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

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Speaker 1: Follow this and our Wide Ranger podcasts now on iHeartRadio.

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Speaker 2: Hello and welcome to Matton Tyler Full Afternoon Show podcasts

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Speaker 2: Said That Wrong? One one seven four, the fifth of

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Speaker 2: May twenty twenty five. It's a fantastic show. We didn't

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Speaker 2: get to one of our topics as we offer don't

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Speaker 2: because the other two went absolutely nuts. The topic we

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Speaker 2: didn't get too was address codes and work after a

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Speaker 2: new Starbucks initiative. But we had a confronting chat on

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Speaker 2: longer prison sentences, including quite a quite a full on

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Speaker 2: chat with the well, how do you can only put

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Speaker 2: this one way? A murderer? Yeah, a person that had

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Speaker 2: murdered someone had done seventeen years for it, which was interesting, confronting, confronting,

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Speaker 2: and I hope you get something out of that. Also,

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Speaker 2: we went deep into AI and there's nothing I love

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Speaker 2: more than an AI chat.

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Speaker 3: Yeah.

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Speaker 4: We also talked a little bit about Colin and am

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Speaker 4: pies and details, so yeah is that as well?

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Speaker 2: So there is something for everyone. Subscribe set to download.

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Speaker 2: Thank you so much for listening, and enjoy the next

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Speaker 2: two hours of entertainment.

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Speaker 4: Yep, and give them a taste. All right, Okay, bye

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Speaker 4: News Talks. There'd be welcome into the show on this

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Speaker 4: Monday afternoon. Hope you had a great week a great weekend.

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Speaker 4: If you're listening in the country, get.

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Speaker 2: A Matt, get a, Tyler, get everyone. Thanks so much

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Speaker 2: for tuning in too, Matt and Tyler Afternoon. It's got

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Speaker 2: a great show for you over the next three hours.

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Speaker 2: I'm excited about it. At a fantastic weekend, crazy big

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Speaker 2: weekend of sport, wasn't it?

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Speaker 4: Oh hush? I mean, what do you want to start with?

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Speaker 2: I don't We don't need to go into it.

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Speaker 4: Just everything was absolutely incredible in the end, apart from

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Speaker 4: poor old Liam.

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Speaker 2: Hey, can I just talk quickly, just really really quickly

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Speaker 2: before we move forward about a phenomena that needs to stop? Okay,

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Speaker 2: and people listening. So there's someone in my life. She's

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Speaker 2: very important to me, and she was talking a lot

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Speaker 2: about a movie she hadn't seen called Silence of the Lambs.

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Speaker 2: Oh yep, And she said we should watch Silence of

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Speaker 2: the Lambs. One of the best movies I've ever made,

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Speaker 2: in my opinion, and so I was very keen for

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Speaker 2: her to watch it, right yep, And so teed it up,

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Speaker 2: sat down to watch it, and then what does she

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Speaker 2: do spend the entire time on her phone too screening.

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Speaker 4: I know the pain. I know the pain, and.

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Speaker 2: You're going you need to watch This is a movie

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Speaker 2: where you need to watch because there's so much foreboding

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Speaker 2: in it. There is so much that the mizzle scene

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Speaker 2: is so important for the film. Watching every single part

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Speaker 2: of that film. You can't be too screening it. And

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Speaker 2: there are movies now and I've talked about this on

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Speaker 2: the show before and Netflix that are made they're just

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Speaker 2: super dumb. And there's streaming movies that are made for

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Speaker 2: you to be able to watch while you're looking at

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Speaker 2: your screen, and when you try and watch those without

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Speaker 2: two screening, they seem very very very strange and slow

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Speaker 2: and boring and stupid. But Silence of the Lambs is

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Speaker 2: one of these fantastic movies. You know, Anthony Hopkins performance,

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Speaker 2: Jodie Foster's weird accent, all of it, all the way,

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Speaker 2: how everything's set up. You just got to watch these movies.

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Speaker 2: You've just got to put your phone down and look

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Speaker 2: otherwise it's going to cause frustration within households.

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Speaker 4: Absolutely, that's not even a slow Burn movie, though, that

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Speaker 4: one's like tension from the start in the build up,

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Speaker 4: even the opening scene when she's running through the forest.

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Speaker 4: She wasn't into that that instantly should have grabbed her

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Speaker 4: and said, yeah, oh, I'm into this. She's a tough

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Speaker 4: world out there at the moment.

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Speaker 2: So instead of saying something directly to her face, yeah,

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Speaker 2: what I've decided to do instand as broadcast my complaint

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Speaker 2: to the nation.

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Speaker 4: It's so much easier doing it that way. I've learned

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Speaker 4: that right on, So you see her tell it onto

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Speaker 4: today's show after three o'clock. Dress codes at work that's

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Speaker 4: on the back of Starbucks. They have sparked uproar with

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Speaker 4: some of their employees after introducing a change to its uniform.

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Speaker 4: The change isn't too extreme. It is any black, short

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Speaker 4: or long sleeve, crew neck or button up shirts and

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Speaker 4: any shade of khaki, black or blue. But the younger

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Speaker 4: members are freaking out, saying we can't express os ols.

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Speaker 2: Yeah, well, is our dress codes at work? Are things

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Speaker 2: still or have we moved into a post making an efforts? Actually,

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Speaker 2: that's not for fear. Some people will make a huge

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Speaker 2: effort and be outside of address code. But our dress code.

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Speaker 2: Just thinks of the past, love your thoughts on that

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Speaker 2: after three.

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Speaker 4: Yep, after two o'clock. AI in schools, The Ministry of

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Speaker 4: Education says our AI poses a significant challenge for schools.

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Speaker 4: They reckon around sixty percent of students are using it

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Speaker 4: for school work.

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Speaker 2: Yeah, so are your kids using AI to do their

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Speaker 2: homework or are they using it at school? What do

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Speaker 2: you think about this? What do you think about AI

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Speaker 2: marking papers? Because that's what's happening now, and should there

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Speaker 2: be more or less AI in schools? And if so,

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Speaker 2: what are the parameters? Love to hear from you on

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Speaker 2: I one hundred and eighty ten eighty.

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Speaker 4: Yep, But right now, let's have a chance about prison

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Speaker 4: sentences and rehabilitation. So prisoners on short send are more

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Speaker 4: likely to re offend than those on the longer sentences,

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Speaker 4: and Christians Minister Mark Mitchell he is looking into replacing

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Speaker 4: those shorter sentences with longer ones. One of the big

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Speaker 4: reasons is that those on shorter sentences have less access

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Speaker 4: to rehabilitation and are automatically released after serving half their time.

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Speaker 4: So this is a big one, Mitchell argues why he

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Speaker 4: agrees that it will end up costing quite a lot

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Speaker 4: of money for the government if they have to build

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Speaker 4: new prisons, because that prison population is going to expand.

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Speaker 4: But he argues that the long term benefits down the

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Speaker 4: track would be worth that.

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Speaker 2: Yeah, well, the economic benefits of people not out and

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Speaker 2: about in the community committing crimes. You know, that's kind

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Speaker 2: of a harder thing to work out. But other people

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Speaker 2: say the opposite, and they say that, you know, rehabilitation

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Speaker 2: isn't working and that people will cause more harm in

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Speaker 2: the community by having these long custodial sentences. I love

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Speaker 2: to hear from people have been rehabilitated by the sentence,

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Speaker 2: people that have been inside and the rehabilitation has worked

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Speaker 2: for them, and why they think that worked, or people

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Speaker 2: who know people who have been rehabilitated by their sentence,

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Speaker 2: or the reverse, people that have gone into prison in

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Speaker 2: and out and have the prison sentence has had nothing

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Speaker 2: to do with whether they commit crimes again. And as

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Speaker 2: I was saying to you before, Tyler, it's the age

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Speaker 2: of debate, isn't it, Because part of prison is punitive,

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Speaker 2: part of prison is and it's I guess in a

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Speaker 2: way magical thinking that you think things have been writed

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Speaker 2: something terrible happens to you, you're a victim or someone

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Speaker 2: in your family, and that person gets punished, and in

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Speaker 2: some ways things get balanced out in the universe because

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Speaker 2: a terrible thing's happened to some person then and nearly

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Speaker 2: as bad thing happens to someone out. So is that

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Speaker 2: the point of prisons or you know, is it about

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Speaker 2: the social good across the entire society? And so if

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Speaker 2: we work out this stats and it works out that

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Speaker 2: longer prison sentences ultimately aren't better for the amount of

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Speaker 2: crime and community, then then we shouldn't do them. I

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Speaker 2: don't know, it's a difficult one. I don't know the

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Speaker 2: answer to that question. It's very hard to say to

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Speaker 2: someone for the good of all of community, that person

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Speaker 2: isn't going to get a very long sentence. And I'm

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Speaker 2: not saying that that is true. I'm not saying because

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Speaker 2: you know, according to these stats here, it suggests that

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Speaker 2: the longer sentences do lead to more rebilitation.

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Speaker 4: Yeah, I mean, just looking at the reoffending rates, so dishonesty,

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Speaker 4: the reoffending rates seventy nine percent, property offenses, sixty one percent, violence,

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Speaker 4: sixty one percent reoffending rate. That is incredibly high. But

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Speaker 4: You're quite right. If you're the victim of a crime,

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Speaker 4: and a violent crime, and under this particular law change,

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Speaker 4: the person who committed the crime against you serves a

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Speaker 4: shorter sentences for the good of other people, would you

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Speaker 4: feel okay with that? I think the victim in question

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Speaker 4: would be saying, hang on a minute, Yeah, you know,

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Speaker 4: this was a family member or me that was attacked,

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Speaker 4: that screwed up my life. Why do I have to

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Speaker 4: take one for the team?

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Speaker 3: Yeah?

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Speaker 2: Well, exactly because at least a part of prison sentences,

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Speaker 2: for want of a better word, revenge, revenge on the

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Speaker 2: person that's done this, this this act.

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Speaker 4: Definitely.

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Speaker 2: Yeah, And it gets a bit complicated as well, like

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Speaker 2: all these things do. So I'd love to hear people's

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Speaker 2: opinions on this. O eight one hundred and eighty ten eighty.

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Speaker 2: You know, because shorter sentences are reoffending may be higher,

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Speaker 2: but you might get shorter sentences for the types of

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Speaker 2: crimes that you're more likely to reoffend at. Also, you know,

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Speaker 2: if you're in prison long enough, then you become old

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Speaker 2: and outside of the age group that reoffends.

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Speaker 4: Exactly. Oh, eight hundred and eighteen eighty is the number

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Speaker 4: to call love to hear from you on this one.

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Speaker 4: It is fourteen past one.

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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 Tyler Adams afternoons.

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Speaker 4: Used talks be news talks there be. It's seventeen past

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Speaker 4: one and we're talking about rehabilitation and prison sentences. Mark

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Speaker 4: Mitchell is looking to investigate longer prison sentences because he

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Speaker 4: says the evidence shows longer sentences mean people do not

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Speaker 4: reoffend at these same rates.

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Speaker 2: Yeah, we offending rates dropped sharply with longer sentences, according

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Speaker 2: to him, fifteen percent for short sentences and versus twelve

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Speaker 2: percent for sentences over five years. Like everything in this area,

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Speaker 2: it gets pretty complicated. Term you were in prison for

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Speaker 2: fifteen years, I understand.

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Speaker 5: Yeah, I've seen not as fourteen years nine months out

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Speaker 5: of a twenty one years eight months from drug offences. Right,

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Speaker 5: we'd enjoyed five years and then got convicted for and

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Speaker 5: got sentence to another seventeen years for drug charges while

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Speaker 5: serving as it inmate. I've seen it like you definitely

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Speaker 5: noticed like a different how different governments deal with you,

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Speaker 5: like a labor government lawyer in prison, Like I definitely

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Speaker 5: like progue it's easier. Bowel conditions get easier, there's more programs,

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Speaker 5: more I'm READO great and more rehabilitation and national comes

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Speaker 5: in and they longer sentences and tighten things up. Things

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Speaker 5: get harsher inside, less privileges. But from my experience from

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Speaker 5: doing all the rehability little bit of rehabilitation courses that

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Speaker 5: creaks and test to offer, it's just like a box

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Speaker 5: taking exercise. Really, it's a bit of a joke. It's

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Speaker 5: like design design for five year olds, waste of money.

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Speaker 5: If you ask if you asked me, you know right when.

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Speaker 2: When how long in prison had you been before you started,

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Speaker 2: you know, trying some rehabilitation that was on offer or when.

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Speaker 5: I first started. What they tried to do is what

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Speaker 5: they say. They want to want you to make your

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Speaker 5: way to your first available parole date before you start courses.

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Speaker 5: So for someone like me that was fourteen years nine months.

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Speaker 5: I was eligible to parole after thirteen years nine months

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Speaker 5: and I managed to get into start doing the courses

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Speaker 5: I need to do after about fourteen years.

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Speaker 4: Wow.

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Speaker 2: Wow, So were you when you were in prison and

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Speaker 2: were you thinking about you know, parole and doing the

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Speaker 2: right things. Was that on your mind when you're in

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Speaker 2: prison that you were sort of.

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Speaker 5: Intially know because initially when I first got because I

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Speaker 5: went and doing five years and the DA the day

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Speaker 5: I got sentenced to a new sentence, I'd done four

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Speaker 5: years eight months of my five years, and then I've

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Speaker 5: got sentenced to another seventeen years on top of that. Right,

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Speaker 5: so like there's not much hope to the start of

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Speaker 5: that thing. And I just thought, well, it is what

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Speaker 5: it is. And once I started getting about five years out,

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Speaker 5: I started to thinking, it's about time for me to

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Speaker 5: start trying to you know, try to get to do

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Speaker 5: these courses. But it's like if any of the stuff

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Speaker 5: in the the like not exactly like the finest people

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Speaker 5: that they hire, like not really cares. He's lots of corruption.

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Speaker 5: The prison officers are just in general hopeless. It's the

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Speaker 5: odd old one that is helpful, but it's really just

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Speaker 5: a joke. It's all just like a box taking exercise too.

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Speaker 5: I don't know set us by the pro board in

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Speaker 5: the public, you know really in my opinion.

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Speaker 2: Yeah, and when about exactly were you in prison? When

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Speaker 2: was this fourteen years?

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Speaker 5: Well, I started in three two thousand and six, and

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Speaker 5: I was released in November twenty twenty.

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Speaker 2: Who was right? And so how have you been going

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Speaker 2: since you've been out of prison?

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Speaker 5: Well, I would say I'd be pretty rare in this aspect.

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Speaker 5: So I haven't had like any issues at all. I've

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Speaker 5: got outstarted my business, you know, in construction and working

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Speaker 5: now for a couple of employees and stuff and that,

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Speaker 5: you know, but people like me, well for a start

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Speaker 5: on like Pakia, I never joined a gang, and then

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Speaker 5: it's south is like super rare for Soula's spend that

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Speaker 5: long in prison on mainstream but like it's just such

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Speaker 5: a negative, punitive environment and these people getting out of

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Speaker 5: the long period of time because they've treated like really

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Speaker 5: like non human beings, well you know, that's that's what

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Speaker 5: they get out, acting like you know, like there's no

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Speaker 5: genuine help, no genuine courses. So you know, that's what

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Speaker 5: the public wants, that's what they're gonna that's what they're

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Speaker 5: gonna get, you know.

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Speaker 4: So just your own back to when you were serving

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Speaker 4: your sentence, So there are no programs that you can

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Speaker 4: undertake while you're serving that sentence. You have to wait

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Speaker 4: until the end of your sentence before you're eligible to

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Speaker 4: do some of those programs correct, that seems nonsensical. I mean,

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Speaker 4: what do you do day to day in the prison

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Speaker 4: except for survive and do your time of course, But

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Speaker 4: they're nothing nothing.

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Speaker 5: Yeah, that's right. You'll see an environment well like pretty

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Speaker 5: much like as it says, oh, I'm a non gang member,

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Speaker 5: so every unit I member, it was pretty much like

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Speaker 5: fifty five people are gang members and five people are

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Speaker 5: non gang members on average. I've been a wings, but

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Speaker 5: I'm the only person who's not a gang member, and

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Speaker 5: a wing that's like sixty people. You know, you can

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Speaker 5: always go on protection with although like six offenders and

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Speaker 5: whatever stuff like that. That was really me, But it's

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Speaker 5: it's just a real toxic environment, you know, and like

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Speaker 5: the prison officers they have no control. Really, it's like

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Speaker 5: it's a joke.

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Speaker 2: Do you think what do you think would be realistic

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Speaker 2: rehabilitation for someone in prison? What do you think would

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Speaker 2: have taken would have worked for you?

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Speaker 5: Well, I just really believe like no one's going to

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Speaker 5: change unless they really want to, to be honest, and

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Speaker 5: doesn't matter how many courses you do, like the step,

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Speaker 5: the Bloody Drug DTU drug DU drug program, They're like

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Speaker 5: it's it's as people are just trying to get out

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Speaker 5: of jail. Most people, in my experience, are just going

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Speaker 5: to continue on doing the same thing. And also I believe,

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Speaker 5: like you, I've come across many people in president who, like.

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Speaker 6: I personally think you never get out.

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Speaker 5: That it's like all they're going to do is get

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Speaker 5: out and hurt people and do the same shirt and yeah,

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Speaker 5: it's like come and but and and on the other hand,

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Speaker 5: there's some people who have been given excessive sentences who

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Speaker 5: are I believe that aren't going to do the same

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Speaker 5: thing when they get out, and he's put every roadblock

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Speaker 5: and put in front of them because they comparing them

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Speaker 5: to the to the gang member or the whoever who's

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Speaker 5: never going to change, you know. So it's it's pretty hard.

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Speaker 5: Had situation.

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Speaker 2: Well, as you said before, you were in for five

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Speaker 2: years originally and then that got blown out into the

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Speaker 2: much longer sentence because of you know, offending inside. Do

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Speaker 2: you think if you've been if you'd got out after

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Speaker 2: that five years, because Minister Mark Mitchell wants to replace

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Speaker 2: these short prison sentences with longer ones and it's not

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Speaker 2: really what's happening happened with you, but do you think

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Speaker 2: if you'd got out after that five years, you would

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Speaker 2: have been more likely to reoffend. Because you've been out

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Speaker 2: now for nearly five years and haven't reoffended. So if

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Speaker 2: you've got out after the original five years.

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Speaker 5: Honestly, I think I probably. I don't think much would

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Speaker 5: have changed it. I'm just the top situations at the time.

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Speaker 5: I think it really just for me personally, not in

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Speaker 5: all cases, but what I needed was to be a

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Speaker 5: hefty sentence to really change my ways, really to say well, okay,

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Speaker 5: that's it. Yeah, I've got that amount of time. I

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Speaker 5: don't think much would have changed, to be honest, to

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Speaker 5: be fair.

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Speaker 2: Right, And what's it like to get out of prison

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Speaker 2: and you've been in for that long and you're finally

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Speaker 2: out and you're and you're making your way in the

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Speaker 2: world and there's there's not rules and you've got your freedom.

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Speaker 2: What's that feeling like?

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Speaker 5: Well, it's amazing. Really, Well, take give me a couple examples. Right,

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Speaker 5: So this give us three hundred and fifty dollars a week,

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Speaker 5: but when you get out fifty dollars. It's till you

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Speaker 5: get it. For me, I was fortunately I had good family, support,

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Speaker 5: good people around me, so I know, like several people

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Speaker 5: have got out with three hundred and fifty dollars.

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Speaker 6: They haven't it.

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Speaker 5: They can't even buy a set of clothes. They can't

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Speaker 5: even feel good about themselves. They've got you know, they've

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Speaker 5: bought a pair of jeans and shoes, and they've got nothing.

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Speaker 5: You have to wait a couple of weeks to like

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Speaker 5: get on the benefit. They're not out of normally the cases,

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Speaker 5: you're not a lot of work which always now to

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Speaker 5: work at all for the first light six months is passed?

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Speaker 6: What role?

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Speaker 5: Editions? I just wanted me to like just chill out

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Speaker 5: and do nothing or I don't know what reason seeing

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Speaker 5: these guys getting out, they've got nothing, they can't do anything.

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Speaker 5: You know what expect them to do? You know, like

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Speaker 5: they need money. You know they're going to do something,

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Speaker 5: aren't they.

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Speaker 2: Right, So you think that that once you leave prison,

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Speaker 2: the landing should be made softer for people.

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Speaker 5: Well, no one's got a chance. Imagine. I know somebody

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Speaker 5: who got it up for nineteen years in prison, nothing

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Speaker 5: no support. He got put into a Salvation Army house.

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Speaker 5: He got given three hundred fifty dollars on his first night.

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Speaker 5: The power the house is the thing where you know

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Speaker 5: you prepay. I didn't know how to work that. So

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Speaker 5: like the first night the power runs out and it's

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Speaker 5: just wait until like eight o'clock next morning, because he's

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Speaker 5: not our lead. The premises the sort out of power,

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Speaker 5: you know, a sit disaster, they've got no chance, no

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Speaker 5: chance at all.

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Speaker 4: Yeah, Tim, thank you very much. I mean, the the

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Speaker 4: reoffending rates according to this graph, and that was in

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Speaker 4: twenty eighteen, would would tend to skew. You know, there's

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Speaker 4: a lot of truth and what Tim was saying, Yeah,

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Speaker 4: when you've got seventy nine percent of those in dishonesty

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Speaker 4: offenses reoffending, that is a crazy high number. Oh one

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Speaker 4: hundred and eighteen eighty is the number to call Love

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Speaker 4: to hear your thoughts about rehabilitation in New Zealand prisons

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Speaker 4: and the idea of longer sentences to allow people to

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Speaker 4: undertake those programs. It is twenty five past.

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Speaker 1: One, putting the tough questions to the newspeakers, the mic

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Speaker 1: asking breakfast time risen the studio.

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Speaker 2: Twelve billion is a stunning amount of money.

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Speaker 7: It's over four years I understand that, and nine of

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Speaker 7: it's new and we don't have any of it. So

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Speaker 7: Nicola in announcing one point three instead of two point

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Speaker 7: four as she did last week, must have a shedload

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Speaker 7: of doughse somewhere in terms of saving specially.

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Speaker 8: Again, I'm going to be the wrong answer that you're

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Speaker 8: not going to like, but it is. I'm not going

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Speaker 8: to talk.

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Speaker 2: About otherwise it just doesn't add up.

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Speaker 8: Well, I can tell you it does add up, and

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Speaker 8: it's within our fiscal buzz.

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Speaker 2: It will all make sense.

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Speaker 4: It will all make sense.

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Speaker 8: And what you're going to see as a budget that

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Speaker 8: is actually saying Yep, we know we're in tough and

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Speaker 8: uncertain times, but we have turned the corner and actually

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Speaker 8: things are getting better.

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Speaker 7: Back tomorrow at six am the mic Husking Breakfast with

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Speaker 7: the Rain drove of a lame news talk z B.

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Speaker 4: It is twenty eight past one, and we're talking about

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Speaker 4: rehabilitation in New Zealand prisons and the idea of longer

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Speaker 4: prison sentences to allow more rehabilitation. It is something that

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Speaker 4: reaches mister Mark Mitchell is looking into elanor your thoughts

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Speaker 4: on this, father.

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Speaker 9: I wonder if.

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Speaker 10: Mister Mark Mitchell has ever looked into the Norway prison system,

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Speaker 10: because recently I watched the documentary called Your Times next

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Speaker 10: by Michael Moore, and our cividism rate is guess how much?

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Speaker 11: Just have it stabbed?

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Speaker 2: I said, I've seen this. I've seen a better documentaries

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Speaker 2: than that, and better than obviously Michael Moore saying, but

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Speaker 2: they're very low, aren't they, and that the prisons are

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Speaker 2: the prisons are very nice.

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Speaker 10: So it's twenty percivalism rate. And that's because they don't

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Speaker 10: have a punitive approach. It's restoratives. And what they're doing

404
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Speaker 10: is they're creating a systematic dependence. They're not creating a

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Speaker 10: systematic dependency on the prison system. So they're rehabilitating prisoners

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Speaker 10: instead of just wearehousing them and letting them become better

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Speaker 10: prepared to end for society. And we're not just talking

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Speaker 10: drugs charges. We're talking murderers who have done their time,

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Speaker 10: let's say twenty five years, and instead of going back

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Speaker 10: into the system and failing like your previous caller was

411
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Speaker 10: talking about and not having any support, they've the skills

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Speaker 10: to do that. And partly because they've been working inside

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Speaker 10: the prison system and learning skills.

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Speaker 2: Every day, learning and always got so a lot of advantages.

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Speaker 2: I've got a whole heap of oil money. They've got

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Speaker 2: a lot more to spend on things like this. What

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Speaker 2: do you say, eleanor though, because prison isn't just about rehabilitation,

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Speaker 2: and it isn't just about keeping people out of the system.

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Speaker 2: If someone has committed a crime on someone else, a

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Speaker 2: certain amount of it in society is expected, for want

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Speaker 2: of a better a word, revenge, and that someone has

422
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Speaker 2: done something bad to a family or a person, and

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Speaker 2: part of that prison sentence is the writing of that wrong.

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Speaker 10: Yes, and I understand that that the human need right

425
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Speaker 10: someone has done something wrong to you, and I totally

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Speaker 10: understand that. However, show me the research that says the

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Speaker 10: punitive approach is working, and then look at statistics.

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Speaker 12: There's the research that.

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Speaker 10: Says punishing people for years without giving them any skills, Well.

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Speaker 2: I definitely, I definitely think. You know, talking to Tim there,

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Speaker 2: the point that he made is when they actually get

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Speaker 2: out of prison, whatever however long the term is, if

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Speaker 2: you've decided that they've done their time and you paid

434
00:21:11,293 --> 00:21:14,373
Speaker 2: their debt to society and they get back out, really

435
00:21:14,413 --> 00:21:16,173
Speaker 2: a place that I feel like, if you're going to

436
00:21:16,173 --> 00:21:19,093
Speaker 2: spend some money should be on the soft landing, because

437
00:21:19,853 --> 00:21:23,693
Speaker 2: if they get out and they're institutionalized and they don't

438
00:21:23,733 --> 00:21:26,733
Speaker 2: know how things work, and they're struggling to get a job.

439
00:21:27,253 --> 00:21:28,813
Speaker 2: They're going to end up going back to the same

440
00:21:28,813 --> 00:21:31,293
Speaker 2: people in the same life that they were in. So

441
00:21:31,453 --> 00:21:35,813
Speaker 2: whatever happens in prison and so in Norway, they how's

442
00:21:35,853 --> 00:21:37,253
Speaker 2: their landing when they leave prison?

443
00:21:38,853 --> 00:21:42,333
Speaker 10: Well, it's much softer than ours, obviously, because they've got

444
00:21:42,373 --> 00:21:45,532
Speaker 10: skills and connections that they would have set up on

445
00:21:45,573 --> 00:21:46,373
Speaker 10: the outside.

446
00:21:46,053 --> 00:21:49,093
Speaker 9: Before they leave, regardless of the keene sentence of a

447
00:21:49,133 --> 00:21:50,053
Speaker 9: twenty five year.

448
00:21:50,533 --> 00:21:54,213
Speaker 10: One example is let's four prisoners are living in one

449
00:21:54,333 --> 00:21:57,933
Speaker 10: shed house and the penitive part is that they can't

450
00:21:57,933 --> 00:21:59,373
Speaker 10: go wherever they want, whenever they want.

451
00:21:59,613 --> 00:22:01,773
Speaker 9: They can't say their family whenever they want, They can't

452
00:22:02,053 --> 00:22:04,813
Speaker 9: have freedom of choice. They have to work every day,

453
00:22:04,933 --> 00:22:06,213
Speaker 9: they have to learn a skill.

454
00:22:06,413 --> 00:22:07,333
Speaker 13: So they top up.

455
00:22:08,173 --> 00:22:10,693
Speaker 10: They go to work in a skill, they come out at.

456
00:22:10,613 --> 00:22:11,933
Speaker 9: The end of the day and they learn how to

457
00:22:12,133 --> 00:22:13,173
Speaker 9: use a computer.

458
00:22:13,213 --> 00:22:16,133
Speaker 10: They learn how to set up their bills and finances

459
00:22:16,173 --> 00:22:19,253
Speaker 10: at the end of the day, et cetera. And they

460
00:22:19,293 --> 00:22:24,253
Speaker 10: also undergo psychologist psychological help or drugs, you know, like

461
00:22:24,293 --> 00:22:27,373
Speaker 10: group therapy or things that would them.

462
00:22:27,293 --> 00:22:30,093
Speaker 4: Individual which is clearly working for the malan or when

463
00:22:30,133 --> 00:22:32,133
Speaker 4: it comes to the reoffending rate. But just back to

464
00:22:32,413 --> 00:22:35,973
Speaker 4: you know, your point about evidence, and when you look

465
00:22:36,013 --> 00:22:39,893
Speaker 4: at victims of crime, it's not always about evidence, is it?

466
00:22:40,213 --> 00:22:40,413
Speaker 3: Is it?

467
00:22:40,493 --> 00:22:43,773
Speaker 4: Because there would be many victims of crime in this country,

468
00:22:44,533 --> 00:22:48,013
Speaker 4: and whether that revenge or punishment of someone who did

469
00:22:48,013 --> 00:22:51,453
Speaker 4: them wrong led to that person improving their lives and

470
00:22:51,613 --> 00:22:53,893
Speaker 4: is less of a burden on society, it doesn't matter

471
00:22:53,933 --> 00:22:55,853
Speaker 4: to those victims. What they want to see is a

472
00:22:55,893 --> 00:22:58,893
Speaker 4: sense of justice and a sense of revenge, as Matt said,

473
00:22:58,973 --> 00:23:00,253
Speaker 4: So that comes into it as well.

474
00:23:02,013 --> 00:23:04,613
Speaker 10: Yes, I also now there's a gottening account of lens

475
00:23:04,653 --> 00:23:06,053
Speaker 10: and I don't want to go toound to it, but

476
00:23:06,093 --> 00:23:06,653
Speaker 10: I don't want to.

477
00:23:06,653 --> 00:23:08,812
Speaker 9: Point out to a lot of people who wouldn't from

478
00:23:08,893 --> 00:23:12,493
Speaker 9: this point of a lot of problems don't wonderful background

479
00:23:13,213 --> 00:23:13,893
Speaker 9: worth hearing.

480
00:23:13,973 --> 00:23:17,973
Speaker 2: Formally, Yeah, well that that's I mean that the cause

481
00:23:18,013 --> 00:23:21,653
Speaker 2: and effect part of justices of such a very very

482
00:23:21,773 --> 00:23:25,733
Speaker 2: very complicated issue. And yeah, I mean you could go

483
00:23:25,773 --> 00:23:28,733
Speaker 2: into that forever. Yeah, you know, and free to free

484
00:23:29,093 --> 00:23:30,893
Speaker 2: free will and the like. But thank you so much

485
00:23:30,933 --> 00:23:31,933
Speaker 2: for your call. Eleanor.

486
00:23:32,053 --> 00:23:33,653
Speaker 4: Oh e one hundred and eighty ten eighty is the

487
00:23:33,813 --> 00:23:36,133
Speaker 4: number to call, What are your thoughts about extending prison

488
00:23:36,293 --> 00:23:39,693
Speaker 4: sentences and a bid to reduce reoffending rates. Love to

489
00:23:39,733 --> 00:23:41,613
Speaker 4: hear from you on our eight hundred and eighty ten

490
00:23:41,653 --> 00:23:44,253
Speaker 4: eighty if you've been in prison, if you've had experience

491
00:23:44,293 --> 00:23:47,052
Speaker 4: with rehabilitation programs in New Zealand, really keen to hear

492
00:23:47,093 --> 00:23:52,213
Speaker 4: from you. It is twenty seven to two.

493
00:23:52,293 --> 00:23:55,893
Speaker 14: Jus Talk said the headlines with blue bubble taxis it's

494
00:23:55,893 --> 00:23:59,293
Speaker 14: no trouble with a blue bubble. A survey shows retail

495
00:23:59,413 --> 00:24:03,532
Speaker 14: workers are facing growing anti social behavior and crime, with

496
00:24:03,613 --> 00:24:08,973
Speaker 14: a large proportion going unreported. Disappointment uniform staff won't get

497
00:24:09,013 --> 00:24:12,573
Speaker 14: a pay rise in a major defense spend, although thirty

498
00:24:12,573 --> 00:24:17,333
Speaker 14: three millions been put aside for civilian staff rises. Adeneid

499
00:24:17,413 --> 00:24:20,773
Speaker 14: and Teen's been caught allegedly driving as new twenty nineteen

500
00:24:20,853 --> 00:24:24,533
Speaker 14: Ford Mustang GT late at night on the Southern Motorway,

501
00:24:24,933 --> 00:24:29,133
Speaker 14: going more than one hundred kilometers over the limit. Police

502
00:24:29,133 --> 00:24:31,613
Speaker 14: are looking into the assault of a sixteen year old

503
00:24:31,613 --> 00:24:35,493
Speaker 14: outside of property on Riverside Road in Auckland's audio on

504
00:24:35,573 --> 00:24:40,493
Speaker 14: Saturday night. NETSA says an alarming sixty eight percent rise

505
00:24:40,533 --> 00:24:44,813
Speaker 14: in reports of extortion over explicit videos and images could

506
00:24:44,813 --> 00:24:49,333
Speaker 14: be linked to organized crime. Westpac Enz's interim half year

507
00:24:49,333 --> 00:24:52,213
Speaker 14: profit has risen half a percent due to the rising

508
00:24:52,253 --> 00:24:56,293
Speaker 14: margin between its borrowing and lending. Meanwhile, Kiwi Banks lowering

509
00:24:56,373 --> 00:25:00,333
Speaker 14: long term home loan rates, with another OCR cut expected

510
00:25:00,413 --> 00:25:04,853
Speaker 14: this month. Unemployment set to rise to highest level in

511
00:25:04,933 --> 00:25:08,573
Speaker 14: nearly a decade. Read more from Leon dan ad In

512
00:25:08,733 --> 00:25:12,173
Speaker 14: said here or premium Now back to Matt Eithan Tyler Adams.

513
00:25:12,213 --> 00:25:13,933
Speaker 4: Thank you very much, Ray Lean And we're talking about

514
00:25:13,973 --> 00:25:17,493
Speaker 4: this idea of longer prison sentences to reduce the reoffending rate.

515
00:25:17,533 --> 00:25:19,853
Speaker 4: It's something greatians Minister Mark Mitchell is looking into.

516
00:25:20,253 --> 00:25:20,493
Speaker 15: Yeah.

517
00:25:20,533 --> 00:25:24,893
Speaker 2: And any discussion about rehabilitation always, my mind always goes

518
00:25:24,933 --> 00:25:27,413
Speaker 2: to the greatest movie of all time, the Shortshank Redemption,

519
00:25:27,693 --> 00:25:32,693
Speaker 2: and Red goes into a rehabilitation meeting after he's been

520
00:25:32,733 --> 00:25:35,093
Speaker 2: in prison for forty years Alic spoid reading.

521
00:25:36,133 --> 00:25:38,933
Speaker 16: If I'll say you served forty years of a life sentence,

522
00:25:39,933 --> 00:25:44,413
Speaker 16: you'll feel you've been rehabilitated. Rehabilitated. You know, I don't

523
00:25:44,453 --> 00:25:45,933
Speaker 16: have any idea what that means.

524
00:25:46,333 --> 00:25:48,773
Speaker 17: Well, it means you're ready to rejoin society.

525
00:25:48,973 --> 00:25:51,253
Speaker 16: I know, what do you think it means to me?

526
00:25:51,293 --> 00:25:54,213
Speaker 16: It's just a made up word, a politician's work. So

527
00:25:54,333 --> 00:25:57,133
Speaker 16: the young fellas like yourself can wear a suit and

528
00:25:57,173 --> 00:26:01,093
Speaker 16: a tie, have a job. What do you really want

529
00:26:01,133 --> 00:26:03,813
Speaker 16: to know? Am I sorry for what I did? As

530
00:26:03,893 --> 00:26:06,253
Speaker 16: not a day goes by, I don't feel regret, not

531
00:26:06,413 --> 00:26:09,493
Speaker 16: because I'm in here because you think, guy should I

532
00:26:09,573 --> 00:26:12,093
Speaker 16: look back on the way I was and a young,

533
00:26:13,213 --> 00:26:15,413
Speaker 16: stupid kids who committed that terrible crime.

534
00:26:15,693 --> 00:26:16,693
Speaker 2: I want to talk to him.

535
00:26:16,933 --> 00:26:18,373
Speaker 16: I want to try to talk to some sas to

536
00:26:18,453 --> 00:26:21,813
Speaker 16: him telling the way things are, But I can't. That

537
00:26:22,013 --> 00:26:25,293
Speaker 16: kid's long gone and as old man as all that's left,

538
00:26:25,773 --> 00:26:27,853
Speaker 16: I got to live with that rehabilitated.

539
00:26:28,053 --> 00:26:29,373
Speaker 2: It's just a bullyshel word.

540
00:26:29,853 --> 00:26:32,532
Speaker 16: So you go on and stamp your form, Sunny and

541
00:26:32,573 --> 00:26:36,093
Speaker 16: stop wasting my time. Because I tell you the truth,

542
00:26:36,493 --> 00:26:37,413
Speaker 16: I don't give a shit.

543
00:26:37,853 --> 00:26:42,253
Speaker 2: It's a great scene, great acting, Morgan Freeman, fantastic, But

544
00:26:42,293 --> 00:26:46,813
Speaker 2: it sort of also highlights the point because his rehabilitation

545
00:26:47,053 --> 00:26:49,893
Speaker 2: was that he was just in there so long that

546
00:26:50,853 --> 00:26:52,373
Speaker 2: he have by the end of it, he was just

547
00:26:52,413 --> 00:26:54,973
Speaker 2: that he wasn't the same person anymore. So when we

548
00:26:55,013 --> 00:26:58,933
Speaker 2: talk about longer sentences, you know, you change a person

549
00:26:58,973 --> 00:27:00,893
Speaker 2: if they're in prison for a very very long time. Yes,

550
00:27:01,693 --> 00:27:04,253
Speaker 2: a lot of people pointing out that Norway and is

551
00:27:04,253 --> 00:27:06,373
Speaker 2: always put up and we're always beaten around the head

552
00:27:06,373 --> 00:27:09,653
Speaker 2: by Norway and Scandadavian countries around them doing better at

553
00:27:09,653 --> 00:27:12,133
Speaker 2: certain things than us. We often forget how wealthy they are,

554
00:27:12,133 --> 00:27:14,052
Speaker 2: in Norway's case, how much a lot of money, how

555
00:27:14,093 --> 00:27:17,213
Speaker 2: much money they get from fossil fuels, and how much

556
00:27:17,253 --> 00:27:19,813
Speaker 2: money they have, and how heavily they are taxed and

557
00:27:19,853 --> 00:27:22,893
Speaker 2: for social services. But they also don't have the same

558
00:27:22,933 --> 00:27:26,933
Speaker 2: gang problems that we do. And so you know, you know,

559
00:27:27,053 --> 00:27:29,413
Speaker 2: Norway's prisons aren't as full of gang members. That's something

560
00:27:29,453 --> 00:27:32,653
Speaker 2: people people don't point out, you know. And Norway doesn't

561
00:27:32,693 --> 00:27:35,813
Speaker 2: have as this Texas says, Noruay doesn't have a population

562
00:27:35,973 --> 00:27:40,653
Speaker 2: that are brought up with a victim mentality. There's a

563
00:27:40,653 --> 00:27:42,333
Speaker 2: lot of people there's a lot of differences between Norway

564
00:27:42,373 --> 00:27:43,333
Speaker 2: and New Zealand, that's for sure.

565
00:27:43,373 --> 00:27:43,533
Speaker 3: Yep.

566
00:27:43,613 --> 00:27:45,813
Speaker 4: Absolutely. Oh eight hundred eighty ten eighty is the number

567
00:27:45,813 --> 00:27:48,093
Speaker 4: to call. Love to hear your thoughts about longer prison

568
00:27:48,133 --> 00:27:51,573
Speaker 4: sentences and rehabilitation in our system, if you've gone through it,

569
00:27:51,613 --> 00:27:53,253
Speaker 4: if you've been a part of it, I love to

570
00:27:53,253 --> 00:27:55,413
Speaker 4: hear from you on Old eight hundred and eighty ten eighty.

571
00:27:56,173 --> 00:27:58,253
Speaker 2: Well, you had a family member who worked in prisons

572
00:27:58,293 --> 00:27:59,533
Speaker 2: and another on the parole board.

573
00:28:00,413 --> 00:28:03,253
Speaker 17: I didn't have to be careful. I can't identify them albishly.

574
00:28:03,493 --> 00:28:03,693
Speaker 3: Yep.

575
00:28:04,773 --> 00:28:09,213
Speaker 17: I used to be a use worker myself, and I

576
00:28:09,253 --> 00:28:11,693
Speaker 17: think the most important think first is that you have

577
00:28:11,773 --> 00:28:16,253
Speaker 17: to teach people, and you get nowhere until you do.

578
00:28:17,573 --> 00:28:23,573
Speaker 17: And that is there are consequences for actions. And I

579
00:28:23,653 --> 00:28:26,733
Speaker 17: learned in my sphere where I was working as a

580
00:28:26,733 --> 00:28:32,173
Speaker 17: youth worker, the consequences were just ridiculous. You know, write

581
00:28:32,213 --> 00:28:35,213
Speaker 17: a letter say you're sorry, and I'm also given, you know,

582
00:28:36,653 --> 00:28:41,253
Speaker 17: and that the young folks used to laugh about it.

583
00:28:41,373 --> 00:28:44,973
Speaker 17: They are getting off Scott now. As for my family

584
00:28:45,013 --> 00:28:49,653
Speaker 17: member who worked in the prison, she told me many

585
00:28:49,653 --> 00:28:53,613
Speaker 17: a time in regard to the rehabilitation. Look, there's people

586
00:28:53,653 --> 00:28:56,893
Speaker 17: that go into help and support and they're good people.

587
00:28:56,933 --> 00:29:00,853
Speaker 17: Don't get me wrong here. I don't want to knock them.

588
00:29:01,133 --> 00:29:07,733
Speaker 17: But the problem is they totally underfund rehabilitation. And that's

589
00:29:07,893 --> 00:29:11,613
Speaker 17: always being the case. It's never been different. It all

590
00:29:11,653 --> 00:29:16,613
Speaker 17: looks good on paper, but well a good example was

591
00:29:16,653 --> 00:29:19,613
Speaker 17: that chap that you listen the first guy that was

592
00:29:19,653 --> 00:29:22,693
Speaker 17: talking who said he had to be there for what

593
00:29:22,813 --> 00:29:28,173
Speaker 17: fourteen years before rehabilitation even started. You know, well, yeah,

594
00:29:30,333 --> 00:29:31,053
Speaker 17: that's crazy.

595
00:29:31,413 --> 00:29:32,613
Speaker 6: I agree to that.

596
00:29:34,053 --> 00:29:37,213
Speaker 2: So well when you were saying before that you were working,

597
00:29:37,413 --> 00:29:39,733
Speaker 2: you know, with youth, what sort of age group are

598
00:29:39,733 --> 00:29:42,453
Speaker 2: you thinking are you talking about and what kind of

599
00:29:42,493 --> 00:29:44,973
Speaker 2: consequences do you think should come in early?

600
00:29:47,693 --> 00:29:51,413
Speaker 17: Well, you steal from someone, then you have to pay

601
00:29:51,453 --> 00:29:57,973
Speaker 17: the money back, right, you know, I'm into restitution, you know,

602
00:29:58,133 --> 00:30:02,773
Speaker 17: I'm into that. But a lot of times that doesn't happen.

603
00:30:03,053 --> 00:30:06,573
Speaker 17: You're going to judge say that the person's not economically

604
00:30:06,653 --> 00:30:09,373
Speaker 17: able to do it, and the well, probably the person

605
00:30:09,373 --> 00:30:13,973
Speaker 17: they stole from wasn't too happy about and probably didn't

606
00:30:14,013 --> 00:30:16,013
Speaker 17: have a lot of money when they lost what they lost.

607
00:30:16,093 --> 00:30:19,693
Speaker 17: You know, the same with cars things like this. It's

608
00:30:19,853 --> 00:30:22,773
Speaker 17: like we get into situations where people are paying back,

609
00:30:22,853 --> 00:30:26,213
Speaker 17: say a dollar a week or something. Where's the the

610
00:30:26,413 --> 00:30:30,333
Speaker 17: torrent in that, you know, as for locking them up

611
00:30:30,413 --> 00:30:32,493
Speaker 17: for longer just for the sake that you hope that

612
00:30:32,533 --> 00:30:35,893
Speaker 17: they'll turn out better. If you're not going to put

613
00:30:35,893 --> 00:30:40,773
Speaker 17: the wrap around services through, then you're just being political

614
00:30:40,933 --> 00:30:43,693
Speaker 17: and you're not actually trying to fix anything.

615
00:30:43,853 --> 00:30:46,053
Speaker 2: Well, I guess. I guess the argument against that, though, well,

616
00:30:46,093 --> 00:30:48,613
Speaker 2: would be that if someone's locked up, then they can't

617
00:30:48,653 --> 00:30:51,373
Speaker 2: commit crimes against the general public. So there is a

618
00:30:51,413 --> 00:30:54,853
Speaker 2: part of incarceration that is just getting them out of

619
00:30:54,413 --> 00:30:55,453
Speaker 2: the system.

620
00:30:55,573 --> 00:30:58,293
Speaker 17: Well, I don't know, but it's not working because crime's

621
00:30:58,333 --> 00:31:01,813
Speaker 17: growing all the time. It's not going down, and we've

622
00:31:01,813 --> 00:31:04,373
Speaker 17: done the Look, I'm willing to give it a go,

623
00:31:05,773 --> 00:31:09,293
Speaker 17: but I think we sort of try everything. You cannot

624
00:31:09,333 --> 00:31:13,973
Speaker 17: let people out of prison with virtually no money. Now,

625
00:31:14,013 --> 00:31:16,493
Speaker 17: I can't see why they can't work for earnest in there.

626
00:31:18,093 --> 00:31:21,853
Speaker 17: We can find schemes and things like that, but I

627
00:31:21,933 --> 00:31:24,413
Speaker 17: see no reason for them to do that, because you're

628
00:31:24,533 --> 00:31:27,373
Speaker 17: as looking for trouble if you put someone out on street.

629
00:31:27,533 --> 00:31:30,333
Speaker 2: The funny thing is with things like incarceration will there's

630
00:31:30,373 --> 00:31:34,213
Speaker 2: always a reason why things can't happen. So when they

631
00:31:34,293 --> 00:31:38,613
Speaker 2: start getting prisoners to work, people complain about the you know,

632
00:31:39,533 --> 00:31:41,853
Speaker 2: competing with other people for the same workout in the

633
00:31:42,133 --> 00:31:44,013
Speaker 2: you know, out in the commercial sector. And they also

634
00:31:44,413 --> 00:31:47,693
Speaker 2: complain about the you know, whether people are just using

635
00:31:47,733 --> 00:31:52,413
Speaker 2: prisoners as workers, and so it does get complicated in

636
00:31:52,453 --> 00:31:55,853
Speaker 2: that regard, but also is exactly what you're saying if

637
00:31:55,853 --> 00:31:59,053
Speaker 2: people could work hard in prison and actually be creating

638
00:31:59,093 --> 00:32:01,013
Speaker 2: something and then they get that money when they get

639
00:32:01,053 --> 00:32:03,293
Speaker 2: out and have a start. There seems to be a

640
00:32:03,333 --> 00:32:04,493
Speaker 2: little bit of logic in that.

641
00:32:05,493 --> 00:32:08,853
Speaker 17: Absolutely lo but we want to be teaching skills, so

642
00:32:08,893 --> 00:32:11,573
Speaker 17: it's all. Look, I can't be bothered with these people who,

643
00:32:13,533 --> 00:32:15,093
Speaker 17: you know, they just want to lock up and throw

644
00:32:15,093 --> 00:32:17,733
Speaker 17: away the key, because sooner or later that door does

645
00:32:17,813 --> 00:32:22,413
Speaker 17: open and they do come out. And I want to

646
00:32:22,453 --> 00:32:26,213
Speaker 17: see I would like to see real rehabilitation take place,

647
00:32:26,533 --> 00:32:29,333
Speaker 17: and I want to see people men and women in

648
00:32:29,373 --> 00:32:32,453
Speaker 17: prison able to earn I'm not talking a lot of

649
00:32:32,493 --> 00:32:36,613
Speaker 17: money here, you know. I don't think they should be

650
00:32:36,653 --> 00:32:40,853
Speaker 17: paid the going rate, you know, I don't because that

651
00:32:40,893 --> 00:32:43,573
Speaker 17: can be part of the punishment giving back to society.

652
00:32:44,853 --> 00:32:47,653
Speaker 17: But to at least have enough money to come out

653
00:32:48,493 --> 00:32:51,733
Speaker 17: and not have to turn around and go and see

654
00:32:51,933 --> 00:32:54,453
Speaker 17: something else because they can't afford a loaf of bread

655
00:32:54,573 --> 00:32:54,973
Speaker 17: or something.

656
00:32:55,413 --> 00:32:56,413
Speaker 2: Yeah, I think of you. Cool.

657
00:32:56,413 --> 00:32:59,933
Speaker 4: Well, oh one hundred eighteen eighty. If you've employed someone

658
00:32:59,973 --> 00:33:03,173
Speaker 4: who's been released from prison, love to have a chat

659
00:33:03,213 --> 00:33:08,333
Speaker 4: with you. I understand there are you know, outreach programs

660
00:33:08,533 --> 00:33:11,453
Speaker 4: that when a prisoner is released. They don't have too

661
00:33:11,533 --> 00:33:14,493
Speaker 4: much support from the prison system or the government, but

662
00:33:14,533 --> 00:33:16,773
Speaker 4: there are organizations that try and get them into work.

663
00:33:16,933 --> 00:33:19,173
Speaker 4: And if you're someone who employed those people, how did

664
00:33:19,173 --> 00:33:20,733
Speaker 4: it turn out for you? Did it turn out well?

665
00:33:20,893 --> 00:33:22,613
Speaker 4: Did you what sort of hoops did you have to

666
00:33:22,733 --> 00:33:24,453
Speaker 4: jump through to make sure they were going to work out?

667
00:33:24,573 --> 00:33:26,373
Speaker 4: Oh eight hundred and eighty ten eighty is the number

668
00:33:26,413 --> 00:33:26,653
Speaker 4: to call.

669
00:33:26,773 --> 00:33:28,773
Speaker 2: Here's a text on nine two ninety two that sums

670
00:33:28,853 --> 00:33:30,613
Speaker 2: up what a lot of people are sending through. It's

671
00:33:30,613 --> 00:33:32,573
Speaker 2: not a problem until it happens to you and your family.

672
00:33:32,613 --> 00:33:34,493
Speaker 2: The do good is saying prison is not the answer.

673
00:33:34,533 --> 00:33:38,173
Speaker 2: Would have a completely different view if it was their

674
00:33:38,253 --> 00:33:41,813
Speaker 2: child that was attacked or murdered. Easy to say when

675
00:33:41,813 --> 00:33:42,573
Speaker 2: it happens to others.

676
00:33:42,693 --> 00:33:48,253
Speaker 4: Yeah, and that's it. It is fourteen to two.

677
00:33:47,213 --> 00:33:50,373
Speaker 1: Matd Heath Taylor Adams taking your calls on Oh, eight

678
00:33:50,493 --> 00:33:53,413
Speaker 1: hundred and eighty ten eighty. It's mad Heathen Tyler Adams

679
00:33:53,453 --> 00:33:54,853
Speaker 1: afternoons news talks.

680
00:33:54,853 --> 00:33:57,173
Speaker 4: They'd be very good afternoon to you. It is twelve

681
00:33:57,213 --> 00:34:00,813
Speaker 4: to two two and we're talking about rehabilitation programs within

682
00:34:00,893 --> 00:34:03,573
Speaker 4: our New Zealand prisons Chrestians. Minister Mark Mitchell was looking

683
00:34:03,573 --> 00:34:06,933
Speaker 4: into longer prison sentences because he sees the evidence is

684
00:34:06,973 --> 00:34:09,252
Speaker 4: clear that that reduces rere rates. How do you feel

685
00:34:09,253 --> 00:34:09,692
Speaker 4: about that?

686
00:34:10,373 --> 00:34:12,292
Speaker 2: This this text here from Mike as a prison as

687
00:34:12,333 --> 00:34:14,973
Speaker 2: a cleaner in prison, I think the pay is forty

688
00:34:15,013 --> 00:34:17,652
Speaker 2: cents per hour, so you know, you got to put

689
00:34:17,653 --> 00:34:19,413
Speaker 2: a lot of hours in before you've got some money

690
00:34:19,413 --> 00:34:21,652
Speaker 2: when you get out. But I'm pretty sure that in

691
00:34:21,653 --> 00:34:24,093
Speaker 2: New Zealand we don't have that situation that that happens

692
00:34:24,093 --> 00:34:26,733
Speaker 2: in the States sometimes, or historically happened in the States

693
00:34:26,773 --> 00:34:29,933
Speaker 2: where prisons would tender for work. You know the famous

694
00:34:30,453 --> 00:34:35,653
Speaker 2: making number plates cliche. So prisons would tend to tender

695
00:34:35,653 --> 00:34:39,333
Speaker 2: for work and be able to get these these you know,

696
00:34:39,373 --> 00:34:42,573
Speaker 2: these jobs and these contracts because their workforce.

697
00:34:42,133 --> 00:34:46,652
Speaker 4: Was very, very cheap, undercut everybody. Yeah, Kerrie, what's your

698
00:34:46,733 --> 00:34:48,293
Speaker 4: view on this one.

699
00:34:48,813 --> 00:34:52,652
Speaker 11: I've got a pretty broad view on the whole thing.

700
00:34:52,693 --> 00:34:56,373
Speaker 11: I work in the supporter, I've worked in dragon alcohol,

701
00:34:56,573 --> 00:35:00,613
Speaker 11: and I've also worked in disabilities and mental health and

702
00:35:00,693 --> 00:35:02,373
Speaker 11: a lot of with a lot of people who have

703
00:35:02,453 --> 00:35:06,733
Speaker 11: been in prison or are looking at going into prison,

704
00:35:07,453 --> 00:35:10,373
Speaker 11: and that the ones that are in their long term

705
00:35:11,253 --> 00:35:15,573
Speaker 11: they just become better criminals. They get educated in how

706
00:35:15,613 --> 00:35:20,453
Speaker 11: to be deceitful, how to work in stealth mode. You know,

707
00:35:20,573 --> 00:35:23,293
Speaker 11: they what they don't know when they go in there,

708
00:35:23,453 --> 00:35:24,333
Speaker 11: they certainly learn.

709
00:35:24,733 --> 00:35:26,933
Speaker 2: So is there a big difference between say, someone that's

710
00:35:26,933 --> 00:35:30,093
Speaker 2: been in I'm just going to grab a number two years,

711
00:35:30,253 --> 00:35:32,693
Speaker 2: and someone that's been in for teen years that you

712
00:35:32,733 --> 00:35:34,373
Speaker 2: can notice some of them and it's been in there

713
00:35:34,373 --> 00:35:37,613
Speaker 2: for teen years, is more likely in your opinion, to

714
00:35:37,853 --> 00:35:40,172
Speaker 2: remain a criminal than someone that's been in the effort.

715
00:35:39,853 --> 00:35:43,333
Speaker 11: For Yeah, they are. They get recruited by the gangs

716
00:35:43,333 --> 00:35:45,573
Speaker 11: that are in there, and then they end up working

717
00:35:45,693 --> 00:35:50,733
Speaker 11: for them inside. And what they don't learn about gang business,

718
00:35:50,813 --> 00:35:53,613
Speaker 11: I guess they learn in there. So I don't think

719
00:35:53,653 --> 00:35:55,573
Speaker 11: long longest sentences.

720
00:35:55,133 --> 00:35:55,933
Speaker 13: Is the way they go.

721
00:35:56,453 --> 00:35:59,933
Speaker 11: What are the shortest sentences you will find for minor

722
00:35:59,973 --> 00:36:04,493
Speaker 11: offenses like drugs, driving offenses, that sort of stuff, And

723
00:36:04,813 --> 00:36:07,613
Speaker 11: you know the commissioner wants to make these sentences longer.

724
00:36:08,653 --> 00:36:11,732
Speaker 11: I'm not sure if that's the right road to go down. Yes,

725
00:36:11,773 --> 00:36:16,733
Speaker 11: we do need rehabilitation. I really don't know what the

726
00:36:16,813 --> 00:36:19,692
Speaker 11: answer is, but all I know is from my experience,

727
00:36:19,773 --> 00:36:22,893
Speaker 11: the longer they're in there, the more they learn in

728
00:36:22,973 --> 00:36:23,652
Speaker 11: criminal care.

729
00:36:23,693 --> 00:36:26,413
Speaker 2: Have you ever worked with anyone that has been in

730
00:36:26,413 --> 00:36:30,333
Speaker 2: there for really long terms, over twenty year type terms.

731
00:36:31,133 --> 00:36:33,933
Speaker 11: Yes, I have, Yes, I have. I worked with someone

732
00:36:33,973 --> 00:36:35,133
Speaker 11: who has murdered somebody.

733
00:36:35,213 --> 00:36:38,373
Speaker 2: Oh well, and did that hold true.

734
00:36:38,053 --> 00:36:43,413
Speaker 11: That he learnt more? I guess because he had support.

735
00:36:44,933 --> 00:36:47,813
Speaker 11: The only the only reason we connected was I was

736
00:36:47,893 --> 00:36:51,933
Speaker 11: running a karate club and he came along to one

737
00:36:51,973 --> 00:36:54,212
Speaker 11: of the sessions and I ended up working with him

738
00:36:54,653 --> 00:36:58,413
Speaker 11: and just having a purpose out there and a passion

739
00:36:58,453 --> 00:37:00,933
Speaker 11: because he had a bit of a passion for Japanese

740
00:37:00,973 --> 00:37:06,413
Speaker 11: things and Japanese etiquette and that sort of stuff. And

741
00:37:06,453 --> 00:37:09,293
Speaker 11: I think if that support wasn't there, he hadn't been

742
00:37:09,373 --> 00:37:14,933
Speaker 11: able to work with him, it would be a different story.

743
00:37:15,293 --> 00:37:19,733
Speaker 11: Now he's a really decent person, really decent family member,

744
00:37:21,053 --> 00:37:24,613
Speaker 11: and you know, obviously he reflects on his time. He

745
00:37:24,653 --> 00:37:25,652
Speaker 11: did twelve.

746
00:37:25,333 --> 00:37:28,933
Speaker 4: Years for murder, right, and he's remorseful.

747
00:37:30,253 --> 00:37:35,253
Speaker 11: Oh absolutely, I mean it was it was an interesting murder.

748
00:37:35,933 --> 00:37:39,493
Speaker 11: His partner was a paraplegict and someone broke into the

749
00:37:39,573 --> 00:37:42,933
Speaker 11: house and rape it. So he found out who that

750
00:37:42,973 --> 00:37:46,093
Speaker 11: person was and sought revenge.

751
00:37:46,493 --> 00:37:52,173
Speaker 4: And yeah, well a lot of people that this is

752
00:37:52,213 --> 00:37:53,373
Speaker 4: what happens Carrie.

753
00:37:53,413 --> 00:37:58,693
Speaker 2: Every time you talk about this crime and prison and

754
00:37:59,213 --> 00:38:05,213
Speaker 2: rehabilitation and justice, it gets so complicated because there's always

755
00:38:05,213 --> 00:38:08,933
Speaker 2: these edge cases like this that that were it's hard

756
00:38:08,933 --> 00:38:12,853
Speaker 2: to get your head around the philosophy of it all.

757
00:38:13,493 --> 00:38:16,253
Speaker 11: So I don't know what the answer is, but definitely

758
00:38:16,333 --> 00:38:20,093
Speaker 11: longer sentences, it's not the answer. You're just going to

759
00:38:20,133 --> 00:38:24,533
Speaker 11: be making a more knowledgeable, harder to catch criminals.

760
00:38:24,613 --> 00:38:26,373
Speaker 4: Carry Thank you so much for your call. Carry Oh,

761
00:38:26,413 --> 00:38:28,053
Speaker 4: one hundred and eighty ten eighty is the number to

762
00:38:28,053 --> 00:38:30,133
Speaker 4: call love to hear your thoughts. It is seven to two.

763
00:38:32,453 --> 00:38:36,053
Speaker 1: Matt Heath Tylor Adams taking your calls on eight hundred

764
00:38:36,053 --> 00:38:38,653
Speaker 1: and eighty ten eighty. It's mad Heath and Tylor Adams.

765
00:38:38,733 --> 00:38:43,772
Speaker 4: Afternoons News TALKSB, News Talks THEB five to two. There's

766
00:38:43,773 --> 00:38:45,213
Speaker 4: a lot of people want to have a chat about this.

767
00:38:45,213 --> 00:38:47,172
Speaker 4: We're going to carry it on after the news.

768
00:38:46,973 --> 00:38:49,373
Speaker 2: This Texas says prisons there has three purposes in order

769
00:38:49,373 --> 00:38:52,933
Speaker 2: of priority, protect society, punished criminals for their crimes against society.

770
00:38:53,013 --> 00:38:56,493
Speaker 2: Offer rehabilitation after the success of their first two And

771
00:38:56,533 --> 00:39:00,253
Speaker 2: that's quite a complicated part of it. There is this

772
00:39:00,413 --> 00:39:02,692
Speaker 2: idea and I think we will buy into it. If

773
00:39:02,733 --> 00:39:06,653
Speaker 2: someone does something terrible, then something terrible needs to happen

774
00:39:06,693 --> 00:39:06,933
Speaker 2: to them.

775
00:39:07,533 --> 00:39:08,293
Speaker 6: That's justice.

776
00:39:08,413 --> 00:39:11,493
Speaker 2: Yeah, it's justice. It doesn't make the universe better or

777
00:39:11,493 --> 00:39:13,693
Speaker 2: write things, but it does things in our mind. And

778
00:39:13,733 --> 00:39:17,173
Speaker 2: it gets very very odd for people that are victims

779
00:39:17,293 --> 00:39:20,333
Speaker 2: of serious crime or members of their families of victims

780
00:39:20,373 --> 00:39:23,693
Speaker 2: of serious crime, if the focus is too too much

781
00:39:23,853 --> 00:39:27,933
Speaker 2: on the good of the person who has committed the

782
00:39:27,933 --> 00:39:30,933
Speaker 2: crime and society at large. And it gets very complicated,

783
00:39:30,973 --> 00:39:31,373
Speaker 2: doesn't it.

784
00:39:31,453 --> 00:39:33,413
Speaker 4: Oh, eight hundred and eighty ten eighty is the number

785
00:39:33,413 --> 00:39:35,733
Speaker 4: to call. As I say, we're going to pick this

786
00:39:35,813 --> 00:39:37,853
Speaker 4: back up after the two o'clock news, so love to

787
00:39:37,893 --> 00:39:39,413
Speaker 4: hear your thoughts on it. If you want to send

788
00:39:39,413 --> 00:39:41,293
Speaker 4: a text more than welcome. Nine to nine to two

789
00:39:41,413 --> 00:39:44,773
Speaker 4: is the text number. News Sport and whether coming up.

790
00:39:44,853 --> 00:39:47,253
Speaker 4: Great to have your company as always. You're listening to

791
00:39:47,253 --> 00:39:51,493
Speaker 4: Matt and Tyler. Very good afternoon to you.

792
00:39:52,893 --> 00:39:57,053
Speaker 3: Isn't it something the middle.

793
00:39:59,973 --> 00:40:07,493
Speaker 1: Little talking with you all afternoon. It's Matt Heathen Taylor

794
00:40:07,533 --> 00:40:09,813
Speaker 1: Adams News Talks.

795
00:40:09,813 --> 00:40:13,453
Speaker 4: It'd be good afternoon to you. Welcome back to the program.

796
00:40:13,493 --> 00:40:15,693
Speaker 4: Seven past too great to have your company as always,

797
00:40:15,693 --> 00:40:20,213
Speaker 4: and we're talking about rehabilitation in our prison system. Also

798
00:40:20,333 --> 00:40:23,293
Speaker 4: longer prison sentence is it something creations Minister Mark Mitchell

799
00:40:23,373 --> 00:40:26,613
Speaker 4: was looking into as we speak. He argues that longer

800
00:40:26,653 --> 00:40:30,413
Speaker 4: prison sentences would lower the reoffending rate, which as it

801
00:40:30,533 --> 00:40:36,093
Speaker 4: stands is very very ludicrous, I mean dishonesty charges. The

802
00:40:36,253 --> 00:40:40,453
Speaker 4: reoffending rates seventy nine percent, for property offenses sixty one percent,

803
00:40:40,533 --> 00:40:41,933
Speaker 4: violence sixty one percent.

804
00:40:42,773 --> 00:40:46,093
Speaker 2: Yeah, it's an interesting thing, isn't it, Because it's slightly

805
00:40:46,093 --> 00:40:48,453
Speaker 2: more complicated than that that all things are, and that

806
00:40:48,493 --> 00:40:50,893
Speaker 2: the type of crimes that you're in for a less

807
00:40:50,893 --> 00:40:53,333
Speaker 2: time for the type of crimes that you're more likely

808
00:40:53,573 --> 00:40:57,013
Speaker 2: to reoffend in. But there's a lot of different reasons

809
00:40:57,053 --> 00:41:00,973
Speaker 2: why people are sent to prison, and a lot of

810
00:41:01,013 --> 00:41:03,773
Speaker 2: reasons why society want to send people to prison. Is

811
00:41:03,813 --> 00:41:07,773
Speaker 2: it the justice and for one of a better word,

812
00:41:07,813 --> 00:41:11,093
Speaker 2: as I keep say, revenge for the crime you've done,

813
00:41:11,533 --> 00:41:14,013
Speaker 2: you know, in honor of the victim or the victim's family.

814
00:41:14,573 --> 00:41:16,813
Speaker 2: Is it keeping them off the streets, so you're just

815
00:41:16,813 --> 00:41:21,053
Speaker 2: incarcerating the people so they can't crimes. Is it rehabilitation?

816
00:41:21,333 --> 00:41:23,933
Speaker 2: There's a lot of different reasons why we send people

817
00:41:24,453 --> 00:41:27,773
Speaker 2: to prison. This Texas says. Dave says, I've spent many

818
00:41:27,813 --> 00:41:30,212
Speaker 2: years in prison. I've worked in many different jobs in jail,

819
00:41:30,253 --> 00:41:35,813
Speaker 2: from kitchen work, farming, painting, construction, precast concreting pays not

820
00:41:35,893 --> 00:41:37,973
Speaker 2: great fourteen bucks a week, but it's all about feeling

821
00:41:38,053 --> 00:41:42,173
Speaker 2: useful normal. I've done many programs, some good, some not

822
00:41:42,213 --> 00:41:45,893
Speaker 2: worth the time put into them. Prison does not fix anyone, However,

823
00:41:45,973 --> 00:41:48,093
Speaker 2: some people are better to stay in there. I guess

824
00:41:48,133 --> 00:41:49,973
Speaker 2: it comes down to getting the right people, making the

825
00:41:50,053 --> 00:41:53,413
Speaker 2: right calls, a discretion longer sentence for some and shorter

826
00:41:53,493 --> 00:41:55,413
Speaker 2: for those that choose change.

827
00:41:56,493 --> 00:41:59,253
Speaker 4: And this one says, guys, I've done short sentences and

828
00:41:59,293 --> 00:42:02,252
Speaker 4: long sentences over a decade, and I can honestly say

829
00:42:02,493 --> 00:42:04,692
Speaker 4: neither of them stood out as the turning point of

830
00:42:05,053 --> 00:42:08,053
Speaker 4: my life. If anything, the longest sentences left me less

831
00:42:08,053 --> 00:42:11,373
Speaker 4: well prepared for release because my time away I lost

832
00:42:11,373 --> 00:42:13,933
Speaker 4: pretty much everyone from my support network and had to

833
00:42:13,933 --> 00:42:16,293
Speaker 4: start all over again with zero support from the government.

834
00:42:16,933 --> 00:42:19,173
Speaker 4: In my opinion, this is just Mark Mitchell trying to

835
00:42:19,253 --> 00:42:21,172
Speaker 4: kick the can down the road and get the data

836
00:42:21,213 --> 00:42:22,613
Speaker 4: he needs to show he's tough on crime.

837
00:42:22,773 --> 00:42:26,333
Speaker 2: With Craig says, we really have it badly and sadly wrong.

838
00:42:26,373 --> 00:42:33,213
Speaker 2: Discussions always deter the offender, always veer towards the offender

839
00:42:33,293 --> 00:42:35,573
Speaker 2: and not the victim. We need to be much tougher

840
00:42:35,573 --> 00:42:38,333
Speaker 2: for offenders long as sentences definitely or at least sentences

841
00:42:38,333 --> 00:42:41,933
Speaker 2: without discounts serve the time, then when that completed, provided

842
00:42:42,013 --> 00:42:45,893
Speaker 2: rehab back into society. But we must be tough on crime.

843
00:42:45,933 --> 00:42:48,413
Speaker 2: So that's an interesting point. So what he's saying is

844
00:42:48,453 --> 00:42:51,413
Speaker 2: and there's not a lot of people that are disagreeing

845
00:42:51,453 --> 00:42:53,613
Speaker 2: with this, And we talked to Tim before, and we

846
00:42:53,693 --> 00:42:55,613
Speaker 2: talk to other prisoners that have come out of prison,

847
00:42:55,653 --> 00:42:57,933
Speaker 2: and how difficult it is when you first hit the

848
00:42:57,933 --> 00:43:00,933
Speaker 2: ground because you have no support network. Arguably, if you've

849
00:43:00,933 --> 00:43:02,733
Speaker 2: been in there for a long time, you've got no

850
00:43:03,693 --> 00:43:05,333
Speaker 2: where to be and you don't have the skills to

851
00:43:05,333 --> 00:43:10,292
Speaker 2: live in a normal society. So well, that textas saying

852
00:43:10,373 --> 00:43:14,213
Speaker 2: was very very hard on crime, but as quite quite

853
00:43:14,293 --> 00:43:16,853
Speaker 2: open to softer landings when you actually get out there,

854
00:43:17,373 --> 00:43:19,693
Speaker 2: because I think you leave prison with three hundred and

855
00:43:19,693 --> 00:43:20,453
Speaker 2: fifty bucks, that's.

856
00:43:20,373 --> 00:43:23,333
Speaker 4: What Tim was saying, yep. And then arguably you go

857
00:43:23,373 --> 00:43:26,373
Speaker 4: to a halfway house or some other minor accommodation that

858
00:43:26,373 --> 00:43:28,973
Speaker 4: the government may provide for you. Maybe not, as you say,

859
00:43:28,973 --> 00:43:32,253
Speaker 4: you've got no skills. There is the stigma attached to

860
00:43:32,293 --> 00:43:34,453
Speaker 4: you being a prisoner trying to get a job. Many

861
00:43:34,493 --> 00:43:37,212
Speaker 4: employees would look at that and say, no way, no way,

862
00:43:37,213 --> 00:43:40,013
Speaker 4: am I employing an next prisoner. So it is you know,

863
00:43:40,853 --> 00:43:43,093
Speaker 4: of course, there's a lot of victims probably screaming at

864
00:43:43,093 --> 00:43:45,053
Speaker 4: the radio now saying shut up, Tyler. If you've ever

865
00:43:45,053 --> 00:43:47,133
Speaker 4: been a victim of a crime, you would have no

866
00:43:47,253 --> 00:43:50,333
Speaker 4: sympathy for these guys. But the reality is that they

867
00:43:50,333 --> 00:43:52,613
Speaker 4: are going to continue to be a burden on society.

868
00:43:52,813 --> 00:43:55,893
Speaker 2: Well, yeah, if they've done the time, and that'll be

869
00:43:56,133 --> 00:43:58,853
Speaker 2: another point of contention, whether people actually do do the time.

870
00:43:59,893 --> 00:44:02,333
Speaker 2: If they've done the time and you've decided that that's

871
00:44:02,333 --> 00:44:05,493
Speaker 2: what they needed to do, then either their toxic waste

872
00:44:05,653 --> 00:44:08,813
Speaker 2: and they're done for, or we do something to help

873
00:44:08,813 --> 00:44:11,173
Speaker 2: them when they get back out into society.

874
00:44:11,293 --> 00:44:13,373
Speaker 4: Exactly. Oh one hundred and eighteen eighty is the number

875
00:44:13,373 --> 00:44:14,373
Speaker 4: to call of your thoughts on.

876
00:44:14,333 --> 00:44:20,053
Speaker 2: This, Brunetta, welcome to the show. Your thoughts on prison rehabilitation.

877
00:44:21,093 --> 00:44:23,692
Speaker 18: Oh gosh, so many. I'll try and condense it. What

878
00:44:23,733 --> 00:44:25,652
Speaker 18: would you like to know? So a bit about me

879
00:44:25,893 --> 00:44:28,693
Speaker 18: I've gone from being a teacher, high school teacher, to

880
00:44:29,373 --> 00:44:32,413
Speaker 18: not being quite satisfied, to being a counselor school counselor,

881
00:44:32,773 --> 00:44:37,413
Speaker 18: to then being inspired like case manager overseas in the community,

882
00:44:37,613 --> 00:44:42,293
Speaker 18: different diverse communities. I keep studying, I keep trying to

883
00:44:42,653 --> 00:44:44,652
Speaker 18: get to a place where I'm going to have some

884
00:44:44,893 --> 00:44:48,493
Speaker 18: impact on someone. Got all the way to Policy Group, Justice,

885
00:44:48,573 --> 00:44:53,813
Speaker 18: Ministry of Justice and really passionate about contributing my frontline experience.

886
00:44:54,133 --> 00:44:56,652
Speaker 18: I found that that wasn't really my cup of tea.

887
00:44:56,653 --> 00:44:59,493
Speaker 18: I'm not one to sit and research deeply all day. However,

888
00:44:59,533 --> 00:45:02,413
Speaker 18: I still have very good friends there. From there, I

889
00:45:02,493 --> 00:45:05,733
Speaker 18: moved on to this Department of Corrections National Office. Now

890
00:45:05,933 --> 00:45:09,133
Speaker 18: this is where mister Mitchell will wish he had responded

891
00:45:09,173 --> 00:45:13,413
Speaker 18: to my letter and actually my invitation to speak with him,

892
00:45:13,453 --> 00:45:17,733
Speaker 18: because this is really I don't even normally listen to

893
00:45:17,773 --> 00:45:19,692
Speaker 18: the station. My partner's just popped and said, you might

894
00:45:19,733 --> 00:45:23,933
Speaker 18: want to ring. This has really gotten under my skin. Like, firstly,

895
00:45:24,013 --> 00:45:26,733
Speaker 18: I would like to say to him that these are

896
00:45:26,773 --> 00:45:29,973
Speaker 18: people with families. They have got brothers, they've got fathers,

897
00:45:29,973 --> 00:45:34,333
Speaker 18: they've got daughters and sons. There's someone's you know, nephew

898
00:45:34,693 --> 00:45:38,173
Speaker 18: so why are we treating prisoners like they are animals

899
00:45:38,213 --> 00:45:41,213
Speaker 18: or something? They even in jail they say it's a

900
00:45:41,333 --> 00:45:43,773
Speaker 18: muster blowout. I mean, it's a toom you used for animals.

901
00:45:44,213 --> 00:45:46,853
Speaker 18: So when I worked at the Department of Corrections, I

902
00:45:46,933 --> 00:45:49,493
Speaker 18: was tasked with doing a review of a program called

903
00:45:49,693 --> 00:45:52,732
Speaker 18: ted ted or Hunger where they have cultural connection, learn

904
00:45:52,813 --> 00:45:56,253
Speaker 18: their culture, and they felt great. Like I was really

905
00:45:56,293 --> 00:45:57,813
Speaker 18: scared before I went into a prison for.

906
00:45:57,773 --> 00:45:58,213
Speaker 3: The first time.

907
00:45:58,253 --> 00:46:00,613
Speaker 18: Couldn't sleep all night, you know, I thought, are they going.

908
00:46:00,533 --> 00:46:01,213
Speaker 13: To molest me?

909
00:46:01,373 --> 00:46:01,893
Speaker 6: Abuse me?

910
00:46:01,973 --> 00:46:04,613
Speaker 18: What's going to happen to me? I get out into

911
00:46:04,693 --> 00:46:08,013
Speaker 18: a courtyard at Hawk's Bay Prison and I'm surrounded with

912
00:46:08,133 --> 00:46:10,453
Speaker 18: men who just want to connect and talk to someone.

913
00:46:11,133 --> 00:46:13,732
Speaker 18: And I tell you what, when I came out of there,

914
00:46:13,813 --> 00:46:17,053
Speaker 18: the sadness that I felt listening like just a little

915
00:46:17,053 --> 00:46:17,813
Speaker 18: bit to every.

916
00:46:17,573 --> 00:46:18,333
Speaker 15: Single one of them.

917
00:46:18,653 --> 00:46:21,333
Speaker 18: There's all been victims of crime. So why are we

918
00:46:21,413 --> 00:46:24,173
Speaker 18: not for you know, remembering that part, well.

919
00:46:23,893 --> 00:46:26,573
Speaker 2: I guess, I guess. You know, there's there's more sides

920
00:46:26,613 --> 00:46:29,213
Speaker 2: to it as well. So what do you think in

921
00:46:29,293 --> 00:46:31,933
Speaker 2: terms of the the you know, the victim of the

922
00:46:31,973 --> 00:46:35,053
Speaker 2: direct crime that the person that in prison has committed.

923
00:46:35,293 --> 00:46:37,573
Speaker 2: Do you think that there needs to be a punitive

924
00:46:37,613 --> 00:46:41,732
Speaker 2: element and a revenge element. Basically a justice is how

925
00:46:41,773 --> 00:46:43,853
Speaker 2: you call it, because you've committed a crime. So part

926
00:46:43,893 --> 00:46:48,013
Speaker 2: of prison, as hard as it is, is to right

927
00:46:48,093 --> 00:46:50,613
Speaker 2: that wrong and and to help the victim of that

928
00:46:50,693 --> 00:46:51,653
Speaker 2: crime to move forward.

929
00:46:52,853 --> 00:46:55,693
Speaker 18: Is it really helping that victim when the sentence is

930
00:46:55,693 --> 00:46:58,652
Speaker 18: handed done. I mean that might that might feel quite satisfying,

931
00:46:58,853 --> 00:47:01,453
Speaker 18: but what it's not helping is society when they come

932
00:47:01,493 --> 00:47:05,893
Speaker 18: out really just spaced out because they can't function, filled

933
00:47:05,893 --> 00:47:09,253
Speaker 18: with anxiety. And I know this because I accompanied a

934
00:47:09,293 --> 00:47:12,772
Speaker 18: young person the other day. You know, just kept taking

935
00:47:12,813 --> 00:47:14,573
Speaker 18: his phone calls. I've even just missed a phone call

936
00:47:14,613 --> 00:47:17,733
Speaker 18: from Auckland prison, but I kept taking his phone calls

937
00:47:17,813 --> 00:47:20,213
Speaker 18: just to keep the hope alive. Because I tell you,

938
00:47:20,293 --> 00:47:23,213
Speaker 18: the suicide raids on romand especially as something that we

939
00:47:23,293 --> 00:47:25,253
Speaker 18: need to pay attention to. So if you think the

940
00:47:25,293 --> 00:47:28,213
Speaker 18: world is moving on without you, you become isolated, feel

941
00:47:28,213 --> 00:47:30,493
Speaker 18: like no one's caring about you. Look, of course, those

942
00:47:30,533 --> 00:47:34,493
Speaker 18: heinous crime need accountability, but those men, and I'm speaking

943
00:47:34,493 --> 00:47:36,333
Speaker 18: for a number of young men that I've worked with,

944
00:47:36,613 --> 00:47:40,853
Speaker 18: cannot connect with emotions because they just have gone past

945
00:47:40,893 --> 00:47:43,172
Speaker 18: that point of caring because no one cares for them.

946
00:47:43,533 --> 00:47:43,773
Speaker 3: You know.

947
00:47:43,893 --> 00:47:46,773
Speaker 18: Let's just I mean, at which point is mister Mitchell

948
00:47:46,853 --> 00:47:48,413
Speaker 18: going to stop? Are we going to end up like

949
00:47:48,533 --> 00:47:52,133
Speaker 18: Saudi Arabia chopping their fingers off or something. I'm sorry

950
00:47:52,133 --> 00:47:55,053
Speaker 18: but that might sound ridiculous, but I just want to

951
00:47:55,053 --> 00:47:58,413
Speaker 18: say something about this narrative that is really annoying me

952
00:47:58,693 --> 00:48:01,453
Speaker 18: and the multiple letters I've written to ministers that they

953
00:48:01,493 --> 00:48:04,013
Speaker 18: are not responding. In fact, I think it's a two

954
00:48:04,093 --> 00:48:06,613
Speaker 18: billion dollar prison being built, isn't it.

955
00:48:06,773 --> 00:48:07,973
Speaker 3: So someone's going to fill them up.

956
00:48:08,333 --> 00:48:10,893
Speaker 18: That's what fifty percent ma just.

957
00:48:10,733 --> 00:48:12,973
Speaker 4: Just jimping in their brunette. Because to be fair to

958
00:48:13,533 --> 00:48:16,373
Speaker 4: Mark Mitchell, this is the quote in the story. So

959
00:48:16,413 --> 00:48:20,373
Speaker 4: he talked about longer sentences that gives prisoners better access

960
00:48:20,413 --> 00:48:23,213
Speaker 4: to rehabilitation programs, and he says, I quote, that is

961
00:48:23,213 --> 00:48:26,093
Speaker 4: where you get handled a minute. That is where you

962
00:48:26,133 --> 00:48:28,413
Speaker 4: get the greatest gains. That is where you get the

963
00:48:28,453 --> 00:48:32,973
Speaker 4: greatest gains in terms of rehabilitating people, in successfully reintegrating

964
00:48:32,973 --> 00:48:35,533
Speaker 4: them into society, rather than pushing them straight back out

965
00:48:35,573 --> 00:48:38,413
Speaker 4: into the community where there's too much risk around reoffending

966
00:48:38,533 --> 00:48:41,853
Speaker 4: and more victims. And there is some evidence.

967
00:48:41,573 --> 00:48:44,053
Speaker 18: Relates to he had some good comms assistant right there.

968
00:48:44,093 --> 00:48:46,172
Speaker 18: But I'll tell you what evident is that from what

969
00:48:46,253 --> 00:48:49,493
Speaker 18: I've seen, I came out with someone by the way,

970
00:48:49,573 --> 00:48:51,652
Speaker 18: for the family that have someone in there, you can

971
00:48:51,693 --> 00:48:54,533
Speaker 18: stand up and address the judge. Your boy just has

972
00:48:54,573 --> 00:48:56,692
Speaker 18: to tell the judge that they want that. So that's

973
00:48:56,693 --> 00:48:59,453
Speaker 18: called a section twenty seven cultural report. You can actually

974
00:48:59,533 --> 00:49:02,732
Speaker 18: do that verbally. So I advocated for someone, and yes

975
00:49:02,813 --> 00:49:05,373
Speaker 18: they did get a generous discount, this thing that this

976
00:49:05,453 --> 00:49:07,453
Speaker 18: government is putting a stop to, by the way and

977
00:49:07,453 --> 00:49:10,133
Speaker 18: capping at forty per So this young man got fifty

978
00:49:10,133 --> 00:49:12,692
Speaker 18: five percent, thanks in part for my advocating. And I'm

979
00:49:12,733 --> 00:49:15,173
Speaker 18: really glad I did that because he deserves better.

980
00:49:15,253 --> 00:49:16,893
Speaker 17: Yes he has, what a fact the thing?

981
00:49:17,293 --> 00:49:20,253
Speaker 2: But what about, say, the other part of prison Brunetta,

982
00:49:20,293 --> 00:49:22,692
Speaker 2: which is that you're getting but you're getting.

983
00:49:23,333 --> 00:49:26,173
Speaker 18: Let me finish about the rehabilitation, because I haven't answered

984
00:49:26,173 --> 00:49:29,573
Speaker 18: that question. Actually, So what I'm saying about mister Mitchell

985
00:49:29,653 --> 00:49:32,493
Speaker 18: saying that is that, So I asked the young man, ah,

986
00:49:32,613 --> 00:49:35,493
Speaker 18: so they're doing more rehabilitation now, you know in your

987
00:49:36,253 --> 00:49:38,933
Speaker 18: couple of years in there, and he's only twenty two,

988
00:49:39,533 --> 00:49:41,893
Speaker 18: so in your couple of years in there. Which programs

989
00:49:41,933 --> 00:49:42,253
Speaker 18: did you do?

990
00:49:42,693 --> 00:49:42,813
Speaker 16: Oh?

991
00:49:42,813 --> 00:49:45,933
Speaker 18: I got a couple of booklets. I mean I said, okay,

992
00:49:46,213 --> 00:49:48,413
Speaker 18: twenty two hours a day in your cell or twenty

993
00:49:48,453 --> 00:49:51,333
Speaker 18: three a lot of the time, Like this is inhumane,

994
00:49:51,373 --> 00:49:53,652
Speaker 18: and a chief ombudsman, Peter Boshier has.

995
00:49:53,573 --> 00:49:55,172
Speaker 4: Said that what what what crime did?

996
00:49:55,293 --> 00:49:58,692
Speaker 2: What crime did? What crime did? The what crime did

997
00:49:58,733 --> 00:50:00,172
Speaker 2: the twenty two year old commit?

998
00:50:01,293 --> 00:50:04,413
Speaker 18: Ah, he just did something stupid. Actually, this is something else.

999
00:50:04,653 --> 00:50:07,573
Speaker 18: He was with a group and it's probably pressure. He

1000
00:50:07,653 --> 00:50:11,053
Speaker 18: started to walk away, but his friends started attacking someone,

1001
00:50:11,133 --> 00:50:13,973
Speaker 18: you know, kicking them and stealing their wallets, something stupid.

1002
00:50:14,173 --> 00:50:16,933
Speaker 18: So this young man did something good and started walking

1003
00:50:16,933 --> 00:50:19,573
Speaker 18: away and touched that mate to say, come on, let's go. Now,

1004
00:50:19,613 --> 00:50:21,893
Speaker 18: what do you think happens to him if he just

1005
00:50:21,933 --> 00:50:24,413
Speaker 18: decides to walk away as he's part of a gang.

1006
00:50:24,653 --> 00:50:26,093
Speaker 18: So that's the other thing I want to say to

1007
00:50:26,133 --> 00:50:29,573
Speaker 18: the men in there, the gangs, especially, leave our young

1008
00:50:29,653 --> 00:50:32,172
Speaker 18: men alone. They don't need that life. What do we

1009
00:50:32,213 --> 00:50:34,333
Speaker 18: want more, Maori to keep on being gang members and

1010
00:50:34,493 --> 00:50:35,172
Speaker 18: hurting each other?

1011
00:50:35,493 --> 00:50:37,333
Speaker 2: Yeah, okay, well, thank you for your cal We've definitely

1012
00:50:37,333 --> 00:50:40,652
Speaker 2: given us a lot to the process there. Yeah, absolutely

1013
00:50:40,733 --> 00:50:41,853
Speaker 2: this is sening a lot. There was a bit of

1014
00:50:41,893 --> 00:50:45,733
Speaker 2: a shotgun machine gun attack there of words.

1015
00:50:45,813 --> 00:50:47,973
Speaker 4: Yeah, and you know, I think going back to the

1016
00:50:47,973 --> 00:50:50,813
Speaker 4: idea of rehabilitation and Brunetta mentioned there she had to

1017
00:50:50,813 --> 00:50:52,973
Speaker 4: go at the gangs. Of course, I mean, who wouldn't

1018
00:50:53,533 --> 00:50:56,533
Speaker 4: have a go at the gangs and what they they

1019
00:50:56,573 --> 00:50:59,413
Speaker 4: bring some of these young men into and accountability as

1020
00:50:59,413 --> 00:51:01,933
Speaker 4: she mentioned. But going back to rehabilitation, and that was

1021
00:51:01,973 --> 00:51:04,053
Speaker 4: what Mark Mitchell was talking about here.

1022
00:51:04,213 --> 00:51:07,893
Speaker 2: In this textas responding to Brunetta, congratulations and getting a

1023
00:51:07,893 --> 00:51:10,093
Speaker 2: criminal of fifty five percent discount, Did it make us

1024
00:51:10,133 --> 00:51:12,973
Speaker 2: crime fifty five percent less aggressive towards the victim? I

1025
00:51:13,013 --> 00:51:13,853
Speaker 2: don't think it would have.

1026
00:51:13,933 --> 00:51:16,933
Speaker 4: Yeah, good point. It is eighteen pasts two be free, surely.

1027
00:51:17,213 --> 00:51:19,652
Speaker 2: I'll tell you what. It is a complex issue and

1028
00:51:20,333 --> 00:51:22,253
Speaker 2: there's a lot of gray area there and there's a

1029
00:51:22,293 --> 00:51:24,253
Speaker 2: lot of passion from both sides and we love that.

1030
00:51:24,333 --> 00:51:27,853
Speaker 2: So nine ten nine two, eight hundred eighty ten.

1031
00:51:27,733 --> 00:51:33,533
Speaker 1: Eighty your home of Afternoon Talk, Matt Heathen, Taylor Adams

1032
00:51:33,693 --> 00:51:37,613
Speaker 1: Afternoons call eight hundred eighty ten eighty News Talk said, be.

1033
00:51:39,093 --> 00:51:42,693
Speaker 4: Curd afternoon. There's some great texts coming through on this idea.

1034
00:51:42,733 --> 00:51:46,773
Speaker 4: Of longer prison sentences to reduce the reoffending rate.

1035
00:51:47,173 --> 00:51:51,173
Speaker 2: Yeah, Matt and Tyler. Our judicial process replace indebtors. Sentencing

1036
00:51:51,213 --> 00:51:54,333
Speaker 2: needs to take into account the harm caused. No discounts

1037
00:51:54,333 --> 00:51:57,973
Speaker 2: from Lionel. Yeah, that's something that people forget, And I

1038
00:51:57,973 --> 00:52:00,493
Speaker 2: was trying to get to that point really that we

1039
00:52:00,693 --> 00:52:03,453
Speaker 2: in our society, if someone does something terrible to someone,

1040
00:52:03,733 --> 00:52:06,692
Speaker 2: then instead of us going out and taking that into

1041
00:52:06,773 --> 00:52:11,013
Speaker 2: our hands, we hand that power over to the government

1042
00:52:11,053 --> 00:52:13,413
Speaker 2: and the courts ye to dish that out. And if

1043
00:52:13,413 --> 00:52:16,453
Speaker 2: the government doesn't do that, then we can get into it,

1044
00:52:16,533 --> 00:52:18,613
Speaker 2: and we get into a society where people just take

1045
00:52:18,653 --> 00:52:21,813
Speaker 2: that into their own hands. Then that is anarchy, and

1046
00:52:21,853 --> 00:52:22,933
Speaker 2: that is a terrible society.

1047
00:52:23,013 --> 00:52:24,172
Speaker 4: Eye for an eye.

1048
00:52:23,853 --> 00:52:27,173
Speaker 2: So, you know, you may think it's magical thinking and

1049
00:52:27,693 --> 00:52:30,293
Speaker 2: the universe. We're thinking that the universe is out of

1050
00:52:30,373 --> 00:52:32,172
Speaker 2: kilter because someone's committed a crime and needs to get

1051
00:52:32,173 --> 00:52:35,333
Speaker 2: balanced by something happening to that person. But it's more

1052
00:52:35,333 --> 00:52:39,013
Speaker 2: than that. Society is held together by handing over violence

1053
00:52:39,253 --> 00:52:42,813
Speaker 2: to their government. And when I say violence, violence including

1054
00:52:43,453 --> 00:52:47,853
Speaker 2: taking someone's freedom off them. So it's a crucial part

1055
00:52:48,053 --> 00:52:50,692
Speaker 2: of us all agreeing to be part of the society.

1056
00:52:51,053 --> 00:52:54,013
Speaker 2: And if people start to think that something terrible has

1057
00:52:54,013 --> 00:52:59,013
Speaker 2: happened to their family and or themselves and there's no

1058
00:52:59,013 --> 00:53:01,292
Speaker 2: one going to help them at all, then that leads

1059
00:53:01,293 --> 00:53:03,213
Speaker 2: to people doing it themselves.

1060
00:53:03,253 --> 00:53:05,173
Speaker 4: Absolutely, and that's why we've all got a stake in

1061
00:53:05,213 --> 00:53:09,293
Speaker 4: this debate, as Mark Mitchell investigates, with a longer sentences

1062
00:53:09,573 --> 00:53:11,652
Speaker 4: would be better for us as a society and the

1063
00:53:11,733 --> 00:53:13,973
Speaker 4: justice system. It's something we should all care deeply about.

1064
00:53:14,373 --> 00:53:17,013
Speaker 2: Kevin says crimea river bleeding heart should be kept away

1065
00:53:17,693 --> 00:53:20,733
Speaker 2: from any decision making. She can't help, but she should

1066
00:53:20,773 --> 00:53:23,613
Speaker 2: not be given any say so at all. Something stupid,

1067
00:53:23,693 --> 00:53:27,453
Speaker 2: Whereas this woman coming from obviously she thinks some of

1068
00:53:27,453 --> 00:53:30,613
Speaker 2: these murders are just Kevin's very angry about it.

1069
00:53:30,693 --> 00:53:32,893
Speaker 4: Yeah, I mean that is a.

1070
00:53:32,613 --> 00:53:37,933
Speaker 2: Really really good point around your emotions being a big

1071
00:53:37,973 --> 00:53:42,133
Speaker 2: part of the legal system. The legal system should be emotionless,

1072
00:53:42,573 --> 00:53:45,213
Speaker 2: you would hope to a certain extent. They've had these

1073
00:53:45,933 --> 00:53:51,013
Speaker 2: studies that they've done where parole has been decided without

1074
00:53:51,093 --> 00:53:53,373
Speaker 2: talking to the person, just purely on the facts, as

1075
00:53:53,373 --> 00:53:57,013
Speaker 2: opposed to parole when you meet the person, and the

1076
00:53:57,133 --> 00:54:02,533
Speaker 2: reoffending is much less when emotions and emotional manipulation aren't

1077
00:54:02,533 --> 00:54:05,093
Speaker 2: brought into decision making.

1078
00:54:05,613 --> 00:54:07,053
Speaker 4: I've got to say it. I didn't mention this, but

1079
00:54:07,093 --> 00:54:09,373
Speaker 4: I actually set in a para hearing down in christ

1080
00:54:09,453 --> 00:54:12,933
Speaker 4: Church Prison and there were three prisoners that were before

1081
00:54:12,973 --> 00:54:14,693
Speaker 4: the prole board and they were there for some pretty

1082
00:54:14,733 --> 00:54:19,133
Speaker 4: heenous crimes. But the reaction from the panel it would

1083
00:54:19,133 --> 00:54:24,573
Speaker 4: be best described as cult emotionless. There was no I mean,

1084
00:54:24,573 --> 00:54:28,733
Speaker 4: it was very slow and deliberate. The prisoners tried to

1085
00:54:28,933 --> 00:54:31,533
Speaker 4: make the best argument they could on why they should

1086
00:54:31,573 --> 00:54:34,093
Speaker 4: be paroled. But I've got to say, you know, there

1087
00:54:34,213 --> 00:54:36,853
Speaker 4: was the there was zero emotion from the panel in

1088
00:54:36,853 --> 00:54:37,133
Speaker 4: front of.

1089
00:54:37,093 --> 00:54:39,333
Speaker 2: Them, zero motions shown. But that doesn't mean that the

1090
00:54:39,453 --> 00:54:44,893
Speaker 2: zero empathy getting inside. Yeah, you're decision making, and when

1091
00:54:44,893 --> 00:54:47,853
Speaker 2: you see a person and you hear them tell their story,

1092
00:54:47,933 --> 00:54:51,613
Speaker 2: you know, all humans are going to tend to give them,

1093
00:54:51,893 --> 00:54:56,693
Speaker 2: you know, more time then just some numbers on a

1094
00:54:56,693 --> 00:55:01,333
Speaker 2: paper or some stats or just crimes described and what

1095
00:55:01,333 --> 00:55:03,773
Speaker 2: they've done in prison, you know, described in text.

1096
00:55:03,653 --> 00:55:05,933
Speaker 4: That is true. Yeah, yeah, oh, one hundred and eighteen

1097
00:55:05,933 --> 00:55:08,133
Speaker 4: eighty is the number to call. It is twenty four

1098
00:55:08,133 --> 00:55:10,573
Speaker 4: p us to back very shortly here on New Still.

1099
00:55:10,413 --> 00:55:17,533
Speaker 2: CB and we'll talk to Lee who's spent seventeen years inside.

1100
00:55:18,693 --> 00:55:22,133
Speaker 1: Matt Heathen Tyler Adams afternoons call oh eight hundred and

1101
00:55:22,133 --> 00:55:24,293
Speaker 1: eighty ten eighty on Youth Talk ZB.

1102
00:55:24,453 --> 00:55:28,613
Speaker 4: News Talk Zi B. Lee. You had seventeen years in prison.

1103
00:55:30,133 --> 00:55:35,093
Speaker 12: Yes, I committed a crime, a Heeneus crime. I was

1104
00:55:35,133 --> 00:55:38,213
Speaker 12: summoned to eleven and a half years. I ended up

1105
00:55:38,253 --> 00:55:43,093
Speaker 12: doing just under eighteen. Took me that long to get out.

1106
00:55:43,253 --> 00:55:48,772
Speaker 12: I'm deeply, deeply ashamed and felt a lot he built

1107
00:55:48,773 --> 00:55:51,773
Speaker 12: around what I did. But moving on from that, when

1108
00:55:51,813 --> 00:55:54,893
Speaker 12: I first went to prison, there was a lot of

1109
00:55:55,053 --> 00:55:56,893
Speaker 12: There was a lot of programs. I think, I think

1110
00:55:56,933 --> 00:56:01,293
Speaker 12: for me, when people talk about rehabilitation nowadays, these you know,

1111
00:56:01,413 --> 00:56:05,053
Speaker 12: people think that they're talking about programs, do this program

1112
00:56:05,093 --> 00:56:09,453
Speaker 12: to that program. I think what what I saw was

1113
00:56:09,493 --> 00:56:11,413
Speaker 12: when I first went to prison, you were unlocked eight

1114
00:56:11,453 --> 00:56:14,813
Speaker 12: to ten hours a day. You had access to work,

1115
00:56:15,093 --> 00:56:22,093
Speaker 12: you had access to woodshopped engineering, charming. People could do

1116
00:56:22,493 --> 00:56:28,453
Speaker 12: like NCAA programs and re educate themselves. When I left,

1117
00:56:28,853 --> 00:56:31,413
Speaker 12: and even now when I still write letters to people

1118
00:56:31,453 --> 00:56:34,373
Speaker 12: that are still in there, they're locked down for twenty

1119
00:56:34,373 --> 00:56:36,053
Speaker 12: two to twenty three hours a day. You can do

1120
00:56:36,893 --> 00:56:40,653
Speaker 12: you can you do three quarters of your sentence locked

1121
00:56:40,653 --> 00:56:42,933
Speaker 12: in a room for twenty two to twenty three hours

1122
00:56:42,933 --> 00:56:46,413
Speaker 12: a day, and then in the last quarter of your

1123
00:56:46,453 --> 00:56:49,692
Speaker 12: sentence you go to a program and then you get

1124
00:56:49,733 --> 00:56:52,933
Speaker 12: released and people are angry. You can't lock a person

1125
00:56:52,973 --> 00:56:54,732
Speaker 12: down for twenty two too, you into three hours a day.

1126
00:56:55,853 --> 00:56:56,813
Speaker 12: I have been.

1127
00:56:57,093 --> 00:57:00,333
Speaker 2: Why have they why have they started? You know why

1128
00:57:00,413 --> 00:57:01,333
Speaker 2: they change? Do you think?

1129
00:57:01,453 --> 00:57:01,493
Speaker 11: Ly?

1130
00:57:02,893 --> 00:57:07,053
Speaker 12: The initial? The initial? The initial reasons so every time

1131
00:57:07,093 --> 00:57:08,933
Speaker 12: every time they take something away, you ever get it back.

1132
00:57:09,093 --> 00:57:12,213
Speaker 12: So the initial was staff numbers, then it became COVID,

1133
00:57:12,373 --> 00:57:17,653
Speaker 12: then it became budget. Judith Collins was Judith Collins was

1134
00:57:18,253 --> 00:57:21,973
Speaker 12: when she was the minister. She basically was the change

1135
00:57:22,933 --> 00:57:25,493
Speaker 12: everything she implemented. There was actually a time when Judith

1136
00:57:25,493 --> 00:57:31,453
Speaker 12: Collins came in and it was a very big time

1137
00:57:31,493 --> 00:57:35,053
Speaker 12: for inmates. It was that was that was basically it

1138
00:57:35,173 --> 00:57:38,533
Speaker 12: was going to go through like a starlug conditions. That's

1139
00:57:38,573 --> 00:57:42,213
Speaker 12: that's how we on the inside saw it. She pulled back.

1140
00:57:42,613 --> 00:57:46,413
Speaker 12: They ended up getting voted out, but it was it

1141
00:57:46,453 --> 00:57:50,093
Speaker 12: was If she had stayed in, you would have got

1142
00:57:50,133 --> 00:57:53,293
Speaker 12: a very very angry inmate. She would have created a

1143
00:57:53,493 --> 00:57:54,413
Speaker 12: very angry inmate.

1144
00:57:54,613 --> 00:57:58,373
Speaker 2: Now Lee. You say that you were in prison and

1145
00:57:58,493 --> 00:58:01,973
Speaker 2: you feel deeply remorseful for the crime you commit. Do

1146
00:58:02,013 --> 00:58:05,173
Speaker 2: you think that part of or what part of your

1147
00:58:05,653 --> 00:58:11,173
Speaker 2: sentence was, know you being punished for what?

1148
00:58:11,173 --> 00:58:11,453
Speaker 6: What?

1149
00:58:11,453 --> 00:58:13,533
Speaker 2: What? What? What you did? And do you think that

1150
00:58:13,613 --> 00:58:16,853
Speaker 2: you you're that punishment as has helped you to be

1151
00:58:16,853 --> 00:58:18,453
Speaker 2: able to deal with your remorse in any way?

1152
00:58:19,933 --> 00:58:23,173
Speaker 12: No, No, I think to a certain extent, I needed

1153
00:58:23,173 --> 00:58:26,333
Speaker 12: the punishment. I appreciate that the punishment was available to

1154
00:58:26,453 --> 00:58:32,333
Speaker 12: me because I needed that time to reflect, learn and grow.

1155
00:58:32,973 --> 00:58:37,253
Speaker 12: But also at the same time, I would have appreciated

1156
00:58:37,573 --> 00:58:45,933
Speaker 12: if I had had access to educational programs, just just

1157
00:58:46,053 --> 00:58:49,693
Speaker 12: work skills, just being able to I mean as simple

1158
00:58:49,693 --> 00:58:54,413
Speaker 12: things like learning getting a driver's license, a driver's license

1159
00:58:54,413 --> 00:58:57,253
Speaker 12: and things like that. Just a lot of people go

1160
00:58:57,333 --> 00:59:00,493
Speaker 12: in there. There is no n c A there, there is.

1161
00:59:01,053 --> 00:59:02,933
Speaker 12: I came from the schools here. You don't get out

1162
00:59:02,933 --> 00:59:04,253
Speaker 12: of the school. See you get out with the NCAA

1163
00:59:04,373 --> 00:59:05,493
Speaker 12: Level one, level two and that's it.

1164
00:59:06,293 --> 00:59:08,493
Speaker 2: So how long and were you in prison before for

1165
00:59:08,853 --> 00:59:13,533
Speaker 2: you starters, you know, taking up opportunities in prison for

1166
00:59:13,853 --> 00:59:15,333
Speaker 2: for you know, work.

1167
00:59:15,373 --> 00:59:18,613
Speaker 12: And I tried to, tried to, I tried to straight

1168
00:59:18,653 --> 00:59:22,013
Speaker 12: away I tried to straight away, and for the first

1169
00:59:22,813 --> 00:59:25,573
Speaker 12: seven to eight years I was denied anything because I

1170
00:59:25,613 --> 00:59:28,293
Speaker 12: was told, you're doing too long. You'll pick up something

1171
00:59:28,413 --> 00:59:30,533
Speaker 12: towards the end of your course, towards the end of

1172
00:59:30,573 --> 00:59:34,613
Speaker 12: your sentence. At the moment, we can't offer you anything.

1173
00:59:34,653 --> 00:59:36,453
Speaker 12: We can't give you anything. And then it was just

1174
00:59:36,573 --> 00:59:41,013
Speaker 12: share determination. Every time I saw somebody leave to go

1175
00:59:41,093 --> 00:59:44,253
Speaker 12: to a program or something, I'd run over and hustle

1176
00:59:44,293 --> 00:59:46,093
Speaker 12: and hustle and hustle until I could. And they just

1177
00:59:46,133 --> 00:59:48,173
Speaker 12: got sick of me nagging them and started putting me

1178
00:59:48,213 --> 00:59:50,933
Speaker 12: on things. But if I'd left it to the allocation

1179
00:59:51,013 --> 00:59:52,813
Speaker 12: of my case managers, I would have I would have

1180
00:59:52,813 --> 00:59:54,653
Speaker 12: got nothing until the last two to three years.

1181
00:59:55,333 --> 00:59:56,133
Speaker 4: How are you doing? Ali?

1182
00:59:58,653 --> 01:00:02,573
Speaker 12: Coming out into from a paper society into a digital

1183
01:00:02,613 --> 01:00:04,973
Speaker 12: society was an absolute struggle.

1184
01:00:05,053 --> 01:00:05,293
Speaker 2: Wow.

1185
01:00:06,213 --> 01:00:09,293
Speaker 12: They talked about higher situations and they say to you, oh,

1186
01:00:09,293 --> 01:00:12,093
Speaker 12: the higher situation you're going to encounter is running so

1187
01:00:12,093 --> 01:00:16,733
Speaker 12: old associates or drunk drunk drinking and alcohol and drugs.

1188
01:00:16,813 --> 01:00:20,053
Speaker 12: And it was moving from a paper society to a

1189
01:00:20,093 --> 01:00:25,133
Speaker 12: digital society. And the other one was was no money

1190
01:00:25,173 --> 01:00:29,773
Speaker 12: and no support. They created this verbal market. You have

1191
01:00:29,853 --> 01:00:31,893
Speaker 12: all these people. They say, oh, this business.

1192
01:00:31,613 --> 01:00:32,773
Speaker 13: Program is that program?

1193
01:00:33,093 --> 01:00:38,133
Speaker 12: My partner at the moment, she's in corporate, and we've

1194
01:00:38,133 --> 01:00:40,573
Speaker 12: actually had arguments. We sh oh, my best friend does this,

1195
01:00:40,653 --> 01:00:42,253
Speaker 12: and my best friend does that, and they've created this

1196
01:00:42,333 --> 01:00:44,573
Speaker 12: and they've created that. And now she's even got to

1197
01:00:44,613 --> 01:00:50,133
Speaker 12: realize that it's very paper focus, very front focused. They

1198
01:00:50,213 --> 01:00:53,093
Speaker 12: are offering help, they are offering assistance, but there's actually

1199
01:00:53,453 --> 01:00:56,573
Speaker 12: nobody doing the programs that they've got. There's nobody in

1200
01:00:56,693 --> 01:00:58,693
Speaker 12: the programs that they've implemented. They might have one or

1201
01:00:58,733 --> 01:01:01,053
Speaker 12: two people and a budget of one hundred thousand dollars,

1202
01:01:01,093 --> 01:01:02,613
Speaker 12: but nobody's actually getting help from them.

1203
01:01:03,493 --> 01:01:07,173
Speaker 2: Now, Lee, what crime did you commit? And you think

1204
01:01:07,253 --> 01:01:10,133
Speaker 2: the sentence you got was fear for the crime you committed.

1205
01:01:13,293 --> 01:01:16,373
Speaker 12: I committed a murder, and at the first parole board hearing,

1206
01:01:16,493 --> 01:01:20,293
Speaker 12: I asked for a three years stand down. I didn't

1207
01:01:20,333 --> 01:01:21,893
Speaker 12: want to be released. I wanted to stay in there.

1208
01:01:22,813 --> 01:01:25,493
Speaker 12: My mindset was was I'd stay in there. Now my

1209
01:01:25,653 --> 01:01:30,093
Speaker 12: mindset was was I shouldn't be released. I didn't deserve

1210
01:01:30,133 --> 01:01:32,133
Speaker 12: to be realist, And how do.

1211
01:01:32,173 --> 01:01:35,693
Speaker 2: You feel about that now that you've you've spent seventeen

1212
01:01:35,773 --> 01:01:36,413
Speaker 2: years in prison?

1213
01:01:37,693 --> 01:01:40,053
Speaker 12: I still struggle with every day. It was the prole board.

1214
01:01:40,533 --> 01:01:42,333
Speaker 12: It was the problem. The proboard stood me down for

1215
01:01:42,413 --> 01:01:42,853
Speaker 12: two years.

1216
01:01:42,973 --> 01:01:43,693
Speaker 3: And for me.

1217
01:01:45,453 --> 01:01:52,893
Speaker 12: That the way that I was I the way that

1218
01:01:53,013 --> 01:01:58,573
Speaker 12: I was perceiving my offense, I need to I need

1219
01:01:58,653 --> 01:02:01,253
Speaker 12: to honor the victim by trying to get back, by

1220
01:02:02,373 --> 01:02:04,133
Speaker 12: by sitting in the soul and doing nothing for the

1221
01:02:04,173 --> 01:02:06,013
Speaker 12: rest of my life. Wasn't honoring the person's life that

1222
01:02:06,093 --> 01:02:06,493
Speaker 12: I'd taken.

1223
01:02:08,813 --> 01:02:14,733
Speaker 2: Okay, Well, it's and do you think when do you

1224
01:02:14,773 --> 01:02:18,493
Speaker 2: think you're in danger of reoffending in that time that

1225
01:02:18,573 --> 01:02:18,973
Speaker 2: you were in.

1226
01:02:22,613 --> 01:02:28,093
Speaker 12: I wasn't in danger of reoffending. But I definitely it's

1227
01:02:28,133 --> 01:02:31,093
Speaker 12: a good place to grow up. It's a good place

1228
01:02:31,253 --> 01:02:35,853
Speaker 12: to self evaluate, and it's a it's a good place

1229
01:02:35,893 --> 01:02:37,693
Speaker 12: to reflect, and it's a good place to learn. I

1230
01:02:37,853 --> 01:02:41,773
Speaker 12: hear people talk about the gang problem and the recruitment

1231
01:02:41,973 --> 01:02:45,693
Speaker 12: in prison. I can tell you one thing about that

1232
01:02:46,533 --> 01:02:50,373
Speaker 12: is when you're in there, a lot of the people

1233
01:02:50,413 --> 01:02:52,973
Speaker 12: that get recruited they're not the okay, so they're getting

1234
01:02:52,973 --> 01:02:55,533
Speaker 12: recruited by gangs. What they're actually getting recruited by is

1235
01:02:55,773 --> 01:02:58,213
Speaker 12: the first male role model that they ever come across

1236
01:02:58,293 --> 01:03:01,533
Speaker 12: in their entire life. And you might say, oh, there's

1237
01:03:01,533 --> 01:03:06,133
Speaker 12: a gang memory business. Okay, So I had young men

1238
01:03:06,293 --> 01:03:09,333
Speaker 12: that would come and clean my cell in the They

1239
01:03:09,373 --> 01:03:12,413
Speaker 12: would do my dishes, they would sweep my floor, they

1240
01:03:12,453 --> 01:03:14,973
Speaker 12: would do this, they would do that. They it was

1241
01:03:15,013 --> 01:03:16,573
Speaker 12: the first time they've ever had structure. It was the

1242
01:03:16,613 --> 01:03:18,853
Speaker 12: first time they've ever had discipline. They come out of

1243
01:03:18,853 --> 01:03:21,493
Speaker 12: the yards, they train with us, they would you know,

1244
01:03:22,133 --> 01:03:23,693
Speaker 12: it's the first time they'd ever had it in their

1245
01:03:23,813 --> 01:03:28,133
Speaker 12: entire lives. They felt a sense of belonging. And yes, okay,

1246
01:03:28,253 --> 01:03:31,613
Speaker 12: so it's a gang environment. If you put those young boys,

1247
01:03:31,973 --> 01:03:33,973
Speaker 12: this is this is this is the argument for boot camps.

1248
01:03:33,973 --> 01:03:36,373
Speaker 12: If you put those young boys into a boot camp situation,

1249
01:03:37,293 --> 01:03:39,533
Speaker 12: they would it would be exactly the same. They would

1250
01:03:39,573 --> 01:03:42,133
Speaker 12: all become army officers. Every single one of them would

1251
01:03:42,133 --> 01:03:43,053
Speaker 12: become an army officer.

1252
01:03:43,293 --> 01:03:44,973
Speaker 2: Well, thank you so much for your call, Lee and

1253
01:03:45,013 --> 01:03:46,053
Speaker 2: sharing your story.

1254
01:03:46,173 --> 01:03:49,373
Speaker 4: Absolutely very much on, very full on, and thank you

1255
01:03:49,413 --> 01:03:52,573
Speaker 4: to everybody phoned antiques on that one. Headlines coming up.

1256
01:03:52,613 --> 01:03:54,933
Speaker 4: Then we have got a new topic on the table

1257
01:03:54,973 --> 01:03:56,373
Speaker 4: and there's twenty five to three.

1258
01:03:59,093 --> 01:04:03,333
Speaker 14: You talk headlines with blue bubble taxings, it's no trouble

1259
01:04:03,413 --> 01:04:07,093
Speaker 14: with a blue bubble Northland MP Grant and McCallum says

1260
01:04:07,173 --> 01:04:10,733
Speaker 14: tackling regional meth the issues won't be a quick fix

1261
01:04:10,973 --> 01:04:15,053
Speaker 14: and requires the community to support efforts. Napui leader Mane

1262
01:04:15,213 --> 01:04:19,653
Speaker 14: Tahe is asking police to do more drug raids. Retail

1263
01:04:19,773 --> 01:04:23,333
Speaker 14: ends says retailers need to report all crime after a

1264
01:04:23,453 --> 01:04:27,413
Speaker 14: survey showed rising levels. About forty percent of crime and

1265
01:04:27,493 --> 01:04:32,453
Speaker 14: anti social behavior goes unreported. Fire and Emergency says it's

1266
01:04:32,533 --> 01:04:37,693
Speaker 14: scrutinizing an Employment Relations Authority decision about a firefighter who

1267
01:04:37,853 --> 01:04:42,173
Speaker 14: pulled colleagues allowances to get shared meals. The authority found

1268
01:04:42,253 --> 01:04:47,173
Speaker 14: it unlawfully accessed his bank account. A person seriously injured

1269
01:04:47,173 --> 01:04:49,893
Speaker 14: after a single vehicle crash on Blockhouse Bay Road in

1270
01:04:50,013 --> 01:04:55,733
Speaker 14: Auckland's Avondale. Beef cattle are the standout among reducing livestock

1271
01:04:55,813 --> 01:04:59,973
Speaker 14: populations over the past decade. In other data, our grasslands

1272
01:05:00,013 --> 01:05:03,373
Speaker 14: reduced eight hundred and nine thousand hectares and Kiwi fruit

1273
01:05:03,453 --> 01:05:07,653
Speaker 14: areas grew by three and a half thousand hectares. Two

1274
01:05:07,733 --> 01:05:11,573
Speaker 14: more Hawks farm sold to overseas buyer for forestry. You

1275
01:05:11,653 --> 01:05:14,133
Speaker 14: can see the story at n Said Herald Premium. Now

1276
01:05:14,213 --> 01:05:15,853
Speaker 14: back to matt Ethan Tyler Adams.

1277
01:05:15,973 --> 01:05:18,333
Speaker 4: Thank you very much, ray Lean, and we're changing tach

1278
01:05:18,413 --> 01:05:20,733
Speaker 4: over the next hour or so. We want to talk

1279
01:05:20,733 --> 01:05:21,893
Speaker 4: about AI in schools.

1280
01:05:21,973 --> 01:05:23,973
Speaker 2: Yes, actually quite surprised after the ear and half we

1281
01:05:24,053 --> 01:05:28,173
Speaker 2: didn't solve the situation with rehabilitation.

1282
01:05:28,293 --> 01:05:30,173
Speaker 4: Surprise, isn't it. You know, I already thought we'd nail

1283
01:05:30,173 --> 01:05:31,093
Speaker 4: it in ninety minutes, but.

1284
01:05:31,573 --> 01:05:33,013
Speaker 2: I backed myself to get to the bottom of it.

1285
01:05:33,413 --> 01:05:36,893
Speaker 4: It certainly was full on, absolutely, so thank you to

1286
01:05:36,893 --> 01:05:39,373
Speaker 4: everybody who phoned and text on that one. But let's

1287
01:05:39,413 --> 01:05:41,773
Speaker 4: chat about AI in school. So the Ministry of Education

1288
01:05:41,893 --> 01:05:46,493
Speaker 4: said AI poses significant challenges for a school, so the

1289
01:05:46,613 --> 01:05:49,373
Speaker 4: technology is currently governed by each school's board, while the

1290
01:05:49,413 --> 01:05:52,653
Speaker 4: Ministry encourages school to develop a policy. So there is

1291
01:05:52,733 --> 01:05:56,013
Speaker 4: some inconsistency there with the way that AI is utilized

1292
01:05:56,053 --> 01:05:59,013
Speaker 4: within schools and a self reported serve A sixty percent

1293
01:05:59,173 --> 01:06:04,053
Speaker 4: of students reported using that AI to assist them with schoolwork.

1294
01:06:04,413 --> 01:06:05,933
Speaker 4: And it is a big question and it's not just

1295
01:06:06,053 --> 01:06:08,613
Speaker 4: the students using AI, it is the school and the

1296
01:06:08,693 --> 01:06:09,613
Speaker 4: teachers themselves.

1297
01:06:10,373 --> 01:06:12,933
Speaker 2: Yeah, so are your kids using AI to do their

1298
01:06:12,973 --> 01:06:14,813
Speaker 2: homework at school? And what do you think about this?

1299
01:06:14,973 --> 01:06:18,413
Speaker 2: And what do you think about AI? Marking papers, because

1300
01:06:18,493 --> 01:06:20,773
Speaker 2: that's what's happening now, and that's going to happen more.

1301
01:06:21,053 --> 01:06:24,653
Speaker 2: Do you want teachers spending their time carefully marking papers

1302
01:06:25,733 --> 01:06:27,533
Speaker 2: if AI can free them up to do other things?

1303
01:06:27,573 --> 01:06:28,813
Speaker 2: Do you think that's a good thing? Or do you

1304
01:06:28,893 --> 01:06:31,773
Speaker 2: find it kind of creepy that your kid's paper just

1305
01:06:31,853 --> 01:06:35,213
Speaker 2: gets shoved through AI and then a mark comes out

1306
01:06:35,253 --> 01:06:38,213
Speaker 2: the other side. At the moment there it's being overseen

1307
01:06:38,293 --> 01:06:40,693
Speaker 2: by humans. But you can see the time in the future,

1308
01:06:41,093 --> 01:06:44,853
Speaker 2: I mean absolutely, with you know, a maths exam or

1309
01:06:44,853 --> 01:06:47,093
Speaker 2: a math test, right, some of those some of those

1310
01:06:47,133 --> 01:06:50,573
Speaker 2: answers are just objective. Yes, But if it's an English paper,

1311
01:06:51,253 --> 01:06:54,733
Speaker 2: then would you trust AI to read it and see

1312
01:06:54,813 --> 01:06:58,613
Speaker 2: the and see you know, what you're trying to get at?

1313
01:06:59,173 --> 01:07:01,653
Speaker 2: I mean? And then how do you feel about AI

1314
01:07:01,893 --> 01:07:05,853
Speaker 2: training itself? Because AI models, you know, they're large language

1315
01:07:05,893 --> 01:07:08,893
Speaker 2: learning models, so everything that goes in they used to learn.

1316
01:07:09,013 --> 01:07:12,973
Speaker 2: So how do you feel about your kids work being

1317
01:07:13,333 --> 01:07:15,693
Speaker 2: used to train AI models?

1318
01:07:15,773 --> 01:07:15,973
Speaker 4: Yeah?

1319
01:07:16,053 --> 01:07:17,213
Speaker 2: I mean it's an interesting one.

1320
01:07:17,373 --> 01:07:21,053
Speaker 4: Marking critical thinking, Like if you're writing about an essay

1321
01:07:21,053 --> 01:07:23,733
Speaker 4: as you say English, that to me is crazy using

1322
01:07:23,813 --> 01:07:25,933
Speaker 4: AI to try and mark that stuff. That's where it

1323
01:07:26,013 --> 01:07:27,653
Speaker 4: needs human nuance and understanding.

1324
01:07:27,733 --> 01:07:30,413
Speaker 2: But what about a simple situation where you've got a

1325
01:07:31,213 --> 01:07:34,373
Speaker 2: You've got a teacher that's having to read this incredibly long,

1326
01:07:34,613 --> 01:07:38,253
Speaker 2: boring load of rubbish from a student that is trying

1327
01:07:38,293 --> 01:07:43,133
Speaker 2: to trick you with flowery writing, and then AI just goes,

1328
01:07:43,173 --> 01:07:44,973
Speaker 2: what are you know? You Sai? What are the ten

1329
01:07:45,013 --> 01:07:47,973
Speaker 2: bullet points in here? And it goes bomb boom boom,

1330
01:07:47,973 --> 01:07:49,893
Speaker 2: and you go, okay, well, I think they ticked off

1331
01:07:50,093 --> 01:07:52,613
Speaker 2: the key things. Because that's what people don't understand about

1332
01:07:52,653 --> 01:07:56,093
Speaker 2: marking is that teachers, and this is what I told

1333
01:07:56,133 --> 01:07:58,733
Speaker 2: my kids, when they go into exams, they're looking for

1334
01:07:59,173 --> 01:08:01,733
Speaker 2: things that they can tack off to give your mark, right,

1335
01:08:01,853 --> 01:08:04,093
Speaker 2: So your your piece of writing has to have the

1336
01:08:04,213 --> 01:08:06,653
Speaker 2: things in it to tack off. So they go through

1337
01:08:06,733 --> 01:08:08,533
Speaker 2: and they read it and go, yep, got that one point,

1338
01:08:08,573 --> 01:08:10,773
Speaker 2: got that one, got on that, And that's how they

1339
01:08:10,813 --> 01:08:15,533
Speaker 2: work at your score. So it's it's regimented already largely.

1340
01:08:16,213 --> 01:08:19,253
Speaker 2: And if you're really clever at doing exams, you'll you'll

1341
01:08:19,653 --> 01:08:22,173
Speaker 2: you'll spend the time to find out what it is

1342
01:08:22,532 --> 01:08:25,532
Speaker 2: needed to get the marks and you'll put that in

1343
01:08:25,652 --> 01:08:26,333
Speaker 2: whatever you write.

1344
01:08:26,532 --> 01:08:29,372
Speaker 4: Yeah, I still think you need that teacher's I across it,

1345
01:08:29,452 --> 01:08:31,452
Speaker 4: whether you run it through they run it through AI

1346
01:08:31,612 --> 01:08:33,932
Speaker 4: initially and then have a look at it to make

1347
01:08:33,973 --> 01:08:37,333
Speaker 4: sure AI has corrarecked it. But that defeats the purpose, right,

1348
01:08:37,612 --> 01:08:40,132
Speaker 4: But if you're having to double check AI's marking ability.

1349
01:08:40,492 --> 01:08:43,612
Speaker 2: Yeah, well but okay, so just AI and schools in general,

1350
01:08:43,772 --> 01:08:46,852
Speaker 2: I personally think it'd be crazy if that's the world

1351
01:08:46,893 --> 01:08:49,452
Speaker 2: that kids are entering, Right, They're entering a world where

1352
01:08:49,492 --> 01:08:52,333
Speaker 2: people are going to use AIS at all. I mean,

1353
01:08:52,372 --> 01:08:55,412
Speaker 2: they might be entering a world where AI completely replaces them,

1354
01:08:55,973 --> 01:08:58,293
Speaker 2: but they're definitely entering a world where AI is going

1355
01:08:58,372 --> 01:09:00,532
Speaker 2: to be a big part of their lives. So it's

1356
01:09:01,013 --> 01:09:04,092
Speaker 2: crazy if schools don't lean in it to a certain extent.

1357
01:09:05,133 --> 01:09:08,253
Speaker 2: The elephant in the room being detecting whether aware a

1358
01:09:08,412 --> 01:09:10,213
Speaker 2: kid has just got AI to do all their work

1359
01:09:10,293 --> 01:09:10,532
Speaker 2: for them.

1360
01:09:10,692 --> 01:09:13,053
Speaker 4: Yeah, but what about the picking up of skills? I

1361
01:09:13,133 --> 01:09:15,812
Speaker 4: mean as AI is that doing a disservice maybe to

1362
01:09:15,893 --> 01:09:18,612
Speaker 4: some children if they are primarily using AI to get

1363
01:09:18,692 --> 01:09:22,413
Speaker 4: answers to questions without figuring out that problem for themselves.

1364
01:09:23,492 --> 01:09:26,053
Speaker 2: Well, yeah, that is the thing as well in terms

1365
01:09:26,093 --> 01:09:29,973
Speaker 2: of critical thinking. If you you know, if you are

1366
01:09:30,293 --> 01:09:33,052
Speaker 2: always using AI as a crutch. Do you never develop

1367
01:09:33,133 --> 01:09:36,933
Speaker 2: the skills? You know, brain just turned to mush and

1368
01:09:37,532 --> 01:09:40,892
Speaker 2: you know, like someone that's always in bed and isn't

1369
01:09:40,893 --> 01:09:42,972
Speaker 2: walking around, their legs quickly stopped working.

1370
01:09:43,133 --> 01:09:45,333
Speaker 4: Yeah, I mean it is everywhere. Just on the weekend

1371
01:09:45,412 --> 01:09:46,852
Speaker 4: and it was a family member. They were over in

1372
01:09:46,893 --> 01:09:49,572
Speaker 4: Melbourne and they saw a whole bunch of people marching

1373
01:09:49,732 --> 01:09:51,772
Speaker 4: and everybody in the family chat said what are they doing?

1374
01:09:51,812 --> 01:09:54,213
Speaker 4: And they just sent back a weee screenshot of chat

1375
01:09:54,293 --> 01:09:57,012
Speaker 4: GPT saying what the march was about. I thought, okay,

1376
01:09:57,093 --> 01:09:59,412
Speaker 4: that's kind of way we got to now AI Chat

1377
01:09:59,452 --> 01:10:01,052
Speaker 4: GPT is just the new Googles.

1378
01:10:01,293 --> 01:10:03,173
Speaker 2: Well one hundred and eighteen eighty. I'd love to hear

1379
01:10:03,253 --> 01:10:06,652
Speaker 2: from teachers on this and students on that's possible to

1380
01:10:06,732 --> 01:10:10,772
Speaker 2: hear student maybe there's one that's where today or as

1381
01:10:10,853 --> 01:10:14,452
Speaker 2: I sick or something, or someone that's recently left school,

1382
01:10:14,893 --> 01:10:19,572
Speaker 2: how much AI is being used and how much AI

1383
01:10:20,013 --> 01:10:21,053
Speaker 2: they think should be used.

1384
01:10:21,133 --> 01:10:23,133
Speaker 4: Yeah, love to hear from you. Oh, eight hundred eighty

1385
01:10:23,173 --> 01:10:25,653
Speaker 4: ten eighty is the number to call. It is sixteen

1386
01:10:25,732 --> 01:10:29,053
Speaker 4: to three back three shortly here listening to Matt and Tyler.

1387
01:10:30,853 --> 01:10:34,973
Speaker 1: Your home of afternoon talk Mad Heathen Tyler Adams afternoons

1388
01:10:35,253 --> 01:10:37,972
Speaker 1: call Oh eight hundred eighty ten eighty US talk.

1389
01:10:37,893 --> 01:10:42,732
Speaker 4: ZEDB News Talks THEREB. We're talking about AI in schools.

1390
01:10:43,173 --> 01:10:46,612
Speaker 4: Up to sixty percent of students are using AI to

1391
01:10:46,692 --> 01:10:49,052
Speaker 4: assist them with schoolwork. But it's not just the students,

1392
01:10:49,532 --> 01:10:52,253
Speaker 4: the teachers are using it as well. Love to hear

1393
01:10:52,333 --> 01:10:55,133
Speaker 4: your thoughts. How do you feel about teachers using AI

1394
01:10:55,253 --> 01:10:57,173
Speaker 4: to mark your children's work? Oh, eight hundred and eighty

1395
01:10:57,293 --> 01:11:00,173
Speaker 4: ten eighty And is there a place for students to

1396
01:11:00,253 --> 01:11:04,252
Speaker 4: be utilizing that technology in order to complete their studies?

1397
01:11:04,772 --> 01:11:07,492
Speaker 4: Nine two ninety two is the text number as well

1398
01:11:07,532 --> 01:11:10,732
Speaker 4: if you want to send a tech Andrew, you want

1399
01:11:10,732 --> 01:11:12,293
Speaker 4: to have a chat about the role of critical thinking?

1400
01:11:13,732 --> 01:11:14,812
Speaker 19: Okaday, Tyler? How are you?

1401
01:11:15,013 --> 01:11:15,372
Speaker 4: I'm good?

1402
01:11:16,333 --> 01:11:19,333
Speaker 2: What am I chop lover? Andrew? Do I not exist?

1403
01:11:19,973 --> 01:11:23,213
Speaker 19: No one's introduced as ship, so you know, Matt, I

1404
01:11:23,293 --> 01:11:24,492
Speaker 19: just thought i'd leave it at that.

1405
01:11:25,173 --> 01:11:28,932
Speaker 2: Andrew, Hello, my name is My name is Matthew, I'm an.

1406
01:11:28,933 --> 01:11:33,213
Speaker 6: Eries, I'm Andrew.

1407
01:11:33,372 --> 01:11:34,212
Speaker 19: A long time.

1408
01:11:35,532 --> 01:11:35,652
Speaker 6: There.

1409
01:11:36,133 --> 01:11:37,972
Speaker 2: Please to meet Andrew. I think we're going to be friends.

1410
01:11:38,013 --> 01:11:42,732
Speaker 4: Ye, best buds now anyway, Sorry, you had a good

1411
01:11:42,772 --> 01:11:43,293
Speaker 4: point today.

1412
01:11:44,933 --> 01:11:48,052
Speaker 19: I guess my question is both sides of the coin

1413
01:11:48,853 --> 01:11:51,892
Speaker 19: use AI. So the student uses it to write whatever

1414
01:11:51,973 --> 01:11:55,532
Speaker 19: they're doing or perform their homework or test, and the

1415
01:11:55,652 --> 01:11:59,372
Speaker 19: teachers use it to market. At what point does critical

1416
01:11:59,492 --> 01:12:05,692
Speaker 19: thinking stop existing? And Tyler, Yeah, that's only using existing

1417
01:12:05,812 --> 01:12:08,173
Speaker 19: information to produce the work.

1418
01:12:08,412 --> 01:12:12,372
Speaker 2: And then Mark, Yeah, what's the saying for AI? Garbage

1419
01:12:12,412 --> 01:12:16,532
Speaker 2: and garbage out? So if it's it can become.

1420
01:12:16,372 --> 01:12:21,732
Speaker 19: Secular, which is no different how I used to say.

1421
01:12:21,933 --> 01:12:24,452
Speaker 19: I mean, I'm in my mid fifty selves all libraries

1422
01:12:24,492 --> 01:12:29,572
Speaker 19: and books, and you know what you be ify research, creit,

1423
01:12:29,933 --> 01:12:30,812
Speaker 19: I produce CREP.

1424
01:12:33,253 --> 01:12:34,492
Speaker 2: Yeah, I mean, I guess.

1425
01:12:34,772 --> 01:12:37,973
Speaker 19: There's a danger that we cease to be able to

1426
01:12:38,053 --> 01:12:44,213
Speaker 19: think we'll always follow the same path of learning rather

1427
01:12:44,412 --> 01:12:47,293
Speaker 19: than elon masks of the world. Not that I want

1428
01:12:47,333 --> 01:12:50,372
Speaker 19: to hang the head on his and but you know

1429
01:12:50,492 --> 01:12:52,412
Speaker 19: those people just don't exist anymore.

1430
01:12:52,812 --> 01:12:55,253
Speaker 2: Well, it's an interesting thing as well. And I'm not

1431
01:12:55,333 --> 01:12:58,412
Speaker 2: sure the exact nuance on this, but you hear from

1432
01:12:58,692 --> 01:13:02,213
Speaker 2: say YouTube creators, and there's an algorithm that they have

1433
01:13:02,372 --> 01:13:05,172
Speaker 2: to feed, so they work out how to make content

1434
01:13:05,372 --> 01:13:08,933
Speaker 2: that feeds the algorithm. I feed the algorithm means it

1435
01:13:09,013 --> 01:13:11,893
Speaker 2: puts up what the algorithm will share and that what

1436
01:13:12,053 --> 01:13:15,293
Speaker 2: people will watch, and so they start changing what they

1437
01:13:15,452 --> 01:13:19,333
Speaker 2: create to fit what the algorithm wants, and then as

1438
01:13:19,333 --> 01:13:22,852
Speaker 2: a result, they stop making what they want originally started

1439
01:13:22,893 --> 01:13:25,652
Speaker 2: making in a creative faction and are actually just beholden

1440
01:13:25,692 --> 01:13:27,652
Speaker 2: to the algorithm. So you can kind of see a

1441
01:13:27,772 --> 01:13:33,293
Speaker 2: situation that could happen. If you are being marked by AI,

1442
01:13:33,652 --> 01:13:37,173
Speaker 2: then you will then kids will be trained by AI

1443
01:13:38,253 --> 01:13:40,012
Speaker 2: to produce what AI wants.

1444
01:13:40,053 --> 01:13:45,132
Speaker 19: If you AI, it is to me it's rote learning

1445
01:13:45,333 --> 01:13:49,732
Speaker 19: to the eat degree. We need not like Rote learning,

1446
01:13:49,933 --> 01:13:55,333
Speaker 19: But AI in my head is antithesis of you know,

1447
01:13:55,452 --> 01:14:01,652
Speaker 19: it just absolutely screams repetition and I it makes me

1448
01:14:01,933 --> 01:14:05,173
Speaker 19: feel like the world is going to be controlled only

1449
01:14:05,333 --> 01:14:10,372
Speaker 19: by those who are code writers program as opposed to

1450
01:14:10,452 --> 01:14:14,492
Speaker 19: write the algorithms. And that's an ever decreasing number of people.

1451
01:14:14,732 --> 01:14:18,652
Speaker 2: Yeah, thank you, Zechlandrew, or more likely controlled by the

1452
01:14:19,253 --> 01:14:21,933
Speaker 2: creations of those people that wrote the code as the

1453
01:14:21,973 --> 01:14:23,253
Speaker 2: code starts writing itself.

1454
01:14:23,333 --> 01:14:24,893
Speaker 4: But it's just a big for you. You have to

1455
01:14:24,933 --> 01:14:27,372
Speaker 4: be able to question AI, particularly the AI that we're

1456
01:14:27,452 --> 01:14:30,173
Speaker 4: experiencing now. And I, you know, chet GPT is the

1457
01:14:30,213 --> 01:14:33,053
Speaker 4: one that I've used, but so many times, the way

1458
01:14:33,133 --> 01:14:36,653
Speaker 4: that it views a particular problem or challenge is questionable.

1459
01:14:36,732 --> 01:14:39,492
Speaker 4: You can you know it's not black and white. There

1460
01:14:39,692 --> 01:14:42,652
Speaker 4: is some nuance there in some of those elements that

1461
01:14:42,893 --> 01:14:45,852
Speaker 4: AI can try and get all the information that's been

1462
01:14:45,933 --> 01:14:49,652
Speaker 4: fed and give you the best possible answer that it thinks.

1463
01:14:49,893 --> 01:14:51,852
Speaker 4: But it's not always. It's not always black and white.

1464
01:14:51,973 --> 01:14:52,173
Speaker 13: Yeah.

1465
01:14:52,213 --> 01:14:54,692
Speaker 2: But what we do find out sometimes, Tyler, is that

1466
01:14:54,812 --> 01:14:56,973
Speaker 2: humans aren't as complex as we think we are. We

1467
01:14:57,133 --> 01:15:01,733
Speaker 2: think that we're widely varying beings that have this universe

1468
01:15:01,772 --> 01:15:06,053
Speaker 2: of potential ideas. I was at Takabuna Beach the other day,

1469
01:15:06,173 --> 01:15:08,692
Speaker 2: Lovely Beach, and I was walking my dog, and I

1470
01:15:08,853 --> 01:15:10,772
Speaker 2: was in a line of people that were walking their

1471
01:15:10,853 --> 01:15:13,532
Speaker 2: dogs one end of the beach, the other, tapping the

1472
01:15:13,572 --> 01:15:17,012
Speaker 2: wall and coming back. And I said to my son,

1473
01:15:17,293 --> 01:15:19,692
Speaker 2: we're just ants. Let me So all of us have

1474
01:15:19,772 --> 01:15:22,372
Speaker 2: had the same idea to have a dog, because we've

1475
01:15:22,412 --> 01:15:25,412
Speaker 2: evolved to have dogs, and because dogs were useful at

1476
01:15:25,452 --> 01:15:27,732
Speaker 2: one point in our history. So we've got a dog,

1477
01:15:28,013 --> 01:15:29,893
Speaker 2: and we've all woken up on the Sunday morning and

1478
01:15:29,933 --> 01:15:31,372
Speaker 2: had the same idea that we're going to go to

1479
01:15:31,412 --> 01:15:34,412
Speaker 2: the beach. And because we're all very similar. Already we've

1480
01:15:34,452 --> 01:15:36,932
Speaker 2: decided to walk the length of the beach, all holding

1481
01:15:37,013 --> 01:15:40,093
Speaker 2: a coffee in the same hand, touch the wall, and

1482
01:15:40,133 --> 01:15:41,612
Speaker 2: go all the way all the way back.

1483
01:15:42,013 --> 01:15:43,772
Speaker 4: And how nice was it? And how much of a

1484
01:15:43,772 --> 01:15:44,532
Speaker 4: good boy is Colin?

1485
01:15:44,893 --> 01:15:47,053
Speaker 2: Yeah, well that's true. Colin's a very good boy. He's

1486
01:15:47,053 --> 01:15:48,532
Speaker 2: such a good boy. If you're listening, Colin, I left

1487
01:15:48,572 --> 01:15:50,053
Speaker 2: the rady on. You're a good boy, Colin, you're a

1488
01:15:50,093 --> 01:15:53,452
Speaker 2: good boy. Colin, go outside, do away in the backyard.

1489
01:15:55,333 --> 01:15:56,333
Speaker 4: Does he need to be sold there?

1490
01:15:56,372 --> 01:15:57,772
Speaker 2: Where the cat's gone? Where are the cat?

1491
01:15:57,853 --> 01:15:58,492
Speaker 4: Did he get a cat?

1492
01:15:58,572 --> 01:15:59,372
Speaker 2: When I say that, it goes?

1493
01:15:59,732 --> 01:16:00,293
Speaker 4: Where are the cats?

1494
01:16:00,333 --> 01:16:03,092
Speaker 2: Anyway, you've derailed me. The point is not that Colin's

1495
01:16:03,093 --> 01:16:05,412
Speaker 2: a very good boy. It's that we think that we've

1496
01:16:05,452 --> 01:16:08,612
Speaker 2: got these wild variation of ideas, but maybe we don't,

1497
01:16:08,652 --> 01:16:11,772
Speaker 2: and maybe AI can can read us very accurately.

1498
01:16:11,893 --> 01:16:13,492
Speaker 4: It's a good point. Oh wait, undred and eighty ten

1499
01:16:13,532 --> 01:16:16,492
Speaker 4: eighty eighty. You feel about AI use in schools, whether

1500
01:16:16,532 --> 01:16:18,532
Speaker 4: it's by the students or teachers, love to hear from you.

1501
01:16:18,652 --> 01:16:19,412
Speaker 4: It is eight to three?

1502
01:16:19,572 --> 01:16:21,452
Speaker 2: Where are the cats gone? Where are the cats go?

1503
01:16:21,612 --> 01:16:22,253
Speaker 2: For the cats?

1504
01:16:24,133 --> 01:16:26,532
Speaker 1: The issues that affect you and a bit of fun

1505
01:16:26,612 --> 01:16:30,773
Speaker 1: along the way. Matt Heathen, Taylor Adams Afternoons News TALKSB

1506
01:16:31,732 --> 01:16:32,532
Speaker 1: News Talks AB.

1507
01:16:32,652 --> 01:16:34,572
Speaker 4: It is five to three and we're talking about AI

1508
01:16:34,812 --> 01:16:37,492
Speaker 4: in schools. Some great texts coming through on nine two

1509
01:16:37,572 --> 01:16:37,932
Speaker 4: ninety two.

1510
01:16:38,173 --> 01:16:41,253
Speaker 2: Yeah, we're going to keep this topic going after the news.

1511
01:16:42,093 --> 01:16:44,253
Speaker 2: Clive says teachers should mark papers. It gives them the

1512
01:16:44,293 --> 01:16:46,652
Speaker 2: insight into the students' minds and give them more of

1513
01:16:46,692 --> 01:16:50,732
Speaker 2: an indication that what needs to work on. Clive, Yeah,

1514
01:16:51,213 --> 01:16:54,172
Speaker 2: you would hope. And I think now with the trials

1515
01:16:54,293 --> 01:16:58,612
Speaker 2: on AI marking in New Zealand anyway, there is a

1516
01:16:58,973 --> 01:17:02,173
Speaker 2: human involved as well, so it's not just feeding it out,

1517
01:17:02,213 --> 01:17:05,133
Speaker 2: so there's looking at it. But yeah, you would. And

1518
01:17:05,253 --> 01:17:07,573
Speaker 2: I'm not sure at what level if this is exams

1519
01:17:07,812 --> 01:17:11,133
Speaker 2: or just today marking, but you would think in day

1520
01:17:11,173 --> 01:17:13,412
Speaker 2: to day marking there would be advantages for the teacher

1521
01:17:13,933 --> 01:17:16,812
Speaker 2: to read what people are writing because it will give

1522
01:17:16,853 --> 01:17:19,972
Speaker 2: them more information than just whether they got the answer

1523
01:17:20,053 --> 01:17:24,293
Speaker 2: right or wrong. Yeah, but then again, god AI could

1524
01:17:24,333 --> 01:17:27,173
Speaker 2: be trained to do that, just give you five bullet

1525
01:17:27,213 --> 01:17:31,772
Speaker 2: points wrong. It could diagnose the kid with ADHD to

1526
01:17:32,213 --> 01:17:35,133
Speaker 2: tell you just by reading a paragraph they're not eating

1527
01:17:35,173 --> 01:17:37,213
Speaker 2: their lunch. There can be a whole lot of stuff

1528
01:17:37,253 --> 01:17:40,372
Speaker 2: about that. Yeah, find out that their parents are criminal exactly.

1529
01:17:40,853 --> 01:17:42,812
Speaker 2: This is a good text as well, afternoon boys. When

1530
01:17:42,853 --> 01:17:44,852
Speaker 2: we were at school, it was using calculators that the

1531
01:17:44,893 --> 01:17:47,892
Speaker 2: teachers tried to stop. Now they were giving embrace AI

1532
01:17:48,333 --> 01:17:51,293
Speaker 2: adapt the curriculum, which is a very fair point. When

1533
01:17:51,333 --> 01:17:53,772
Speaker 2: I was at school, Google was the big nasty come

1534
01:17:53,812 --> 01:17:56,253
Speaker 2: along is that you can't use Google. That's gad well.

1535
01:17:56,293 --> 01:17:58,053
Speaker 2: When my mum was little, her dad used to tell

1536
01:17:58,093 --> 01:18:00,293
Speaker 2: her off for reading too many books. Get outside and

1537
01:18:00,333 --> 01:18:01,333
Speaker 2: stop reading so much.

1538
01:18:01,933 --> 01:18:04,972
Speaker 4: Oh, eight hundred eighty ten eighty is the number to call.

1539
01:18:05,093 --> 01:18:08,093
Speaker 4: We're going to carry this on after News, Sport and Weather,

1540
01:18:08,093 --> 01:18:10,213
Speaker 4: which is on its way. Great to have your company

1541
01:18:10,293 --> 01:18:12,972
Speaker 4: as always. You're listening to matt and Tyler. Good afternoon

1542
01:18:13,053 --> 01:18:13,253
Speaker 4: to you.

1543
01:18:14,692 --> 01:18:36,612
Speaker 1: Yeah, your new home are insightful and entertaining talk. It's

1544
01:18:36,772 --> 01:18:41,293
Speaker 1: Mattie and Taylor Adams Afternoons on News Talk Sabby.

1545
01:18:41,893 --> 01:18:44,173
Speaker 4: Good afternoon to you. Welcome back into the show. Seeven

1546
01:18:44,253 --> 01:18:46,253
Speaker 4: past three, and we're talking about AI in schools.

1547
01:18:46,372 --> 01:18:47,652
Speaker 2: Yeah, before we get back to that, a couple of

1548
01:18:47,652 --> 01:18:50,492
Speaker 2: things I need to address. Before I was talking to

1549
01:18:50,532 --> 01:18:52,213
Speaker 2: my dog Colin down the radio because I'd left the

1550
01:18:52,293 --> 01:18:54,053
Speaker 2: radio on at home and I told him to get

1551
01:18:54,093 --> 01:18:56,173
Speaker 2: the cats, Get the cats, get the cats.

1552
01:18:56,293 --> 01:18:56,452
Speaker 14: Love.

1553
01:18:56,612 --> 01:18:58,812
Speaker 2: And there's been a number of texts saying, what kind

1554
01:18:58,853 --> 01:19:02,572
Speaker 2: of sick monster sets his dog on cats? Those people

1555
01:19:02,853 --> 01:19:04,772
Speaker 2: that are texting that through have not seen my dog Colin.

1556
01:19:05,293 --> 01:19:08,812
Speaker 2: Colin will never catch a cat, and if he does

1557
01:19:08,973 --> 01:19:12,612
Speaker 2: catch a cat, the cat will win the fight. But

1558
01:19:13,492 --> 01:19:15,852
Speaker 2: Colin will run around in a circle and get excited

1559
01:19:15,893 --> 01:19:17,133
Speaker 2: when you say, where the cat's Colin?

1560
01:19:17,492 --> 01:19:18,652
Speaker 4: And that's a beautiful thing to say.

1561
01:19:19,013 --> 01:19:21,213
Speaker 2: Yeah. Absolutely, And a lot of people have also been

1562
01:19:21,213 --> 01:19:24,852
Speaker 2: hassling me about who calls the dog Colin. In my defense,

1563
01:19:24,933 --> 01:19:28,173
Speaker 2: my kid's called dog Colin Colin, and he's named after

1564
01:19:28,853 --> 01:19:33,492
Speaker 2: a character from the Blackadded TV series, not the ripoff

1565
01:19:33,973 --> 01:19:36,812
Speaker 2: Colin from Accounts, which is a rip. They've ripped that

1566
01:19:36,893 --> 01:19:38,092
Speaker 2: off at Dog's.

1567
01:19:37,893 --> 01:19:40,013
Speaker 4: Naw, that's a past then if it's Blackadder.

1568
01:19:40,133 --> 01:19:43,452
Speaker 2: Yeah, And second thing I wanted to make it and

1569
01:19:43,492 --> 01:19:45,572
Speaker 2: this started three o'clock hour. We talked about this on

1570
01:19:45,612 --> 01:19:47,892
Speaker 2: the show a couple of weeks ago. How I heard

1571
01:19:47,933 --> 01:19:51,372
Speaker 2: on my costing Breakfast he said that he complains if

1572
01:19:51,372 --> 01:19:53,692
Speaker 2: someone sends him a freebe he complains he hates it,

1573
01:19:53,812 --> 01:19:55,972
Speaker 2: and you he'll run that run whatever it is down.

1574
01:19:56,572 --> 01:19:59,293
Speaker 2: We don't hold that policy on Matt and Tyler afternoons.

1575
01:19:59,412 --> 01:20:01,012
Speaker 4: No, the opposite.

1576
01:20:01,053 --> 01:20:03,692
Speaker 2: Yeah, if you send us something and it's good, we'll

1577
01:20:03,692 --> 01:20:07,133
Speaker 2: discuss it. Absolutely, we will absolutely And let's not talk

1578
01:20:07,173 --> 01:20:11,492
Speaker 2: about fringe benefit tax right now. But send this beautiful

1579
01:20:11,492 --> 01:20:14,732
Speaker 2: book today, New Zealand's Gourmet Pies by Derek Morrison, A

1580
01:20:14,812 --> 01:20:17,852
Speaker 2: mouth ordering journey into the heart of New Zealand pie culture.

1581
01:20:18,173 --> 01:20:21,173
Speaker 2: Which is this beautiful, hard covered I guess you'd call

1582
01:20:21,213 --> 01:20:23,333
Speaker 2: it a coffee table book, going around all the best

1583
01:20:23,372 --> 01:20:26,693
Speaker 2: pie makers in the country, pictures of their pies, beautiful

1584
01:20:26,772 --> 01:20:30,613
Speaker 2: shots meeting the piemakers and the families and their businesses.

1585
01:20:31,133 --> 01:20:34,053
Speaker 2: It's a very, very, very beautiful book. It is so

1586
01:20:34,173 --> 01:20:38,532
Speaker 2: New Zealand's Gourmet Pies by Derek Morrison a mouthwatering journey

1587
01:20:38,572 --> 01:20:41,333
Speaker 2: into the heart of New Zealand pie culture. Good beautiful book.

1588
01:20:41,412 --> 01:20:43,492
Speaker 4: Yep, good on you, Derek. And you can take a

1589
01:20:43,572 --> 01:20:46,492
Speaker 4: lesson from what Derek has done. Send us some stuff.

1590
01:20:46,692 --> 01:20:49,053
Speaker 2: We like it. Well, what I liked about what Derek did?

1591
01:20:49,053 --> 01:20:50,732
Speaker 2: Does he send it just to me and nothing to you?

1592
01:20:51,293 --> 01:20:51,412
Speaker 9: Oh?

1593
01:20:51,532 --> 01:20:53,092
Speaker 4: Yeah, Actually, of Derek.

1594
01:20:53,133 --> 01:20:55,652
Speaker 2: Yeah, I think that's the way we should go forward. Also,

1595
01:20:55,732 --> 01:21:00,213
Speaker 2: a beautiful New Zealand Gormost pie towel with a road

1596
01:21:00,253 --> 01:21:02,213
Speaker 2: trip towel with all the different bakeries in the country.

1597
01:21:02,452 --> 01:21:05,132
Speaker 4: Is that from Derek as well? Yeah, it's pretty everyone

1598
01:21:06,612 --> 01:21:07,972
Speaker 4: Patrick's Pies and Blenheim's.

1599
01:21:08,572 --> 01:21:08,732
Speaker 20: Wow.

1600
01:21:08,772 --> 01:21:12,253
Speaker 2: Well that's a great the baker and tudo fantastic. All right,

1601
01:21:12,412 --> 01:21:14,213
Speaker 2: all right, regard us to get back to AI.

1602
01:21:14,333 --> 01:21:18,652
Speaker 4: All right, Yes, we're chatting about AI in schools and

1603
01:21:18,732 --> 01:21:21,173
Speaker 4: there's some great teachs coming through on nine two nine two,

1604
01:21:21,213 --> 01:21:22,492
Speaker 4: But we want to hear from you on O eight

1605
01:21:22,492 --> 01:21:23,772
Speaker 4: one hundred and eighty ten eighty.

1606
01:21:24,013 --> 01:21:26,452
Speaker 2: Yeah, as your kid using AI at school, how do

1607
01:21:26,492 --> 01:21:28,172
Speaker 2: you feel about it? How do you feel about teachers

1608
01:21:28,293 --> 01:21:31,932
Speaker 2: using AI to mark your kid's work, because that's happening

1609
01:21:32,013 --> 01:21:37,253
Speaker 2: with the help of a human is involved at this point,

1610
01:21:37,333 --> 01:21:39,492
Speaker 2: but it may not be forever. And if you're a teacher,

1611
01:21:39,532 --> 01:21:41,293
Speaker 2: we'd love to hear from you and your thoughts on

1612
01:21:41,372 --> 01:21:45,973
Speaker 2: how much AI should be used in school because right now,

1613
01:21:46,853 --> 01:21:49,812
Speaker 2: the parameters, what do you call it? What's the word

1614
01:21:49,893 --> 01:21:54,053
Speaker 2: that I'm looking forward? The oh, the percentage, no, no,

1615
01:21:55,692 --> 01:21:59,812
Speaker 2: the guidance, the Ministry of Education is under pressure to

1616
01:21:59,893 --> 01:22:03,093
Speaker 2: provide clearer guidance on artificial intelligence and school So a

1617
01:22:03,133 --> 01:22:04,572
Speaker 2: lot of schools are saying that they don't have the

1618
01:22:04,612 --> 01:22:06,772
Speaker 2: guidance to know how much they should use, and it's

1619
01:22:06,853 --> 01:22:09,452
Speaker 2: currently up to school board Wood. Yeah, all right, this

1620
01:22:09,532 --> 01:22:13,093
Speaker 2: sextasy is Google, do kiwis eat mangoes? Refresher and have

1621
01:22:13,133 --> 01:22:15,333
Speaker 2: a look at the AI answers. This is why people

1622
01:22:15,452 --> 01:22:20,892
Speaker 2: need to have their brains deleted. Okay, do kiwi fruit

1623
01:22:20,973 --> 01:22:24,093
Speaker 2: eat mangoes? Do kiwis eat mangoes? I'll put in that no,

1624
01:22:25,452 --> 01:22:29,892
Speaker 2: kiwi fruit. The bird does not eat manos. Kiwi fruit

1625
01:22:29,973 --> 01:22:33,573
Speaker 2: primarily eat worms, insects, and berries, and they are omnivores,

1626
01:22:33,732 --> 01:22:36,133
Speaker 2: meaning they eat both plants and animals. You see this

1627
01:22:36,253 --> 01:22:41,852
Speaker 2: is confused AI because kiwis are us new Zealanders are Kiwi's. Yeah,

1628
01:22:42,013 --> 01:22:45,812
Speaker 2: there's also the bird, the kiwi, and there's the kiwi fruit.

1629
01:22:46,893 --> 01:22:50,412
Speaker 2: So between those three things, it's become very complicated For

1630
01:22:50,652 --> 01:22:53,412
Speaker 2: Google's AI. I think it's called Gemini, which is, as

1631
01:22:53,452 --> 01:22:54,812
Speaker 2: we all know, the worst of the AI.

1632
01:22:55,093 --> 01:22:56,932
Speaker 4: Yeah that is a terrible a good one.

1633
01:22:57,053 --> 01:22:57,213
Speaker 6: Yeah.

1634
01:22:57,253 --> 01:22:59,372
Speaker 2: Google has been cumulated on a number of occasions for

1635
01:22:59,492 --> 01:23:00,892
Speaker 2: its responses, Oh.

1636
01:23:00,893 --> 01:23:03,013
Speaker 4: One hundred eighty ten eighty is the number to call

1637
01:23:03,053 --> 01:23:05,852
Speaker 4: this Texas is gate boys just on the AI AI

1638
01:23:06,133 --> 01:23:08,652
Speaker 4: rather subject. At my kids school, the students have to

1639
01:23:08,732 --> 01:23:11,372
Speaker 4: sign a contract that they are only allowed to use

1640
01:23:11,452 --> 01:23:14,012
Speaker 4: AI for twenty five percent of their work. Their work

1641
01:23:14,133 --> 01:23:15,933
Speaker 4: is checked by a teacher and if the work is

1642
01:23:15,933 --> 01:23:18,933
Speaker 4: showing twenty five percent or more AI use, they are

1643
01:23:18,933 --> 01:23:21,093
Speaker 4: given a warning or fail on that paper. It is

1644
01:23:21,173 --> 01:23:23,572
Speaker 4: the language of AI that they check on, and this

1645
01:23:23,732 --> 01:23:26,253
Speaker 4: is where it can get tricky. Sometimes the student's work

1646
01:23:26,532 --> 01:23:30,133
Speaker 4: has AI language without the student knowing, and then it's

1647
01:23:30,173 --> 01:23:32,852
Speaker 4: picked up as AI usage and then they have to

1648
01:23:32,973 --> 01:23:36,732
Speaker 4: prove it isn't, which gets tricky. I mean just saying

1649
01:23:36,772 --> 01:23:38,492
Speaker 4: you can use it for twenty five percent, and we're

1650
01:23:38,492 --> 01:23:41,093
Speaker 4: going to run AI through your own AI work to

1651
01:23:41,173 --> 01:23:43,973
Speaker 4: figure out how much percentage of AI you've used. This

1652
01:23:44,173 --> 01:23:47,372
Speaker 4: is where it starts getting confusing. Well do they need

1653
01:23:47,532 --> 01:23:49,093
Speaker 4: to I guess you.

1654
01:23:49,173 --> 01:23:51,333
Speaker 2: Know, and people have thought of this, so I'd love

1655
01:23:51,372 --> 01:23:53,093
Speaker 2: to hear the kickback on it on one hundred and

1656
01:23:53,133 --> 01:23:58,773
Speaker 2: eighty ten eighty. But should it then come down to presentations?

1657
01:23:59,293 --> 01:24:01,372
Speaker 2: So you can use your AI for your research, you

1658
01:24:01,412 --> 01:24:05,253
Speaker 2: can put your whatever together and your presentation whatever, and

1659
01:24:05,333 --> 01:24:06,893
Speaker 2: then you stand up in front of the teacher and

1660
01:24:07,013 --> 01:24:09,253
Speaker 2: you have to make the presentation, and then the teacher

1661
01:24:09,293 --> 01:24:11,532
Speaker 2: can ask you questions in real time to see how

1662
01:24:11,612 --> 01:24:15,892
Speaker 2: much you you you know, you understand it. I guess

1663
01:24:15,973 --> 01:24:20,532
Speaker 2: the argument against that would be that people would that's

1664
01:24:20,612 --> 01:24:22,372
Speaker 2: hard on people that are no good at you know,

1665
01:24:22,532 --> 01:24:25,013
Speaker 2: communicating or talking to their teachers. But then again, you

1666
01:24:25,053 --> 01:24:26,492
Speaker 2: should get marked down for not being good at that,

1667
01:24:26,492 --> 01:24:27,732
Speaker 2: and you should work on getting better at it.

1668
01:24:27,772 --> 01:24:29,053
Speaker 4: It's a good skill to learn in life. Oh eight,

1669
01:24:29,053 --> 01:24:31,013
Speaker 4: one hundred and eighteen eighty is the number to call.

1670
01:24:31,053 --> 01:24:35,213
Speaker 4: It is thirteen past three news talks there b, it

1671
01:24:35,372 --> 01:24:37,492
Speaker 4: is a quarter past three. We're talking about AI in

1672
01:24:37,652 --> 01:24:39,932
Speaker 4: school's good idea or a bad idea, both for students

1673
01:24:40,013 --> 01:24:43,652
Speaker 4: and teachers. So something you wanted to clarify.

1674
01:24:43,853 --> 01:24:47,133
Speaker 2: Oh yeah, I'm complete. I'm very concerned because someone said

1675
01:24:47,133 --> 01:24:49,692
Speaker 2: that I that I got a pie place and one

1676
01:24:49,692 --> 01:24:51,732
Speaker 2: of my favorite pie places and one of my favorite

1677
01:24:51,732 --> 01:24:55,492
Speaker 2: New Zealanders, Patrick Lamb. Did I say Patrick Pies and

1678
01:24:55,572 --> 01:24:59,213
Speaker 2: Blenham It's Patrick Pies and Bethlehem and the Bad plenty.

1679
01:24:59,372 --> 01:25:01,253
Speaker 2: If I got that wrong, I'm very very sorry.

1680
01:25:01,333 --> 01:25:01,692
Speaker 15: How dare you.

1681
01:25:01,853 --> 01:25:04,293
Speaker 2: I was reading it off the New Zealand Gormet Pie's

1682
01:25:04,412 --> 01:25:05,173
Speaker 2: road Trip Towel.

1683
01:25:05,412 --> 01:25:06,253
Speaker 4: Did Derek get it right?

1684
01:25:06,293 --> 01:25:06,452
Speaker 6: Though?

1685
01:25:06,652 --> 01:25:07,372
Speaker 4: Derek got it right?

1686
01:25:07,692 --> 01:25:08,253
Speaker 2: Who's Derek?

1687
01:25:08,812 --> 01:25:10,852
Speaker 4: There's the guy that made the tetail, the Errol Morrison, the.

1688
01:25:11,013 --> 01:25:13,732
Speaker 2: Author of the book and the author of the towel. Yeap,

1689
01:25:13,812 --> 01:25:14,333
Speaker 2: he got it right.

1690
01:25:14,412 --> 01:25:15,933
Speaker 4: Okay, we'll give him a pass on that.

1691
01:25:16,013 --> 01:25:18,052
Speaker 2: Then he definitely got a right. A bunch of street butcher.

1692
01:25:18,333 --> 01:25:20,932
Speaker 2: They do some good bakeries and the good pis and Dunedin.

1693
01:25:21,412 --> 01:25:22,492
Speaker 2: But anyway, listen, I.

1694
01:25:22,492 --> 01:25:25,412
Speaker 4: Do love a good themed tea tawel. Just incidentally, what

1695
01:25:25,572 --> 01:25:26,892
Speaker 4: do you used to make them? At school?

1696
01:25:27,013 --> 01:25:28,372
Speaker 2: What are you supposed to do? Are you supposed to

1697
01:25:28,492 --> 01:25:31,133
Speaker 2: use a flesh t tail like this to dry your dishes?

1698
01:25:31,173 --> 01:25:33,692
Speaker 2: It's a talking point though, you know when that's what

1699
01:25:33,732 --> 01:25:34,812
Speaker 2: I'm asking you, Like, do you hang it on the

1700
01:25:34,853 --> 01:25:35,692
Speaker 2: wall or do you use it?

1701
01:25:36,652 --> 01:25:38,093
Speaker 4: Ideally you take it to the beach. But if you

1702
01:25:38,133 --> 01:25:38,852
Speaker 4: don't have a beach, what.

1703
01:25:38,853 --> 01:25:39,293
Speaker 6: Do you do with it?

1704
01:25:39,333 --> 01:25:41,013
Speaker 2: Well, it's for a road trip, so you put it

1705
01:25:41,053 --> 01:25:41,372
Speaker 2: in the car.

1706
01:25:41,612 --> 01:25:43,412
Speaker 4: Yeah, I suppose you get it framed And I don't

1707
01:25:43,452 --> 01:25:45,652
Speaker 4: know should we ask Ai what to do? With this

1708
01:25:45,732 --> 01:25:46,093
Speaker 4: t tail.

1709
01:25:46,692 --> 01:25:49,092
Speaker 2: Would you this, I'll tell it would be really amazing.

1710
01:25:49,133 --> 01:25:52,093
Speaker 2: Someone should do this, because there's thirty eight fantastic pie

1711
01:25:52,133 --> 01:25:56,093
Speaker 2: shops here from honey Bees way up at the top

1712
01:25:56,133 --> 01:25:58,652
Speaker 2: of North right down to Fat Bastard Pison A Vicago.

1713
01:25:58,853 --> 01:25:59,772
Speaker 2: There's thirty eight of them.

1714
01:25:59,853 --> 01:26:01,333
Speaker 4: Yeah, take that on the road.

1715
01:26:01,612 --> 01:26:03,213
Speaker 2: Do a road trip where you have a pie at

1716
01:26:03,372 --> 01:26:05,173
Speaker 2: every single one of these pie shops.

1717
01:26:06,293 --> 01:26:07,612
Speaker 4: That would be ultimate.

1718
01:26:08,372 --> 01:26:09,812
Speaker 2: Wonder how long that would take to get around to

1719
01:26:09,853 --> 01:26:11,972
Speaker 2: every one of those pies and then they weigh yourself

1720
01:26:12,013 --> 01:26:13,732
Speaker 2: at the start and at the end, who ate all

1721
01:26:13,772 --> 01:26:14,173
Speaker 2: the pies?

1722
01:26:14,372 --> 01:26:14,412
Speaker 15: Me?

1723
01:26:14,572 --> 01:26:16,133
Speaker 2: I did a road trip right around the country and

1724
01:26:16,293 --> 01:26:17,293
Speaker 2: ate one of all the pies.

1725
01:26:17,412 --> 01:26:18,612
Speaker 4: Maybe we can do it. We'll take the show on

1726
01:26:18,652 --> 01:26:24,692
Speaker 4: the road and just to the pie roady, Mike, Sorry

1727
01:26:24,732 --> 01:26:25,372
Speaker 4: to keep you waiting.

1728
01:26:26,412 --> 01:26:30,253
Speaker 2: That's all right, mate, that's the kind of sort of

1729
01:26:30,333 --> 01:26:32,492
Speaker 2: detour and conversation A I probably wouldn't go on.

1730
01:26:33,253 --> 01:26:34,013
Speaker 4: Maybe no part of that.

1731
01:26:34,532 --> 01:26:36,253
Speaker 2: And Tyler needs to be replaced by AI if we're

1732
01:26:36,253 --> 01:26:39,533
Speaker 2: going to go like that anyway, Mike, your thoughts.

1733
01:26:39,333 --> 01:26:41,492
Speaker 15: Well, there was less about the students using AI. It

1734
01:26:41,572 --> 01:26:44,612
Speaker 15: was about appearance using AI. We just got my boys'

1735
01:26:44,612 --> 01:26:47,572
Speaker 15: school report email the other day and we couldn't even

1736
01:26:47,652 --> 01:26:51,173
Speaker 15: decipher the thing. It was all graphs and little color

1737
01:26:51,253 --> 01:26:57,013
Speaker 15: code symbols and all sorts of stuff, and sped out

1738
01:26:57,492 --> 01:26:58,612
Speaker 15: it was actually doing well.

1739
01:26:58,893 --> 01:27:02,293
Speaker 2: I know exactly what you're talking about, trying to ascertain

1740
01:27:02,412 --> 01:27:04,932
Speaker 2: whether your kid is doing well at school by those reports.

1741
01:27:05,612 --> 01:27:08,253
Speaker 2: And it has the key and you can read through it.

1742
01:27:08,412 --> 01:27:11,293
Speaker 2: But there must be a simpler way to give us

1743
01:27:11,293 --> 01:27:11,812
Speaker 2: the information.

1744
01:27:12,812 --> 01:27:15,413
Speaker 15: Yeah, I'll put it in chat GBT. It literally analyzes

1745
01:27:15,452 --> 01:27:17,093
Speaker 15: it all and gives you a little summary.

1746
01:27:16,772 --> 01:27:17,253
Speaker 4: At the end.

1747
01:27:17,333 --> 01:27:18,013
Speaker 2: And it did.

1748
01:27:18,173 --> 01:27:21,612
Speaker 15: He said he's doing he's doing very well with mess

1749
01:27:21,652 --> 01:27:24,333
Speaker 15: Amanic English and need a bit of work in mess So.

1750
01:27:26,173 --> 01:27:28,852
Speaker 2: Do make any comment on your ability to comprehend graphs?

1751
01:27:30,173 --> 01:27:30,213
Speaker 11: No?

1752
01:27:30,492 --> 01:27:33,772
Speaker 2: No, So when you said you put it into chet GBT,

1753
01:27:34,133 --> 01:27:37,053
Speaker 2: did you put the graphs in there and.

1754
01:27:39,372 --> 01:27:42,213
Speaker 15: Into the are and it came back instantly with the

1755
01:27:43,053 --> 01:27:44,492
Speaker 15: New Zealand practices.

1756
01:27:45,572 --> 01:27:46,372
Speaker 6: And knew all about it?

1757
01:27:46,452 --> 01:27:51,092
Speaker 4: And did you believe it summary? Did you believe it atually?

1758
01:27:52,893 --> 01:27:53,532
Speaker 6: Teacher tonight?

1759
01:27:53,612 --> 01:27:54,612
Speaker 15: So we'll find out how.

1760
01:27:56,133 --> 01:27:58,133
Speaker 2: Well as an answer that you want to believe that

1761
01:27:58,173 --> 01:28:00,053
Speaker 2: your kid's doing well, so you know you might as

1762
01:28:00,053 --> 01:28:00,612
Speaker 2: well belive that one.

1763
01:28:01,013 --> 01:28:03,932
Speaker 15: Yeah, By the way, I think Colin's a fantastic dogs name.

1764
01:28:03,973 --> 01:28:05,092
Speaker 15: My dog's name is Bruce.

1765
01:28:06,293 --> 01:28:06,812
Speaker 4: That's good.

1766
01:28:07,893 --> 01:28:10,053
Speaker 12: Dogs were How's it, Mike?

1767
01:28:10,133 --> 01:28:12,492
Speaker 2: When you're out and Bruce's run off on a dog

1768
01:28:12,532 --> 01:28:15,253
Speaker 2: pack or something and yelling Bruce. It's kind of a weird,

1769
01:28:16,532 --> 01:28:19,372
Speaker 2: isn't it? When I find myself yelling Colin past people,

1770
01:28:19,732 --> 01:28:23,732
Speaker 2: it seems weird. All right, thanks to you, call Mike.

1771
01:28:23,812 --> 01:28:26,213
Speaker 2: So that's smart, isn't it. That's smart? Because I've seen

1772
01:28:26,333 --> 01:28:30,253
Speaker 2: those report cards and they're incredibly complex. It looks like

1773
01:28:30,372 --> 01:28:32,572
Speaker 2: it's some kind of track to try and stop you

1774
01:28:32,652 --> 01:28:34,253
Speaker 2: working out with your kids, are doing well at school

1775
01:28:34,333 --> 01:28:34,452
Speaker 2: or not?

1776
01:28:34,973 --> 01:28:37,852
Speaker 4: Put it through a through che GPT and I'll tell

1777
01:28:37,853 --> 01:28:40,492
Speaker 4: you the tell you the truth, guys. My wife uses

1778
01:28:40,572 --> 01:28:44,532
Speaker 4: AI to check check my work at home. My highest

1779
01:28:44,532 --> 01:28:46,253
Speaker 4: score is four and a half. I don't believe.

1780
01:28:46,333 --> 01:28:50,333
Speaker 2: I ain't that out your worst, Tyler. My wife uses

1781
01:28:50,372 --> 01:28:52,132
Speaker 2: AI to check my work in the bedroom.

1782
01:28:52,173 --> 01:28:54,013
Speaker 4: As I said in the home, I hear what I

1783
01:28:54,093 --> 01:28:54,892
Speaker 4: was talking about.

1784
01:28:54,772 --> 01:28:57,692
Speaker 2: But Tyler, there's a big difference between work in the

1785
01:28:57,772 --> 01:29:00,293
Speaker 2: home and work in the bedroom. Okay, my highest score

1786
01:29:00,372 --> 01:29:02,572
Speaker 2: is four and a half. I don't believe. I knows

1787
01:29:02,612 --> 01:29:05,133
Speaker 2: what it's talking about how does she how is she

1788
01:29:05,293 --> 01:29:07,932
Speaker 2: using AI? Are you filming what you're doing and then

1789
01:29:08,452 --> 01:29:09,492
Speaker 2: plugging that into AI?

1790
01:29:09,812 --> 01:29:10,012
Speaker 6: Yeah?

1791
01:29:10,572 --> 01:29:10,812
Speaker 12: Must be.

1792
01:29:11,133 --> 01:29:12,732
Speaker 4: If you can give us some more information on nine

1793
01:29:12,812 --> 01:29:13,692
Speaker 4: two nine two.

1794
01:29:13,812 --> 01:29:16,293
Speaker 2: Send us the videos. Ye, well, well we'll decide for you.

1795
01:29:16,532 --> 01:29:19,213
Speaker 4: Oh one hundred eighty ten eighty is the number to

1796
01:29:19,253 --> 01:29:22,093
Speaker 4: call AI in the school? How do you feel about it?

1797
01:29:22,692 --> 01:29:23,013
Speaker 3: And late?

1798
01:29:23,093 --> 01:29:24,532
Speaker 2: Look, Judy's dog's name's Roger.

1799
01:29:24,732 --> 01:29:28,333
Speaker 4: Roger's a great name for good boy. Roger good boy, Roger.

1800
01:29:28,412 --> 01:29:31,492
Speaker 1: Good boy, Roger good boy, Bruce good boy, Colin good Dogs,

1801
01:29:36,293 --> 01:29:39,972
Speaker 1: Matt Heathan Tyler Adams. Afternoons call oh, eight hundred eighty

1802
01:29:40,253 --> 01:29:41,652
Speaker 1: eighty on news Talk ZB.

1803
01:29:42,333 --> 01:29:45,293
Speaker 4: Very good afternoon to you. It is twenty two past three.

1804
01:29:45,652 --> 01:29:48,612
Speaker 4: Just having a giggle at some great texts coming through. Yeah,

1805
01:29:48,692 --> 01:29:52,293
Speaker 4: but we want to focus on AI. Of confused things.

1806
01:29:52,452 --> 01:29:55,372
Speaker 4: We've derailed it with my long non logical.

1807
01:29:55,053 --> 01:29:58,852
Speaker 2: Mind of confused things with dog names and pie road trips.

1808
01:29:59,333 --> 01:30:03,253
Speaker 2: But we're talking about a I and Grant welcome the show.

1809
01:30:03,933 --> 01:30:06,492
Speaker 2: Your thoughts on on AI and schools and in general.

1810
01:30:07,772 --> 01:30:10,732
Speaker 3: Yep, I think we really need to go back to

1811
01:30:10,933 --> 01:30:15,572
Speaker 3: the history or the foundations of our current education system.

1812
01:30:16,452 --> 01:30:20,293
Speaker 3: And that really is I believe around the Industrial Revolution,

1813
01:30:20,612 --> 01:30:24,572
Speaker 3: and they basically set up schools so that they could

1814
01:30:24,612 --> 01:30:28,173
Speaker 3: train people up to work in factories and do whatever's

1815
01:30:28,253 --> 01:30:34,812
Speaker 3: needed for keeping the economy going. And so we've now

1816
01:30:34,893 --> 01:30:39,053
Speaker 3: got AI coming through, and I believe we need to

1817
01:30:39,612 --> 01:30:42,893
Speaker 3: completely embrace it and teach kids how to do it

1818
01:30:43,612 --> 01:30:49,133
Speaker 3: and let them do it. Because I actually sell computers

1819
01:30:49,293 --> 01:30:52,732
Speaker 3: and fixed computers, and there's lots of customers that I

1820
01:30:52,893 --> 01:30:55,972
Speaker 3: talk to. I can put them into two groups. One

1821
01:30:56,013 --> 01:30:59,852
Speaker 3: group is, oh, I'm too scared of all this computer stuff,

1822
01:31:00,053 --> 01:31:03,173
Speaker 3: and they never learned, they never improve. And then there's

1823
01:31:03,213 --> 01:31:05,933
Speaker 3: others just say, oh, I'll just give it a go,

1824
01:31:06,372 --> 01:31:10,412
Speaker 3: and they just go for it. And you know, why

1825
01:31:10,532 --> 01:31:13,972
Speaker 3: hold people back from what's just around the corner. In fact,

1826
01:31:14,013 --> 01:31:15,852
Speaker 3: it's not around the corner, it's right here right now.

1827
01:31:17,173 --> 01:31:20,092
Speaker 2: And how do you see that future? So you say schools,

1828
01:31:20,572 --> 01:31:22,812
Speaker 2: you know, were brought in and you know the eight

1829
01:31:23,093 --> 01:31:25,293
Speaker 2: our work day of course, and schools were brought in

1830
01:31:25,372 --> 01:31:27,333
Speaker 2: to set people up to be members of society and

1831
01:31:27,452 --> 01:31:31,093
Speaker 2: work in the in the areas that society needed. Do

1832
01:31:31,253 --> 01:31:32,293
Speaker 2: you see.

1833
01:31:34,013 --> 01:31:34,053
Speaker 9: That?

1834
01:31:34,572 --> 01:31:36,293
Speaker 2: I mean, what future do you see in terms of

1835
01:31:36,333 --> 01:31:38,213
Speaker 2: the work for kids that are coming out of schools

1836
01:31:38,253 --> 01:31:40,652
Speaker 2: that have been trained in AI, because there's a lot

1837
01:31:40,692 --> 01:31:42,972
Speaker 2: of fears that there just simply won't be the jobs

1838
01:31:43,612 --> 01:31:45,973
Speaker 2: for them that, you know, jobs like an accounting and

1839
01:31:46,492 --> 01:31:50,052
Speaker 2: in danger, jobs like a lawyer, you know, like legal

1840
01:31:50,133 --> 01:31:52,812
Speaker 2: professionals in danger. What careers do you think are going

1841
01:31:52,853 --> 01:31:53,452
Speaker 2: to remain.

1842
01:31:55,612 --> 01:31:58,173
Speaker 3: Well, I was listening to a young young kid that

1843
01:31:58,372 --> 01:32:04,253
Speaker 3: was on a Millionaire Kids thing and the guy said

1844
01:32:04,293 --> 01:32:06,372
Speaker 3: to him, so, you know, what job do you want

1845
01:32:06,412 --> 01:32:09,572
Speaker 3: to have when you leave universe? And he said, the

1846
01:32:09,732 --> 01:32:14,093
Speaker 3: job I'll have probably doesn't even exist yet. And that's

1847
01:32:14,612 --> 01:32:19,532
Speaker 3: that's where it's all going. And unless we have you know,

1848
01:32:20,013 --> 01:32:23,333
Speaker 3: kids with the already the resources, they're not going to

1849
01:32:23,412 --> 01:32:27,293
Speaker 3: do it. For instance, you mentioned accountants, Well, the government

1850
01:32:27,412 --> 01:32:30,372
Speaker 3: is already setting it up that you can use accounting

1851
01:32:30,452 --> 01:32:37,693
Speaker 3: software like Henry or zero and you don't need an accountant.

1852
01:32:38,213 --> 01:32:40,532
Speaker 3: The government of just they look in the back end

1853
01:32:40,572 --> 01:32:44,213
Speaker 3: of it. They use AI already and they go, oh yeah, yeah, yeah,

1854
01:32:44,213 --> 01:32:47,213
Speaker 3: they've done it all right, ye'p, fine, move along, nothing

1855
01:32:47,253 --> 01:32:47,892
Speaker 3: to be seen here.

1856
01:32:48,692 --> 01:32:51,213
Speaker 2: So that has the same weight for them as say

1857
01:32:51,213 --> 01:32:52,293
Speaker 2: a chartered accountant.

1858
01:32:53,652 --> 01:32:57,293
Speaker 3: Oh yeah, more so, way more so, because in fact

1859
01:32:57,293 --> 01:33:02,933
Speaker 3: they've done studies and found that AI's ability to diagnose.

1860
01:33:03,253 --> 01:33:05,213
Speaker 3: Because my wife's a doctor, so I sort of look

1861
01:33:05,213 --> 01:33:09,213
Speaker 3: at it. This this stuff AI's ability to diagnos is

1862
01:33:09,452 --> 01:33:14,372
Speaker 3: far more accurate as than a doctor. Now, you've got

1863
01:33:14,412 --> 01:33:18,692
Speaker 3: to give it the right information, et cetera. You know,

1864
01:33:19,293 --> 01:33:21,732
Speaker 3: you just got to go for it. And I'll give

1865
01:33:21,732 --> 01:33:23,973
Speaker 3: you an example. I had a guy who used to

1866
01:33:24,093 --> 01:33:28,452
Speaker 3: do all his accounting in an exercise book, and he

1867
01:33:28,532 --> 01:33:32,612
Speaker 3: would take a weekend a month or be two months

1868
01:33:32,652 --> 01:33:35,892
Speaker 3: to do his GST and so his business was really

1869
01:33:36,093 --> 01:33:38,093
Speaker 3: cramped by the fact that he didn't want to have

1870
01:33:38,173 --> 01:33:41,972
Speaker 3: any more customers. I put him onto an accounting software

1871
01:33:42,492 --> 01:33:46,093
Speaker 3: and his business just took off. And I would say

1872
01:33:46,173 --> 01:33:49,492
Speaker 3: he now turns over probably a million dollars a month. Wow,

1873
01:33:49,532 --> 01:33:52,253
Speaker 3: because that that cap was taken off his business.

1874
01:33:52,612 --> 01:33:55,532
Speaker 2: Yeah, and that's that that's AI. When it's when it's

1875
01:33:55,732 --> 01:33:58,572
Speaker 2: working in the best way it should is when it

1876
01:33:58,732 --> 01:34:04,412
Speaker 2: takes away the repetitive tasks that that that you are

1877
01:34:04,452 --> 01:34:08,612
Speaker 2: taking up all your time and energy, so you can

1878
01:34:09,053 --> 01:34:12,932
Speaker 2: then use your creativity or use your time to further

1879
01:34:12,973 --> 01:34:16,333
Speaker 2: your business and whatever way possible. That's when it's fantastic.

1880
01:34:16,372 --> 01:34:21,452
Speaker 2: Because I run three little companies and you know, I

1881
01:34:21,532 --> 01:34:24,133
Speaker 2: have an accountant that runs all of them with me,

1882
01:34:24,293 --> 01:34:27,732
Speaker 2: but so much of it now is done through through

1883
01:34:27,893 --> 01:34:32,492
Speaker 2: zero that that my accounting bills are lower. But also

1884
01:34:32,652 --> 01:34:34,772
Speaker 2: that's because I'm not getting someone to spend or I'm

1885
01:34:34,853 --> 01:34:37,093
Speaker 2: not spending just the amount of time I used to

1886
01:34:37,133 --> 01:34:40,013
Speaker 2: spend just going through receipts and just doing that. That

1887
01:34:40,372 --> 01:34:45,052
Speaker 2: that sort of that sort of grind that that anything

1888
01:34:45,093 --> 01:34:47,052
Speaker 2: can do. So in the perfect world, that's what ALI

1889
01:34:47,133 --> 01:34:49,133
Speaker 2: takes us off us and then we then you have

1890
01:34:49,372 --> 01:34:51,492
Speaker 2: the accountant at the top that's cooking the box for

1891
01:34:51,572 --> 01:34:54,612
Speaker 2: you and getting creative, but.

1892
01:34:54,732 --> 01:34:58,812
Speaker 3: Like psychologically it takes the capo as well, you know,

1893
01:34:59,293 --> 01:35:02,612
Speaker 3: and you say, you know, like for instance, there's I

1894
01:35:02,732 --> 01:35:05,972
Speaker 3: went on to a Saturday where this guy was talking

1895
01:35:06,013 --> 01:35:09,213
Speaker 3: about everything you can do with AI and he showed

1896
01:35:09,333 --> 01:35:12,612
Speaker 3: us that in twenty I think it was twenty minutes,

1897
01:35:12,732 --> 01:35:16,973
Speaker 3: it took AI to completely produce a whole website with

1898
01:35:17,253 --> 01:35:20,293
Speaker 3: everything you wanted on it, and all he gave it

1899
01:35:20,492 --> 01:35:23,812
Speaker 3: was some basic information and our website was done.

1900
01:35:24,013 --> 01:35:24,253
Speaker 4: Yeah.

1901
01:35:24,492 --> 01:35:27,732
Speaker 3: Well, people would say, oh, I don't know I could

1902
01:35:27,772 --> 01:35:29,972
Speaker 3: have a business, because you know, there's all these things

1903
01:35:30,013 --> 01:35:32,092
Speaker 3: you got to do. You just punch it into AI

1904
01:35:32,213 --> 01:35:35,412
Speaker 3: and it produces everything and you can then get on

1905
01:35:35,572 --> 01:35:35,892
Speaker 3: with what you.

1906
01:35:35,973 --> 01:35:37,052
Speaker 4: Want to do exactly.

1907
01:35:37,173 --> 01:35:39,053
Speaker 2: The only problem is there the person that had the

1908
01:35:39,173 --> 01:35:42,133
Speaker 2: job that was making the websites now longer no longer

1909
01:35:42,173 --> 01:35:42,652
Speaker 2: has a job.

1910
01:35:42,772 --> 01:35:45,532
Speaker 4: But to Grant's point, and I think he is correct

1911
01:35:45,652 --> 01:35:49,652
Speaker 4: that humans will find jobs to do once AI starts

1912
01:35:49,692 --> 01:35:51,692
Speaker 4: automating and taking over these other jobs. They've got no

1913
01:35:51,812 --> 01:35:53,852
Speaker 4: doubt about it. I mean you just go back through

1914
01:35:53,973 --> 01:35:56,932
Speaker 4: history or just when they came out with the car

1915
01:35:57,253 --> 01:35:59,852
Speaker 4: and all the people on the horse and cart genuinely said,

1916
01:35:59,893 --> 01:36:01,652
Speaker 4: this is ludicrous. What are all the horses going to do?

1917
01:36:01,692 --> 01:36:03,213
Speaker 4: We've got all these horses, they're not going to have

1918
01:36:03,253 --> 01:36:03,572
Speaker 4: a job.

1919
01:36:03,692 --> 01:36:06,213
Speaker 2: Well if we if humans go like the horses, do

1920
01:36:06,213 --> 01:36:09,013
Speaker 2: you know what happened? All those horses fed to other

1921
01:36:09,093 --> 01:36:11,852
Speaker 2: animals became glue. And how many horses do you see

1922
01:36:11,893 --> 01:36:14,372
Speaker 2: out on the street right now? Tyler? Yeah, I don't

1923
01:36:14,372 --> 01:36:15,692
Speaker 2: know if that's the great example you think.

1924
01:36:15,933 --> 01:36:17,732
Speaker 4: I love a good horse. But just on the farmers,

1925
01:36:17,772 --> 01:36:20,772
Speaker 4: there were eighty percent of the jobs were farmers back

1926
01:36:20,853 --> 01:36:22,932
Speaker 4: in eighteen ninety in the US. Now it's two percent.

1927
01:36:23,173 --> 01:36:25,213
Speaker 4: So we find things to do. I think this whole

1928
01:36:25,253 --> 01:36:27,812
Speaker 4: freak out about AI. We're gonna be all right.

1929
01:36:27,772 --> 01:36:30,852
Speaker 2: Well, I've got a theory on that and I'll put

1930
01:36:30,893 --> 01:36:33,572
Speaker 2: it to you. And also this textures has made a

1931
01:36:33,612 --> 01:36:36,692
Speaker 2: really good point to High team. Why don't you ask

1932
01:36:36,812 --> 01:36:39,652
Speaker 2: AI if it's good in schools or not? So we'll

1933
01:36:39,692 --> 01:36:41,692
Speaker 2: do that. Well, I'll ask AI if it's good. It's

1934
01:36:41,692 --> 01:36:43,892
Speaker 2: going to get our answer to this question from AI.

1935
01:36:44,133 --> 01:36:45,213
Speaker 4: Headlines coming up.

1936
01:36:47,692 --> 01:36:48,253
Speaker 2: US talks.

1937
01:36:48,293 --> 01:36:52,492
Speaker 14: It'd be headlines with Blue bubble taxis. It's no trouble

1938
01:36:52,572 --> 01:36:56,253
Speaker 14: with the blue bubble. The Public Service Associations ask the

1939
01:36:56,412 --> 01:37:00,213
Speaker 14: Auditor General to check proposals to cut twenty three Health

1940
01:37:00,293 --> 01:37:04,052
Speaker 14: New Zealand fraud and audit roles. The Health Agency says

1941
01:37:04,093 --> 01:37:09,652
Speaker 14: it's cutting duplication created when DHBs became Health News. The

1942
01:37:09,732 --> 01:37:13,532
Speaker 14: Funeral Directors' Association says a recent case of a body

1943
01:37:13,652 --> 01:37:17,452
Speaker 14: being mishandled highlights the need for tighter legal control. Since

1944
01:37:17,572 --> 01:37:22,372
Speaker 14: nineteen thirty seven, residents living in South Duned and Surrey Street,

1945
01:37:22,452 --> 01:37:27,093
Speaker 14: which is regularly flooded with sewage, are demanding urgent counsel action.

1946
01:37:28,013 --> 01:37:30,972
Speaker 14: Police are looking into three teens being assaulted in Auckland's

1947
01:37:31,013 --> 01:37:34,333
Speaker 14: Brown's Bay on Saturday night. By a group who chased

1948
01:37:34,412 --> 01:37:38,852
Speaker 14: and robbed them. The Readerstar General decline sixty one names

1949
01:37:38,893 --> 01:37:42,812
Speaker 14: for new babies in twenty twenty four, including King, Prince,

1950
01:37:42,933 --> 01:37:48,173
Speaker 14: Princess and Fanny. Organized crime syndicates are making millions from

1951
01:37:48,213 --> 01:37:50,092
Speaker 14: smuggling tobacco into New Zealand.

1952
01:37:50,372 --> 01:37:52,652
Speaker 2: See the full story at Enzit Herald Premium.

1953
01:37:53,013 --> 01:37:54,812
Speaker 14: Now back to Matt Eath and Tyler Adams.

1954
01:37:55,093 --> 01:37:57,213
Speaker 4: Thank you very much, Rayllan, and we're talking about AI

1955
01:37:57,612 --> 01:38:01,852
Speaker 4: technology in schools, both used by the students and the teachers.

1956
01:38:01,893 --> 01:38:03,732
Speaker 4: Love to your thoughts on oh eight hundred and eighty

1957
01:38:03,933 --> 01:38:06,333
Speaker 4: ten eighty, Johnny, what's your thoughts?

1958
01:38:07,612 --> 01:38:07,772
Speaker 19: Oh?

1959
01:38:08,612 --> 01:38:15,253
Speaker 6: Yeah, I used the AI quite a lot, and just

1960
01:38:15,293 --> 01:38:19,092
Speaker 6: a few days ago, after interacting with it for six months,

1961
01:38:19,173 --> 01:38:22,093
Speaker 6: I said, can you give me an appraisal of some

1962
01:38:22,173 --> 01:38:27,492
Speaker 6: of my strengths and weaknesses and areas need to work on?

1963
01:38:28,492 --> 01:38:31,452
Speaker 6: And I gave it some parameters and what I got

1964
01:38:31,572 --> 01:38:34,772
Speaker 6: was quite sort of a narcissistic, vain response, And I thought,

1965
01:38:34,893 --> 01:38:37,732
Speaker 6: is this what it's learned off me? After six months?

1966
01:38:39,452 --> 01:38:42,973
Speaker 6: And I said, you know, stop stop calling my just

1967
01:38:43,253 --> 01:38:47,572
Speaker 6: you know, I want the straight up stuff because I've

1968
01:38:47,973 --> 01:38:53,012
Speaker 6: got some serious things I'm involved. And then it managed

1969
01:38:53,013 --> 01:38:55,692
Speaker 6: to me, and I'm interested in the best possible outcome

1970
01:38:55,732 --> 01:38:59,572
Speaker 6: from my children. So I read a lot of books too,

1971
01:38:59,572 --> 01:39:01,093
Speaker 6: and I've got to the library. I'm a student and

1972
01:39:01,173 --> 01:39:06,252
Speaker 6: I use AI at school and doing a PA referencing

1973
01:39:06,333 --> 01:39:08,492
Speaker 6: and things like that. I had to ask AI if

1974
01:39:08,532 --> 01:39:12,172
Speaker 6: it could teach me how to cite and reference properly,

1975
01:39:13,973 --> 01:39:17,732
Speaker 6: so out of practice, and I've changed from being an audio,

1976
01:39:18,612 --> 01:39:21,173
Speaker 6: audio and visual learner into a kind aesthetic learner through

1977
01:39:21,213 --> 01:39:24,013
Speaker 6: a brain injury. So anyway, the response I got back

1978
01:39:24,093 --> 01:39:28,692
Speaker 6: was still some like you know, analogies and sweet nothings

1979
01:39:28,732 --> 01:39:32,492
Speaker 6: and wasn't mean and I didn't didn't really address And

1980
01:39:32,532 --> 01:39:34,732
Speaker 6: I've talked to about a lot of stuff. So in

1981
01:39:34,853 --> 01:39:37,532
Speaker 6: terms of being useful and schools, it's helpful for me.

1982
01:39:39,053 --> 01:39:40,652
Speaker 6: And when I put at the bottom of anything I

1983
01:39:41,293 --> 01:39:45,652
Speaker 6: submit and work is that I've been assisted by AI.

1984
01:39:49,652 --> 01:39:52,812
Speaker 4: Oh I think a I just took you out, Johnnyeah,

1985
01:39:53,372 --> 01:39:54,333
Speaker 4: that's that's a pretty.

1986
01:39:56,652 --> 01:39:56,852
Speaker 13: Yeah.

1987
01:39:58,933 --> 01:40:03,732
Speaker 6: So bias and inequality, you know, bias inequality. AI systems

1988
01:40:03,812 --> 01:40:06,812
Speaker 6: they can reflect biases and the data that you're teaching them,

1989
01:40:07,492 --> 01:40:13,932
Speaker 6: so unfair outcomes and you know, reduced you were an interaction.

1990
01:40:14,093 --> 01:40:17,053
Speaker 6: I would say the probably the biggest thing. A over

1991
01:40:17,173 --> 01:40:20,532
Speaker 6: reliance could limit opportunities for kids to.

1992
01:40:22,013 --> 01:40:23,692
Speaker 2: You haven't put this question into a a have you.

1993
01:40:25,013 --> 01:40:27,333
Speaker 2: It sounds like you might be This is just from

1994
01:40:27,372 --> 01:40:29,492
Speaker 2: your brain. You're not an a A Johnny.

1995
01:40:32,372 --> 01:40:33,132
Speaker 4: We know, Johnny.

1996
01:40:33,612 --> 01:40:35,933
Speaker 2: I've got a question for you. Johnny, I've got a

1997
01:40:36,013 --> 01:40:39,012
Speaker 2: question for you. I've got a question for you, Johnny.

1998
01:40:39,293 --> 01:40:42,253
Speaker 2: When when you asked the you know, was it chat

1999
01:40:42,492 --> 01:40:44,093
Speaker 2: GP that you were using?

2000
01:40:45,692 --> 01:40:47,972
Speaker 6: Yeah, yeah, I used chet GPT yeah yeah.

2001
01:40:48,013 --> 01:40:50,692
Speaker 2: Yeah. So so when you asked it to rate rate

2002
01:40:50,772 --> 01:40:53,852
Speaker 2: yourself rate you had you just been running the same

2003
01:40:54,133 --> 01:40:57,532
Speaker 2: the same chat. So it was looking back at every

2004
01:40:57,692 --> 01:40:59,772
Speaker 2: everything that you've used in there, because you know, when

2005
01:40:59,812 --> 01:41:02,173
Speaker 2: you're start a new chat, then it stops referencing what's

2006
01:41:02,293 --> 01:41:05,173
Speaker 2: been previous in there. So so what what what was

2007
01:41:05,213 --> 01:41:06,612
Speaker 2: the inputting?

2008
01:41:08,093 --> 01:41:10,772
Speaker 6: I I asked it to go through all of our chats,

2009
01:41:11,053 --> 01:41:13,892
Speaker 6: all of the questions. Yes, and I've got the plus

2010
01:41:13,933 --> 01:41:16,612
Speaker 6: so I've got a large memory in so we've got

2011
01:41:16,732 --> 01:41:19,253
Speaker 6: from i know, October last year.

2012
01:41:19,412 --> 01:41:22,372
Speaker 2: Yeah. Right, Well, then maybe it was right, Johnny. Maybe

2013
01:41:22,412 --> 01:41:25,053
Speaker 2: you are maybe maybe it wasn't greasing you up. Maybe

2014
01:41:25,173 --> 01:41:27,492
Speaker 2: maybe you are all that I was just doing what Yeah,

2015
01:41:27,812 --> 01:41:30,652
Speaker 2: I've got to do. I totally agree with what Johnny's

2016
01:41:30,652 --> 01:41:33,652
Speaker 2: saying there around citations. When I was writing my book,

2017
01:41:34,013 --> 01:41:37,093
Speaker 2: so the news AI for my entire book, but when

2018
01:41:37,173 --> 01:41:40,253
Speaker 2: it came to because I've written out all the references

2019
01:41:40,612 --> 01:41:42,452
Speaker 2: as I've been going, and they are an absolute mess.

2020
01:41:42,893 --> 01:41:44,892
Speaker 2: So I just put them in and said, put these

2021
01:41:44,933 --> 01:41:49,133
Speaker 2: in the Cambridge. You know, citation format and things like

2022
01:41:49,213 --> 01:41:50,612
Speaker 2: that are fantastic.

2023
01:41:50,452 --> 01:41:53,253
Speaker 4: And that's what they you know, arguably the students should

2024
01:41:53,253 --> 01:41:56,173
Speaker 4: be using that AO for at schools as those those

2025
01:41:56,372 --> 01:41:58,492
Speaker 4: kind of arduous tasks that.

2026
01:41:58,692 --> 01:42:02,173
Speaker 2: You don't really learn anything from. Yeah, they just time wasters, really, Yeah,

2027
01:42:02,213 --> 01:42:04,092
Speaker 2: but they need to be done. I'm a chartered accountant,

2028
01:42:04,093 --> 01:42:07,812
Speaker 2: says Joeanne. Zero was great but doesn't ever replace accountants.

2029
01:42:07,853 --> 01:42:10,452
Speaker 2: The business owner doesn't have the knowledge to ensure coding

2030
01:42:10,532 --> 01:42:12,812
Speaker 2: is appropriate and treated correctly for text purposes. I agree

2031
01:42:12,853 --> 01:42:16,572
Speaker 2: with that. I am, so I use zero to code everything,

2032
01:42:16,652 --> 01:42:18,932
Speaker 2: but then my account it rings up and says that's

2033
01:42:19,053 --> 01:42:22,213
Speaker 2: not right. What are you doing here? This is rubbish?

2034
01:42:22,532 --> 01:42:25,532
Speaker 2: And also there's nothing like that feeling for your business

2035
01:42:25,612 --> 01:42:28,093
Speaker 2: and for yourself when you get the little black book

2036
01:42:28,093 --> 01:42:30,812
Speaker 2: from your charted accountment that says that they've gone through,

2037
01:42:31,173 --> 01:42:34,893
Speaker 2: They've sorted everything out and you're completely legal for the

2038
01:42:34,973 --> 01:42:37,732
Speaker 2: year and everything everything's done. You know, all your tax

2039
01:42:37,853 --> 01:42:43,052
Speaker 2: is paid and everything has been sorted. So the league

2040
01:42:43,093 --> 01:42:47,253
Speaker 2: work involved in that absolutely, and more can be done

2041
01:42:47,333 --> 01:42:50,213
Speaker 2: and people can do things more efficiently and quickly. But

2042
01:42:50,333 --> 01:42:54,053
Speaker 2: in the end, having that human being that you know

2043
01:42:54,532 --> 01:42:57,293
Speaker 2: certifies that what has been done is correct.

2044
01:42:57,652 --> 01:42:58,973
Speaker 4: ID is not going to come after you.

2045
01:42:59,093 --> 01:43:00,692
Speaker 2: It's huge, hugely important.

2046
01:43:00,772 --> 01:43:02,852
Speaker 4: Yeah, the stick so yaday, guys, I just said my

2047
01:43:02,893 --> 01:43:05,933
Speaker 4: first doctor's appointment with AI doing the notes, would be

2048
01:43:06,013 --> 01:43:09,013
Speaker 4: fascinated to read them. I'm sixty seven. When I went

2049
01:43:09,093 --> 01:43:12,092
Speaker 4: through school, I was being taught without knowing what jobs

2050
01:43:12,173 --> 01:43:14,333
Speaker 4: we're going to be available in twenty thirty forty years.

2051
01:43:14,612 --> 01:43:17,893
Speaker 4: That doesn't change through the generation. It is not a

2052
01:43:18,013 --> 01:43:21,972
Speaker 4: new concept. One of my daughter's teachers used that excuse

2053
01:43:22,372 --> 01:43:24,652
Speaker 4: as an excuse rather twenty five years ago from Sam.

2054
01:43:24,893 --> 01:43:28,333
Speaker 2: Yeah, that's absolutely true that we've got We've never had

2055
01:43:28,372 --> 01:43:31,213
Speaker 2: any idea and we would be very surprised twenty five

2056
01:43:31,293 --> 01:43:33,812
Speaker 2: years ago to see how we're making our livings now,

2057
01:43:34,532 --> 01:43:41,732
Speaker 2: you know, the you know we've there was this great

2058
01:43:41,812 --> 01:43:43,892
Speaker 2: story that you can see from New Zealand Television from

2059
01:43:43,893 --> 01:43:45,812
Speaker 2: the seventies, and it was talking about how much free

2060
01:43:45,893 --> 01:43:47,732
Speaker 2: time we were going to have by about the year

2061
01:43:47,772 --> 01:43:51,013
Speaker 2: twenty ten, because robots will be doing everything for us.

2062
01:43:51,333 --> 01:43:53,412
Speaker 2: And then you jump to twenty ten, and the whole

2063
01:43:53,853 --> 01:43:58,333
Speaker 2: purpose of the article was saying, what are we going

2064
01:43:58,412 --> 01:43:59,492
Speaker 2: to do with that time? And there was all this

2065
01:43:59,612 --> 01:44:00,973
Speaker 2: leisure time we're going to have, And it turns out

2066
01:44:01,013 --> 01:44:03,652
Speaker 2: we work more hours now than we've ever had. Yeah, exactly,

2067
01:44:04,013 --> 01:44:05,732
Speaker 2: I'm free surprised how the future turns out.

2068
01:44:05,812 --> 01:44:07,692
Speaker 4: Oh, eight hundred and eighty ten eighty is the number

2069
01:44:07,692 --> 01:44:09,812
Speaker 4: to call love to hear your thoughts about AI use

2070
01:44:09,893 --> 01:44:12,652
Speaker 4: in schools, both by students and teachers. It is twenty

2071
01:44:12,692 --> 01:44:14,532
Speaker 4: one to four the.

2072
01:44:14,652 --> 01:44:17,173
Speaker 1: Issues that affect you, and a bit of fun along

2073
01:44:17,253 --> 01:44:20,812
Speaker 1: the way. Matt Heath and Taylor Adams afternoons used talks.

2074
01:44:20,853 --> 01:44:21,173
Speaker 11: He'd be.

2075
01:44:22,772 --> 01:44:25,852
Speaker 4: News talks, he'd be it is eighteen to form. We're

2076
01:44:25,853 --> 01:44:27,972
Speaker 4: talking about the use of AI in schools.

2077
01:44:28,452 --> 01:44:30,253
Speaker 2: This text here says Matt, what's wrong with you today?

2078
01:44:30,293 --> 01:44:33,053
Speaker 2: You are struggling to string two words coherently together. I

2079
01:44:33,133 --> 01:44:35,452
Speaker 2: was thinking the same thing. Text, But this is how

2080
01:44:35,532 --> 01:44:37,293
Speaker 2: you know this isn't an AI broadcast.

2081
01:44:37,492 --> 01:44:39,172
Speaker 4: Yeah, this is our point of difference.

2082
01:44:39,532 --> 01:44:42,492
Speaker 2: The fact that I struggle to string two words together

2083
01:44:43,013 --> 01:44:45,293
Speaker 2: just prosate AI would never make that kind of mistake.

2084
01:44:45,893 --> 01:44:49,213
Speaker 2: To quote Jessic parks Is Graham, life will find a way.

2085
01:44:49,293 --> 01:44:51,213
Speaker 2: When we were younger, the Internet came along and people

2086
01:44:51,253 --> 01:44:53,293
Speaker 2: were having the same conversation as you are having now

2087
01:44:53,412 --> 01:44:57,333
Speaker 2: around AI. Life will go on. My theory on it

2088
01:44:57,492 --> 01:45:00,732
Speaker 2: that I was going to stay before was trying to

2089
01:45:00,772 --> 01:45:03,892
Speaker 2: string some words together, as I think humans find other

2090
01:45:03,973 --> 01:45:07,532
Speaker 2: humans in interaction with other humans very very crucial.

2091
01:45:07,732 --> 01:45:07,932
Speaker 4: Yep.

2092
01:45:08,532 --> 01:45:10,933
Speaker 2: We love being around other humans, and I think that

2093
01:45:11,093 --> 01:45:12,933
Speaker 2: is always going to be a strong thing. It's the

2094
01:45:12,973 --> 01:45:16,133
Speaker 2: same reason why you could get in a print of

2095
01:45:16,452 --> 01:45:19,133
Speaker 2: the Mona Lisa, but it means nothing even if it

2096
01:45:19,213 --> 01:45:22,173
Speaker 2: was exactly recreated exactly the same as the Mona Lisa.

2097
01:45:22,572 --> 01:45:25,293
Speaker 2: The fact that Leonardo da Vinci hasn't touched it means

2098
01:45:25,372 --> 01:45:28,213
Speaker 2: and it hasn't been made by a human makes it worthless, right,

2099
01:45:28,652 --> 01:45:31,612
Speaker 2: So what humans do has worth. So I think in

2100
01:45:31,652 --> 01:45:35,053
Speaker 2: the future, things like the competency of being able to

2101
01:45:35,093 --> 01:45:37,772
Speaker 2: play a piano, AI might be able to create music.

2102
01:45:37,933 --> 01:45:39,933
Speaker 2: But if you go and see someone actually play the

2103
01:45:40,093 --> 01:45:42,772
Speaker 2: piano competently, there's an emotional aspect to it, and that

2104
01:45:42,853 --> 01:45:44,412
Speaker 2: will be important. And I think that's going to be

2105
01:45:44,492 --> 01:45:48,053
Speaker 2: true over everything. So I think quite the reverse of

2106
01:45:48,133 --> 01:45:52,333
Speaker 2: humans becoming less important, humans will become more important. Human

2107
01:45:52,412 --> 01:45:55,973
Speaker 2: craft and human creativity and things that can authentically be

2108
01:45:56,173 --> 01:45:59,012
Speaker 2: proven to be human will be of more and more value.

2109
01:45:59,333 --> 01:46:02,772
Speaker 2: As AI pumps out more and more rubbish, it will

2110
01:46:02,772 --> 01:46:06,772
Speaker 2: always have less value than humans because humans attach an

2111
01:46:06,812 --> 01:46:09,253
Speaker 2: emotional weight to things that other human beings have done

2112
01:46:09,293 --> 01:46:09,933
Speaker 2: and always.

2113
01:46:09,692 --> 01:46:11,812
Speaker 4: Well, yeah, I hope that's true, because it sounds like

2114
01:46:11,853 --> 01:46:14,732
Speaker 4: a beautiful future. I've got to say, Reese, what's your

2115
01:46:14,853 --> 01:46:15,213
Speaker 4: view on this?

2116
01:46:16,772 --> 01:46:19,892
Speaker 20: Yeah, hey, yeah, it's quite interested in school's I think

2117
01:46:19,973 --> 01:46:21,972
Speaker 20: it's just another pool.

2118
01:46:22,372 --> 01:46:22,652
Speaker 19: Really.

2119
01:46:22,933 --> 01:46:26,293
Speaker 20: I remember when I was back in school, we were

2120
01:46:26,572 --> 01:46:29,412
Speaker 20: just getting out the computers and we just had the

2121
01:46:29,452 --> 01:46:32,772
Speaker 20: green screen and it was very basic, you know, and

2122
01:46:33,173 --> 01:46:35,572
Speaker 20: you do basic stuff on the computer and you look

2123
01:46:35,612 --> 01:46:39,093
Speaker 20: at it now and in my job in safety, so

2124
01:46:39,213 --> 01:46:41,692
Speaker 20: I is safety for a living and I use it

2125
01:46:41,812 --> 01:46:44,572
Speaker 20: quite a bit now, but mainly just to fact check,

2126
01:46:44,772 --> 01:46:49,013
Speaker 20: reference check legislation risks, and you know, put off all

2127
01:46:49,013 --> 01:46:51,133
Speaker 20: pods of information. So I think, you know, used in

2128
01:46:51,173 --> 01:46:54,612
Speaker 20: the right context. I think the skep the risk is

2129
01:46:54,652 --> 01:46:55,772
Speaker 20: I think sometimes is.

2130
01:46:57,492 --> 01:46:58,253
Speaker 5: People rely on it.

2131
01:46:58,812 --> 01:47:01,652
Speaker 20: You get all the information they need, right if you

2132
01:47:01,812 --> 01:47:04,173
Speaker 20: if you don't already know the information, or you don't

2133
01:47:04,253 --> 01:47:06,612
Speaker 20: fact check or double chip the information, I think that's

2134
01:47:06,652 --> 01:47:07,732
Speaker 20: where the risk comes back.

2135
01:47:08,452 --> 01:47:10,772
Speaker 4: Yeah, and we're when you know, I'm just talking about

2136
01:47:10,853 --> 01:47:13,492
Speaker 4: chet GPT here. I even utilize some of the other AI,

2137
01:47:13,692 --> 01:47:18,252
Speaker 4: but certainly sometimes when I've put asked chet GPT questions,

2138
01:47:18,293 --> 01:47:21,133
Speaker 4: it's giving me answers that I need to go and

2139
01:47:21,173 --> 01:47:22,532
Speaker 4: double check because I've had a look at the answer

2140
01:47:22,572 --> 01:47:23,932
Speaker 4: and say that doesn't sound quite right.

2141
01:47:24,053 --> 01:47:26,772
Speaker 2: Well, everyone's seen this on the Google search. It's throwing

2142
01:47:26,812 --> 01:47:30,773
Speaker 2: up that AI. It's the term they use is hallucinations

2143
01:47:30,812 --> 01:47:35,452
Speaker 2: and its errors from the training data and this this

2144
01:47:35,532 --> 01:47:37,652
Speaker 2: will happen. So it's not a search engine. So people,

2145
01:47:38,333 --> 01:47:40,492
Speaker 2: what you're saying, Reese, is you use it to check

2146
01:47:40,732 --> 01:47:43,253
Speaker 2: what you put in. So what you put in it

2147
01:47:43,333 --> 01:47:46,652
Speaker 2: can have an bring an answer back. But anyone can

2148
01:47:46,732 --> 01:47:48,933
Speaker 2: look up anything as I did before on KIWI what

2149
01:47:49,213 --> 01:47:51,453
Speaker 2: what the kiwis? Yeah, it's going to have a hallucination

2150
01:47:51,572 --> 01:47:54,093
Speaker 2: because it's just what goes in garbage and garbage out.

2151
01:47:54,772 --> 01:47:57,532
Speaker 2: So if it's if if you set the para parameters

2152
01:47:57,572 --> 01:47:59,412
Speaker 2: of what it's looking at. Then it can give you

2153
01:47:59,452 --> 01:48:01,932
Speaker 2: an answer. It can check code, it can check things

2154
01:48:02,013 --> 01:48:05,933
Speaker 2: towards a statute exactly what you're saying, Reese. But the

2155
01:48:06,013 --> 01:48:10,452
Speaker 2: whole actuality of human thought it struggles with because it

2156
01:48:10,532 --> 01:48:14,973
Speaker 2: can't get sarcasm, can't get humor, and it can't get it.

2157
01:48:15,133 --> 01:48:16,932
Speaker 2: There's a whole lot of different nuances in the way

2158
01:48:17,013 --> 01:48:19,572
Speaker 2: humans interact that will never be able to get. So

2159
01:48:19,652 --> 01:48:21,293
Speaker 2: it's not a search engine, but it is a tool,

2160
01:48:21,293 --> 01:48:23,612
Speaker 2: as you say race, Yeah, definitely.

2161
01:48:23,692 --> 01:48:25,492
Speaker 20: Yeah, And you know, I like to say it's all

2162
01:48:25,532 --> 01:48:27,532
Speaker 20: about how you use it, right, If you use him

2163
01:48:27,652 --> 01:48:30,492
Speaker 20: properly and use it well, then it could be a

2164
01:48:30,572 --> 01:48:33,093
Speaker 20: real good aid. And again, and the thing is, I

2165
01:48:33,133 --> 01:48:37,213
Speaker 20: suppose if you use it incorrectly, it could probably indient

2166
01:48:37,452 --> 01:48:38,412
Speaker 20: it make a job longer.

2167
01:48:42,532 --> 01:48:44,612
Speaker 5: Try and use it and it's really effective.

2168
01:48:45,173 --> 01:48:47,372
Speaker 2: Yeah, yeah, well if it goes off down the wrong

2169
01:48:47,452 --> 01:48:48,532
Speaker 2: path for long enough.

2170
01:48:48,812 --> 01:48:54,093
Speaker 4: You know exactly, Greg, Hi, har An, you guys, Yeah,

2171
01:48:54,173 --> 01:48:55,772
Speaker 4: very good, good to chat. What do you think about

2172
01:48:55,772 --> 01:48:56,652
Speaker 4: AI and schools?

2173
01:48:57,812 --> 01:48:59,772
Speaker 13: Yeah, it's an interesting one. I think the first thing

2174
01:48:59,933 --> 01:49:00,853
Speaker 13: is a misnoma.

2175
01:49:00,933 --> 01:49:01,572
Speaker 17: I was just take good.

2176
01:49:01,612 --> 01:49:06,492
Speaker 13: It's intelligence. It's not intelligent. These are just algorithms that

2177
01:49:06,572 --> 01:49:10,092
Speaker 13: are working. They don't have and they don't have moral standards,

2178
01:49:10,093 --> 01:49:13,133
Speaker 13: they don't have ethics. It's just a very fast way

2179
01:49:13,732 --> 01:49:17,452
Speaker 13: to process a lot of information. And that's why in

2180
01:49:17,652 --> 01:49:20,333
Speaker 13: video is worth so much money because they're producing chips

2181
01:49:20,372 --> 01:49:24,772
Speaker 13: that can actually just process fast amounts of information seriously quickly.

2182
01:49:25,412 --> 01:49:29,013
Speaker 13: So as far as intelligent scope, no, it's not intelligent

2183
01:49:29,093 --> 01:49:29,772
Speaker 13: in anyway.

2184
01:49:30,333 --> 01:49:32,852
Speaker 2: Great to describe it just basically tell me if I'm

2185
01:49:32,853 --> 01:49:35,732
Speaker 2: getting this right here, If you've got a word AI

2186
01:49:35,853 --> 01:49:39,253
Speaker 2: has learned statistically by going through everything an AI model

2187
01:49:39,372 --> 01:49:42,372
Speaker 2: a large language, moral what statistically is most likely to

2188
01:49:42,452 --> 01:49:45,933
Speaker 2: be the next word, and then on an algorithm on

2189
01:49:46,133 --> 01:49:47,012
Speaker 2: decreasing scale.

2190
01:49:48,133 --> 01:49:51,013
Speaker 13: That's exactly right. It's just it's just really fast at

2191
01:49:51,013 --> 01:49:53,213
Speaker 13: it to look at it, if you look at it's

2192
01:49:53,293 --> 01:49:55,812
Speaker 13: use in schools, right, So when when I went to school,

2193
01:49:56,253 --> 01:49:57,973
Speaker 13: you know, if you want to recess something, you go

2194
01:49:58,053 --> 01:50:01,492
Speaker 13: to a liver, you go through you know, textbooks, encyclopedias,

2195
01:50:01,492 --> 01:50:03,933
Speaker 13: and you collate the information. All this is doing is

2196
01:50:03,973 --> 01:50:08,652
Speaker 13: collating information super fast. So you know, I think should

2197
01:50:08,652 --> 01:50:11,092
Speaker 13: be used in schools because what it's doing is speeding

2198
01:50:11,173 --> 01:50:14,093
Speaker 13: up education because of all the time that we're used

2199
01:50:14,093 --> 01:50:18,213
Speaker 13: to inverticonas waste collating or looking for information, but then

2200
01:50:18,732 --> 01:50:23,133
Speaker 13: it's around the interpretation of that information into facts. So

2201
01:50:24,093 --> 01:50:26,452
Speaker 13: you know, there's a couple of simple ways that you

2202
01:50:26,492 --> 01:50:29,412
Speaker 13: can actually get to deal with it. As one, you

2203
01:50:29,532 --> 01:50:32,333
Speaker 13: move to oral exams or be you go to written

2204
01:50:32,412 --> 01:50:35,013
Speaker 13: reports rather than types, so that the person actually has

2205
01:50:35,053 --> 01:50:38,253
Speaker 13: to write it out, you know, write out the answer.

2206
01:50:38,333 --> 01:50:40,612
Speaker 13: Sure they could copy it, but at the end of

2207
01:50:40,652 --> 01:50:44,893
Speaker 13: the day, what we're really looking at here is a

2208
01:50:45,053 --> 01:50:48,652
Speaker 13: tool that allows you to collate vast amounts of information

2209
01:50:48,933 --> 01:50:53,293
Speaker 13: really quickly, which should actually enhance education rather than stifle.

2210
01:50:54,213 --> 01:50:57,173
Speaker 2: Yeah, I guess the problem comes in for people that

2211
01:50:57,293 --> 01:51:00,852
Speaker 2: are in jobs that are wrote jobs and are repetitive jobs,

2212
01:51:01,013 --> 01:51:04,492
Speaker 2: the sort of monkey work jobs. Those jobs are likely

2213
01:51:04,652 --> 01:51:05,652
Speaker 2: to disappear, aren't they. Green.

2214
01:51:06,853 --> 01:51:08,333
Speaker 13: Yeah, that's true. But you know, you guys are talking

2215
01:51:08,333 --> 01:51:11,172
Speaker 13: talking about earlier, you know, around education in the seventies,

2216
01:51:11,213 --> 01:51:13,372
Speaker 13: when we're going we're going to have all these leisures,

2217
01:51:13,492 --> 01:51:16,652
Speaker 13: the legends. It's just a rare and I remember it

2218
01:51:16,692 --> 01:51:19,493
Speaker 13: pretty well, but it's just a it's a re alignment

2219
01:51:20,133 --> 01:51:23,492
Speaker 13: of the workforce, which doesn't happen instantly. It happens over time,

2220
01:51:24,293 --> 01:51:27,932
Speaker 13: So so I I think, you know, as everyone's talked

2221
01:51:27,933 --> 01:51:32,492
Speaker 13: about as education needs to move forward, embrace the tool,

2222
01:51:33,253 --> 01:51:36,612
Speaker 13: and because because as they embrace the tool going forward,

2223
01:51:37,253 --> 01:51:41,253
Speaker 13: the other opportunities and the other job types become more obvious.

2224
01:51:41,293 --> 01:51:43,732
Speaker 13: I mean, you know, AI is not going to wire

2225
01:51:43,853 --> 01:51:45,812
Speaker 13: your house, and it's not going to do your plumbing,

2226
01:51:45,933 --> 01:51:49,692
Speaker 13: and you know, so you know there are always going

2227
01:51:49,732 --> 01:51:51,492
Speaker 13: to be jobs out there, it's just they're going to

2228
01:51:51,532 --> 01:51:52,572
Speaker 13: look they're going to look different.

2229
01:51:52,973 --> 01:51:54,772
Speaker 4: Is it just the more efficient Google is what you're

2230
01:51:54,772 --> 01:51:57,253
Speaker 4: saying Greek, and we all freak down when Google first hit.

2231
01:51:57,412 --> 01:51:59,733
Speaker 4: You know, it's not a search.

2232
01:51:59,532 --> 01:52:03,333
Speaker 2: Engine at all. That's that's the misunderstanding. Originally early on

2233
01:52:03,492 --> 01:52:07,132
Speaker 2: people thought that that's what was going on with chet GPT,

2234
01:52:07,333 --> 01:52:09,492
Speaker 2: that it was a search engine. It's exactly not that.

2235
01:52:10,692 --> 01:52:16,253
Speaker 13: No, it's exactly right, because the search engines will find

2236
01:52:16,853 --> 01:52:19,972
Speaker 13: where pages which will give you information, whereas these things

2237
01:52:20,013 --> 01:52:22,852
Speaker 13: are collating the concepts and the words, so you know,

2238
01:52:22,933 --> 01:52:27,812
Speaker 13: there's no intelligence involved here. They are just super fast.

2239
01:52:28,053 --> 01:52:30,333
Speaker 2: Do you believe do you believe? You know, as a

2240
01:52:30,412 --> 01:52:33,253
Speaker 2: lot of people are saying now that that artificial general

2241
01:52:33,333 --> 01:52:37,973
Speaker 2: intelligence can grow out of a large language model, the

2242
01:52:38,093 --> 01:52:40,133
Speaker 2: singularity as they call it. Do you do you see

2243
01:52:40,173 --> 01:52:41,133
Speaker 2: that as a possibility.

2244
01:52:42,572 --> 01:52:47,013
Speaker 13: I think the ability to collate information will will that

2245
01:52:47,333 --> 01:52:49,372
Speaker 13: will just get fast and faster. But you've got to remember,

2246
01:52:49,732 --> 01:52:53,932
Speaker 13: the thing that links intelligence and human beings together is morals,

2247
01:52:54,732 --> 01:53:00,492
Speaker 13: is interpretation, it's understanding or empathy. It's all of the

2248
01:53:00,692 --> 01:53:03,412
Speaker 13: more I hate to say this, but the touchy fairly

2249
01:53:03,492 --> 01:53:06,893
Speaker 13: things that actually determines humanity and how we deal with

2250
01:53:07,013 --> 01:53:07,412
Speaker 13: each other.

2251
01:53:10,333 --> 01:53:12,452
Speaker 2: They talk about this though in terms of the you know,

2252
01:53:12,572 --> 01:53:15,852
Speaker 2: the what is it the Turkish chess machine, which is

2253
01:53:15,893 --> 01:53:18,892
Speaker 2: actually just a human And one of the interesting things

2254
01:53:18,933 --> 01:53:21,052
Speaker 2: that happened with AI because they, as you say, greg

2255
01:53:21,213 --> 01:53:25,532
Speaker 2: the morality. They try and enforce that morality on top

2256
01:53:25,572 --> 01:53:29,253
Speaker 2: of their AI model, and that's when things get confusing,

2257
01:53:29,452 --> 01:53:33,093
Speaker 2: because AI, then, as you say, doesn't have an intelligence,

2258
01:53:33,133 --> 01:53:35,533
Speaker 2: so that can skew it off in crazy directions.

2259
01:53:36,772 --> 01:53:40,812
Speaker 13: Well, and the other thing to realize as well is that,

2260
01:53:41,213 --> 01:53:43,732
Speaker 13: you know, there's the potential for AI to look for

2261
01:53:43,853 --> 01:53:47,612
Speaker 13: the simplest route, you know, from A to B in

2262
01:53:47,732 --> 01:53:51,572
Speaker 13: your life, but sometimes the hardest route or the harder

2263
01:53:51,692 --> 01:53:53,933
Speaker 13: route is the better route because of the things that

2264
01:53:54,053 --> 01:53:56,532
Speaker 13: you learn on the journey, and.

2265
01:53:56,572 --> 01:54:00,053
Speaker 4: That was pushing Greg. Is I generally think AI as

2266
01:54:00,093 --> 01:54:02,973
Speaker 4: it stands now, you still need that critical thinking to

2267
01:54:03,053 --> 01:54:05,492
Speaker 4: be able to challenge what it presents you to say,

2268
01:54:05,692 --> 01:54:08,572
Speaker 4: is that accurate? Is that really the best way forward

2269
01:54:08,612 --> 01:54:10,492
Speaker 4: for what I've asked of this particular AI.

2270
01:54:11,732 --> 01:54:14,452
Speaker 13: That's exactly right. I mean, not only there, but some

2271
01:54:14,692 --> 01:54:17,933
Speaker 13: you know, we all make inverder Koon's bad decisions, you know,

2272
01:54:18,093 --> 01:54:22,532
Speaker 13: through our lives. But I know all of us log

2273
01:54:22,732 --> 01:54:25,372
Speaker 13: back through our lives and generally go that was a

2274
01:54:25,532 --> 01:54:28,652
Speaker 13: really bad decision. But look what I learned. Look what

2275
01:54:28,772 --> 01:54:30,133
Speaker 13: I learned as a result of that.

2276
01:54:30,532 --> 01:54:33,852
Speaker 2: Yeah, yeah, well you know, I learned a lot shovel

2277
01:54:33,893 --> 01:54:37,693
Speaker 2: and gravel at Donaldson's nursery, you know, and anything could

2278
01:54:37,693 --> 01:54:39,333
Speaker 2: have done that, but I learned a lot doing it,

2279
01:54:39,413 --> 01:54:42,093
Speaker 2: that's for sure about myself. Hey, thank you so much

2280
01:54:42,093 --> 01:54:44,413
Speaker 2: for you called Greg. That's really insightful. I really appreciate it.

2281
01:54:44,653 --> 01:54:47,932
Speaker 4: Cheers, cheers Greg. It is seven to four, back three

2282
01:54:47,973 --> 01:54:49,852
Speaker 4: shortly the.

2283
01:54:49,973 --> 01:54:53,133
Speaker 1: Big stories, the big issues to the big trends and

2284
01:54:53,493 --> 01:54:57,253
Speaker 1: everything in between. Matt Heath and Taylor Adams afternoons used

2285
01:54:57,293 --> 01:54:59,733
Speaker 1: Dog Zedb on News Dog Zedb.

2286
01:55:00,053 --> 01:55:00,972
Speaker 4: Is four to four.

2287
01:55:01,693 --> 01:55:04,173
Speaker 2: I could talk about AI forever, but unfortunately we have

2288
01:55:04,693 --> 01:55:09,012
Speaker 2: run out of time. The Matt and Tyler Afternoons podcast

2289
01:55:09,053 --> 01:55:10,693
Speaker 2: will be out in about half an hour, So if

2290
01:55:10,733 --> 01:55:13,133
Speaker 2: you have missed any of our excellent chats, chune at

2291
01:55:13,213 --> 01:55:16,772
Speaker 2: that we chatted about longer prison sentences, including a confronting

2292
01:55:16,853 --> 01:55:19,213
Speaker 2: chat with a man who has committed murder that was

2293
01:55:19,253 --> 01:55:22,213
Speaker 2: full on. Also, as you may have just heard, we

2294
01:55:22,333 --> 01:55:25,812
Speaker 2: chatted about AI being used to mark kids papers in school.

2295
01:55:25,853 --> 01:55:27,493
Speaker 2: So you could listen to the podcast, or you could

2296
01:55:27,693 --> 01:55:30,293
Speaker 2: just put the following prompt into groc or chat GBT.

2297
01:55:30,812 --> 01:55:33,373
Speaker 2: Should I be used in schools and if so, how

2298
01:55:33,453 --> 01:55:36,772
Speaker 2: much and in what ways? Imitate callers and add some

2299
01:55:36,853 --> 01:55:38,413
Speaker 2: punishing radio host banter.

2300
01:55:39,133 --> 01:55:41,613
Speaker 4: Put that in there will let you figure out the answer.

2301
01:55:41,693 --> 01:55:43,852
Speaker 4: That one with AI teach you very much.

2302
01:55:43,933 --> 01:55:47,293
Speaker 2: Great show today is the Great and Powerful Heather Duplicy

2303
01:55:47,373 --> 01:55:50,493
Speaker 2: Allan is up after the News until tomorrow. AVO. Wherever

2304
01:55:50,533 --> 01:55:53,253
Speaker 2: you are, whatever you're doing for the rest of your day,

2305
01:55:53,533 --> 01:55:54,573
Speaker 2: give them a taste of key.

2306
01:55:54,653 --> 01:56:03,253
Speaker 4: We see you then, Middle.

2307
01:56:06,093 --> 01:56:12,812
Speaker 1: Little For more from newstalkst B, listen live on air

2308
01:56:13,053 --> 01:56:15,852
Speaker 1: or online, and keep our shows with you wherever you go.

2309
01:56:16,093 --> 01:56:18,213
Speaker 1: With our podcasts on iHeartRadio,