:38:27,653
Speaker 9: is a standard training the language final, and it makes

805
00:38:27,773 --> 00:38:32,613
Speaker 9: the image absolutely perfect because it's a hard service. What

806
00:38:32,693 --> 00:38:36,093
Speaker 9: the technology is a bit he is with tissue. It

807
00:38:36,133 --> 00:38:38,533
Speaker 9: can't quite detect it catch it.

808
00:38:39,573 --> 00:38:41,333
Speaker 4: Do you think do you think this is going to

809
00:38:41,493 --> 00:38:44,653
Speaker 4: end in job losses in your profession?

810
00:38:45,733 --> 00:38:46,453
Speaker 5: Yes, But.

811
00:38:48,173 --> 00:38:51,773
Speaker 9: Joe to the stage where you'll have people trained differently.

812
00:38:51,813 --> 00:38:54,212
Speaker 9: You'll have to do computer science and you have an

813
00:38:54,213 --> 00:38:58,173
Speaker 9: idea about your But I was in the like for

814
00:38:58,253 --> 00:39:02,813
Speaker 9: your son. I used to make when I started what

815
00:39:02,813 --> 00:39:07,373
Speaker 9: we called retainers from moving the teeth. Well, you had

816
00:39:07,733 --> 00:39:10,772
Speaker 9: really comp designs that you had to learn. All that's

817
00:39:10,773 --> 00:39:13,613
Speaker 9: gone by the wayside was the imaging with your son.

818
00:39:13,813 --> 00:39:16,453
Speaker 9: So it's actually it's taking all the skill away from

819
00:39:16,453 --> 00:39:16,772
Speaker 9: the job.

820
00:39:16,893 --> 00:39:19,853
Speaker 3: So fair point, John, I mean amazing. Similar to radiologists, right,

821
00:39:20,013 --> 00:39:23,212
Speaker 3: and you know there's a big backlog of enough radiologists

822
00:39:23,213 --> 00:39:25,493
Speaker 3: to be able to check Mr Rice scans to determine

823
00:39:25,493 --> 00:39:27,973
Speaker 3: what's going on. You bring AI into the picture that

824
00:39:28,013 --> 00:39:29,533
Speaker 3: they can do that instantly.

825
00:39:29,653 --> 00:39:32,893
Speaker 2: Well, there's a lot of backlog and dentistry at the moment,

826
00:39:32,973 --> 00:39:35,573
Speaker 2: So maybe we'll just clean up everyone's teeth. Maybe we'll

827
00:39:35,613 --> 00:39:38,093
Speaker 2: get truth through more people with this new technology.

828
00:39:38,173 --> 00:39:39,093
Speaker 3: I need that, that's for sure.

829
00:39:39,213 --> 00:39:41,453
Speaker 4: Yep, God you certainly snaggle tooth.

830
00:39:42,013 --> 00:39:44,732
Speaker 3: We're going to carry this on after two o'clock. Love

831
00:39:44,773 --> 00:39:46,773
Speaker 3: to hear from you. Oh, eight hundred and eighty ten

832
00:39:46,853 --> 00:39:49,692
Speaker 3: eighty is the number of cool news, sport and weather

833
00:39:49,773 --> 00:39:51,373
Speaker 3: on its way. Great to have your company. As always,

834
00:39:51,373 --> 00:40:03,053
Speaker 3: you're listening to Matt and Tyler. Good afternoon, talking with

835
00:40:03,213 --> 00:40:04,333
Speaker 3: you all afternoon.

836
00:40:04,653 --> 00:40:15,133
Speaker 1: It's Matt Heathen, Taylor Adams Afternoons, us Dogs be News,

837
00:40:15,173 --> 00:40:15,733
Speaker 1: Talk to it B.

838
00:40:15,893 --> 00:40:20,573
Speaker 3: Welcome back into the show. Seven past too. Now, I

839
00:40:20,653 --> 00:40:24,893
Speaker 3: notice you got on your neck Matte Heath. Yep, a lanyard,

840
00:40:25,013 --> 00:40:28,053
Speaker 3: Yeah I do, and with my name on it, Met Heath.

841
00:40:28,253 --> 00:40:30,853
Speaker 3: So apparently I saw a few texts having to go

842
00:40:30,893 --> 00:40:34,213
Speaker 3: at lanyard's earlier this morning. So apparently my costking was

843
00:40:34,573 --> 00:40:37,373
Speaker 3: also having to go at lanyard wearing people.

844
00:40:37,733 --> 00:40:39,533
Speaker 11: He's a little bit of Winston and he's going to

845
00:40:39,573 --> 00:40:42,253
Speaker 11: apologize to the hector at Wellington Rail yesterday who may

846
00:40:42,293 --> 00:40:46,173
Speaker 11: now lose his job. Grant, get real. He's not apologizing

847
00:40:46,213 --> 00:40:48,613
Speaker 11: to him. He's the one who started it. It is

848
00:40:48,653 --> 00:40:51,652
Speaker 11: an interesting debate, as I wouldn't have thought he's going

849
00:40:51,693 --> 00:40:54,373
Speaker 11: to lose his job. But it is an interesting debate

850
00:40:54,373 --> 00:40:56,133
Speaker 11: as to when you're an individual and when you're a

851
00:40:56,133 --> 00:40:57,973
Speaker 11: member of the company. Now, the problem was he was

852
00:40:58,093 --> 00:41:00,173
Speaker 11: wearing his Tonguin and Taylor as the company's wearing his

853
00:41:00,253 --> 00:41:03,173
Speaker 11: Tonquin and Taylor lanyard. Can I just say something, just

854
00:41:03,213 --> 00:41:05,693
Speaker 11: for the record, this is just me. Don't wear lanyards.

855
00:41:06,213 --> 00:41:09,373
Speaker 11: They are the rudest thing going Put pins in your

856
00:41:09,413 --> 00:41:11,493
Speaker 11: pocket or wear lanyards.

857
00:41:11,533 --> 00:41:12,253
Speaker 4: Wake up people.

858
00:41:12,293 --> 00:41:14,493
Speaker 11: And as for you people who have got your cards,

859
00:41:14,533 --> 00:41:18,013
Speaker 11: your swipe cards on a stretchy bit of elastic to

860
00:41:18,093 --> 00:41:20,613
Speaker 11: your belt, come on, get it together. You're probably wear

861
00:41:21,053 --> 00:41:22,853
Speaker 11: That's what I do exactly.

862
00:41:22,573 --> 00:41:23,133
Speaker 4: Say no more.

863
00:41:23,253 --> 00:41:27,333
Speaker 11: You're docker Docker wearing.

864
00:41:27,933 --> 00:41:31,252
Speaker 3: So you and Glen z be effectively Mike is calling

865
00:41:31,253 --> 00:41:34,973
Speaker 3: you guys nerds in your pocket.

866
00:41:33,893 --> 00:41:36,213
Speaker 2: Your point being I mean, I don't get my fashion

867
00:41:36,253 --> 00:41:37,453
Speaker 2: tips from my cost game.

868
00:41:37,933 --> 00:41:38,853
Speaker 4: I wear a lanyard.

869
00:41:40,453 --> 00:41:42,093
Speaker 3: Have you got it on the wie stretcher You don't,

870
00:41:42,133 --> 00:41:43,173
Speaker 3: You've got it on the elastic.

871
00:41:43,253 --> 00:41:44,293
Speaker 4: Okay, I'll tell.

872
00:41:44,173 --> 00:41:46,093
Speaker 2: You a couple of reasons, a couple of reasons why

873
00:41:46,093 --> 00:41:48,173
Speaker 2: I were at lanyard and look, will get to this

874
00:41:48,253 --> 00:41:50,732
Speaker 2: guy in a little bit from Tonkin and Taylor. Yeah,

875
00:41:50,773 --> 00:41:53,213
Speaker 2: the guy that was yelling at at Winston Peters and

876
00:41:53,213 --> 00:41:56,413
Speaker 2: asked the question about what you can and can't do

877
00:41:56,493 --> 00:41:58,853
Speaker 2: outside of work, etc. And whether you should get in

878
00:41:58,893 --> 00:42:00,453
Speaker 2: trouble for acting like a bit of a dick in

879
00:42:00,453 --> 00:42:03,133
Speaker 2: public like he did. But there's a couple of reasons

880
00:42:03,133 --> 00:42:07,093
Speaker 2: why we're a lanyard and A I disagree with my costing.

881
00:42:07,173 --> 00:42:08,853
Speaker 2: I think I look cool. It's kind of like the

882
00:42:08,933 --> 00:42:10,333
Speaker 2: lanyard around me kind of it's kind of like a

883
00:42:10,413 --> 00:42:12,172
Speaker 2: nick tie, So I look cool.

884
00:42:12,173 --> 00:42:14,533
Speaker 3: So there's actually three reasons I argue them, yep, Cara.

885
00:42:15,053 --> 00:42:17,173
Speaker 2: Second, it makes me feel like I work for the CIA.

886
00:42:17,893 --> 00:42:20,853
Speaker 2: I like walking around I've watched enough movies, or it

887
00:42:20,973 --> 00:42:23,493
Speaker 2: makes me think I work for Shield or something. Yeah,

888
00:42:23,533 --> 00:42:27,013
Speaker 2: I like pulling it out and swiping my way into things.

889
00:42:27,093 --> 00:42:28,772
Speaker 3: You've got quite the struck when you come in there.

890
00:42:28,773 --> 00:42:30,773
Speaker 3: Actually it does look like you're on West Wang or something.

891
00:42:30,813 --> 00:42:31,732
Speaker 3: Just so bit all right.

892
00:42:31,773 --> 00:42:34,493
Speaker 2: And Thirdly, I think it's rich coming from Hosky because

893
00:42:34,493 --> 00:42:36,253
Speaker 2: the only reason why we have to have these things

894
00:42:36,373 --> 00:42:38,253
Speaker 2: is all the security. It's in place to protect the

895
00:42:38,613 --> 00:42:41,573
Speaker 2: my Costing Memorial studio from people that he aggravates.

896
00:42:41,653 --> 00:42:43,293
Speaker 3: It is a very good points.

897
00:42:43,653 --> 00:42:45,933
Speaker 2: So to get into the studio to do my show,

898
00:42:46,013 --> 00:42:48,733
Speaker 2: I think I have to swipe through four doors. You know,

899
00:42:48,853 --> 00:42:51,453
Speaker 2: there's four levels of security here at News Talks. He'd

900
00:42:51,453 --> 00:42:53,733
Speaker 2: be before you can get in, so I don't know.

901
00:42:53,813 --> 00:42:55,693
Speaker 2: Maybe they've chipped Hosking and he can just walk in,

902
00:42:55,733 --> 00:42:57,453
Speaker 2: but for the rest of us, we're haavy to swipe.

903
00:42:57,933 --> 00:42:59,093
Speaker 2: And the best way to do it is with a

904
00:42:59,173 --> 00:43:00,133
Speaker 2: language unix.

905
00:43:00,213 --> 00:43:00,853
Speaker 4: So it looks cool.

906
00:43:00,973 --> 00:43:02,653
Speaker 2: Yeah, it makes me feel like I'm on the CIA,

907
00:43:02,813 --> 00:43:05,253
Speaker 2: and it keeps our breakfast host safe.

908
00:43:05,293 --> 00:43:06,813
Speaker 3: And that is a very good point for my day.

909
00:43:06,813 --> 00:43:08,733
Speaker 3: Ever ago when it's his fault we've got where these

910
00:43:08,773 --> 00:43:10,493
Speaker 3: women Laniards in the first place.

911
00:43:10,613 --> 00:43:12,573
Speaker 2: Anyway, that's not what we're talking about, Tyler. If derailed

912
00:43:12,573 --> 00:43:13,973
Speaker 2: the whole show. We're going to get to that in

913
00:43:14,013 --> 00:43:14,253
Speaker 2: a bit.

914
00:43:14,493 --> 00:43:16,692
Speaker 3: I just wanted to ear that, So that was good

915
00:43:16,693 --> 00:43:19,293
Speaker 3: to ear. And if you want to chip in on

916
00:43:19,453 --> 00:43:21,293
Speaker 3: Laniards and how much of a nerd Matt looks, you

917
00:43:21,413 --> 00:43:22,933
Speaker 3: more than welcome nine to nine to two. But least

918
00:43:22,933 --> 00:43:26,093
Speaker 3: get back to artificial intelligence, because this is a good

919
00:43:26,133 --> 00:43:29,093
Speaker 3: topic and an important topic. Ye are you fearful that

920
00:43:29,173 --> 00:43:31,853
Speaker 3: it may take your job. What kind of job are

921
00:43:31,893 --> 00:43:34,252
Speaker 3: you in? Do you think it is? Artificial intelligence proof

922
00:43:34,373 --> 00:43:35,573
Speaker 3: eight hundred and eighty ten eighty.

923
00:43:35,893 --> 00:43:39,213
Speaker 2: We were just talking to a dentist before, someone that

924
00:43:39,253 --> 00:43:41,853
Speaker 2: works in the dental profession that's said that AI is

925
00:43:41,893 --> 00:43:46,253
Speaker 2: making huge advances in dentistry in terms of the scanning

926
00:43:46,293 --> 00:43:49,373
Speaker 2: of mouths and the making of well I'm always talking

927
00:43:49,373 --> 00:43:52,212
Speaker 2: about the visil line, making of things that are put

928
00:43:52,253 --> 00:43:55,652
Speaker 2: into your mouth to fix problems and such. Yep, that's

929
00:43:55,653 --> 00:43:59,732
Speaker 2: making huge differences. This person says, I have recently had

930
00:43:59,853 --> 00:44:04,293
Speaker 2: a total knee replacement that was robot assisted. The surgeon

931
00:44:04,333 --> 00:44:06,733
Speaker 2: made the cut, and the surgeon gave the robot measurements,

932
00:44:06,853 --> 00:44:10,453
Speaker 2: and under the surgeon's guide, the robot did the soaring, etcetera.

933
00:44:10,973 --> 00:44:13,333
Speaker 4: I am very pleased with the outcome. My recovery went well.

934
00:44:13,453 --> 00:44:14,453
Speaker 4: Would hardly recommend it.

935
00:44:14,533 --> 00:44:17,053
Speaker 3: That's the recommendation at the end.

936
00:44:17,253 --> 00:44:20,212
Speaker 4: That's quite a sentence. Though the robot did the soaring, etc.

937
00:44:21,613 --> 00:44:23,293
Speaker 3: That's all you need to know if you have the patient.

938
00:44:23,653 --> 00:44:26,533
Speaker 2: So right now, there's a lot of robotic surgery being done,

939
00:44:26,613 --> 00:44:31,853
Speaker 2: but it's normally being kind of remote controlled by the surgeon.

940
00:44:32,093 --> 00:44:34,573
Speaker 2: So the surgeon is placing it and it's doing some

941
00:44:34,613 --> 00:44:38,013
Speaker 2: fine stuff and it's just steady hands and can operate

942
00:44:38,053 --> 00:44:41,333
Speaker 2: in minute areas. But there is surgery now that has

943
00:44:41,333 --> 00:44:43,893
Speaker 2: started to happen more and more where the surgeons just

944
00:44:44,013 --> 00:44:45,733
Speaker 2: on the other side of the room let letting the

945
00:44:45,813 --> 00:44:47,053
Speaker 2: robot do do its thing.

946
00:44:47,573 --> 00:44:49,252
Speaker 4: And we talked about them in the show a couple

947
00:44:49,293 --> 00:44:50,732
Speaker 4: of weeks ago. There was a.

948
00:44:50,613 --> 00:44:54,253
Speaker 2: Claim that in five years these robot surgeons doing complete

949
00:44:54,253 --> 00:44:57,093
Speaker 2: themselves will be better than the best surgeons. So that's

950
00:44:57,453 --> 00:44:59,533
Speaker 2: that's going to raise some questions. But you've got to say,

951
00:44:59,573 --> 00:45:02,613
Speaker 2: for waiting lists, if you can just get the surgeons,

952
00:45:02,773 --> 00:45:05,373
Speaker 2: these the robotic surgeon going through working twenty four hours

953
00:45:05,413 --> 00:45:07,973
Speaker 2: a day, blast people's hips, get it all.

954
00:45:07,853 --> 00:45:11,453
Speaker 4: Done being banged, you know?

955
00:45:11,653 --> 00:45:12,613
Speaker 3: Yeah, disgusted?

956
00:45:12,973 --> 00:45:13,733
Speaker 4: Are you AI?

957
00:45:14,653 --> 00:45:17,653
Speaker 2: Matt Sisus texture No, But I would say that, wouldn't

958
00:45:17,653 --> 00:45:19,493
Speaker 2: I If I was AI, I would say that I

959
00:45:19,533 --> 00:45:21,893
Speaker 2: wasn't just take my job very suspicious?

960
00:45:21,933 --> 00:45:24,333
Speaker 4: So no, I'm not, Yeah, or am I?

961
00:45:25,693 --> 00:45:30,652
Speaker 3: You will never know, Malcolm, you reckon your your job?

962
00:45:30,733 --> 00:45:31,453
Speaker 3: Is AI proof?

963
00:45:32,333 --> 00:45:37,013
Speaker 18: I think I'm pretty safe. Yeah. I find leaks and buildings.

964
00:45:37,013 --> 00:45:39,773
Speaker 18: I specialize in finding leaks in waterfrick membranes with it.

965
00:45:40,013 --> 00:45:44,133
Speaker 18: Dtake New Zealand, so we we look at buildings we

966
00:45:44,213 --> 00:45:46,813
Speaker 18: got leaks and we find them can point them down

967
00:45:46,813 --> 00:45:47,293
Speaker 18: to a been here.

968
00:45:47,613 --> 00:45:53,213
Speaker 4: We have the technology, So why couldn't a robot with

969
00:45:53,293 --> 00:45:57,813
Speaker 4: the same scanning equipment find the same things as you, Malcolm,

970
00:45:58,453 --> 00:46:00,413
Speaker 4: Because you've got.

971
00:46:00,813 --> 00:46:03,493
Speaker 18: You've got the human factor that you're dealing with. So

972
00:46:03,693 --> 00:46:05,493
Speaker 18: you know, if people took care of business looking out

973
00:46:05,453 --> 00:46:08,573
Speaker 18: of business, that's folly to look at it. But you

974
00:46:08,653 --> 00:46:11,652
Speaker 18: get a waterfric membrane, say, for example, on the roof

975
00:46:11,693 --> 00:46:14,653
Speaker 18: gets put down and waterproof does the job. He puts

976
00:46:14,653 --> 00:46:16,933
Speaker 18: it down to the great job and then you know

977
00:46:17,813 --> 00:46:21,053
Speaker 18: some of the contractor comes around afterwards and bangs a

978
00:46:21,093 --> 00:46:24,133
Speaker 18: hole in it somehow. Now you've got a you know,

979
00:46:24,333 --> 00:46:27,013
Speaker 18: go understand the material that you're dealing with, which you

980
00:46:27,093 --> 00:46:29,172
Speaker 18: can teach to a certain extent I expect, but there's

981
00:46:29,173 --> 00:46:32,853
Speaker 18: also that experience that comes along with it, and you

982
00:46:32,933 --> 00:46:35,693
Speaker 18: get different anomalies of what people do in order to

983
00:46:35,733 --> 00:46:40,853
Speaker 18: make holes and holes. And so you've got you've got

984
00:46:40,893 --> 00:46:45,293
Speaker 18: different materials. You like porch on, you've got what's called

985
00:46:45,293 --> 00:46:47,813
Speaker 18: TPOs and PVCs, a different popes of materials to your

986
00:46:48,053 --> 00:46:52,413
Speaker 18: membrane roof here liquids, you know, and you know people

987
00:46:52,453 --> 00:46:54,213
Speaker 18: do all kinds of some crazy things to get but

988
00:46:54,573 --> 00:46:57,533
Speaker 18: order proven does this job, beautiful job. And then somebody

989
00:46:57,533 --> 00:47:00,333
Speaker 18: else comes along and just when you think, I think

990
00:47:00,333 --> 00:47:02,333
Speaker 18: you've seen it all for somebody doing damage to other

991
00:47:02,333 --> 00:47:04,253
Speaker 18: person's work, they come up with something new.

992
00:47:04,733 --> 00:47:05,692
Speaker 4: How long are you doing that?

993
00:47:05,693 --> 00:47:05,773
Speaker 5: For?

994
00:47:05,933 --> 00:47:08,293
Speaker 16: Malcolm Las few years?

995
00:47:09,133 --> 00:47:11,893
Speaker 18: I came back from Australia, did Astura for a few years.

996
00:47:11,933 --> 00:47:18,453
Speaker 18: I've brought the technology back here and and yeah, out

997
00:47:18,493 --> 00:47:22,213
Speaker 18: of the hundreds of one thousands of test things that

998
00:47:22,213 --> 00:47:27,653
Speaker 18: have done, i'd probably say that ninety percent of failure

999
00:47:27,653 --> 00:47:28,573
Speaker 18: are caused by people.

1000
00:47:29,293 --> 00:47:30,813
Speaker 2: Right, So do you get when you're looking at the

1001
00:47:30,853 --> 00:47:34,493
Speaker 2: situation you're saying that there's something in your humanity that

1002
00:47:34,613 --> 00:47:38,413
Speaker 2: means that you get the idea that something might be

1003
00:47:38,453 --> 00:47:41,133
Speaker 2: wrong and where it is just by your experience of

1004
00:47:41,173 --> 00:47:44,573
Speaker 2: how things are, how things have been layered.

1005
00:47:44,853 --> 00:47:47,853
Speaker 18: Yeah, the experience. The experience tells you a lot. Like

1006
00:47:47,933 --> 00:47:53,533
Speaker 18: if you're depending on the environment, how how it's been there,

1007
00:47:53,733 --> 00:47:57,293
Speaker 18: how many you know, what's the condition of the of

1008
00:47:57,413 --> 00:48:00,573
Speaker 18: the roof at the time, and from there you can

1009
00:48:00,653 --> 00:48:02,093
Speaker 18: you start to build up a picture and then you

1010
00:48:02,093 --> 00:48:03,692
Speaker 18: can go right, I think I'm going to start looking

1011
00:48:03,693 --> 00:48:06,053
Speaker 18: in this direction. I I didn't want to Wellington where

1012
00:48:06,053 --> 00:48:09,613
Speaker 18: the guy when on lame thing key, where the guys

1013
00:48:09,613 --> 00:48:11,853
Speaker 18: are saying, we think the leak is coming from here

1014
00:48:12,653 --> 00:48:17,133
Speaker 18: this area, and no it's I think it's funning. It's

1015
00:48:17,213 --> 00:48:20,573
Speaker 18: outside the zone of where you're talking about. And we

1016
00:48:20,733 --> 00:48:22,293
Speaker 18: kicked all the area that they thought it was and

1017
00:48:22,773 --> 00:48:24,893
Speaker 18: I couldn't find a leak. Thought I'm not that bad

1018
00:48:24,933 --> 00:48:26,533
Speaker 18: at it, so I thought I must I must be

1019
00:48:26,533 --> 00:48:29,893
Speaker 18: doing something wrong. But anyway, sure enough, went with my gut,

1020
00:48:29,933 --> 00:48:31,853
Speaker 18: went outside the area that they thought it wasn't I

1021
00:48:31,933 --> 00:48:34,933
Speaker 18: found it. It was coming from an area you would

1022
00:48:34,933 --> 00:48:37,413
Speaker 18: think would be completely unrelated to where the leak was coming.

1023
00:48:37,453 --> 00:48:40,893
Speaker 4: Internally, you're the leak whisperer. You're like a leak diviner

1024
00:48:41,573 --> 00:48:42,253
Speaker 4: and awes.

1025
00:48:42,853 --> 00:48:45,973
Speaker 18: I wouldn't. I wouldn't call myself that. But but yeah,

1026
00:48:45,973 --> 00:48:47,813
Speaker 18: when you have to, like the goo buses, you.

1027
00:48:47,853 --> 00:48:50,613
Speaker 4: Have the tools, you have the talent, and so if

1028
00:48:50,613 --> 00:48:52,293
Speaker 4: you if this was day one, when you know, ask

1029
00:48:52,373 --> 00:48:54,173
Speaker 4: how long you've been doing it on day one, you

1030
00:48:54,213 --> 00:48:58,173
Speaker 4: wouldn't necessarily have the sense of where the problem is

1031
00:48:58,253 --> 00:49:00,652
Speaker 4: that you would have in year five. If you see

1032
00:49:00,653 --> 00:49:01,133
Speaker 4: what I'm saying.

1033
00:49:01,813 --> 00:49:04,253
Speaker 18: Well, probably not to the same extent, but I come

1034
00:49:04,293 --> 00:49:07,773
Speaker 18: from a construction background, I mean quantity survey originally, so yeah,

1035
00:49:07,933 --> 00:49:09,853
Speaker 18: I was. You know, you're taught and you learn all

1036
00:49:09,853 --> 00:49:13,133
Speaker 18: about construction. It's like any job, I mean, first job,

1037
00:49:14,093 --> 00:49:16,893
Speaker 18: even accountant. You're not dealing with high intact you're dealing

1038
00:49:16,893 --> 00:49:19,973
Speaker 18: with you know, you might be just dealing with the

1039
00:49:20,573 --> 00:49:23,573
Speaker 18: day to day alleges or something of people. But it

1040
00:49:23,573 --> 00:49:26,173
Speaker 18: comes with experience. But there were certain things that you

1041
00:49:26,253 --> 00:49:29,453
Speaker 18: can't teach. It's like, I remember all I had to

1042
00:49:29,493 --> 00:49:32,293
Speaker 18: work with. She said, teach me everything I know about

1043
00:49:34,093 --> 00:49:37,533
Speaker 18: this particular topic. And it's like, well, can't answer that

1044
00:49:37,693 --> 00:49:40,093
Speaker 18: because you don't know what you don't know until you

1045
00:49:40,173 --> 00:49:42,733
Speaker 18: asked the question, where you know, you just have to

1046
00:49:42,933 --> 00:49:45,933
Speaker 18: teach the basics and then as you come across things,

1047
00:49:45,973 --> 00:49:48,093
Speaker 18: you can go, oh, yeah, I've seen that before. It

1048
00:49:48,253 --> 00:49:52,373
Speaker 18: was X Y Z, and that's but that comes the

1049
00:49:52,413 --> 00:49:55,733
Speaker 18: experience in any role. But if we're but it's like

1050
00:49:55,773 --> 00:49:58,533
Speaker 18: a person I spoke with one, so we're into a

1051
00:49:58,573 --> 00:50:02,013
Speaker 18: shop to buy something. You know, it didn't quite see

1052
00:50:02,053 --> 00:50:05,053
Speaker 18: the relationship between me arriving in the shop and actually

1053
00:50:05,493 --> 00:50:08,013
Speaker 18: them having a job. You know, I walked in there

1054
00:50:08,053 --> 00:50:09,693
Speaker 18: to buy something and the first thing that says, so,

1055
00:50:09,853 --> 00:50:11,533
Speaker 18: I'm going on our shelves. Have you tried looking for

1056
00:50:11,613 --> 00:50:17,493
Speaker 18: it online? Wow, I'm saying rather than saying, yeah, we

1057
00:50:17,613 --> 00:50:19,172
Speaker 18: haven't got at the moment, but let me take your

1058
00:50:19,213 --> 00:50:21,172
Speaker 18: name a number and I'll call you when it's coming in.

1059
00:50:21,533 --> 00:50:21,733
Speaker 16: You know.

1060
00:50:26,133 --> 00:50:28,533
Speaker 18: Yeah, So you would think as an employee, you know,

1061
00:50:28,613 --> 00:50:30,093
Speaker 18: the first thing you want to be doing is saying

1062
00:50:30,173 --> 00:50:33,613
Speaker 18: not promoting AI before so that you still have a job.

1063
00:50:34,013 --> 00:50:36,373
Speaker 18: We still have people that can, but you're always going

1064
00:50:36,413 --> 00:50:41,213
Speaker 18: to need the human factor because people do things that

1065
00:50:41,853 --> 00:50:43,893
Speaker 18: the computer is going to go, What the heck is

1066
00:50:43,933 --> 00:50:46,373
Speaker 18: that you know? It's just going to go I've never

1067
00:50:46,413 --> 00:50:49,533
Speaker 18: seen that before. Computer says no, shuts down, and the

1068
00:50:49,693 --> 00:50:52,093
Speaker 18: splashes a big red placing right until someone tells how

1069
00:50:52,093 --> 00:50:54,053
Speaker 18: to deal with it. Because there is a point that,

1070
00:50:54,493 --> 00:50:57,053
Speaker 18: like I said, with the human factor, you can't you

1071
00:50:57,093 --> 00:51:00,413
Speaker 18: can't program for that. Ye belief you can anyway.

1072
00:51:00,573 --> 00:51:03,773
Speaker 2: Thank you for your cool Malcoln appreciate it. Yeah, I mean,

1073
00:51:03,813 --> 00:51:06,172
Speaker 2: it's just can we get our hit around the magnitude

1074
00:51:06,453 --> 00:51:08,693
Speaker 2: of of what.

1075
00:51:09,133 --> 00:51:09,653
Speaker 1: It can do?

1076
00:51:09,813 --> 00:51:12,093
Speaker 2: Though, because I think sometimes we think it can't do

1077
00:51:12,133 --> 00:51:15,053
Speaker 2: something and then six months later it can While we're

1078
00:51:15,093 --> 00:51:17,613
Speaker 2: talking about AI, do you think your job is replaceable

1079
00:51:17,853 --> 00:51:20,893
Speaker 2: or not? Bill Gates reckons teachers and doctors are done.

1080
00:51:21,053 --> 00:51:24,613
Speaker 2: But Bell Gates may be an AI, so you don't know.

1081
00:51:24,853 --> 00:51:25,973
Speaker 2: You don't know if you can trust him.

1082
00:51:26,253 --> 00:51:28,253
Speaker 3: Is he right? Oh, eight hundred and eighty ten eighty

1083
00:51:28,453 --> 00:51:30,853
Speaker 3: And if you're have been in a job where you

1084
00:51:30,973 --> 00:51:33,693
Speaker 3: were replaced by AI or let go because the company

1085
00:51:33,693 --> 00:51:37,173
Speaker 3: decided to outsource to artificial intelligence, love to hear from you.

1086
00:51:37,253 --> 00:51:38,493
Speaker 3: It is eighteen past two.

1087
00:51:39,013 --> 00:51:43,493
Speaker 1: Wow your home of Afternoon Talk, Mad Heathen Taylor Adams

1088
00:51:43,653 --> 00:51:47,652
Speaker 1: afternoons call Oh eight hundred eighty ten eighty us Talk said, be.

1089
00:51:49,493 --> 00:51:52,212
Speaker 3: Afternoon to you twenty one past two, and we're talking

1090
00:51:52,253 --> 00:51:55,413
Speaker 3: about artificial intelligence and where they you think it may

1091
00:51:55,493 --> 00:51:58,253
Speaker 3: take your job or not a lot of people are

1092
00:51:58,253 --> 00:52:00,933
Speaker 3: calling up saying that they think their job as AI

1093
00:52:01,053 --> 00:52:02,533
Speaker 3: proof and we want to hear from you if you

1094
00:52:02,573 --> 00:52:03,293
Speaker 3: think that shit.

1095
00:52:03,213 --> 00:52:05,772
Speaker 4: Well, it's amazing because you know, sometimes you see something

1096
00:52:05,813 --> 00:52:06,773
Speaker 4: that proves.

1097
00:52:06,413 --> 00:52:09,252
Speaker 2: How crazy and weird and random humanity is. Because there's

1098
00:52:09,253 --> 00:52:10,973
Speaker 2: a text here that thinks that Bill Gates is in

1099
00:52:11,053 --> 00:52:14,652
Speaker 2: a dick. You two afternoon bars lost me with one

1100
00:52:14,693 --> 00:52:18,573
Speaker 2: of those ignorant swipes at the philanthropist Bill Gates's character.

1101
00:52:19,493 --> 00:52:21,133
Speaker 4: How dare you buy forever?

1102
00:52:22,973 --> 00:52:25,493
Speaker 2: If either that's like an evil AI robot or it's

1103
00:52:25,533 --> 00:52:29,733
Speaker 2: just a proof that humanity is just so crazy that

1104
00:52:29,813 --> 00:52:31,613
Speaker 2: someone would think that Bill Gates wasn't a dick.

1105
00:52:31,813 --> 00:52:34,053
Speaker 3: That feels like it was written by check GBT. I

1106
00:52:34,093 --> 00:52:35,773
Speaker 3: mean it started to trail off towards the end and

1107
00:52:35,773 --> 00:52:38,573
Speaker 3: got a bit confused, So that feels like early AI

1108
00:52:38,653 --> 00:52:39,893
Speaker 3: to me. Maybe Bill Gates are off.

1109
00:52:39,973 --> 00:52:42,293
Speaker 2: Yeah, And also the spelling boar in a different way,

1110
00:52:42,533 --> 00:52:45,613
Speaker 2: like it's not we're not running around in the but

1111
00:52:45,693 --> 00:52:46,573
Speaker 2: that's what the AI does.

1112
00:52:46,613 --> 00:52:47,493
Speaker 4: It puts in a little mistakes.

1113
00:52:49,173 --> 00:52:50,493
Speaker 3: You're almost had you put.

1114
00:52:50,333 --> 00:52:50,652
Speaker 4: Them in there.

1115
00:52:50,693 --> 00:52:52,973
Speaker 2: You're writing boor as if we've got like little horns,

1116
00:52:52,973 --> 00:52:54,053
Speaker 2: we're running around in the bush.

1117
00:52:54,133 --> 00:52:56,093
Speaker 4: Yeah, anyway, we see you, We see you.

1118
00:52:56,573 --> 00:52:59,013
Speaker 2: AI will do everything if we let it, so we

1119
00:52:59,093 --> 00:53:01,573
Speaker 2: must decide not to let it. Just because something is

1120
00:53:01,653 --> 00:53:03,812
Speaker 2: possible does not make it right. One hundred percent agree

1121
00:53:03,853 --> 00:53:05,893
Speaker 2: with that. But it's the problem is that no one's

1122
00:53:05,893 --> 00:53:09,453
Speaker 2: going to stop because if one, say, for example, of America,

1123
00:53:09,573 --> 00:53:13,093
Speaker 2: wants to put some restrictions on what AI does, China won't,

1124
00:53:13,853 --> 00:53:15,813
Speaker 2: so then America won't.

1125
00:53:16,133 --> 00:53:18,172
Speaker 3: It's an arms race, and you never stop an arm.

1126
00:53:18,133 --> 00:53:21,693
Speaker 4: So no one wants to be behind when this singularity comes.

1127
00:53:21,773 --> 00:53:23,573
Speaker 2: That's for sure. You want the singularity to happen in

1128
00:53:23,613 --> 00:53:26,453
Speaker 2: your country. Good quote on X Today. You know what

1129
00:53:26,453 --> 00:53:29,733
Speaker 2: the biggest problem with pushing all things AI is wrong direction.

1130
00:53:29,893 --> 00:53:32,493
Speaker 2: I want AI to do my laundry and dishes so

1131
00:53:32,533 --> 00:53:34,133
Speaker 2: that I can do art and writing.

1132
00:53:34,213 --> 00:53:36,373
Speaker 4: Not for AI to do my art and writing.

1133
00:53:37,573 --> 00:53:38,252
Speaker 3: It's very good.

1134
00:53:38,533 --> 00:53:40,253
Speaker 4: I mean, that's the whole problem with it, isn't it.

1135
00:53:40,293 --> 00:53:42,692
Speaker 3: I heard it in an analogy, you know, with if

1136
00:53:42,733 --> 00:53:45,613
Speaker 3: AI becomes all powerful and takes care of everything in

1137
00:53:45,653 --> 00:53:49,013
Speaker 3: our lives, that the analogy was we effectively become housecats

1138
00:53:49,413 --> 00:53:52,293
Speaker 3: that we get fed, we get looked after, we don't

1139
00:53:52,333 --> 00:53:55,333
Speaker 3: really mind where the food comes from, and we just

1140
00:53:55,413 --> 00:53:57,813
Speaker 3: live these little, happy lives where everything gets taken care

1141
00:53:57,853 --> 00:54:00,533
Speaker 3: of things for us. And I kind of like that analogy.

1142
00:54:00,573 --> 00:54:03,053
Speaker 3: We just become housecats. As human beings, I let the

1143
00:54:03,133 --> 00:54:03,773
Speaker 3: robots take over.

1144
00:54:03,893 --> 00:54:06,013
Speaker 2: If our minds aren't right, we'll make a nightmare of

1145
00:54:06,013 --> 00:54:08,613
Speaker 2: wherever we end up. Wherever this humans there's politics. I

1146
00:54:08,653 --> 00:54:12,093
Speaker 2: know a farmer that has robots smoking his cows, says Don, Yeah,

1147
00:54:12,093 --> 00:54:13,853
Speaker 2: that's kind of what you're talking about. That the cows

1148
00:54:13,933 --> 00:54:15,533
Speaker 2: just go in, they don't care, they just wander up,

1149
00:54:15,613 --> 00:54:16,732
Speaker 2: get milk walked out again.

1150
00:54:17,693 --> 00:54:18,533
Speaker 4: Now this is interesting.

1151
00:54:18,533 --> 00:54:20,733
Speaker 2: This is on We were talking before about the farm

1152
00:54:20,813 --> 00:54:24,653
Speaker 2: robots that a caller's daughter was working on. Just driving

1153
00:54:24,693 --> 00:54:27,373
Speaker 2: down the beautiful Dunedin Peninsula, admiring the green hills and

1154
00:54:27,413 --> 00:54:30,693
Speaker 2: lovely vista. Your talk of mechanical entities roaming across the

1155
00:54:30,773 --> 00:54:33,653
Speaker 2: hills doing gardening and lawns brings to mind those creatures

1156
00:54:33,693 --> 00:54:36,613
Speaker 2: on War of the World. Would we be better for it?

1157
00:54:36,693 --> 00:54:39,453
Speaker 2: Humanity is slowly being made redundant. Sorry for ruining your

1158
00:54:39,493 --> 00:54:42,093
Speaker 2: drive across the beautiful Peninsua. I absolutely love it out

1159
00:54:42,133 --> 00:54:44,732
Speaker 2: that way, how dam but eyes on the road as well.

1160
00:54:44,933 --> 00:54:46,732
Speaker 3: Yeah, yeah, it's very easy to go into the drink

1161
00:54:46,773 --> 00:54:51,133
Speaker 3: along the peninsula exactly, is it, Evan?

1162
00:54:51,213 --> 00:54:51,413
Speaker 15: Ash?

1163
00:54:51,533 --> 00:54:52,053
Speaker 3: Have I said that?

1164
00:54:52,133 --> 00:54:52,373
Speaker 16: Ryan?

1165
00:54:53,693 --> 00:54:55,373
Speaker 10: Yeah, it is a nice share.

1166
00:54:55,413 --> 00:54:55,853
Speaker 5: How are you?

1167
00:54:56,253 --> 00:54:56,733
Speaker 9: Very thanks?

1168
00:54:56,933 --> 00:55:00,293
Speaker 2: You will work and it so you'll probably be on

1169
00:55:00,333 --> 00:55:03,493
Speaker 2: the cold face of AI developments.

1170
00:55:04,773 --> 00:55:08,413
Speaker 19: I am not a quarter as we call it, and

1171
00:55:08,493 --> 00:55:12,173
Speaker 19: that I don't write code, but I am in the

1172
00:55:12,213 --> 00:55:15,493
Speaker 19: sect and I I've got a lot of friends who

1173
00:55:16,013 --> 00:55:20,893
Speaker 19: work in the sector and or rather who do coding,

1174
00:55:21,093 --> 00:55:24,013
Speaker 19: and what I have learned from them in the last

1175
00:55:24,133 --> 00:55:34,733
Speaker 19: couple of months is that eventually, especially programmers, those jobs.

1176
00:55:34,453 --> 00:55:36,173
Speaker 9: Could possibly be taken by AI.

1177
00:55:36,373 --> 00:55:37,893
Speaker 10: So he's given me an example.

1178
00:55:37,973 --> 00:55:43,973
Speaker 19: So this lad is in the States and works for Amazon,

1179
00:55:44,293 --> 00:55:49,093
Speaker 19: and he is pretty senior. He's been quoting for like

1180
00:55:49,373 --> 00:55:50,733
Speaker 19: thirty five odd years.

1181
00:55:51,973 --> 00:55:53,653
Speaker 20: And this guy.

1182
00:55:55,013 --> 00:55:59,613
Speaker 19: Has like just to test out the AI, ask the

1183
00:55:59,653 --> 00:56:03,653
Speaker 19: AI engine to write a program which, in his opinion,

1184
00:56:03,893 --> 00:56:07,093
Speaker 19: even for him who's been quoting for such a long time,

1185
00:56:07,653 --> 00:56:09,212
Speaker 19: would take somewhere.

1186
00:56:08,933 --> 00:56:12,013
Speaker 10: Up to a week of work, which is forty hours.

1187
00:56:12,533 --> 00:56:17,853
Speaker 19: And the AI wrote that through overnight and it was

1188
00:56:18,013 --> 00:56:19,253
Speaker 19: absolutely spot on.

1189
00:56:19,933 --> 00:56:21,933
Speaker 5: So that's what we are talking about.

1190
00:56:23,093 --> 00:56:25,133
Speaker 2: Right, So, I mean, you could argue that as a

1191
00:56:25,173 --> 00:56:29,453
Speaker 2: percentage that needs you know, twenty percent of the people.

1192
00:56:29,693 --> 00:56:32,653
Speaker 2: Then you know, if you're doing it overnight, you know

1193
00:56:32,853 --> 00:56:35,893
Speaker 2: all the people, the hours that are going to be

1194
00:56:35,893 --> 00:56:38,573
Speaker 2: just you lose four hours of employment, four days of

1195
00:56:38,613 --> 00:56:40,413
Speaker 2: employment for someone.

1196
00:56:40,733 --> 00:56:44,253
Speaker 19: And actually, what is happening because of that, all the

1197
00:56:44,493 --> 00:56:51,573
Speaker 19: inn three level jobs in the US, especially for the programmers,

1198
00:56:53,213 --> 00:56:59,093
Speaker 19: they are becoming scarce and scarce. And these guys are

1199
00:56:59,093 --> 00:57:06,613
Speaker 19: not anything, to be honest, the computer science engineers and programmers,

1200
00:57:06,893 --> 00:57:10,293
Speaker 19: so it is tough times have to realign what they

1201
00:57:10,333 --> 00:57:12,333
Speaker 19: would like to do in the sense there are other

1202
00:57:12,413 --> 00:57:13,893
Speaker 19: other things that you can do in it.

1203
00:57:14,853 --> 00:57:18,453
Speaker 10: But I think one of the major.

1204
00:57:19,653 --> 00:57:25,133
Speaker 19: Job creation in it was programming and that seems will

1205
00:57:25,133 --> 00:57:26,013
Speaker 19: be taken away.

1206
00:57:26,413 --> 00:57:27,493
Speaker 4: Thank you so much for your call.

1207
00:57:27,693 --> 00:57:28,973
Speaker 3: Yeah, he's got points.

1208
00:57:29,053 --> 00:57:31,733
Speaker 4: Although it is it is grind and grind and grind

1209
00:57:31,733 --> 00:57:32,973
Speaker 4: when famously.

1210
00:57:33,173 --> 00:57:35,613
Speaker 2: It people are just coming in and turning and turning

1211
00:57:35,613 --> 00:57:36,933
Speaker 2: the computer off and back on again.

1212
00:57:36,773 --> 00:57:37,053
Speaker 1: An't they?

1213
00:57:37,173 --> 00:57:39,213
Speaker 4: Yeah, it works, it doesn't it the past to keep

1214
00:57:39,253 --> 00:57:41,333
Speaker 4: the pambamy keeps their jobs for a very long time.

1215
00:57:41,533 --> 00:57:43,613
Speaker 3: The center of the job and it works.

1216
00:57:43,933 --> 00:57:44,133
Speaker 16: Right.

1217
00:57:44,213 --> 00:57:46,213
Speaker 3: We are going to take more of your phone calls

1218
00:57:46,293 --> 00:57:48,173
Speaker 3: very shortly. Oh eight hundred and eighty teen eighty. It

1219
00:57:48,253 --> 00:57:49,573
Speaker 3: is twenty seven past two.

1220
00:57:53,733 --> 00:57:57,093
Speaker 1: Matt Heath and Tyler Adams afternoons call oh eight hundred

1221
00:57:57,093 --> 00:57:59,213
Speaker 1: and eighty ten eighty on Youth Talks, EDB.

1222
00:57:59,493 --> 00:58:00,293
Speaker 3: Yu Talks, Ed B.

1223
00:58:00,493 --> 00:58:00,893
Speaker 19: Bernard.

1224
00:58:01,013 --> 00:58:04,373
Speaker 3: What's your view of of artificial intelligence in the job market?

1225
00:58:05,533 --> 00:58:09,173
Speaker 20: Yeah, good, afternoons. Just some of the previous callers were

1226
00:58:09,333 --> 00:58:12,413
Speaker 20: making mention of the fact that you know there will

1227
00:58:12,413 --> 00:58:15,253
Speaker 20: always be the human element, et cetera. That reminded me

1228
00:58:15,333 --> 00:58:18,413
Speaker 20: of some conversation that I witnessed back in the mid eighties.

1229
00:58:18,453 --> 00:58:22,293
Speaker 20: To modulate eighties in in the good old video video

1230
00:58:22,373 --> 00:58:27,973
Speaker 20: store video Movie where you enter rent videos, and it

1231
00:58:28,013 --> 00:58:30,293
Speaker 20: was just at the time when DVDs were starting to

1232
00:58:30,293 --> 00:58:32,973
Speaker 20: come out, and I one of the customers asked the

1233
00:58:33,013 --> 00:58:35,853
Speaker 20: owner of the store, you know, what's the impact of

1234
00:58:35,893 --> 00:58:38,573
Speaker 20: these DVD is going to be on your video business?

1235
00:58:38,613 --> 00:58:42,333
Speaker 21: And he very proudly said, you know what, There'll always

1236
00:58:42,333 --> 00:58:44,813
Speaker 21: be videos, because how on earth else would you be

1237
00:58:44,853 --> 00:58:50,093
Speaker 21: a video recording programs off the TV. I find that

1238
00:58:50,213 --> 00:58:52,853
Speaker 21: pretty funny because if you think back between what happened

1239
00:58:52,893 --> 00:58:57,373
Speaker 21: between vhs and where we are today, I think very

1240
00:58:57,373 --> 00:59:01,013
Speaker 21: few people truly understand the capability of what that AI

1241
00:59:01,133 --> 00:59:03,893
Speaker 21: will have in the future. And I think we should

1242
00:59:03,933 --> 00:59:06,653
Speaker 21: be very careful to say things like that, they'll always

1243
00:59:06,653 --> 00:59:09,253
Speaker 21: be the element of the human being, you know, don't.

1244
00:59:09,453 --> 00:59:11,613
Speaker 4: Yeah, yeah, well, I mean read Hastings.

1245
00:59:11,613 --> 00:59:13,333
Speaker 2: I read his book you Know the Sea Over and

1246
00:59:13,413 --> 00:59:17,053
Speaker 2: you know, the founder of Netflix going into Blockbuster Video

1247
00:59:17,373 --> 00:59:19,693
Speaker 2: and saying, do you want to buy Netflix for fifty

1248
00:59:20,173 --> 00:59:22,013
Speaker 2: million dollars? And they laughed him out of the office

1249
00:59:22,133 --> 00:59:24,533
Speaker 2: because idiots, because they hadn't seen what was going to

1250
00:59:24,773 --> 00:59:28,613
Speaker 2: come with streaming. Yeah, you know, and good luck finding

1251
00:59:28,653 --> 00:59:31,533
Speaker 2: a DVD store. I saw Conon O'Brien must go the

1252
00:59:31,573 --> 00:59:33,373
Speaker 2: TV show and he found there is still a video

1253
00:59:33,413 --> 00:59:36,213
Speaker 2: store and DVD store in New Zealand somewhere. Can't remember

1254
00:59:36,253 --> 00:59:38,133
Speaker 2: exactly where it is. Someone will tell me where it is.

1255
00:59:39,133 --> 00:59:40,213
Speaker 2: Eighty is it Littleton?

1256
00:59:40,253 --> 00:59:44,173
Speaker 3: Littleton? And he rents out videos and DVDs as well.

1257
00:59:44,253 --> 00:59:46,493
Speaker 3: Still going well, I think it's still going well. Oh,

1258
00:59:46,533 --> 00:59:48,053
Speaker 3: look up the name. But if you know nine two

1259
00:59:48,173 --> 00:59:49,413
Speaker 3: nine two, please let us know.

1260
00:59:49,653 --> 00:59:50,973
Speaker 4: Thank you so much for your call, Burnett.

1261
00:59:51,053 --> 00:59:53,573
Speaker 3: Yeah, that was a great discussion. Thank you very much

1262
00:59:53,573 --> 00:59:55,133
Speaker 3: to everyone who phoned and called on that one.

1263
00:59:55,133 --> 00:59:56,853
Speaker 4: Shall I just finish with this text?

1264
00:59:56,933 --> 00:59:57,253
Speaker 3: Please?

1265
00:59:57,533 --> 01:00:00,893
Speaker 4: AI cannot love. It has no compassion. If we allow

1266
01:00:00,973 --> 01:00:03,653
Speaker 4: AI and everything, our children will lose the ability to love.

1267
01:00:03,733 --> 01:00:07,133
Speaker 4: AI needs to stay out of teaching medicine and psychology

1268
01:00:07,453 --> 01:00:11,453
Speaker 4: or we risk him. Unfortunately, it's already in teaching medicine

1269
01:00:11,493 --> 01:00:14,133
Speaker 4: and psychology, so we are risky our humanity.

1270
01:00:13,813 --> 01:00:15,293
Speaker 3: And it will learn how to love you. So don't

1271
01:00:15,333 --> 01:00:19,653
Speaker 3: worry about that. Right, good discussion coming up headlines with

1272
01:00:19,733 --> 01:00:23,573
Speaker 3: ray Lane, then let's have a chat about what responsibility

1273
01:00:23,613 --> 01:00:27,093
Speaker 3: your company has if you want to heckel politicians and

1274
01:00:27,093 --> 01:00:29,653
Speaker 3: be a bit rowdy in public. That is coming up

1275
01:00:29,773 --> 01:00:32,053
Speaker 3: very shortly. It is twenty nine to three.

1276
01:00:34,733 --> 01:00:35,333
Speaker 4: US talks.

1277
01:00:35,333 --> 01:00:38,933
Speaker 15: It'd be headlines with blue bubble taxis. It's no trouble

1278
01:00:39,013 --> 01:00:42,853
Speaker 15: with a blue bubble. The Electricity Authority says New Zealand's

1279
01:00:42,893 --> 01:00:46,213
Speaker 15: looking good for winter in terms of having enough stored

1280
01:00:46,373 --> 01:00:50,013
Speaker 15: energy and supply. It says we'll help by good hydrolate

1281
01:00:50,133 --> 01:00:53,253
Speaker 15: levels after rain and a gas supply boosts from a

1282
01:00:53,293 --> 01:00:58,253
Speaker 15: deal with heavy user method X. Fear of retaliation has

1283
01:00:58,333 --> 01:01:02,453
Speaker 15: led New Zealand to abandon a digital services tax introduced

1284
01:01:02,453 --> 01:01:06,933
Speaker 15: to tax KEIW revenue of platforms like Facebook and Google.

1285
01:01:07,453 --> 01:01:10,613
Speaker 15: In February, Donald Trump threatened to act against attempts he

1286
01:01:10,733 --> 01:01:16,533
Speaker 15: describes as oversees extortion. The Finance Minister's promising money saved

1287
01:01:16,613 --> 01:01:21,173
Speaker 15: by government changes to pay equity law or go into education, health,

1288
01:01:21,213 --> 01:01:25,413
Speaker 15: police and defense. The new law rushed through under urgency,

1289
01:01:25,813 --> 01:01:31,653
Speaker 15: largely affects women workers. Under Needin police officers suffered an

1290
01:01:31,693 --> 01:01:34,933
Speaker 15: asthma attack when a man being arrested spray deodorant in

1291
01:01:34,973 --> 01:01:38,533
Speaker 15: her face this morning. More than fifteen hundred Ministry of

1292
01:01:38,653 --> 01:01:42,293
Speaker 15: Education staff are walking off the job this afternoon for

1293
01:01:42,333 --> 01:01:46,733
Speaker 15: the first time in two decades, protesting a pay freeze.

1294
01:01:47,053 --> 01:01:50,813
Speaker 15: Madame and Davidson on why the budget needs to fund communities,

1295
01:01:51,173 --> 01:01:54,333
Speaker 15: not corporate greed. You can see her full column at

1296
01:01:54,373 --> 01:01:57,573
Speaker 15: ends at Herald Premium. Now back to matt Ethan Tyler Adams.

1297
01:01:57,613 --> 01:01:59,973
Speaker 3: Thank you very much, Raylene. So what power does your

1298
01:01:59,973 --> 01:02:03,893
Speaker 3: employer have over you when it comes to heckling politicians

1299
01:02:03,973 --> 01:02:07,253
Speaker 3: protesting bad behavior, arguably in public?

1300
01:02:07,453 --> 01:02:09,213
Speaker 2: Just going to stop you for second there, Yeah, please

1301
01:02:09,253 --> 01:02:11,373
Speaker 2: before we go into this key topic. Yeah, you were

1302
01:02:11,413 --> 01:02:13,933
Speaker 2: asking before where there are still video stores and DVD stores?

1303
01:02:14,013 --> 01:02:14,293
Speaker 5: Yes?

1304
01:02:14,813 --> 01:02:17,933
Speaker 4: This pin, says Allison one Church Tyler. Well know it.

1305
01:02:18,053 --> 01:02:18,253
Speaker 3: Yep.

1306
01:02:18,373 --> 01:02:21,733
Speaker 4: Take Patridge's DVD old School and a theater. How good?

1307
01:02:22,373 --> 01:02:25,653
Speaker 2: Pyroa still has a DVD shop Mournsville United Video.

1308
01:02:26,013 --> 01:02:27,773
Speaker 3: There you go, and that one I was talking about

1309
01:02:27,773 --> 01:02:29,093
Speaker 3: in Littleton did video?

1310
01:02:29,293 --> 01:02:29,653
Speaker 4: Yeah?

1311
01:02:29,493 --> 01:02:31,893
Speaker 3: Yeah, okay, cool, So so it still exists. Sorry, Yeah,

1312
01:02:31,933 --> 01:02:33,653
Speaker 3: that's all right, that's right. That's important to get out

1313
01:02:33,693 --> 01:02:35,333
Speaker 3: there for you want to go rent some videos? They

1314
01:02:35,373 --> 01:02:35,893
Speaker 3: still exist.

1315
01:02:36,013 --> 01:02:36,853
Speaker 4: Yeah, so there you go.

1316
01:02:37,013 --> 01:02:38,973
Speaker 2: That's so like if you know AI might be coming

1317
01:02:38,973 --> 01:02:41,373
Speaker 2: for us. Yeah, but the video stores are still just

1318
01:02:41,413 --> 01:02:41,893
Speaker 2: holding on.

1319
01:02:42,413 --> 01:02:44,533
Speaker 3: Yes, right, let's have a chat about this. So what

1320
01:02:44,573 --> 01:02:46,733
Speaker 3: power does your employeer have over you when it comes to,

1321
01:02:47,093 --> 01:02:50,773
Speaker 3: for example, hickling politicians. Now you may have seen this story,

1322
01:02:50,813 --> 01:02:53,373
Speaker 3: but here's what happened when Winston Peters was at a

1323
01:02:53,453 --> 01:02:54,333
Speaker 3: stand up yesterday.

1324
01:02:55,013 --> 01:02:58,533
Speaker 1: Now we're not an acceptance is the punishment of a

1325
01:02:58,573 --> 01:03:02,373
Speaker 1: lot of bollocks. It's looking in a mirror, Sunchoine, you look

1326
01:03:02,493 --> 01:03:04,813
Speaker 1: like like bollocks.

1327
01:03:04,413 --> 01:03:10,213
Speaker 22: Mate, Sunshine, Donald Trump with the you're to you that

1328
01:03:10,373 --> 01:03:19,173
Speaker 22: on look at you want to see you?

1329
01:03:17,693 --> 01:03:21,093
Speaker 12: You look Trump's up.

1330
01:03:21,533 --> 01:03:24,653
Speaker 22: You get out of here, get out good, last and

1331
01:03:24,693 --> 01:03:25,653
Speaker 22: don't bloody.

1332
01:03:25,413 --> 01:03:30,933
Speaker 1: Dead last league. You're married, now, are you?

1333
01:03:31,733 --> 01:03:31,933
Speaker 22: Yeah?

1334
01:03:31,973 --> 01:03:34,253
Speaker 23: You're feeling well every day if you want it?

1335
01:03:35,053 --> 01:03:39,173
Speaker 24: Okay, thanks guys. Do you swear as well?

1336
01:03:39,213 --> 01:03:41,053
Speaker 1: Eh?

1337
01:03:41,213 --> 01:03:43,253
Speaker 3: So rather spicy, But you got to say, I think

1338
01:03:43,293 --> 01:03:46,773
Speaker 3: Winston probably came off better on that interchange.

1339
01:03:46,853 --> 01:03:49,133
Speaker 2: Yeah, and look, let's not go to in the details.

1340
01:03:49,133 --> 01:03:51,253
Speaker 2: We don't know exactly who this guy is, but he's

1341
01:03:51,293 --> 01:03:53,013
Speaker 2: a Tonquin and Taylor employee.

1342
01:03:53,133 --> 01:03:54,293
Speaker 4: And you can see that from his.

1343
01:03:54,613 --> 01:03:57,773
Speaker 2: Very cool langyard that he was wearing. Sounds a lot,

1344
01:03:58,933 --> 01:04:01,133
Speaker 2: like he has been spending a lot of time online

1345
01:04:01,293 --> 01:04:05,933
Speaker 2: and has been had a mind warped by whatever messaging

1346
01:04:05,973 --> 01:04:08,173
Speaker 2: he's got over there, whatever bubble he's operating in, and

1347
01:04:08,213 --> 01:04:10,933
Speaker 2: he's taken that to the streets to yell at Winston Peter's.

1348
01:04:11,013 --> 01:04:13,413
Speaker 2: It's funny because he sort of starts pushing back and

1349
01:04:13,413 --> 01:04:15,533
Speaker 2: start when he started it. That's the whole weird thing

1350
01:04:15,533 --> 01:04:18,413
Speaker 2: about this interaction. He's started it and then he loses

1351
01:04:18,453 --> 01:04:21,733
Speaker 2: it so badly, which is free speech, though, isn't it

1352
01:04:21,773 --> 01:04:23,973
Speaker 2: surely that you're allowed to go up and yell at politicians?

1353
01:04:24,013 --> 01:04:26,093
Speaker 2: I mean, in that case, that gave Winston Peters an

1354
01:04:26,093 --> 01:04:28,653
Speaker 2: opportunity to completely destroy the guy in public, which Winston

1355
01:04:28,653 --> 01:04:30,093
Speaker 2: Peter's seemed pretty happy about.

1356
01:04:30,053 --> 01:04:31,253
Speaker 4: Because he went off smiling.

1357
01:04:31,693 --> 01:04:35,253
Speaker 2: So Winston Peters didn't lose anything in that situation, did he.

1358
01:04:35,453 --> 01:04:35,573
Speaker 1: No?

1359
01:04:35,853 --> 01:04:40,373
Speaker 2: But as you were saying before, Tonkin and Taylor confer

1360
01:04:40,493 --> 01:04:42,813
Speaker 2: the person involved as one of their employees and that

1361
01:04:42,853 --> 01:04:44,973
Speaker 2: they're investigating under its code of conduct.

1362
01:04:45,853 --> 01:04:49,173
Speaker 3: So it's an interesting wasn't it. And We've got an

1363
01:04:49,213 --> 01:04:52,213
Speaker 3: email from the Free Speech Union that had our own

1364
01:04:52,293 --> 01:04:55,653
Speaker 3: boxes this afternoon, and easy to imagine they think that

1365
01:04:55,733 --> 01:04:58,973
Speaker 3: Tonkin and Taylor, investigating this employee is way too far.

1366
01:04:59,093 --> 01:05:01,653
Speaker 3: They say, individuals don't give up their speech rights when

1367
01:05:01,653 --> 01:05:04,373
Speaker 3: they accept a job. That's from Nick Harney of the

1368
01:05:04,413 --> 01:05:09,493
Speaker 3: Free Speech Union. He said, I quote, employees don't own employers. Rather,

1369
01:05:09,533 --> 01:05:12,453
Speaker 3: don't own employees' time when they are commuting to work,

1370
01:05:12,493 --> 01:05:14,893
Speaker 3: and the choice to heckel Winston Peters has nothing to

1371
01:05:14,933 --> 01:05:17,893
Speaker 3: do with Tonkin and Taylor. No one asked their opinion.

1372
01:05:18,053 --> 01:05:19,733
Speaker 3: They have nothing to do with this situation.

1373
01:05:20,973 --> 01:05:25,533
Speaker 4: Yeah, absolutely right. So I don't think people should lose

1374
01:05:25,573 --> 01:05:27,653
Speaker 4: their jobs for that. So can you read that again?

1375
01:05:27,973 --> 01:05:30,973
Speaker 3: So they said, here's the direct quote from the Free

1376
01:05:30,973 --> 01:05:34,493
Speaker 3: Speech Union. Employers don't own employees' time when they are

1377
01:05:34,493 --> 01:05:37,253
Speaker 3: commuting to work, and the choice to heckele Winston Peters

1378
01:05:37,253 --> 01:05:39,533
Speaker 3: has nothing to do with Tonkin and Taylor. No one

1379
01:05:39,573 --> 01:05:41,653
Speaker 3: asked their opinion. They have nothing to do with the situation.

1380
01:05:41,773 --> 01:05:42,373
Speaker 4: Yeah, I'd agree.

1381
01:05:42,413 --> 01:05:43,813
Speaker 2: I mean you would look at that and go, well,

1382
01:05:43,853 --> 01:05:46,093
Speaker 2: they've hired quite an odd person to work for them,

1383
01:05:46,213 --> 01:05:47,853
Speaker 2: and maybe they could look at them and go as

1384
01:05:47,893 --> 01:05:51,893
Speaker 2: he the kind of person they want working for them.

1385
01:05:51,973 --> 01:05:53,333
Speaker 2: But it'll be a bit of a leap for me

1386
01:05:53,493 --> 01:05:56,613
Speaker 2: to think that I would think less of Tonkin and Taylor. Yeah,

1387
01:05:56,733 --> 01:06:00,973
Speaker 2: I mean potentially Tonkin and Taylor goes, well, you know,

1388
01:06:01,693 --> 01:06:03,133
Speaker 2: we do a bit of work with the government. Maybe

1389
01:06:03,173 --> 01:06:04,853
Speaker 2: it's not great if our employees are running around a

1390
01:06:04,893 --> 01:06:06,773
Speaker 2: music members of the government that make decisions.

1391
01:06:07,013 --> 01:06:07,413
Speaker 4: Yeah.

1392
01:06:07,453 --> 01:06:11,173
Speaker 2: But my feeling on it is we live in free

1393
01:06:11,173 --> 01:06:15,133
Speaker 2: speech is very very important and people should be allowed

1394
01:06:15,173 --> 01:06:17,573
Speaker 2: to yell and reveal who they are. I mean, he's

1395
01:06:17,613 --> 01:06:21,093
Speaker 2: revealed who he was, and so that's great for the

1396
01:06:21,133 --> 01:06:23,613
Speaker 2: overall country. I don't know if it's great for the company.

1397
01:06:24,693 --> 01:06:27,093
Speaker 3: See, I agree with that. But where I think he

1398
01:06:27,133 --> 01:06:30,613
Speaker 3: went wrong is we're in the lanyard and whatever you

1399
01:06:30,613 --> 01:06:33,213
Speaker 3: think about people that we're at lanyard, whether the Geeks

1400
01:06:33,293 --> 01:06:35,493
Speaker 3: or not, the fact that said Tonkin and Taylor on it.

1401
01:06:35,813 --> 01:06:37,773
Speaker 3: That is where he went wrong. That if he took

1402
01:06:37,813 --> 01:06:40,973
Speaker 3: that lanyard off and he had nothing to identify where

1403
01:06:41,013 --> 01:06:43,533
Speaker 3: he worked, who he was, then Gopher Gold you can

1404
01:06:43,533 --> 01:06:44,613
Speaker 3: say whatever you want to say.

1405
01:06:44,893 --> 01:06:46,813
Speaker 4: Well, yeah, and he's made a mistake there.

1406
01:06:46,893 --> 01:06:49,133
Speaker 2: But you know, he also clearly proved in the back

1407
01:06:49,133 --> 01:06:51,933
Speaker 2: and forth that he wasn't the sharpest mind an operation.

1408
01:06:52,133 --> 01:06:54,293
Speaker 2: Oh he lost his call. He was a knob to

1409
01:06:54,333 --> 01:06:58,373
Speaker 2: get owned that thoroughly. You might ask questions about his

1410
01:06:58,733 --> 01:07:01,213
Speaker 2: competency to deal with anything on a day to day

1411
01:07:01,253 --> 01:07:03,733
Speaker 2: basis in a company. Doesn't look like he can deal

1412
01:07:03,773 --> 01:07:06,333
Speaker 2: with pressure situations or can think on the fly at all.

1413
01:07:06,853 --> 01:07:10,173
Speaker 2: But that's not Tonkin and Taylor's fault for us to

1414
01:07:10,173 --> 01:07:12,373
Speaker 2: be angry at them. It might be information that Tonkin

1415
01:07:12,413 --> 01:07:16,613
Speaker 2: and Taylor can use to decide whether they continue employing him,

1416
01:07:16,813 --> 01:07:18,573
Speaker 2: but not for what he's done in public.

1417
01:07:18,693 --> 01:07:20,933
Speaker 4: Yeah, not for the yelling at it. This is what

1418
01:07:21,013 --> 01:07:22,093
Speaker 4: I this is personally what.

1419
01:07:22,093 --> 01:07:26,373
Speaker 2: I think that that shouldn't be grounds to fire him.

1420
01:07:26,493 --> 01:07:26,853
Speaker 4: Yeah.

1421
01:07:26,933 --> 01:07:28,813
Speaker 2: I mean, he's probably got part of his contract which

1422
01:07:28,853 --> 01:07:30,853
Speaker 2: says that he can't bring the company into distribute, and

1423
01:07:30,893 --> 01:07:32,893
Speaker 2: that's a different issue. That's a legal issue there with

1424
01:07:32,973 --> 01:07:36,253
Speaker 2: his contract. But for me, I don't think that that's

1425
01:07:36,253 --> 01:07:38,253
Speaker 2: grounds to fire him. It's grounds to look at him

1426
01:07:38,253 --> 01:07:40,893
Speaker 2: and go I don't think he's probably the sharpest tool

1427
01:07:40,893 --> 01:07:44,573
Speaker 2: we've got in our toolbox. Yeah, but that's up to

1428
01:07:44,613 --> 01:07:45,853
Speaker 2: them to decide who they hire.

1429
01:07:45,973 --> 01:07:47,693
Speaker 3: Bang on and I agree, I don't think this guy

1430
01:07:47,773 --> 01:07:49,573
Speaker 3: should get fired. But for Tonkin and Taylor to come

1431
01:07:49,613 --> 01:07:52,933
Speaker 3: out and say, whatever this guy said, we absolutely do

1432
01:07:53,013 --> 01:07:55,653
Speaker 3: not agree as a company what this knob said. We

1433
01:07:55,733 --> 01:07:57,293
Speaker 3: cannot agree with him, but he's got to keep his

1434
01:07:57,413 --> 01:07:59,773
Speaker 3: job because you know, we're not going to interfere with

1435
01:07:59,773 --> 01:08:00,453
Speaker 3: his free speech.

1436
01:08:00,573 --> 01:08:02,613
Speaker 2: Yeah, I mean, and they would have noticed that he's

1437
01:08:02,653 --> 01:08:05,173
Speaker 2: not the sharpest operator quite a long time ago.

1438
01:08:05,213 --> 01:08:06,373
Speaker 4: Imagine judging by that.

1439
01:08:06,413 --> 01:08:08,333
Speaker 3: Oh one hundred eighty ten eighty. Where do you think

1440
01:08:08,413 --> 01:08:12,613
Speaker 3: the line is drawn between your employer and the activity

1441
01:08:12,653 --> 01:08:16,333
Speaker 3: and behavior that you show in public, particularly when it

1442
01:08:16,452 --> 01:08:20,933
Speaker 3: is behavior that may bring the company into disrepute as.

1443
01:08:20,773 --> 01:08:21,372
Speaker 4: This textas said.

1444
01:08:21,412 --> 01:08:23,932
Speaker 2: That's discussing that Tonkin and Taylor have even got involved.

1445
01:08:23,933 --> 01:08:26,892
Speaker 2: Who cares who he works for? When I saw the story,

1446
01:08:26,933 --> 01:08:28,372
Speaker 2: I thought, you're a bit of a nutter. But I

1447
01:08:28,372 --> 01:08:30,933
Speaker 2: didn't go seeing and looking for who he worked for.

1448
01:08:31,412 --> 01:08:34,333
Speaker 2: That's his own personal life that's getting out of control. Yeah,

1449
01:08:34,333 --> 01:08:37,012
Speaker 2: and that's exactly I think. That's a very that person

1450
01:08:37,253 --> 01:08:38,492
Speaker 2: said what I was trying to say. It took me

1451
01:08:38,492 --> 01:08:40,093
Speaker 2: about two hundred and fifty words to say what that

1452
01:08:40,133 --> 01:08:44,012
Speaker 2: person said, very succinctly in about ten words, twenty words

1453
01:08:44,692 --> 01:08:45,652
Speaker 2: that Yeah, who cares?

1454
01:08:45,772 --> 01:08:47,892
Speaker 3: Oh eight hundred and eighty ten eighty. Let's get into it.

1455
01:08:47,893 --> 01:08:49,852
Speaker 3: Love to hear your thoughts. It is eighteen to three,

1456
01:08:51,173 --> 01:08:52,173
Speaker 3: the issues.

1457
01:08:51,812 --> 01:08:54,293
Speaker 1: That affect you and a bit of fun along the way.

1458
01:08:54,532 --> 01:08:58,093
Speaker 1: Matt Heath and Tyler Adams Afternoons News Talk said.

1459
01:08:57,812 --> 01:09:01,612
Speaker 3: Be good afternoon, the Tonquin and Taylor Heckler. Is it

1460
01:09:01,692 --> 01:09:03,973
Speaker 3: right for his company to be investigating him having a

1461
01:09:04,013 --> 01:09:06,652
Speaker 3: go at Winston Peters during a stand up? Or should

1462
01:09:06,692 --> 01:09:08,692
Speaker 3: they but out if the guy wants to act like

1463
01:09:08,732 --> 01:09:10,892
Speaker 3: a knob on his time and it's his problem.

1464
01:09:11,013 --> 01:09:11,173
Speaker 5: Yeah.

1465
01:09:11,213 --> 01:09:13,412
Speaker 4: People are allowed to say things. People are allowed to

1466
01:09:13,492 --> 01:09:16,213
Speaker 4: yell things. Yeah, Yeah, welcome to the show.

1467
01:09:16,293 --> 01:09:20,172
Speaker 3: Mikey a very.

1468
01:09:20,013 --> 01:09:22,052
Speaker 4: Good That sounds like the Mikey Havoc.

1469
01:09:23,093 --> 01:09:24,452
Speaker 24: It surely is, and said he is.

1470
01:09:24,492 --> 01:09:26,572
Speaker 23: And I've got a couple of comments to make about

1471
01:09:26,572 --> 01:09:28,212
Speaker 23: this personally.

1472
01:09:28,452 --> 01:09:30,932
Speaker 24: So I'm not never been that bigger fan of Winston

1473
01:09:30,973 --> 01:09:35,173
Speaker 24: Peters as such, but especially lately, what a rude man

1474
01:09:35,253 --> 01:09:38,572
Speaker 24: he's turned into. Like the lady he talks to jails

1475
01:09:38,732 --> 01:09:41,812
Speaker 24: and reporters and you know, anyone that he disagrees with.

1476
01:09:42,213 --> 01:09:45,253
Speaker 24: But he's pulling the old Grandpark cards, the gloss old

1477
01:09:45,253 --> 01:09:47,892
Speaker 24: Grandpark hards. And it's actually really nice to see somebody

1478
01:09:48,333 --> 01:09:51,293
Speaker 24: just come back and with the same attitude. Lovely I'm

1479
01:09:51,293 --> 01:09:53,572
Speaker 24: still like it. But I've never talked to people though

1480
01:09:53,572 --> 01:09:57,932
Speaker 24: they would the people, but Mikey, he's got telling them

1481
01:09:57,933 --> 01:09:59,372
Speaker 24: off about stuff and all that sort of thing.

1482
01:09:59,652 --> 01:10:01,612
Speaker 2: Would you agree, Mikey that the guy started it though,

1483
01:10:01,612 --> 01:10:03,612
Speaker 2: because the guy was the first person.

1484
01:10:04,013 --> 01:10:07,812
Speaker 4: The guy started the abuse and once some responded to it.

1485
01:10:07,853 --> 01:10:11,532
Speaker 4: In this case, what I think is that that Winston

1486
01:10:11,532 --> 01:10:14,372
Speaker 4: Peters attitude that might have started it, you know, because.

1487
01:10:14,532 --> 01:10:16,412
Speaker 23: He doesn't he doesn't, he doesn't look like the sort

1488
01:10:16,452 --> 01:10:19,812
Speaker 23: of bessy you could go up to it with a comment,

1489
01:10:21,093 --> 01:10:22,893
Speaker 23: you know, with an open mind and that and and

1490
01:10:23,173 --> 01:10:25,452
Speaker 23: the calm to me that you know, we're showing people

1491
01:10:25,452 --> 01:10:27,173
Speaker 23: down recently in a way that's, like.

1492
01:10:27,133 --> 01:10:30,092
Speaker 24: I say, like an angry old man. And the thinking

1493
01:10:30,133 --> 01:10:32,932
Speaker 24: part of my comments met and father that I've never

1494
01:10:32,973 --> 01:10:38,173
Speaker 24: ever heard of before, and you guys must have heard

1495
01:10:38,173 --> 01:10:40,012
Speaker 24: about three thousand times already in the show.

1496
01:10:40,253 --> 01:10:42,333
Speaker 2: Well, the thing is, Mikey, as you know, as a broadcaster,

1497
01:10:42,412 --> 01:10:44,732
Speaker 2: when you get words that are enjoyable to say together,

1498
01:10:44,812 --> 01:10:46,852
Speaker 2: like Tonkin and Taylor, you start saying them as much

1499
01:10:46,893 --> 01:10:47,772
Speaker 2: as you possibly can.

1500
01:10:48,093 --> 01:10:49,333
Speaker 4: Reminds me of Tonka toys.

1501
01:10:49,412 --> 01:10:52,492
Speaker 24: Yeah, then invest them, investigating them for you may not

1502
01:10:52,612 --> 01:10:54,532
Speaker 24: be as great a pr exercise for.

1503
01:10:54,532 --> 01:10:55,733
Speaker 23: Them as they may have interistated.

1504
01:10:56,013 --> 01:10:57,572
Speaker 4: Yeah, well, thank you so much for your call, Mike.

1505
01:10:57,772 --> 01:10:59,692
Speaker 3: It's a fair point. But Winston does love a scrap,

1506
01:10:59,732 --> 01:11:01,333
Speaker 3: doesn't he. And he's very good at it. You know,

1507
01:11:01,412 --> 01:11:03,612
Speaker 3: he would be the only politician I can think of

1508
01:11:03,893 --> 01:11:07,652
Speaker 3: that enjoys getting into scraps with Hiclas. He's he's up

1509
01:11:07,652 --> 01:11:09,213
Speaker 3: for it. Yeah, he's waiting for them.

1510
01:11:09,492 --> 01:11:09,812
Speaker 4: Yeah.

1511
01:11:09,853 --> 01:11:14,812
Speaker 2: And I personally like a back and forth. I personally

1512
01:11:14,893 --> 01:11:18,213
Speaker 2: like you a matching of wits. Yeah and yeah, I

1513
01:11:18,213 --> 01:11:20,612
Speaker 2: mean there could be a wider argument there, as the

1514
01:11:20,612 --> 01:11:23,812
Speaker 2: Great mikey Hewvot points out that that's you know.

1515
01:11:23,772 --> 01:11:26,092
Speaker 4: Maybe there's a way politicians to behave.

1516
01:11:26,652 --> 01:11:29,333
Speaker 2: But you've got to say, in Winston Peter's defense, he

1517
01:11:29,333 --> 01:11:31,812
Speaker 2: didn't get annoyed about it. Yeah, he loved it. He

1518
01:11:31,853 --> 01:11:34,733
Speaker 2: loved the back and forth. So it would be quite hypocritical.

1519
01:11:34,772 --> 01:11:37,972
Speaker 2: I guess if Winston Peters had thrown packed a sad

1520
01:11:38,013 --> 01:11:39,852
Speaker 2: and said, don't talk to me like that. Yeah, he

1521
01:11:39,933 --> 01:11:42,812
Speaker 2: just enjoyed the back and forth and gave us, gave

1522
01:11:42,933 --> 01:11:43,692
Speaker 2: better than he got.

1523
01:11:43,853 --> 01:11:46,652
Speaker 3: He certainly was laughing when he left that interchange with

1524
01:11:46,732 --> 01:11:49,652
Speaker 3: that person. And I think when the feller from Tonkin

1525
01:11:49,692 --> 01:11:51,253
Speaker 3: and Taylor when he first started having a gout, when

1526
01:11:51,293 --> 01:11:54,812
Speaker 3: he I don't think he realized how far or how

1527
01:11:54,893 --> 01:11:56,253
Speaker 3: much he was going to lose that. I think he

1528
01:11:56,293 --> 01:11:59,053
Speaker 3: completely lost his rag and ran out of comebacks and

1529
01:11:59,053 --> 01:12:02,053
Speaker 3: then looked like an absolute tool. But their point from

1530
01:12:02,093 --> 01:12:04,173
Speaker 3: Mikey Havock, oh, eight hundred eighty ten eighty is the

1531
01:12:04,253 --> 01:12:06,612
Speaker 3: number to call. Will take more of your calls on

1532
01:12:06,652 --> 01:12:09,492
Speaker 3: whether Tonkin and Taylor has any right to investigate this

1533
01:12:09,532 --> 01:12:11,572
Speaker 3: guy or if he wants to be a dick in public,

1534
01:12:11,652 --> 01:12:13,452
Speaker 3: that's on his own time. They've got nothing to do

1535
01:12:13,532 --> 01:12:13,732
Speaker 3: with it.

1536
01:12:13,812 --> 01:12:15,612
Speaker 2: And if you're counting how many times we say Tonkin

1537
01:12:15,652 --> 01:12:18,213
Speaker 2: and Taylor, I think it's up around fifty.

1538
01:12:18,253 --> 01:12:20,213
Speaker 3: We'll get a wed bow every time we say it.

1539
01:12:20,213 --> 01:12:21,732
Speaker 3: It is twelve to three.

1540
01:12:22,933 --> 01:12:25,372
Speaker 1: The issues that affect you and a bit of fun

1541
01:12:25,412 --> 01:12:29,613
Speaker 1: along the way. Matt Heath and Tyler Adams Afternoons News Talks.

1542
01:12:29,333 --> 01:12:33,532
Speaker 3: EBB, News Talks AB and we're talking about this Tonkin

1543
01:12:33,652 --> 01:12:37,612
Speaker 3: and Taylor employee who has gotten too a bit of

1544
01:12:37,612 --> 01:12:41,133
Speaker 3: strife for Hecklan Winston Peters. Do you think he should

1545
01:12:41,133 --> 01:12:44,012
Speaker 3: lose his job? Should his company be investigating.

1546
01:12:43,772 --> 01:12:44,852
Speaker 4: And Tyler's so shocked about it.

1547
01:12:44,893 --> 01:12:46,532
Speaker 2: He started bleeding from the nose and we've had to

1548
01:12:46,572 --> 01:12:48,652
Speaker 2: run out and get a bunch of handytails from just

1549
01:12:48,652 --> 01:12:50,933
Speaker 2: to paint the picture in the studio here. Yes, do

1550
01:12:51,412 --> 01:12:52,772
Speaker 2: you get a few nose bleeds, Tyler.

1551
01:12:52,612 --> 01:12:53,852
Speaker 3: I haven't had one for a long time. But I'll

1552
01:12:53,853 --> 01:12:55,532
Speaker 3: tell you what. You wouldn't get ai doing that in

1553
01:12:55,532 --> 01:12:56,732
Speaker 3: the middle of a radio show, would you?

1554
01:12:57,093 --> 01:12:59,452
Speaker 4: There we go. You're so excited to have a legend.

1555
01:12:59,532 --> 01:13:02,372
Speaker 2: That is Mikey Havoc on the line. Hi, guys, why

1556
01:13:02,372 --> 01:13:05,093
Speaker 2: did the heckler not take his lanyard off? Our boss says,

1557
01:13:05,093 --> 01:13:07,253
Speaker 2: if we act like an idiot wearing our company colors,

1558
01:13:07,492 --> 01:13:09,572
Speaker 2: you're for the high jump? Clearly hasn't it? It deserves

1559
01:13:09,612 --> 01:13:14,093
Speaker 2: what he gets. That's from Chris. That's an interesting one.

1560
01:13:14,093 --> 01:13:16,013
Speaker 2: I mean, it does seem like a foolish idea to

1561
01:13:16,293 --> 01:13:19,612
Speaker 2: leave your lanyard on and reveal you work. But I

1562
01:13:19,612 --> 01:13:21,012
Speaker 2: mean I didn't know was the guy as the guy

1563
01:13:21,093 --> 01:13:24,933
Speaker 2: come down to the stand up with Winston. Peter's on

1564
01:13:24,933 --> 01:13:27,612
Speaker 2: this rail announcement, the announcement of six hundred and four

1565
01:13:27,652 --> 01:13:32,053
Speaker 2: million dollars investment, and at a Wellington stations he come

1566
01:13:32,173 --> 01:13:35,213
Speaker 2: down to yell at Winston Peter's Is he just walking

1567
01:13:35,253 --> 01:13:38,372
Speaker 2: past like Bigfoot and starts yelling some abuses he goes past.

1568
01:13:38,372 --> 01:13:40,253
Speaker 3: It appears it was off the cuff. He was a commuter.

1569
01:13:40,372 --> 01:13:43,213
Speaker 3: He was sticking off the train. Funnily enough, Yeah, and

1570
01:13:43,253 --> 01:13:46,173
Speaker 3: then saw Winston Peters doing a stand up. Clearly didn't

1571
01:13:46,253 --> 01:13:48,333
Speaker 3: like Winston Peters and decided to have a crack at

1572
01:13:48,333 --> 01:13:49,052
Speaker 3: I'm right in the middle.

1573
01:13:49,532 --> 01:13:54,333
Speaker 2: Yeah, the Tonquin and Taylor guy has been infected by

1574
01:13:54,333 --> 01:13:56,452
Speaker 2: a mind virus, a woke mind virus.

1575
01:13:56,572 --> 01:13:57,772
Speaker 4: Have a look at his website.

1576
01:13:57,893 --> 01:13:58,892
Speaker 3: Okay, okay, yep.

1577
01:13:59,053 --> 01:14:05,013
Speaker 2: I well, good to hear they good to hear. Politicians

1578
01:14:05,013 --> 01:14:07,973
Speaker 2: getting here held they deserve a rabot river. Some are

1579
01:14:07,973 --> 01:14:10,333
Speaker 2: out of Yeah, I mean I don't really, I don't

1580
01:14:10,372 --> 01:14:14,652
Speaker 2: have a problem at all with with someone. I mean,

1581
01:14:14,732 --> 01:14:17,093
Speaker 2: it's annoying. You know, it's annoying if someone's having a

1582
01:14:17,173 --> 01:14:19,933
Speaker 2: meeting in a hall and people just start yelling to

1583
01:14:19,933 --> 01:14:22,932
Speaker 2: shut people down. You know, the idea that you shut

1584
01:14:22,973 --> 01:14:26,012
Speaker 2: people down free speech is an interesting one because sometimes

1585
01:14:26,013 --> 01:14:29,692
Speaker 2: people just bang things and use their right to be

1586
01:14:29,973 --> 01:14:33,173
Speaker 2: to make a noise to stop other people talking. I

1587
01:14:33,213 --> 01:14:36,132
Speaker 2: hate that, But you have the right to yell stuff

1588
01:14:36,173 --> 01:14:38,892
Speaker 2: and have stuff yelled yelled back at you. Surely, ye,

1589
01:14:39,013 --> 01:14:41,372
Speaker 2: I mean, and you do reveal who you are, you

1590
01:14:41,372 --> 01:14:43,372
Speaker 2: know you risk a bit doing it, of course. I mean,

1591
01:14:43,572 --> 01:14:45,452
Speaker 2: I'm not supporting those people that just turn up and

1592
01:14:45,492 --> 01:14:48,652
Speaker 2: just make noise and try and stop other people talking.

1593
01:14:48,812 --> 01:14:51,172
Speaker 3: But you know, the politician, and in this case winstant

1594
01:14:51,173 --> 01:14:53,452
Speaker 3: Peter's has every right to push back, right. I think

1595
01:14:53,492 --> 01:14:55,333
Speaker 3: we're pretty lucky in this country that you can get

1596
01:14:55,333 --> 01:14:58,293
Speaker 3: as close to our politicians as you can. You wouldn't

1597
01:14:58,333 --> 01:15:00,572
Speaker 3: get away with that and the likes of America, would you?

1598
01:15:00,612 --> 01:15:03,772
Speaker 2: Probably not, although you do see a bit of it online. Josh,

1599
01:15:03,812 --> 01:15:04,892
Speaker 2: welcome to the show. Your thoughts?

1600
01:15:06,013 --> 01:15:08,572
Speaker 7: Yeah, hey, you boys, you'd be greatest. Hope he can

1601
01:15:08,612 --> 01:15:11,612
Speaker 7: get a few good callers on this the text people

1602
01:15:11,692 --> 01:15:14,492
Speaker 7: if if they're not going to ring up, well hey, look,

1603
01:15:14,532 --> 01:15:17,173
Speaker 7: give him less attention. You know they're not. They're not

1604
01:15:17,213 --> 01:15:19,412
Speaker 7: going to ring up and wait for ten minutes to

1605
01:15:19,452 --> 01:15:19,772
Speaker 7: talk to you.

1606
01:15:19,853 --> 01:15:21,612
Speaker 4: But anyway, sounds like.

1607
01:15:24,692 --> 01:15:28,732
Speaker 7: I just want to say that Hitler. I thought it

1608
01:15:28,772 --> 01:15:32,612
Speaker 7: was funny to see Hitler. However, I thought he missed

1609
01:15:32,612 --> 01:15:36,532
Speaker 7: a good opportunity and he played the man, not the ball.

1610
01:15:37,732 --> 01:15:40,692
Speaker 7: If he had actually been a little bit specific as

1611
01:15:40,772 --> 01:15:43,933
Speaker 7: are you know, we're disappointed because of this Winston.

1612
01:15:43,532 --> 01:15:43,972
Speaker 16: And all that.

1613
01:15:44,532 --> 01:15:47,173
Speaker 7: But it was none of that. It wasn't political, it

1614
01:15:47,253 --> 01:15:50,492
Speaker 7: was personal and it just didn't hit the.

1615
01:15:50,452 --> 01:15:53,293
Speaker 4: Mark, Josh.

1616
01:15:53,293 --> 01:15:57,053
Speaker 2: He said, he revealed himself as being agis he went

1617
01:15:57,093 --> 01:16:00,572
Speaker 2: after Winston Peter's age, so he's he's biggoted towards people

1618
01:16:00,812 --> 01:16:01,692
Speaker 2: that are older.

1619
01:16:01,973 --> 01:16:03,333
Speaker 4: He revealed that ring up.

1620
01:16:03,973 --> 01:16:05,852
Speaker 7: Cut me short like a minute.

1621
01:16:05,853 --> 01:16:09,932
Speaker 4: Man, Okay, see you lad you us? Well, well you're

1622
01:16:09,933 --> 01:16:11,572
Speaker 4: trying to ring up the show and trying to run

1623
01:16:11,612 --> 01:16:13,452
Speaker 4: how the show is going to work. Wait, he wanted

1624
01:16:13,452 --> 01:16:15,772
Speaker 4: to heickel us, I think Jesus Josh. Yeah, So he

1625
01:16:15,853 --> 01:16:20,692
Speaker 4: rung up and said we should take calls. Come on mate,

1626
01:16:20,933 --> 01:16:23,333
Speaker 4: like free speech, Josh're willing to bring up and say

1627
01:16:23,333 --> 01:16:23,973
Speaker 4: something out of that?

1628
01:16:24,213 --> 01:16:27,372
Speaker 3: Yeah, yeah, when I'm going to investigate any further.

1629
01:16:29,732 --> 01:16:32,852
Speaker 4: Josh came an angry angry yeah in a china shop.

1630
01:16:32,853 --> 01:16:35,013
Speaker 4: All right, right, yeah, all right, jo, I hope things

1631
01:16:35,133 --> 01:16:35,572
Speaker 4: can inter for you.

1632
01:16:35,652 --> 01:16:35,852
Speaker 10: Josh.

1633
01:16:35,853 --> 01:16:37,852
Speaker 2: All right, ring back anytime. We'll leave you on for

1634
01:16:37,893 --> 01:16:39,732
Speaker 2: ten minutes and if I see your name and the thing,

1635
01:16:39,772 --> 01:16:40,852
Speaker 2: I'll go to text before you.

1636
01:16:42,013 --> 01:16:44,293
Speaker 4: I listen, Tony welcome to.

1637
01:16:44,253 --> 01:16:50,852
Speaker 10: The show, gentlet I'd better be certainly questioned. Well, I'm

1638
01:16:50,853 --> 01:16:52,933
Speaker 10: going to put an investigation and Tom and Taylor and

1639
01:16:53,133 --> 01:16:55,092
Speaker 10: they're involved in a lot of government projects.

1640
01:16:55,093 --> 01:16:57,132
Speaker 7: So at the end of the day, I think.

1641
01:16:56,933 --> 01:16:59,933
Speaker 10: This young gentleman has actually brought the company into disrepute

1642
01:17:00,013 --> 01:17:04,053
Speaker 10: by wearing that identifying He might not have thought about it,

1643
01:17:04,133 --> 01:17:06,772
Speaker 10: but he's actually identified himself as as an employee of

1644
01:17:06,812 --> 01:17:09,892
Speaker 10: the company. And they obviously they've probably got a lot

1645
01:17:09,893 --> 01:17:12,333
Speaker 10: of government contracts. And I think this guy should at

1646
01:17:12,412 --> 01:17:14,612
Speaker 10: least get a final warning for that. I think his

1647
01:17:14,692 --> 01:17:18,093
Speaker 10: behavior is appalling actually, to be honest with you, I mean,

1648
01:17:18,173 --> 01:17:20,333
Speaker 10: if he doesn't like what Winston Peter's are saying, well

1649
01:17:20,333 --> 01:17:21,692
Speaker 10: he doesn't have to listen to it, and he can

1650
01:17:21,732 --> 01:17:25,052
Speaker 10: move away. But this business of making ill informed, smart

1651
01:17:25,093 --> 01:17:28,253
Speaker 10: ass comments, especially by young people against a gentleman who's

1652
01:17:28,293 --> 01:17:30,492
Speaker 10: been in politics for many years, I think it's a calling.

1653
01:17:30,933 --> 01:17:33,092
Speaker 2: Yeah, I mean, and you know, as Josh said before,

1654
01:17:33,253 --> 01:17:35,372
Speaker 2: before he got angry, he was playing. He was playing

1655
01:17:35,412 --> 01:17:38,333
Speaker 2: the man and not the ball. What wasn't he exactly,

1656
01:17:39,213 --> 01:17:41,812
Speaker 2: which which kind of loses you the argument, because if

1657
01:17:41,812 --> 01:17:43,692
Speaker 2: you're down there and you want to make your point

1658
01:17:43,732 --> 01:17:46,492
Speaker 2: against what you disagree with Winston Peters about, then then

1659
01:17:46,572 --> 01:17:47,133
Speaker 2: make your point.

1660
01:17:47,732 --> 01:17:52,452
Speaker 10: Yeah, yeah, he could have easily done that if he

1661
01:17:52,572 --> 01:17:55,732
Speaker 10: actually Winston Peters just quite a reasonable person to talk

1662
01:17:55,812 --> 01:17:57,893
Speaker 10: to if you've got a valid point. He could have

1663
01:17:57,933 --> 01:18:00,253
Speaker 10: actually asked him a question, but he chose just to

1664
01:18:00,293 --> 01:18:01,932
Speaker 10: basically be a pain in the ass.

1665
01:18:02,013 --> 01:18:02,293
Speaker 4: Yeah.

1666
01:18:02,333 --> 01:18:08,612
Speaker 2: Really, But to you, if he wasn't wearing something that field,

1667
01:18:08,612 --> 01:18:11,133
Speaker 2: who was If he didn't have the langyard and he

1668
01:18:11,333 --> 01:18:13,973
Speaker 2: was yelling, and you know that the bosses at his

1669
01:18:14,053 --> 01:18:17,133
Speaker 2: company spotted him, I won't say the name, then would

1670
01:18:17,173 --> 01:18:20,173
Speaker 2: you still would you still think he should be, you know,

1671
01:18:20,253 --> 01:18:21,333
Speaker 2: be in trouble with his boss?

1672
01:18:23,133 --> 01:18:25,812
Speaker 10: No, because he hasn't been identified as an employee of

1673
01:18:25,812 --> 01:18:26,973
Speaker 10: a particular company.

1674
01:18:27,293 --> 01:18:29,372
Speaker 3: Yeah, yeah, got his goal, Tony. We're out of time

1675
01:18:29,372 --> 01:18:30,973
Speaker 3: because news is on the way. But if we're going

1676
01:18:31,053 --> 01:18:35,292
Speaker 3: to pick this up very shortly, your new.

1677
01:18:35,133 --> 01:18:39,532
Speaker 1: Home are instateful and entertaining talk. It's Mattie and Taylor

1678
01:18:39,612 --> 01:18:42,893
Speaker 1: Adams afternoons on news Talk sebby.

1679
01:18:43,133 --> 01:18:46,692
Speaker 3: Good Afternoon, having a great chat about Tonkin and Taylor

1680
01:18:46,772 --> 01:18:49,533
Speaker 3: and do they have any right to investigate their employee

1681
01:18:49,572 --> 01:18:52,012
Speaker 3: who had a bit of a heckl with Winston Peters

1682
01:18:52,053 --> 01:18:54,572
Speaker 3: came off second best. I think that is undisputed. He

1683
01:18:54,612 --> 01:18:57,732
Speaker 3: clearly lost in that exchange with Winston Peters.

1684
01:18:58,492 --> 01:19:01,293
Speaker 2: And yeah, you know, as Josh rangan after a few

1685
01:19:01,412 --> 01:19:04,412
Speaker 2: and said he played the he played the man and

1686
01:19:04,492 --> 01:19:07,013
Speaker 2: not the ball. And you know, whoever the guy is,

1687
01:19:07,053 --> 01:19:08,652
Speaker 2: we don't know he is. We've found out that he

1688
01:19:08,692 --> 01:19:11,412
Speaker 2: is a Tonquin and Taylor employee. Has this stick to

1689
01:19:11,412 --> 01:19:14,572
Speaker 2: Andy says Tonquin and Taylor brought themselves into distribute. No

1690
01:19:14,612 --> 01:19:16,692
Speaker 2: one would have noticed the lanyard if they hadn't started

1691
01:19:16,692 --> 01:19:17,933
Speaker 2: speaking to the media.

1692
01:19:18,093 --> 01:19:19,652
Speaker 4: We have said it a lot, but maybe they wanted

1693
01:19:19,652 --> 01:19:23,772
Speaker 4: a front foot the situation an goal. But you know

1694
01:19:23,893 --> 01:19:24,492
Speaker 4: he did.

1695
01:19:24,612 --> 01:19:27,812
Speaker 2: He did get a bit ageist and obviously he doesn't

1696
01:19:27,893 --> 01:19:30,412
Speaker 2: like old people and his abuse that he threw at

1697
01:19:30,572 --> 01:19:33,733
Speaker 2: Winston Peter's and Winston Peters is definitely not the politest

1698
01:19:33,732 --> 01:19:35,133
Speaker 2: person in the world. As Mike you have it rang

1699
01:19:35,213 --> 01:19:38,293
Speaker 2: up before and said it takes a combative approach. So

1700
01:19:38,933 --> 01:19:41,932
Speaker 2: from my perspective, I want free speech to be out there.

1701
01:19:41,973 --> 01:19:43,492
Speaker 2: I want people to be able to yell and do

1702
01:19:43,572 --> 01:19:45,133
Speaker 2: whatever they want to do. I think that's part of

1703
01:19:45,133 --> 01:19:47,692
Speaker 2: being a member of our society. I think that's a

1704
01:19:47,772 --> 01:19:50,213
Speaker 2: very important thing to protect. And you know, he he,

1705
01:19:50,853 --> 01:19:53,333
Speaker 2: you know, looked by the sword, Diabo's sword. He started

1706
01:19:53,372 --> 01:19:57,173
Speaker 2: the thing and he lost the thing. But wearing the

1707
01:19:57,293 --> 01:20:01,173
Speaker 2: lanyard was a problem, idiots, was a problem. And I

1708
01:20:01,213 --> 01:20:03,492
Speaker 2: think that his employee might be able to have a

1709
01:20:03,492 --> 01:20:05,412
Speaker 2: complaint or some words with him and saying that, you know,

1710
01:20:05,452 --> 01:20:07,612
Speaker 2: if you're going to be wearing something identifies you as

1711
01:20:07,652 --> 01:20:10,093
Speaker 2: a work of our com then we might have a

1712
01:20:10,133 --> 01:20:12,333
Speaker 2: couple of words to say about that. But if he wasn't,

1713
01:20:12,572 --> 01:20:15,333
Speaker 2: let's just say he wasn't, then I don't think anyone

1714
01:20:15,412 --> 01:20:17,972
Speaker 2: getting out in the public and yelling should come back

1715
01:20:18,013 --> 01:20:19,772
Speaker 2: on their work, or should come back on their employer,

1716
01:20:20,253 --> 01:20:22,853
Speaker 2: or should have anything to do with their their employment.

1717
01:20:22,933 --> 01:20:26,492
Speaker 2: I think that's their time, their life outside of the job.

1718
01:20:26,612 --> 01:20:29,652
Speaker 2: We're not owned twenty we're not owned twenty four to seven.

1719
01:20:29,452 --> 01:20:30,172
Speaker 4: By our employees.

1720
01:20:30,452 --> 01:20:32,412
Speaker 2: And I know what people are saying that you do

1721
01:20:32,612 --> 01:20:35,652
Speaker 2: have things in your contract to not bring the company

1722
01:20:35,652 --> 01:20:37,532
Speaker 2: and to distribute. I understand that, but.

1723
01:20:38,133 --> 01:20:40,932
Speaker 3: Just morally, but it's like anyone taking part in a protest,

1724
01:20:40,973 --> 01:20:42,852
Speaker 3: right And there was a protest down in Queen Street

1725
01:20:42,853 --> 01:20:44,812
Speaker 3: on Saturday, and a lot of people yelling out some

1726
01:20:44,933 --> 01:20:47,293
Speaker 3: very obnoxious things, and they annoyed me. But I'm not

1727
01:20:47,293 --> 01:20:49,253
Speaker 3: going to look at them unless they were actually wearing

1728
01:20:49,412 --> 01:20:52,093
Speaker 3: a T shirt that said where they work. I don't care.

1729
01:20:52,253 --> 01:20:53,692
Speaker 3: Do what you want to do on a Saturday. If

1730
01:20:53,692 --> 01:20:54,612
Speaker 3: you want to be an idiot.

1731
01:20:55,053 --> 01:20:57,133
Speaker 2: Should see the kind of drunken behavior I get up to.

1732
01:20:57,213 --> 01:20:59,093
Speaker 2: And we're in one news talk z'd b polo. I'll

1733
01:20:59,093 --> 01:21:02,213
Speaker 2: be on top of a pool table, toilet seat round may.

1734
01:21:02,293 --> 01:21:04,253
Speaker 3: I've seen it multiple times, so god knows how they

1735
01:21:04,293 --> 01:21:05,093
Speaker 3: even pulled you up on.

1736
01:21:05,093 --> 01:21:06,532
Speaker 4: That candy, Wendy.

1737
01:21:06,933 --> 01:21:09,293
Speaker 2: You were there, You were at the at the station

1738
01:21:09,372 --> 01:21:10,533
Speaker 2: for the actual exchange.

1739
01:21:10,532 --> 01:21:12,652
Speaker 4: I understand, yes, I.

1740
01:21:12,853 --> 01:21:15,652
Speaker 25: Was, yes, wow, And I must say it was I

1741
01:21:15,692 --> 01:21:18,652
Speaker 25: was there from the beginning and everything was going very peaceful.

1742
01:21:18,772 --> 01:21:23,013
Speaker 25: The reporters were there, obviously asking the correct questions when

1743
01:21:23,053 --> 01:21:26,173
Speaker 25: Si Peters was asking, you know, answering them, and then

1744
01:21:26,173 --> 01:21:29,852
Speaker 25: this guy just came out of nowhere and just muffled

1745
01:21:29,933 --> 01:21:34,253
Speaker 25: himself in to where the reporters were and then just

1746
01:21:34,532 --> 01:21:37,812
Speaker 25: instantly started attacking them like nothing to do with you know,

1747
01:21:37,893 --> 01:21:40,612
Speaker 25: the budget with the rail or anything like that. And

1748
01:21:40,652 --> 01:21:43,093
Speaker 25: the thing I felt really disappointed was there's lots of

1749
01:21:43,093 --> 01:21:45,492
Speaker 25: school kids like standing around because you know they're like

1750
01:21:45,532 --> 01:21:48,213
Speaker 25: all these cameras, there's Winston Peters, you know, there's some

1751
01:21:48,372 --> 01:21:49,133
Speaker 25: parliament people.

1752
01:21:49,133 --> 01:21:50,372
Speaker 9: So the kids, school kids were.

1753
01:21:50,333 --> 01:21:54,013
Speaker 25: You know, gathering around and yeah, the sky was just

1754
01:21:55,213 --> 01:21:59,812
Speaker 25: so rude and you know, it's locktious and just didn't stop. Yeah,

1755
01:21:59,853 --> 01:22:01,972
Speaker 25: And I just thought that was like, you know, we're

1756
01:22:02,013 --> 01:22:05,532
Speaker 25: in a public place and you know, the abuse this

1757
01:22:05,612 --> 01:22:09,173
Speaker 25: guy was giving Munstone was just so uncle for like,

1758
01:22:09,253 --> 01:22:11,972
Speaker 25: he wasn't there, he wasn't there listening to it all

1759
01:22:12,053 --> 01:22:14,692
Speaker 25: from the beginning. He just basically came off the train.

1760
01:22:14,933 --> 01:22:17,213
Speaker 2: So do you think do you think he just arrived, Wendy,

1761
01:22:17,253 --> 01:22:19,093
Speaker 2: I was sort of speculating on this before. Did he

1762
01:22:19,133 --> 01:22:21,612
Speaker 2: come down to see Winston or was he just cruising

1763
01:22:21,652 --> 01:22:22,532
Speaker 2: past and good annoyed?

1764
01:22:22,612 --> 01:22:25,412
Speaker 25: No, I believe he came off the train right and

1765
01:22:25,492 --> 01:22:28,133
Speaker 25: he saw he saw him, and then he just just

1766
01:22:28,692 --> 01:22:31,452
Speaker 25: basically pushed his way into where the media and stuff

1767
01:22:31,492 --> 01:22:33,253
Speaker 25: were and then just started having to go.

1768
01:22:33,213 --> 01:22:35,732
Speaker 4: A m So he got so he got so triggered.

1769
01:22:35,853 --> 01:22:37,732
Speaker 4: He got so triggered that he couldn't help himself even

1770
01:22:37,772 --> 01:22:40,372
Speaker 4: though he is landed on he just got needed to

1771
01:22:41,093 --> 01:22:44,013
Speaker 4: need to yell some ageous abuse at a man.

1772
01:22:44,293 --> 01:22:46,053
Speaker 3: Yeah, it must have been a bit of a red

1773
01:22:46,372 --> 01:22:48,452
Speaker 3: a red miss situation, Whendy, by the sound of it,

1774
01:22:48,492 --> 01:22:50,652
Speaker 3: that he just completely lost his mind. Maybe he never

1775
01:22:50,652 --> 01:22:51,492
Speaker 3: had it in the first place.

1776
01:22:52,612 --> 01:22:54,412
Speaker 25: Yeah, well I don't know. And it was just like

1777
01:22:54,572 --> 01:22:57,492
Speaker 25: it just came from nowhere, and Okay, Winston, you know,

1778
01:22:57,612 --> 01:23:01,093
Speaker 25: gave back, you know exactly what the guy was giving him.

1779
01:23:01,253 --> 01:23:04,053
Speaker 25: But yeah, the guy knew that, you know, this was

1780
01:23:04,133 --> 01:23:07,213
Speaker 25: not going anywhere and didn't stop, but just carried on

1781
01:23:07,612 --> 01:23:10,213
Speaker 25: and made it.

1782
01:23:10,412 --> 01:23:12,253
Speaker 4: Did you think do you think Winston won?

1783
01:23:12,492 --> 01:23:16,052
Speaker 2: Do you think Winston won the exchange?

1784
01:23:16,452 --> 01:23:18,333
Speaker 25: And I was just like, you know, abuse and stuff.

1785
01:23:18,333 --> 01:23:20,053
Speaker 25: It's like I just thought, you know, like couse the

1786
01:23:20,093 --> 01:23:22,213
Speaker 25: kids with you, and I just thought, you know, it's

1787
01:23:22,213 --> 01:23:23,213
Speaker 25: a public place.

1788
01:23:23,133 --> 01:23:23,293
Speaker 5: And.

1789
01:23:25,532 --> 01:23:25,933
Speaker 4: I get that.

1790
01:23:26,812 --> 01:23:29,492
Speaker 2: It's interesting because, Wendy, because we've got this text here

1791
01:23:29,612 --> 01:23:32,052
Speaker 2: that says, I'm a member of the Free Speech Union.

1792
01:23:32,133 --> 01:23:35,333
Speaker 2: I disagree with them on this Isshue. It's abuse, nothing less.

1793
01:23:35,572 --> 01:23:38,052
Speaker 2: If say a policeman or a nurse in uniform dished

1794
01:23:38,133 --> 01:23:40,892
Speaker 2: out this mindus abuse, what would we think do deserve

1795
01:23:40,973 --> 01:23:44,052
Speaker 2: to be fired? So do you think that in terms

1796
01:23:44,093 --> 01:23:46,852
Speaker 2: of a free speech issue, Wendy that people should be

1797
01:23:47,213 --> 01:23:50,973
Speaker 2: allowed to yell things out. You take umbrage with the

1798
01:23:51,572 --> 01:23:54,012
Speaker 2: words he was using and the abuse he was giving.

1799
01:23:54,372 --> 01:23:56,253
Speaker 2: So if he if he had turned up Wendy and

1800
01:23:56,333 --> 01:24:00,652
Speaker 2: just sort of yelled some political points he disagreed with

1801
01:24:01,253 --> 01:24:03,572
Speaker 2: in a reasoned manner, you wouldn't have had a problem.

1802
01:24:04,893 --> 01:24:07,532
Speaker 25: No, I probably wouldn't have, because yeah, that was you know,

1803
01:24:07,692 --> 01:24:10,852
Speaker 25: like that was that was on topic and yeah, and

1804
01:24:10,893 --> 01:24:12,893
Speaker 25: you know that could have been something you know, he

1805
01:24:13,013 --> 01:24:15,053
Speaker 25: thought about, but it was just the way that he

1806
01:24:15,293 --> 01:24:18,133
Speaker 25: just came all of a sudden, he just appeared and

1807
01:24:18,133 --> 01:24:23,532
Speaker 25: then just abused abused Winston totally things that weren't even like,

1808
01:24:23,933 --> 01:24:25,892
Speaker 25: you know, we're talking about a bloody budget for rail

1809
01:24:25,973 --> 01:24:31,372
Speaker 25: for God's sake. So yeah, it was just like really,

1810
01:24:31,412 --> 01:24:34,213
Speaker 25: and everybody basically was just the mouth dropped and we're

1811
01:24:34,253 --> 01:24:34,612
Speaker 25: looking with.

1812
01:24:35,173 --> 01:24:36,492
Speaker 4: Was it awkward? Did you did you?

1813
01:24:36,692 --> 01:24:36,933
Speaker 19: Did you?

1814
01:24:37,053 --> 01:24:38,093
Speaker 16: Did you feel good?

1815
01:24:38,133 --> 01:24:40,572
Speaker 25: I did feel yeah. I did feel awkward. And I

1816
01:24:40,612 --> 01:24:43,213
Speaker 25: was standing quite close to the guy too, and I

1817
01:24:43,293 --> 01:24:46,972
Speaker 25: was just looking at him going oh my god, like yah, yeah,

1818
01:24:47,213 --> 01:24:49,492
Speaker 25: and I just felt like saying to him, you know,

1819
01:24:49,492 --> 01:24:52,372
Speaker 25: you should be ashamed of yourself. You know, everybody thinks

1820
01:24:52,372 --> 01:24:56,093
Speaker 25: you're idiots, and Winston was laughing and you know, you know,

1821
01:24:56,293 --> 01:24:58,452
Speaker 25: saying yeah, I thought I.

1822
01:24:58,492 --> 01:25:00,772
Speaker 3: Think I thought the bollocks line back to him was

1823
01:25:00,772 --> 01:25:03,133
Speaker 3: pretty good from Winston, Wendy, when I think the guy

1824
01:25:03,133 --> 01:25:04,732
Speaker 3: said to him, you're talking a load of bollocks and

1825
01:25:04,772 --> 01:25:07,452
Speaker 3: head and you look like bollocks.

1826
01:25:08,053 --> 01:25:10,012
Speaker 25: Yeah, exactly, yes.

1827
01:25:09,893 --> 01:25:10,933
Speaker 4: And what do you think about that?

1828
01:25:11,053 --> 01:25:13,093
Speaker 2: So, Wendy, what do you think about people saying that

1829
01:25:13,133 --> 01:25:16,333
Speaker 2: Winston Peters is you know, he's a member of parliament,

1830
01:25:16,812 --> 01:25:20,372
Speaker 2: you know, Deputy Prime minister. Should he behave with more

1831
01:25:20,372 --> 01:25:22,693
Speaker 2: decorum than he behaved?

1832
01:25:24,333 --> 01:25:25,133
Speaker 17: Oh?

1833
01:25:25,213 --> 01:25:28,372
Speaker 25: Yes, yeah, yeah, probably, yeah, But I just think it

1834
01:25:28,412 --> 01:25:31,173
Speaker 25: was just so unprovoked. It was just, you know, he

1835
01:25:31,293 --> 01:25:33,492
Speaker 25: was he was concentrating on reading the budget and the

1836
01:25:33,532 --> 01:25:36,772
Speaker 25: reporters were the asking questions about the rail and stuff,

1837
01:25:36,933 --> 01:25:39,732
Speaker 25: and the sky just came out of nowhere. So yeah,

1838
01:25:39,812 --> 01:25:41,973
Speaker 25: I think it. I think, yeah, it's sort of you know,

1839
01:25:42,372 --> 01:25:45,333
Speaker 25: and yeah, he was talking to Winston and no one

1840
01:25:45,372 --> 01:25:47,892
Speaker 25: else was saying, excuse me, you need to leave. So

1841
01:25:47,933 --> 01:25:50,333
Speaker 25: Winston was the only one that actually was addressing him.

1842
01:25:50,372 --> 01:25:52,652
Speaker 25: No one there wasn't any security or any thinks that

1843
01:25:52,692 --> 01:25:54,612
Speaker 25: you're saying to the skuy you know, like you actually

1844
01:25:54,612 --> 01:25:58,173
Speaker 25: need to leave. So yeah, I suppose if Winston didn't

1845
01:25:58,973 --> 01:26:02,012
Speaker 25: reply to him, you know, I don't know if anyone

1846
01:26:02,053 --> 01:26:02,572
Speaker 25: else would have.

1847
01:26:03,133 --> 01:26:06,412
Speaker 7: So yeah, yeah, well thank you, thank.

1848
01:26:06,253 --> 01:26:08,812
Speaker 4: You, thank you so much for you for your support.

1849
01:26:08,853 --> 01:26:11,452
Speaker 4: I appreciate it, very detailed. It was excellent, so good

1850
01:26:11,452 --> 01:26:12,492
Speaker 4: to have someone on the spot.

1851
01:26:13,452 --> 01:26:16,812
Speaker 25: Yeah, the guy was a complete knob. And yeah, I

1852
01:26:16,973 --> 01:26:18,772
Speaker 25: just I just felt because the school kits with you.

1853
01:26:18,973 --> 01:26:19,732
Speaker 4: And that's just ye.

1854
01:26:20,253 --> 01:26:22,692
Speaker 3: And that's fair enough because the language when language had it,

1855
01:26:22,732 --> 01:26:25,133
Speaker 3: the language towards the end was full on. And I

1856
01:26:25,173 --> 01:26:28,532
Speaker 3: think Winston even said as much as he was leaving.

1857
01:26:29,412 --> 01:26:31,652
Speaker 2: The Stixa says, I think he was a plant free

1858
01:26:31,692 --> 01:26:36,972
Speaker 2: advertising for Tonkin and Taylor. I'd never heard of them before,

1859
01:26:37,013 --> 01:26:39,293
Speaker 2: but I have said that that Tonkin and Taylor twenty

1860
01:26:39,333 --> 01:26:40,853
Speaker 2: eight times today.

1861
01:26:40,853 --> 01:26:43,093
Speaker 3: Everybody know, so they are eight hundred eighty teen eighty

1862
01:26:43,133 --> 01:26:45,452
Speaker 3: is the number to call. It is fourteen bus three.

1863
01:26:47,372 --> 01:26:49,732
Speaker 3: Very good afternoon to you, seventeen past three. Now, just

1864
01:26:49,732 --> 01:26:52,333
Speaker 3: a reminder, in about thirteen minutes, as part of our

1865
01:26:52,492 --> 01:26:55,532
Speaker 3: Us the Experts series that we do every Wednesday, Mark

1866
01:26:55,652 --> 01:26:58,972
Speaker 3: Vetti will be joining us to take your questions about

1867
01:26:59,013 --> 01:27:02,532
Speaker 3: anything PET related. So it pays again in early because

1868
01:27:02,612 --> 01:27:05,532
Speaker 3: the phone lines light up pretty much instantly. Oh eight

1869
01:27:05,652 --> 01:27:07,293
Speaker 3: hundred eighteen eighty will get you in the QB and

1870
01:27:07,333 --> 01:27:08,892
Speaker 3: nineteen nine two is the ten number.

1871
01:27:09,013 --> 01:27:11,293
Speaker 2: But right now we're talking about free speech and yelling

1872
01:27:11,333 --> 01:27:14,772
Speaker 2: at public, politicians and public when you've got your company's

1873
01:27:14,853 --> 01:27:18,013
Speaker 2: langered on, and what responsibility do you have to your

1874
01:27:18,053 --> 01:27:21,652
Speaker 2: company to behave in a certain way in public?

1875
01:27:22,532 --> 01:27:23,492
Speaker 4: Mark your thoughts.

1876
01:27:24,812 --> 01:27:30,253
Speaker 10: Yeah, guys, A free speech comes at a cost, all

1877
01:27:30,333 --> 01:27:34,333
Speaker 10: right to me. There's things that you can say that

1878
01:27:35,452 --> 01:27:38,372
Speaker 10: you have every right to say, but when you start

1879
01:27:38,612 --> 01:27:42,093
Speaker 10: making it personal, I think it's quite possible that you're

1880
01:27:42,093 --> 01:27:45,532
Speaker 10: going to get yourself into trouble like this guy did. Now,

1881
01:27:45,612 --> 01:27:49,612
Speaker 10: my employer has we have written in our contract this

1882
01:27:49,692 --> 01:27:53,932
Speaker 10: thing about bringing the company into disrepute. I had staff

1883
01:27:53,973 --> 01:27:55,972
Speaker 10: as well that I have to make sure that if

1884
01:27:56,013 --> 01:27:59,173
Speaker 10: they do this, we have to have bring them in

1885
01:27:59,173 --> 01:28:05,772
Speaker 10: and have a word. They have every right, I think,

1886
01:28:05,933 --> 01:28:11,492
Speaker 10: to instigate what damage this may have done to Tonkin

1887
01:28:11,492 --> 01:28:14,492
Speaker 10: and Taylor. You think about how many times you'd mentioned

1888
01:28:14,492 --> 01:28:18,892
Speaker 10: your name on the radio, and I for one too

1889
01:28:18,893 --> 01:28:22,093
Speaker 10: many I had to have dealings with their company. Would

1890
01:28:22,133 --> 01:28:24,372
Speaker 10: be thinking twice because I don't know where the sky

1891
01:28:24,452 --> 01:28:27,133
Speaker 10: works within the company, and I certainly wouldn't want to

1892
01:28:27,133 --> 01:28:30,452
Speaker 10: deal with them. So there's going to be ramifications for

1893
01:28:30,532 --> 01:28:34,853
Speaker 10: the employer. Like at a lumpet, there will be ramifications

1894
01:28:34,893 --> 01:28:36,213
Speaker 10: for the lawyer. Does that make sense?

1895
01:28:36,333 --> 01:28:36,572
Speaker 4: Yeah?

1896
01:28:36,812 --> 01:28:39,412
Speaker 2: I don't think it'd be much fun around the coffee machine,

1897
01:28:39,412 --> 01:28:39,692
Speaker 2: would he?

1898
01:28:40,053 --> 01:28:42,612
Speaker 4: By judges, I mean just.

1899
01:28:43,173 --> 01:28:46,093
Speaker 2: For me for some reason, I don't blame Tonkin and

1900
01:28:46,133 --> 01:28:48,173
Speaker 2: Taylor to say their name for the four thousand time.

1901
01:28:48,492 --> 01:28:48,972
Speaker 1: No.

1902
01:28:49,933 --> 01:28:53,213
Speaker 2: I don't look at them and go they're responsible because

1903
01:28:53,492 --> 01:28:57,132
Speaker 2: I imagine a big company, and every company has good people

1904
01:28:57,173 --> 01:28:59,572
Speaker 2: and their kids. We also know how hard it is

1905
01:28:59,612 --> 01:29:01,892
Speaker 2: to get rid of employees sometimes when they are so

1906
01:29:02,253 --> 01:29:05,612
Speaker 2: for me personally, I would never blame the company, but

1907
01:29:05,652 --> 01:29:09,013
Speaker 2: I can see from their perspective they might look at

1908
01:29:09,053 --> 01:29:11,333
Speaker 2: it and go, well, this doesn't make us look great.

1909
01:29:11,333 --> 01:29:13,412
Speaker 2: But I also wouldn't want him to be fired for this.

1910
01:29:13,772 --> 01:29:17,253
Speaker 3: Yeah, they can't condone what he says, but no, so.

1911
01:29:17,532 --> 01:29:19,812
Speaker 2: I think saying that for them coming out, I think

1912
01:29:19,853 --> 01:29:22,013
Speaker 2: to say, look, we don't support what he said is

1913
01:29:22,133 --> 01:29:24,532
Speaker 2: enough for me, and maybe they'll go mate tail whip

1914
01:29:24,532 --> 01:29:27,293
Speaker 2: your landyard off next time you wanted to throw abuse

1915
01:29:27,572 --> 01:29:28,892
Speaker 2: people for their age and public.

1916
01:29:30,053 --> 01:29:33,333
Speaker 10: Yeah, and look, if you're not identifiable and you keep

1917
01:29:33,372 --> 01:29:36,173
Speaker 10: yourself as anonymous when you when you're doing something like this,

1918
01:29:36,572 --> 01:29:39,812
Speaker 10: by all means, go go for gold. But we actually

1919
01:29:39,812 --> 01:29:42,253
Speaker 10: take time out to educate all our people. It's not

1920
01:29:42,492 --> 01:29:45,612
Speaker 10: just free speech. Well I guess it is free speech.

1921
01:29:46,093 --> 01:29:49,333
Speaker 10: It's social media training and everything. It's like, you know,

1922
01:29:49,333 --> 01:29:52,772
Speaker 10: if you've got your social media Facebook account up and

1923
01:29:52,853 --> 01:29:55,932
Speaker 10: you start slagging off and people can identify what company

1924
01:29:55,973 --> 01:30:00,053
Speaker 10: you work for. Yeah, it's not a good look.

1925
01:30:00,173 --> 01:30:03,093
Speaker 2: Right, Yeah, well, thank for you cool, But you know

1926
01:30:03,253 --> 01:30:07,173
Speaker 2: people say, there's that look guys. Winny and his eft

1927
01:30:07,412 --> 01:30:11,452
Speaker 2: up government ruined thousands of people's lives in Wellington. All

1928
01:30:11,492 --> 01:30:14,572
Speaker 2: government members are legit targets with the way that they behave.

1929
01:30:15,213 --> 01:30:18,612
Speaker 2: This person says, oh please, Winston was awful. They both

1930
01:30:18,612 --> 01:30:22,092
Speaker 2: looked like fools. Winston is full of himself and deserved

1931
01:30:22,133 --> 01:30:24,293
Speaker 2: everything he got. Well, I would push back on that.

1932
01:30:24,333 --> 01:30:28,493
Speaker 2: Winston didn't get much. He got an opportunity to completely

1933
01:30:28,532 --> 01:30:32,372
Speaker 2: destroy someone in public. And Winston Peters is very quick, obviously,

1934
01:30:32,492 --> 01:30:37,333
Speaker 2: and he does professionally debates professionally, so you know you're

1935
01:30:37,333 --> 01:30:40,612
Speaker 2: going up against a tough one. And Winston seem pretty

1936
01:30:40,652 --> 01:30:42,372
Speaker 2: toughed about it because he got an opportunity to get

1937
01:30:42,372 --> 01:30:46,732
Speaker 2: some good zingers back. But yeah, maybe in this situation,

1938
01:30:46,772 --> 01:30:48,812
Speaker 2: the more I think says either way, I pay Winston

1939
01:30:48,853 --> 01:30:50,213
Speaker 2: wages and think his behavior was.

1940
01:30:50,652 --> 01:30:55,252
Speaker 3: Appalling well in this situation. And I've certainly criticized Winston

1941
01:30:55,412 --> 01:30:58,892
Speaker 3: on this program before, but in this situation, it feels

1942
01:30:58,933 --> 01:31:02,133
Speaker 3: that this feller's behavior was uncalled for Winston was They're

1943
01:31:02,253 --> 01:31:03,933
Speaker 3: doing a stand up and all of a sudden, this

1944
01:31:04,013 --> 01:31:07,372
Speaker 3: fowler comes along, just jumped off the train about to

1945
01:31:07,452 --> 01:31:10,333
Speaker 3: head to work and just starts going off at at

1946
01:31:10,372 --> 01:31:13,173
Speaker 3: a government minister. So it's very different than say, someone

1947
01:31:13,253 --> 01:31:15,692
Speaker 3: in a sign written van cuts you off in traffic.

1948
01:31:15,732 --> 01:31:17,852
Speaker 3: They might have done it accidentally. Then you pull over

1949
01:31:17,933 --> 01:31:19,812
Speaker 3: the side of the road and start arguing and having

1950
01:31:19,812 --> 01:31:22,532
Speaker 3: to go at each other. In that situation, then that's

1951
01:31:22,692 --> 01:31:25,492
Speaker 3: very different that even though you're in a sign written car.

1952
01:31:26,372 --> 01:31:29,013
Speaker 3: I think it's about context, and in this context, this

1953
01:31:29,093 --> 01:31:30,213
Speaker 3: guy was being out of line.

1954
01:31:30,293 --> 01:31:30,853
Speaker 1: Yeah.

1955
01:31:31,013 --> 01:31:33,253
Speaker 2: I was just thinking about the time when Sir Rob

1956
01:31:33,293 --> 01:31:36,973
Speaker 2: meldoone punched that bloke in the guts in the cargo.

1957
01:31:36,732 --> 01:31:37,852
Speaker 3: While you got the we video there.

1958
01:31:38,333 --> 01:31:41,412
Speaker 2: No, but so you know that was a different situation.

1959
01:31:41,492 --> 01:31:44,772
Speaker 2: Someone was heckling to Rob Meldon, he wasn't a serving

1960
01:31:45,133 --> 01:31:47,412
Speaker 2: and he just gave him a whack in the guts. Yeah,

1961
01:31:48,253 --> 01:31:52,172
Speaker 2: that's too far, I would say, when some Peters started

1962
01:31:52,173 --> 01:31:54,572
Speaker 2: taking a swing, that would definitely be too far.

1963
01:31:54,772 --> 01:31:57,012
Speaker 3: Yeah, but just on the question, you know, I can't

1964
01:31:57,013 --> 01:32:00,053
Speaker 3: think of any other minister maybe David Seymour that would

1965
01:32:00,133 --> 01:32:02,492
Speaker 3: give back as good as they get. So Whinston Peters

1966
01:32:02,532 --> 01:32:05,333
Speaker 3: are clearly the master, don't don't we kind of want

1967
01:32:05,333 --> 01:32:08,013
Speaker 3: that from our politicians a little bit instead of I

1968
01:32:08,013 --> 01:32:11,732
Speaker 3: think most other ministers faced in that situation, we're just bolt.

1969
01:32:11,812 --> 01:32:14,692
Speaker 3: They'd get out of it and say shows over. We

1970
01:32:14,732 --> 01:32:17,053
Speaker 3: can't go on because this guy won't let us go on,

1971
01:32:17,173 --> 01:32:20,572
Speaker 3: So we're done. Whereas Winnie pushes back, and the part

1972
01:32:20,572 --> 01:32:24,253
Speaker 3: of me likes that. Yeah, you can't caught up with crap.

1973
01:32:24,293 --> 01:32:27,852
Speaker 2: Whenever I see a verbal back and forth of any

1974
01:32:27,893 --> 01:32:32,092
Speaker 2: type between people, I can't help but admire the person

1975
01:32:32,133 --> 01:32:35,213
Speaker 2: that wins the verbal staush. Yeah, And if you're in

1976
01:32:35,213 --> 01:32:37,253
Speaker 2: a situation like this where someone starts it and so

1977
01:32:37,372 --> 01:32:40,372
Speaker 2: clearly loses it, then there is something quite funny about it,

1978
01:32:40,612 --> 01:32:43,133
Speaker 2: you know exactly, But you know a lot of people

1979
01:32:43,173 --> 01:32:47,772
Speaker 2: think that Winston Peters should not be should not be

1980
01:32:47,772 --> 01:32:49,293
Speaker 2: behaving like that in public.

1981
01:32:49,372 --> 01:32:51,133
Speaker 3: You know, oh, one hundred and eighty ten eighty. Keen

1982
01:32:51,213 --> 01:32:56,772
Speaker 3: on your thoughts. Today is twenty three pass three.

1983
01:32:57,933 --> 01:33:01,612
Speaker 1: Matt Heathen Taylor Adams afternoons call oh, eight hundred eighty

1984
01:33:01,652 --> 01:33:04,132
Speaker 1: ten eighty on News Talk ZB afternoon.

1985
01:33:04,213 --> 01:33:05,692
Speaker 3: It is twenty five past three.

1986
01:33:06,053 --> 01:33:07,932
Speaker 4: This texasays public space, free country.

1987
01:33:08,093 --> 01:33:10,293
Speaker 3: Yep, I agree then, yeah, I actually see it.

1988
01:33:10,372 --> 01:33:12,852
Speaker 2: Yeah, but I would just take my lanyard off if

1989
01:33:12,933 --> 01:33:17,652
Speaker 2: I was going to do that. Jim your thoughts.

1990
01:33:17,612 --> 01:33:19,813
Speaker 10: Here, You're very good.

1991
01:33:20,293 --> 01:33:23,293
Speaker 16: I reckon Tom and Telish a good described promotion in

1992
01:33:23,333 --> 01:33:25,732
Speaker 16: a rage he couldn't have couldn't have orchestrated a bit

1993
01:33:25,772 --> 01:33:28,933
Speaker 16: of purplicity was Yeah.

1994
01:33:29,013 --> 01:33:30,772
Speaker 2: I mean I think nineteen nine percent people don't know

1995
01:33:30,772 --> 01:33:33,532
Speaker 2: what they do. But yeah, the name has been I

1996
01:33:33,692 --> 01:33:36,772
Speaker 2: personally said it. I reckon at least at least twenty

1997
01:33:36,772 --> 01:33:38,253
Speaker 2: five times today.

1998
01:33:38,812 --> 01:33:43,052
Speaker 7: Yeah, I know Tom Taylor is with the clients are.

1999
01:33:42,893 --> 01:33:47,052
Speaker 4: The good good company in the opinion, right.

2000
01:33:48,772 --> 01:33:56,732
Speaker 12: All right, mouthy, Yeah.

2001
01:33:54,253 --> 01:33:55,812
Speaker 3: He wanted to say it, but he quite he couldn't

2002
01:33:55,853 --> 01:33:56,372
Speaker 3: quite get there.

2003
01:33:57,213 --> 01:33:59,612
Speaker 2: I think that every employment contract I've signed his stay

2004
01:34:00,093 --> 01:34:02,013
Speaker 2: that I that I agreed to represent the company a

2005
01:34:02,053 --> 01:34:06,772
Speaker 2: positive way so as not to probrium upon it, that

2006
01:34:06,933 --> 01:34:10,493
Speaker 2: is to to custom Yeah right, yeah, I mean Tonkin

2007
01:34:10,532 --> 01:34:12,213
Speaker 2: and Taylor were the one wants to say the name again,

2008
01:34:12,372 --> 01:34:14,852
Speaker 2: did put up their hands and apologize, And I think

2009
01:34:14,853 --> 01:34:18,092
Speaker 2: they do a certain amount of business with the government,

2010
01:34:18,133 --> 01:34:21,293
Speaker 2: which might make it particularly you know, close to close

2011
01:34:21,333 --> 01:34:21,972
Speaker 2: to home for them.

2012
01:34:22,133 --> 01:34:24,652
Speaker 3: Yeah, this takes us here is Tonkin and Taylor are

2013
01:34:24,652 --> 01:34:28,533
Speaker 3: a well respected civil consulting company. This guy will definitely

2014
01:34:28,732 --> 01:34:31,612
Speaker 3: be fired for his actions, particularly ironic as Tonkin and

2015
01:34:31,612 --> 01:34:34,253
Speaker 3: Taylor do the majority of consulting work for Kerry Rail,

2016
01:34:34,293 --> 01:34:35,492
Speaker 3: which is what you were saying there.

2017
01:34:35,853 --> 01:34:37,492
Speaker 2: Hi, guys, the guy thought he was going to it

2018
01:34:37,612 --> 01:34:39,333
Speaker 2: was going to be his moment and then got schooled

2019
01:34:39,333 --> 01:34:40,253
Speaker 2: by an eighty year old car.

2020
01:34:40,492 --> 01:34:40,692
Speaker 16: Yeah.

2021
01:34:40,692 --> 01:34:41,692
Speaker 3: I think that's a lot of it.

2022
01:34:41,772 --> 01:34:44,093
Speaker 2: I mean he was he was hassling Winston Peters for

2023
01:34:44,133 --> 01:34:47,012
Speaker 2: being old in quite a biggoted fashion, and then got

2024
01:34:47,053 --> 01:34:49,173
Speaker 2: proved that the eight year old was smarter than him, yeah,

2025
01:34:49,933 --> 01:34:53,293
Speaker 2: or quicker than him in a back verbal back and forth.

2026
01:34:53,372 --> 01:34:55,692
Speaker 2: So that's a little bit humiliating for the guy, But

2027
01:34:56,372 --> 01:34:58,013
Speaker 2: I absolutely support his right to.

2028
01:34:58,053 --> 01:34:59,412
Speaker 4: Yell whatever he wants in public.

2029
01:34:59,492 --> 01:35:01,852
Speaker 2: Maybe maybe lay off the fall on square words around

2030
01:35:01,893 --> 01:35:04,972
Speaker 2: the school kids potentially, but you know, yeah, you say

2031
01:35:05,133 --> 01:35:07,452
Speaker 2: public place, free speech, let's go free country.

2032
01:35:07,492 --> 01:35:09,372
Speaker 3: Well, as a punishment, you know, whether or not this

2033
01:35:09,452 --> 01:35:12,692
Speaker 3: guy gets sacked from Tonkin and Taylor, we will find out.

2034
01:35:12,772 --> 01:35:14,692
Speaker 3: I hope he doesn't. But in terms of a punishment,

2035
01:35:14,893 --> 01:35:17,732
Speaker 3: it doesn't get worse than being ridiculed by a big

2036
01:35:17,973 --> 01:35:21,293
Speaker 3: proportion of the country. You know, people seeing that and

2037
01:35:21,293 --> 01:35:23,852
Speaker 3: looking at the guy and thinking you're an idiot, You're

2038
01:35:23,893 --> 01:35:24,372
Speaker 3: an idiot.

2039
01:35:24,452 --> 01:35:26,612
Speaker 4: Well, he doesn't look like he's a lot of fun.

2040
01:35:27,253 --> 01:35:29,173
Speaker 4: But you know, we're only seeing a small snap. Maybe

2041
01:35:29,293 --> 01:35:30,013
Speaker 4: is having a bad day.

2042
01:35:30,133 --> 01:35:33,492
Speaker 3: Yeah, exactly right. Eight hundred eighty ten eighty We've got

2043
01:35:33,492 --> 01:35:37,293
Speaker 3: Mark Veddi animal behaviorist with us, very shortly, always a

2044
01:35:37,333 --> 01:35:40,372
Speaker 3: popular segment. If you've got a question related to your pet,

2045
01:35:40,412 --> 01:35:42,772
Speaker 3: he is the man to chat to. Doesn't matter what

2046
01:35:42,812 --> 01:35:45,772
Speaker 3: your pet is. He is across all animals, So the

2047
01:35:45,772 --> 01:35:48,012
Speaker 3: weirder the better. But eight hundred eighty ten eighty nine,

2048
01:35:48,013 --> 01:35:49,932
Speaker 3: two ninety two is the text number. It is twenty

2049
01:35:49,933 --> 01:35:50,532
Speaker 3: eight past three.

2050
01:35:53,293 --> 01:35:56,932
Speaker 15: Jew's talk said, be headlines with blue bubble taxis. It's

2051
01:35:57,053 --> 01:36:00,492
Speaker 15: no trouble with the blue bubble. The Finance Minister says

2052
01:36:00,532 --> 01:36:05,013
Speaker 15: tomorrow's budget won't change superannuation and its policies will let

2053
01:36:05,093 --> 01:36:09,173
Speaker 15: all kiwis look forward to financial security and retirement. Nikola

2054
01:36:09,213 --> 01:36:12,812
Speaker 15: Willis says money saved by rushing through pay equity changes,

2055
01:36:13,293 --> 01:36:17,652
Speaker 15: largely affecting women workers, will go into education, health, police

2056
01:36:17,772 --> 01:36:21,372
Speaker 15: and defense. The government has given up on attacks that

2057
01:36:21,492 --> 01:36:24,933
Speaker 15: would have charged overseas tech companies like Google and Facebook

2058
01:36:25,213 --> 01:36:28,932
Speaker 15: for New Zealand revenue worth nearly one hundred million dollars

2059
01:36:28,973 --> 01:36:32,533
Speaker 15: a year. The US President promised this year to retaliate

2060
01:36:32,772 --> 01:36:37,612
Speaker 15: on what he called overseas extortion. The Electricity Authority says

2061
01:36:37,652 --> 01:36:40,812
Speaker 15: it's confident our supply will last us through the cold

2062
01:36:40,853 --> 01:36:45,133
Speaker 15: winter months. A rural Canterbury school students in hospital in

2063
01:36:45,173 --> 01:36:50,172
Speaker 15: a moderate condition, allegedly assaulted by another child. Emergency services

2064
01:36:50,173 --> 01:36:53,293
Speaker 15: were called to Oxford Area School, just outside of christ Church.

2065
01:36:53,612 --> 01:36:58,612
Speaker 15: About two Auckland emergency departments diverting patients to urgent care

2066
01:36:58,652 --> 01:37:02,452
Speaker 15: clinics with vouchers to cover costs. You can find out

2067
01:37:02,532 --> 01:37:05,452
Speaker 15: more at enzid Herald Premium. Back to matt Eath and

2068
01:37:05,492 --> 01:37:06,772
Speaker 15: Tyler Adams.

2069
01:37:06,333 --> 01:37:08,253
Speaker 3: Thank you very much Rayleen So. Mark VideA is a

2070
01:37:08,333 --> 01:37:11,412
Speaker 3: world renowned animal behavior a dog trainer and educator who

2071
01:37:11,412 --> 01:37:13,732
Speaker 3: has been working with animals for over forty years. He's

2072
01:37:13,772 --> 01:37:17,012
Speaker 3: a trained animal psychologist and created the Dogs in online

2073
01:37:17,053 --> 01:37:20,852
Speaker 3: training program. He's about to launch Kats and Cats in

2074
01:37:20,973 --> 01:37:22,772
Speaker 3: Rather and he joins us once a month on Ask

2075
01:37:22,853 --> 01:37:26,372
Speaker 3: the Experting. He's back with us, Matt Mark, good afternoon,

2076
01:37:26,372 --> 01:37:29,452
Speaker 3: How are you very very good?

2077
01:37:29,732 --> 01:37:33,812
Speaker 2: Let's jump straight into it, Jess, let's do it. Welcome

2078
01:37:33,812 --> 01:37:34,412
Speaker 2: to the show.

2079
01:37:35,213 --> 01:37:37,773
Speaker 5: Hello, Hi Jess.

2080
01:37:38,333 --> 01:37:39,293
Speaker 14: Hey, our question.

2081
01:37:39,492 --> 01:37:41,692
Speaker 25: So, I've got a covertal who's a year and a

2082
01:37:41,732 --> 01:37:42,693
Speaker 25: half old.

2083
01:37:42,652 --> 01:37:47,173
Speaker 14: Who's a six and a half kilo guy, and we

2084
01:37:47,412 --> 01:37:51,093
Speaker 14: have just acquired a beagle who's two years old, a

2085
01:37:51,213 --> 01:37:55,452
Speaker 14: very relaxed beagle, and the convertial hates them and keeps

2086
01:37:56,253 --> 01:37:57,532
Speaker 14: like cruising around trying.

2087
01:37:57,333 --> 01:38:00,852
Speaker 10: To fite beagles years. I thought it would be around

2088
01:38:01,053 --> 01:38:01,412
Speaker 10: how old.

2089
01:38:01,692 --> 01:38:02,532
Speaker 5: How old is the beagle?

2090
01:38:02,572 --> 01:38:10,333
Speaker 14: And he is the both male and the bagel is

2091
01:38:10,372 --> 01:38:14,013
Speaker 14: two years old and he has fourteen so he's the

2092
01:38:14,053 --> 01:38:14,652
Speaker 14: bigger of the.

2093
01:38:14,612 --> 01:38:19,612
Speaker 5: Truth, right, And are either them entire or the desext.

2094
01:38:20,772 --> 01:38:24,333
Speaker 14: A the bagel of desex the little caboodle event.

2095
01:38:24,333 --> 01:38:28,772
Speaker 5: As yet right? Right, okay, yeah, and you're saying the

2096
01:38:28,812 --> 01:38:31,692
Speaker 5: kaboodle is having a crack at the at the beagle.

2097
01:38:32,812 --> 01:38:36,372
Speaker 5: There is being aggressive with the beagel and a lot

2098
01:38:36,412 --> 01:38:39,812
Speaker 5: of humping. Ye, so yeah, I mean the good news

2099
01:38:39,893 --> 01:38:42,053
Speaker 5: is it's a relevant civilians if you're happy to do it.

2100
01:38:42,093 --> 01:38:45,652
Speaker 5: And that's d sex in the cavidal. One of the

2101
01:38:45,652 --> 01:38:48,732
Speaker 5: problems with an entire male with another dog generally, and

2102
01:38:48,772 --> 01:38:51,532
Speaker 5: particularly a D SX male, he'll treat it more like

2103
01:38:51,532 --> 01:38:54,852
Speaker 5: a female as you can see he's doing. And so

2104
01:38:55,093 --> 01:38:58,452
Speaker 5: it doesn't mean that males don't mount female vice versa.

2105
01:38:58,572 --> 01:39:01,772
Speaker 5: But when you've got an entire male, almost definitely, it'll

2106
01:39:01,812 --> 01:39:05,573
Speaker 5: be the the androgens, you know, particularly testosterone that's stimulating

2107
01:39:05,612 --> 01:39:10,772
Speaker 5: the behavior. And the simple answers to if you're happy

2108
01:39:10,812 --> 01:39:13,133
Speaker 5: to do that is to get him d SEXT. So

2109
01:39:13,253 --> 01:39:16,092
Speaker 5: if you're new to him, you'll find that his mounting

2110
01:39:16,133 --> 01:39:19,173
Speaker 5: behavior will fall away quite quickly, normally in about a month.

2111
01:39:20,812 --> 01:39:22,932
Speaker 5: And what you've got to be careful of is that

2112
01:39:23,572 --> 01:39:26,173
Speaker 5: the hump of the mounting behavior can be perceived as

2113
01:39:26,213 --> 01:39:28,572
Speaker 5: a dominance threat as well. You look at this's what

2114
01:39:28,652 --> 01:39:32,652
Speaker 5: dominant dogs do also to subordinates at times, you know,

2115
01:39:33,053 --> 01:39:35,093
Speaker 5: so that can be read that way, and therefore the

2116
01:39:35,093 --> 01:39:37,732
Speaker 5: bigger dog, the beagle, may decide that he's going to

2117
01:39:37,772 --> 01:39:40,732
Speaker 5: sort the cavoodle out and you know, and you end

2118
01:39:40,772 --> 01:39:43,093
Speaker 5: up in a fight. That sounds good that he's laid

2119
01:39:43,133 --> 01:39:45,572
Speaker 5: back eagle. So that's going to good use. And that's

2120
01:39:45,612 --> 01:39:50,213
Speaker 5: partly because of de sext but because of twice his size,

2121
01:39:50,253 --> 01:39:53,093
Speaker 5: you'll you know, there's the risk that you know, the

2122
01:39:53,093 --> 01:39:57,412
Speaker 5: beg will counter respond to theodle. So d sexing is

2123
01:39:57,452 --> 01:40:00,772
Speaker 5: a simple answer. You can do some behavioral techniques that

2124
01:40:00,812 --> 01:40:04,972
Speaker 5: can help and so and we can talk more about that,

2125
01:40:05,013 --> 01:40:07,972
Speaker 5: but it's a little more complex to describe it. Basically

2126
01:40:08,013 --> 01:40:11,013
Speaker 5: where you use the effective meat and greet technique every

2127
01:40:11,053 --> 01:40:13,892
Speaker 5: time they come together for a while. So that's something

2128
01:40:13,893 --> 01:40:16,412
Speaker 5: that you should be doing in the meantime. And the

2129
01:40:16,412 --> 01:40:17,812
Speaker 5: best way to do this is with a clicker.

2130
01:40:18,253 --> 01:40:22,652
Speaker 3: And yes, right, all right, all the best jeers, Thank

2131
01:40:22,692 --> 01:40:23,293
Speaker 3: you very much.

2132
01:40:24,253 --> 01:40:24,652
Speaker 4: Julia.

2133
01:40:24,812 --> 01:40:26,692
Speaker 2: You've got a hunt away a five year old that

2134
01:40:26,973 --> 01:40:28,412
Speaker 2: hates motorbikes and planes.

2135
01:40:29,652 --> 01:40:32,372
Speaker 6: Well, yeah, she's my granddog and I get to look

2136
01:40:32,372 --> 01:40:35,892
Speaker 6: after her quite a lot. She doesn't actually hate them,

2137
01:40:35,933 --> 01:40:38,852
Speaker 6: but she just she just barks. As hundred ways do

2138
01:40:39,933 --> 01:40:43,173
Speaker 6: more at the sound of them. Definitely. If she sees

2139
01:40:43,173 --> 01:40:45,812
Speaker 6: the post ego past on the on a motorbike, she'll

2140
01:40:45,853 --> 01:40:48,452
Speaker 6: bark and as soon as the motorbikes turned off she'll stop,

2141
01:40:48,532 --> 01:40:49,613
Speaker 6: so she's not aggressive.

2142
01:40:50,973 --> 01:40:51,812
Speaker 9: I guess I've got three.

2143
01:40:51,853 --> 01:40:55,612
Speaker 5: That's quite common. Yeah, yeah, it's quite common stuff for

2144
01:40:55,612 --> 01:40:56,572
Speaker 5: a hundaway. Yeah.

2145
01:40:57,173 --> 01:40:57,372
Speaker 22: Yeah.

2146
01:40:57,572 --> 01:40:59,732
Speaker 6: What's the best thing to do when it happens when

2147
01:40:59,772 --> 01:41:03,772
Speaker 6: you're out walking? That's one question? Can you do anything

2148
01:41:03,812 --> 01:41:06,452
Speaker 6: about it long term? And may she grow out of it?

2149
01:41:07,652 --> 01:41:09,293
Speaker 5: Yeah? She probably, you won't go out of it, so

2150
01:41:09,333 --> 01:41:11,572
Speaker 5: it's better as the trainer out of it. And it

2151
01:41:11,652 --> 01:41:16,372
Speaker 5: is very trainable. So normally what I do is part

2152
01:41:16,412 --> 01:41:18,532
Speaker 5: of it that there's to two parts. One that I

2153
01:41:18,652 --> 01:41:21,452
Speaker 5: teach the hunter way to a quiet command, you know,

2154
01:41:21,492 --> 01:41:23,372
Speaker 5: so that and I use the clicker for that. So

2155
01:41:23,772 --> 01:41:26,652
Speaker 5: you set it up in a situation normally on a

2156
01:41:26,652 --> 01:41:29,333
Speaker 5: little short lead while I'm training, and then I get

2157
01:41:29,372 --> 01:41:32,492
Speaker 5: it to bark and then teach it to be quiet.

2158
01:41:32,532 --> 01:41:34,612
Speaker 5: As soon as it's quiet for three to five seconds,

2159
01:41:34,772 --> 01:41:37,293
Speaker 5: I click and reward and then I extend that out

2160
01:41:37,333 --> 01:41:40,932
Speaker 5: to learn is what quiet is. So that's the first

2161
01:41:40,973 --> 01:41:43,253
Speaker 5: technique that I use as I teach the hund way

2162
01:41:43,253 --> 01:41:45,612
Speaker 5: to be quiet, which is pretty important because hunter ways

2163
01:41:45,652 --> 01:41:47,852
Speaker 5: are barking dogs. That's what they do for a job,

2164
01:41:47,933 --> 01:41:50,812
Speaker 5: you know, So when they see a motorbike, when they're

2165
01:41:50,893 --> 01:41:54,492
Speaker 5: hyper arounded by something moving fast like a motorbike or

2166
01:41:54,532 --> 01:41:57,293
Speaker 5: a plane, think about what they bark at. They bark

2167
01:41:57,372 --> 01:42:00,213
Speaker 5: it sheep and cattle that are moving, and they try

2168
01:42:00,253 --> 01:42:03,093
Speaker 5: and make them move. So that's you know, anything that

2169
01:42:03,213 --> 01:42:08,612
Speaker 5: moves stimulates their hurting behavior, and so that orients them

2170
01:42:08,612 --> 01:42:12,532
Speaker 5: to the stimulus. Motorbike noise, main noise. They'll look at

2171
01:42:12,572 --> 01:42:15,333
Speaker 5: it and then they'll bark at it. So normally I

2172
01:42:15,452 --> 01:42:18,452
Speaker 5: teach them. I get some audio tapes of those sounds,

2173
01:42:18,812 --> 01:42:22,412
Speaker 5: and then I am using a desensitization technique and a clicker.

2174
01:42:22,732 --> 01:42:26,933
Speaker 5: I work and teach them to accept those sounds without vocalizing,

2175
01:42:27,253 --> 01:42:29,372
Speaker 5: and I use my quiet command when I'm doing that.

2176
01:42:29,612 --> 01:42:32,892
Speaker 5: Once I've done that in a training context that takes

2177
01:42:33,053 --> 01:42:35,452
Speaker 5: probably a week or two, then I'll start to extend

2178
01:42:35,492 --> 01:42:38,093
Speaker 5: it out in real situations. And I normally get a

2179
01:42:38,133 --> 01:42:39,652
Speaker 5: mate with a motorbike and just do a bit of

2180
01:42:39,692 --> 01:42:42,412
Speaker 5: work around home, and then I slowly build that up

2181
01:42:42,452 --> 01:42:44,532
Speaker 5: and then I'll go to something I can airport and

2182
01:42:44,572 --> 01:42:47,612
Speaker 5: do some plane work. But yeah, you can train it

2183
01:42:47,692 --> 01:42:50,452
Speaker 5: out of them. And that's underways are really smart. So

2184
01:42:51,013 --> 01:42:52,612
Speaker 5: get them on a clicker and you watch how quickly

2185
01:42:52,692 --> 01:42:54,932
Speaker 5: they learn. They love food, very vocal dogs.

2186
01:42:55,013 --> 01:42:56,653
Speaker 3: Underways all the best, Julia.

2187
01:42:56,612 --> 01:42:57,013
Speaker 4: Tell you what.

2188
01:42:57,452 --> 01:42:59,492
Speaker 2: The weirdest thing that I've seen is this dog I

2189
01:42:59,572 --> 01:43:01,933
Speaker 2: know called Benny, who lives in topor.

2190
01:43:01,692 --> 01:43:03,053
Speaker 4: Great name, great dog.

2191
01:43:03,213 --> 01:43:06,852
Speaker 2: Yes, human eye, but he only think. He barks at

2192
01:43:06,893 --> 01:43:09,253
Speaker 2: as parasailors, you know, out the bed of the boats. Yeah,

2193
01:43:09,253 --> 01:43:12,052
Speaker 2: it's so bizarre. He just sees them and they seem

2194
01:43:12,093 --> 01:43:14,133
Speaker 2: so far away. Do nothing else, but he sees these

2195
01:43:14,173 --> 01:43:17,412
Speaker 2: parasailors and they just make him so angry. It's bizarre.

2196
01:43:19,333 --> 01:43:21,693
Speaker 5: Were parasale? It cause the bloody unusual.

2197
01:43:21,293 --> 01:43:28,732
Speaker 3: Things chasing you. Right, thank you very much, and teach

2198
01:43:28,772 --> 01:43:30,772
Speaker 3: them to yeah, perfect, right.

2199
01:43:30,853 --> 01:43:31,053
Speaker 5: Mark.

2200
01:43:31,093 --> 01:43:34,012
Speaker 3: We've got a couple of text questions here. This one

2201
01:43:34,173 --> 01:43:37,333
Speaker 3: says my husband and I have recently bought a new

2202
01:43:37,372 --> 01:43:39,213
Speaker 3: puppy and we have had him for two weeks now.

2203
01:43:39,452 --> 01:43:41,572
Speaker 3: He is six months old from a breeder. Unfortunately, he

2204
01:43:41,572 --> 01:43:44,133
Speaker 3: barks at my husband whenever he enters the room and

2205
01:43:44,173 --> 01:43:46,053
Speaker 3: we are not sure what to do about it. It's

2206
01:43:46,093 --> 01:43:46,852
Speaker 3: driving us mad.

2207
01:43:47,973 --> 01:43:51,572
Speaker 5: Yeah, okay. So first first thing to understand as you

2208
01:43:51,612 --> 01:43:53,972
Speaker 5: should get you puppy eight weeks. When when a breeder

2209
01:43:53,973 --> 01:43:56,732
Speaker 5: gives you a puppy at six months old, then it

2210
01:43:56,853 --> 01:44:00,092
Speaker 5: means it's been kept to see if it's got breeding potential,

2211
01:44:00,732 --> 01:44:03,213
Speaker 5: and then they kept it to six months in the

2212
01:44:03,333 --> 01:44:06,492
Speaker 5: breeding context, which isn't normally very good. It's normally you know,

2213
01:44:06,532 --> 01:44:09,812
Speaker 5: it's normally a Kinnolt situation or they're not getting enough

2214
01:44:09,893 --> 01:44:12,692
Speaker 5: exposure to people and other dogs. You always like to

2215
01:44:12,732 --> 01:44:15,293
Speaker 5: get the puppy at two months, that's always the best.

2216
01:44:15,492 --> 01:44:18,933
Speaker 5: So realizing that you've missed the formative period of socialization

2217
01:44:19,452 --> 01:44:21,732
Speaker 5: for him, which is two to four months, and so

2218
01:44:21,853 --> 01:44:24,452
Speaker 5: now he's six months, he's a teenager and he hasn't

2219
01:44:24,452 --> 01:44:28,492
Speaker 5: probably been socialized well enough. That's my anticipation based on

2220
01:44:28,572 --> 01:44:32,173
Speaker 5: lots of having seen many many dogs. So normally you're

2221
01:44:32,213 --> 01:44:34,852
Speaker 5: now going to teach them a meet and greet technique

2222
01:44:34,893 --> 01:44:38,053
Speaker 5: for people. And the first thing I'd do with the

2223
01:44:38,093 --> 01:44:40,612
Speaker 5: male owner is that I'd get him on to the

2224
01:44:40,612 --> 01:44:43,412
Speaker 5: clicker with the dog and get him working doing what

2225
01:44:43,412 --> 01:44:46,293
Speaker 5: it called joining up. It's a simple little technique with

2226
01:44:46,372 --> 01:44:49,213
Speaker 5: a clicker, the dog larrant to him quite quickly. You

2227
01:44:49,293 --> 01:44:51,333
Speaker 5: need to start the dog on the clicker so he

2228
01:44:51,372 --> 01:44:55,253
Speaker 5: gets responsive and understand what it does. And then within

2229
01:44:55,293 --> 01:44:57,213
Speaker 5: two or three days you should better transfer that to

2230
01:44:57,293 --> 01:45:01,053
Speaker 5: your husband with your partner, and in that context, he

2231
01:45:01,173 --> 01:45:05,173
Speaker 5: needs to take control of the resources, particularly feeding and

2232
01:45:05,213 --> 01:45:08,253
Speaker 5: the clicker training, and you'll see the dog very quickly

2233
01:45:08,372 --> 01:45:13,053
Speaker 5: start to reorient to him as well, and maybe even dominantly.

2234
01:45:13,412 --> 01:45:16,532
Speaker 5: But one way or another, you've now got the relationship built,

2235
01:45:16,772 --> 01:45:19,692
Speaker 5: and then you need to extend that socialization to other people.

2236
01:45:19,933 --> 01:45:22,612
Speaker 5: I would anticipate that that dog would be a bit

2237
01:45:22,612 --> 01:45:26,012
Speaker 5: anxious about meeting any males if if he's anxious about

2238
01:45:26,053 --> 01:45:28,253
Speaker 5: one that he's already got to know very girl trying

2239
01:45:28,293 --> 01:45:28,772
Speaker 5: to get to know.

2240
01:45:28,973 --> 01:45:31,213
Speaker 3: Yeah, great, right, if you've got a question for Mark,

2241
01:45:31,213 --> 01:45:33,133
Speaker 3: now's your opportunity. Oh, eight hundred and eighteen eighty.

2242
01:45:33,213 --> 01:45:34,772
Speaker 4: Yea, that's right, one hundred eighteen eighty.

2243
01:45:34,772 --> 01:45:36,532
Speaker 2: Doesn't need to be a dog, could be a rhino,

2244
01:45:37,013 --> 01:45:40,532
Speaker 2: could be a giraffe, donkey, donkey, absolutely, lama.

2245
01:45:40,692 --> 01:45:43,213
Speaker 3: We love lama questions. We had a few lama questions,

2246
01:45:43,812 --> 01:45:47,133
Speaker 3: So get on the phone. Frog, Yeah, whatever, how are

2247
01:45:47,173 --> 01:45:47,892
Speaker 3: you with the lizards?

2248
01:45:48,173 --> 01:45:50,532
Speaker 5: To both pooky go. Yeah, it's a good.

2249
01:45:50,452 --> 01:45:53,013
Speaker 3: Okay, right, let's get into it. Oh, eight hundred and.

2250
01:45:52,973 --> 01:45:55,932
Speaker 4: Eighty ten eighty a giant shapedin kraken. What have you got?

2251
01:45:56,093 --> 01:45:57,293
Speaker 3: It is nineteen or four.

2252
01:45:59,532 --> 01:46:02,892
Speaker 1: Matt Heath, Taylor Adams with you is your afternoon rolls

2253
01:46:02,933 --> 01:46:06,372
Speaker 1: on madd Heath and Taylor Adams Afternoons news Talks.

2254
01:46:06,372 --> 01:46:09,892
Speaker 3: It'd be afternoon and we are by Mark Vitti, world

2255
01:46:09,933 --> 01:46:13,613
Speaker 3: renowned animal behavior. So he is taking your questions.

2256
01:46:14,333 --> 01:46:17,572
Speaker 4: Hey, so this particular dog, Bennie's a kvoodle and so

2257
01:46:17,652 --> 01:46:18,412
Speaker 4: I just bought it up.

2258
01:46:18,452 --> 01:46:22,452
Speaker 2: And then the mum of Benny the Fantastic Rosi is

2259
01:46:22,532 --> 01:46:25,333
Speaker 2: texting and she said, what can we do about Bennie

2260
01:46:25,452 --> 01:46:26,733
Speaker 2: barking at the parasailors?

2261
01:46:28,293 --> 01:46:28,452
Speaker 14: Oh?

2262
01:46:28,492 --> 01:46:31,012
Speaker 5: What can we do? Exactly what I was talking about

2263
01:46:31,572 --> 01:46:34,053
Speaker 5: for the prior person, you know. So that and that

2264
01:46:34,253 --> 01:46:37,892
Speaker 5: was teaching a quiet command with a clicker and then

2265
01:46:38,412 --> 01:46:40,412
Speaker 5: then we work then and so you do that at home.

2266
01:46:41,093 --> 01:46:43,693
Speaker 5: If you can get some visual or sounds of the parasler,

2267
01:46:44,053 --> 01:46:46,253
Speaker 5: that helps too while you're doing your training at home.

2268
01:46:46,652 --> 01:46:50,012
Speaker 5: And then you take it go to sight and start

2269
01:46:50,053 --> 01:46:52,892
Speaker 5: working him on a clip station with a clicker and

2270
01:46:52,893 --> 01:46:56,173
Speaker 5: you're teaching him to quiet and clicker reward him as

2271
01:46:56,213 --> 01:46:58,652
Speaker 5: the parasailor starts getting up and then while he's up

2272
01:46:58,853 --> 01:47:01,333
Speaker 5: and then right through the routine and then comes down

2273
01:47:01,372 --> 01:47:04,133
Speaker 5: and try and keep him quiet through the routine just

2274
01:47:04,213 --> 01:47:07,213
Speaker 5: using the clicker. Has he got a strong food drug?

2275
01:47:07,933 --> 01:47:10,412
Speaker 5: Got a what h strong food drive?

2276
01:47:10,812 --> 01:47:16,092
Speaker 4: Food drive? He likes to heat, but he's no labrador?

2277
01:47:17,093 --> 01:47:20,972
Speaker 5: Yeah yeah, yeah, where you might need sausages then either way,

2278
01:47:21,412 --> 01:47:24,093
Speaker 5: high value food award and context. But once you've done

2279
01:47:24,133 --> 01:47:26,173
Speaker 5: it at home and you've got the basics of the

2280
01:47:26,213 --> 01:47:30,812
Speaker 5: quiet command working, then it translates to the new situation.

2281
01:47:30,933 --> 01:47:33,012
Speaker 5: If you's going to do it systematically.

2282
01:47:32,572 --> 01:47:34,253
Speaker 2: Oh there you go highly corrupt with me. It is

2283
01:47:34,372 --> 01:47:36,732
Speaker 2: just time for my own family's problems.

2284
01:47:38,133 --> 01:47:39,812
Speaker 4: Peter Work on the show. You've got a problem with

2285
01:47:39,933 --> 01:47:42,053
Speaker 4: ultrasound alarms.

2286
01:47:42,612 --> 01:47:49,452
Speaker 26: Yeah, Mark high Mark. My neighbor has a caboodle and

2287
01:47:50,452 --> 01:47:53,852
Speaker 26: it barks a lot. I don't think it's ever had

2288
01:47:53,853 --> 01:47:56,932
Speaker 26: any training runs around the back section, just barks all

2289
01:47:56,973 --> 01:48:00,012
Speaker 26: the time. And I wanted to ask you whether these

2290
01:48:00,253 --> 01:48:03,892
Speaker 26: ultrasound control boxes are of any use.

2291
01:48:05,732 --> 01:48:08,932
Speaker 5: Yeah, well, I mean the people use them to try

2292
01:48:08,973 --> 01:48:13,372
Speaker 5: and divert you know, a dog from barking, you know,

2293
01:48:13,412 --> 01:48:16,812
Speaker 5: at them in that kind of context, and I'm not

2294
01:48:16,893 --> 01:48:19,692
Speaker 5: quite you know. I mean they work at about twenty

2295
01:48:19,692 --> 01:48:22,973
Speaker 5: to forty five thousand hertz, which is the high end

2296
01:48:23,013 --> 01:48:25,932
Speaker 5: of the dog range and above our range, you know,

2297
01:48:26,572 --> 01:48:28,692
Speaker 5: So they're working at a high level. But the dog

2298
01:48:28,732 --> 01:48:32,412
Speaker 5: can hear it well. But it's you know, it doesn't

2299
01:48:32,412 --> 01:48:34,692
Speaker 5: necessarily mean that it's going to make it aversive, you know,

2300
01:48:35,053 --> 01:48:37,452
Speaker 5: just because it's in their higher range. You know, that's

2301
01:48:37,492 --> 01:48:40,612
Speaker 5: the range of the of the present the prey species

2302
01:48:40,612 --> 01:48:43,093
Speaker 5: that they aren't in the wild, so like mice and

2303
01:48:43,293 --> 01:48:45,973
Speaker 5: rats and so on, So they can hear it that

2304
01:48:46,093 --> 01:48:48,492
Speaker 5: range and that and so it can have a verse

2305
01:48:48,532 --> 01:48:51,253
Speaker 5: in effects. And that's what they're trying to do. And

2306
01:48:51,732 --> 01:48:55,412
Speaker 5: so i'd suspect what you're suggesting as you use it

2307
01:48:55,492 --> 01:48:59,612
Speaker 5: to try and divert the neighbor's dog from barking beside you.

2308
01:49:00,412 --> 01:49:02,492
Speaker 5: It's a possibility that it will help a little bit,

2309
01:49:02,893 --> 01:49:06,212
Speaker 5: but really the bottom line comes down to the owners

2310
01:49:07,013 --> 01:49:10,052
Speaker 5: doing the right thing to train the dog. It's better

2311
01:49:10,093 --> 01:49:13,092
Speaker 5: to solve the problem from the dog's owner's point of view.

2312
01:49:13,293 --> 01:49:14,852
Speaker 5: So I'd go and have a chat to them about

2313
01:49:14,853 --> 01:49:18,452
Speaker 5: it and talk about the fact that you know there

2314
01:49:18,452 --> 01:49:22,253
Speaker 5: are ways of treating barking, but you're probably not going

2315
01:49:22,333 --> 01:49:25,292
Speaker 5: to have much effect from that side. I would suspect

2316
01:49:25,333 --> 01:49:28,012
Speaker 5: with an ultras on a pog alarm.

2317
01:49:28,213 --> 01:49:30,253
Speaker 2: Thank you for be cool, Peter. It looks like dogs

2318
01:49:30,293 --> 01:49:32,372
Speaker 2: are causing a lot more problems in the community than

2319
01:49:32,412 --> 01:49:35,333
Speaker 2: octopi because just a whole heap.

2320
01:49:35,173 --> 01:49:36,173
Speaker 4: Of dog calls.

2321
01:49:36,692 --> 01:49:38,052
Speaker 3: Lot of people want to talk about dogs.

2322
01:49:38,173 --> 01:49:40,133
Speaker 4: Nothing on squids, out of control squid.

2323
01:49:40,333 --> 01:49:41,253
Speaker 3: No, but we did.

2324
01:49:41,692 --> 01:49:47,532
Speaker 5: We did octopus to photographs, so did you? So that

2325
01:49:47,853 --> 01:49:51,053
Speaker 5: was a very good world first, it was good. Yeah,

2326
01:49:51,372 --> 01:49:55,852
Speaker 5: we're Kelly Talton's the family's coming in and having a photograph.

2327
01:49:55,893 --> 01:49:58,652
Speaker 5: It took me about two months to train one and

2328
01:49:58,652 --> 01:50:03,652
Speaker 5: then unfortunately, females when they have their eggs die and

2329
01:50:03,692 --> 01:50:06,012
Speaker 5: it had the eggs three days before the shoot, which

2330
01:50:06,013 --> 01:50:09,612
Speaker 5: was pretty unfortunately. I had two other is watching and

2331
01:50:09,853 --> 01:50:11,732
Speaker 5: managed to bring one of them and he did the

2332
01:50:11,812 --> 01:50:12,492
Speaker 5: job beautifully.

2333
01:50:13,133 --> 01:50:16,452
Speaker 4: Composition beautiful, beautiful. Yeah.

2334
01:50:17,333 --> 01:50:19,732
Speaker 2: Well, one thing that blows my mind about octopus, and

2335
01:50:19,772 --> 01:50:23,652
Speaker 2: I know we're off topic, octopi, octopuses whatever, octopusy. The

2336
01:50:23,732 --> 01:50:27,093
Speaker 2: thing is, they're so smart but they don't live very long.

2337
01:50:27,732 --> 01:50:30,412
Speaker 2: But that's right for a creature to be that intelligent. Well,

2338
01:50:30,412 --> 01:50:32,972
Speaker 2: they only live three years max, don't they.

2339
01:50:33,412 --> 01:50:35,772
Speaker 5: Yeah, well it depends on the species. But yeah, the

2340
01:50:35,853 --> 01:50:39,572
Speaker 5: problem is when the female has her eggs, she dies

2341
01:50:39,652 --> 01:50:42,132
Speaker 5: straight afterwards. So it's a kind of a sad affair.

2342
01:50:43,772 --> 01:50:46,653
Speaker 5: And I didn't really know that while I was training them, unfortunately,

2343
01:50:46,652 --> 01:50:49,532
Speaker 5: which seems a bit silly as a zoologist, but yeah,

2344
01:50:49,572 --> 01:50:52,572
Speaker 5: it nearly caught me out that we succeeded in saving

2345
01:50:52,612 --> 01:50:55,852
Speaker 5: the day. It's very difficult, though, to teach her octopus

2346
01:50:55,933 --> 01:50:59,253
Speaker 5: to take a photographs. They ate ten cameras before we

2347
01:50:59,333 --> 01:51:01,012
Speaker 5: even got to the one that worked.

2348
01:51:01,053 --> 01:51:02,933
Speaker 3: You know, we'll take your word for that, March. Not

2349
01:51:02,973 --> 01:51:04,333
Speaker 3: many people get into that situation.

2350
01:51:05,772 --> 01:51:07,093
Speaker 5: It was not a common thing though.

2351
01:51:07,732 --> 01:51:09,333
Speaker 2: I mean we're getting off topic here, But how do

2352
01:51:09,412 --> 01:51:11,973
Speaker 2: you choose which particular tendacle they're going to use to

2353
01:51:12,013 --> 01:51:14,972
Speaker 2: press the button with the Yeah, well.

2354
01:51:14,853 --> 01:51:19,213
Speaker 5: They get to choose, and because one each each tentacle's

2355
01:51:19,253 --> 01:51:23,452
Speaker 5: got a brain, because they've got nine brains, and so

2356
01:51:23,492 --> 01:51:27,612
Speaker 5: you're actually talking to particular brains. And it's interesting. They

2357
01:51:27,612 --> 01:51:32,732
Speaker 5: do use the same foot and they change certain colors

2358
01:51:32,732 --> 01:51:35,372
Speaker 5: depending on how you're going. You know, do you really

2359
01:51:35,412 --> 01:51:38,213
Speaker 5: pissed them off, they go red, you know, and and

2360
01:51:38,253 --> 01:51:40,972
Speaker 5: then you know, and then they'll normally send them squirt

2361
01:51:40,973 --> 01:51:44,293
Speaker 5: of water straight at you. Quite and so they're fun

2362
01:51:44,372 --> 01:51:46,892
Speaker 5: to work like humans and they don't bite you.

2363
01:51:47,093 --> 01:51:49,732
Speaker 2: That's going to say, it's like working with Tyler. If

2364
01:51:49,732 --> 01:51:53,372
Speaker 2: he gets angry, he goes red, gets really angry, he

2365
01:51:53,412 --> 01:51:53,892
Speaker 2: squirts me.

2366
01:51:55,692 --> 01:51:58,892
Speaker 3: Quick quick question here about donkeys, says Hi, we've recently

2367
01:51:58,893 --> 01:52:01,572
Speaker 3: adopted a donkey. Lovely nature for most of the family. However,

2368
01:52:01,572 --> 01:52:03,412
Speaker 3: when it comes to our ten year old daughter, the

2369
01:52:03,492 --> 01:52:06,452
Speaker 3: donkey will chase her and head butt her at every chance,

2370
01:52:06,973 --> 01:52:09,572
Speaker 3: only only does it to and now she is terrified

2371
01:52:09,572 --> 01:52:11,452
Speaker 3: and said, donkey, why is this and what can we do?

2372
01:52:12,612 --> 01:52:16,372
Speaker 5: Yeah, so it will be to do with you know,

2373
01:52:16,412 --> 01:52:19,213
Speaker 5: how how did the donkey grow up with that with

2374
01:52:19,293 --> 01:52:19,852
Speaker 5: that family?

2375
01:52:20,253 --> 01:52:22,412
Speaker 3: Uh No, they said they've recently not.

2376
01:52:22,732 --> 01:52:25,572
Speaker 5: Yeah, yeah, that's right. So you know, normally with donkeys,

2377
01:52:25,732 --> 01:52:28,333
Speaker 5: you know, they're quite an individual and you do need

2378
01:52:28,333 --> 01:52:31,253
Speaker 5: to be experienced with a donkey. They can they can

2379
01:52:31,333 --> 01:52:33,333
Speaker 5: kick out, and they can be quite aggressive. So don't

2380
01:52:33,652 --> 01:52:36,692
Speaker 5: underestimate a donkey, even though they look small. Donk they

2381
01:52:36,772 --> 01:52:39,973
Speaker 5: use donkeys to control bull herds, so they'll put a

2382
01:52:40,013 --> 01:52:42,572
Speaker 5: male donkey in with a bull herd, and it won't

2383
01:52:42,692 --> 01:52:45,892
Speaker 5: know one much with the donkey, and the donkey sorts

2384
01:52:45,933 --> 01:52:49,412
Speaker 5: out any fighting. So yeah, they can shoot way above

2385
01:52:49,452 --> 01:52:52,772
Speaker 5: their weight range and or punch above their weight range.

2386
01:52:52,973 --> 01:52:55,173
Speaker 5: So be careful with the donkey. But but by the

2387
01:52:55,213 --> 01:52:58,093
Speaker 5: same token, they're beautiful animal. It's all about food for

2388
01:52:58,173 --> 01:53:00,772
Speaker 5: donkeys if you want to, So I click a train

2389
01:53:00,853 --> 01:53:02,812
Speaker 5: a donkey, and I always the best thing for the

2390
01:53:02,893 --> 01:53:05,732
Speaker 5: little for you to do and then to pass on

2391
01:53:05,772 --> 01:53:08,652
Speaker 5: to your daughter, is to use a just a stick

2392
01:53:08,692 --> 01:53:10,253
Speaker 5: with the ball on the end of it, and I

2393
01:53:10,532 --> 01:53:12,692
Speaker 5: teach the donkey to touch it with its nose. If

2394
01:53:12,692 --> 01:53:14,652
Speaker 5: you don't, it touches it. I clicked and food reward

2395
01:53:14,772 --> 01:53:17,452
Speaker 5: with sweet feet. So have a little box of sweet

2396
01:53:17,492 --> 01:53:20,492
Speaker 5: feed on my belt and I click, and don't let

2397
01:53:20,492 --> 01:53:22,572
Speaker 5: it into your sweet feed belt. They make them damn

2398
01:53:22,612 --> 01:53:27,812
Speaker 5: mess quickly. And then you click and reward them for

2399
01:53:27,893 --> 01:53:30,852
Speaker 5: touching the stick. And then you move that round and

2400
01:53:30,933 --> 01:53:33,172
Speaker 5: it follows you and touches it, and click and reward,

2401
01:53:33,452 --> 01:53:35,213
Speaker 5: and then once you get ConTroll of it that way,

2402
01:53:35,612 --> 01:53:38,492
Speaker 5: you can actually move the donkey round and right from

2403
01:53:38,492 --> 01:53:40,612
Speaker 5: that point on you'll be fine with a donkey and

2404
01:53:40,612 --> 01:53:43,492
Speaker 5: then you transfer that to the dater. Will be the

2405
01:53:43,652 --> 01:53:46,932
Speaker 5: time well, and I mean you also should also hold

2406
01:53:46,973 --> 01:53:48,772
Speaker 5: your train them. Of course they should be good on

2407
01:53:48,812 --> 01:53:52,093
Speaker 5: a holter, of course, and so anyone should be able

2408
01:53:52,093 --> 01:53:52,932
Speaker 5: to walk them on a halter.

2409
01:53:53,452 --> 01:53:55,692
Speaker 2: I was staying at a farm, just on a ranch,

2410
01:53:55,812 --> 01:53:59,133
Speaker 2: just out of Los Angeles, and the borrows as they

2411
01:53:59,173 --> 01:54:01,892
Speaker 2: call them, the borrels, the borrols were everywhere, just packs

2412
01:54:01,893 --> 01:54:02,772
Speaker 2: of wild donkeys.

2413
01:54:02,772 --> 01:54:03,333
Speaker 4: It was crazy.

2414
01:54:03,372 --> 01:54:05,692
Speaker 2: You was driving down the road and there'll be twenty

2415
01:54:05,812 --> 01:54:10,572
Speaker 2: donkeys come running past. The bottles, the bottles, all the.

2416
01:54:11,053 --> 01:54:15,412
Speaker 3: Yeah, yeah, very good, Mark, Mike. We're going to take

2417
01:54:15,452 --> 01:54:18,493
Speaker 3: a couple more calls just after we play some messages.

2418
01:54:18,893 --> 01:54:20,852
Speaker 3: So one hundred and eighteen eighty is the number. It

2419
01:54:20,973 --> 01:54:21,652
Speaker 3: is eight to four.

2420
01:54:24,492 --> 01:54:27,972
Speaker 1: The big stories, the big issues, the big trends and

2421
01:54:28,213 --> 01:54:32,333
Speaker 1: everything in between. Matt Heath and Tyler Adams. Afternoons used talks.

2422
01:54:32,333 --> 01:54:34,213
Speaker 3: It'd be afternoon.

2423
01:54:34,413 --> 01:54:34,852
Speaker 1: A vow.

2424
01:54:35,053 --> 01:54:36,133
Speaker 3: You're on with Mark.

2425
01:54:37,373 --> 01:54:41,093
Speaker 17: Thank you, Good afternoon, Mark. It's Poul Nals here. I

2426
01:54:41,173 --> 01:54:44,493
Speaker 17: have a beautiful black labrador and of course he's food orientated.

2427
01:54:44,933 --> 01:54:47,733
Speaker 17: When I go to the dog park, other people have

2428
01:54:47,812 --> 01:54:49,693
Speaker 17: a bag on the side with their treats. And they're

2429
01:54:49,733 --> 01:54:54,493
Speaker 17: training their dogs. My boy, like you know, she's right

2430
01:54:54,733 --> 01:54:59,012
Speaker 17: on the side, sitting down the way wanting a treat.

2431
01:54:59,293 --> 01:55:02,493
Speaker 17: He wants one as well, and sometimes he gets one.

2432
01:55:03,373 --> 01:55:05,573
Speaker 5: Yep. So the trick there is have your own bag

2433
01:55:05,613 --> 01:55:08,573
Speaker 5: of treats. All you need is probably kimble because see

2434
01:55:08,613 --> 01:55:11,413
Speaker 5: all did anything. Probably if he's a lab and I mean,

2435
01:55:11,453 --> 01:55:14,333
Speaker 5: I'd take a clicker as well, and you just reinforce

2436
01:55:14,413 --> 01:55:16,932
Speaker 5: your recall work and I'd run a little long line

2437
01:55:16,973 --> 01:55:18,852
Speaker 5: on him until I knew I could call him back

2438
01:55:19,133 --> 01:55:21,573
Speaker 5: from that situation. But when he comes back, click and

2439
01:55:21,613 --> 01:55:23,613
Speaker 5: reward him. And of course then you're just as an

2440
01:55:23,653 --> 01:55:25,892
Speaker 5: important to him. In fact, we'll be more important to

2441
01:55:25,933 --> 01:55:29,973
Speaker 5: him than the other one and their treats. So just yeah,

2442
01:55:30,173 --> 01:55:33,093
Speaker 5: five treats with treats that should go, no problem.

2443
01:55:33,493 --> 01:55:35,453
Speaker 3: All the bears foul and Mark. That is all the

2444
01:55:35,493 --> 01:55:38,013
Speaker 3: time we've got. Thank you very much again, and we

2445
01:55:38,053 --> 01:55:39,852
Speaker 3: will catch you again in a month's time. We've got

2446
01:55:39,893 --> 01:55:42,493
Speaker 3: so many texts and questions to get next time you're

2447
01:55:42,533 --> 01:55:43,333
Speaker 3: on with us.

2448
01:55:43,812 --> 01:55:45,812
Speaker 5: I clear that anyone needs to jump on the school

2449
01:55:46,053 --> 01:55:47,053
Speaker 5: find out, go for it.

2450
01:55:47,093 --> 01:55:49,413
Speaker 3: We'll be there, yep, love it. You can check out

2451
01:55:49,973 --> 01:55:52,493
Speaker 3: Mark and his business and his work at Mark Vitti

2452
01:55:52,653 --> 01:55:54,932
Speaker 3: dot com. And he'll be back with us in about

2453
01:55:54,933 --> 01:55:55,812
Speaker 3: a month's time.

2454
01:55:56,493 --> 01:55:58,373
Speaker 2: All right, thank you to all your great new zealders

2455
01:55:58,373 --> 01:56:00,173
Speaker 2: for listening to our show. We've had a great time.

2456
01:56:00,253 --> 01:56:02,013
Speaker 2: Hope you have the mat util Laughter. News podcast will

2457
01:56:02,013 --> 01:56:03,613
Speaker 2: be out in about the hour. If you missed any

2458
01:56:03,613 --> 01:56:05,932
Speaker 2: of our excellent chants on jobs that will be sweet

2459
01:56:05,933 --> 01:56:08,573
Speaker 2: in the face of AI or how far Free which

2460
01:56:08,613 --> 01:56:11,693
Speaker 2: goes when you're wearing your company lanyard, jump on our podcast.

2461
01:56:11,733 --> 01:56:13,533
Speaker 2: Go and hear any of that wherever you get your pods.

2462
01:56:13,772 --> 01:56:16,012
Speaker 2: My good buddy, hither Diople see Ellen is up after news.

2463
01:56:16,173 --> 01:56:18,733
Speaker 4: The song here is from the Kiwi band Zoom the

2464
01:56:18,853 --> 01:56:21,613
Speaker 4: new album Something Good is Happening. That's great. I got

2465
01:56:21,613 --> 01:56:24,252
Speaker 4: the album on vinyl on the weekend. Every track is brilliant.

2466
01:56:24,613 --> 01:56:27,013
Speaker 4: That's all from us. See you tomorrow afternoon until the end.

2467
01:56:27,493 --> 01:56:30,733
Speaker 4: Wherever you are, what are you doing, Have a great

2468
01:56:30,812 --> 01:56:49,253
Speaker 4: afternoon and give them a taste of Kiwi from us.

2469
01:56:49,093 --> 01:56:49,852
Speaker 4: Just love.

2470
01:57:00,293 --> 01:57:03,213
Speaker 1: For more from News Talks b listen live on air

2471
01:57:03,413 --> 01:57:06,093
Speaker 1: or online and keep our shows with you wherever you

2472
01:57:06,173 --> 01:57:08,573
Speaker 1: go with our podcast on Iheartdeo