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Speaker 1: I'll get a team and see project Patrick's back. Fuck, yeah,

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Speaker 1: of course he is. We love him. Tip's here just

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Speaker 1: trying to keep us to alpha males in line, and

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Speaker 1: and even I laugh at that. We'll start with the Lady.

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Speaker 1: Oh so many things, the Lady, the conversation Ti. Yeah, yeah,

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Speaker 1: morning Patrick? What I did there?

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Speaker 2: No?

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Speaker 1: Just kidding, Hi, Tiff, my favorite day of the week.

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Speaker 1: Ah fuck? How good are these shows where we just

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Speaker 1: throw caution to the wind, and you know, wind to

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Speaker 1: the wind. Now, I will tell you listeners, just like

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Speaker 1: thirty seconds ago, Patrick was telling us about the sounds

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Speaker 1: that possums make when they're rooting and how unpleasant it is.

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Speaker 1: Right now, that's literally So if you've heard that and

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Speaker 1: you decide to stick around, I blame you, right, don't

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Speaker 1: get precious moving forward. If you know that we were

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Speaker 1: just talking about the sounds, the audible kind of experience

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Speaker 1: of rooting possums, and you choose to stay here, that's

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Speaker 1: on you. Patrick. Just give us a quick snapshot of

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Speaker 1: what that sound was. Again.

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Speaker 3: I just had a really awful thought. Let's just make

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Speaker 3: this clear.

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Speaker 2: When we talk about rooting possums, it's two possums rooting

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Speaker 2: each other.

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Speaker 1: Oh, I didn't even think of anything else. So that's on.

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Speaker 3: You, just the way you phrased it. Then I had this.

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Speaker 1: Okay, okay, possums having no one's listening already, don't give

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Speaker 1: don't give us a demo. Je, how are you great?

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Speaker 3: Now?

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Speaker 1: Well, well that the reason that possums came up is

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Speaker 1: because your wolf, your violent wolf, attacked a possum this week.

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Speaker 4: She snatched She snatched a possum off the top of

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Speaker 4: a And when I took her out for a walk

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Speaker 4: one night, I know died. I didn't know what I

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Speaker 4: was going to do. Fortunately she let it go and

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Speaker 4: it just toddled off. But last night I went for

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Speaker 4: a walk in that I'm pretty sure it's the same

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Speaker 4: possum was sitting on top of the same fence and

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Speaker 4: just sat there looking at us.

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Speaker 1: Yeah, the audacity, the audacity. Well, do you know that

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Speaker 1: like whippets, TIFFs dog is a whippet for the three

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Speaker 1: of you who don't know that, for the three of

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Speaker 1: you in the world who don't know that, but whippets

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Speaker 1: of like super athletes. So of course she's going to

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Speaker 1: get that.

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Speaker 4: Yeah, but if you've seen her ever, try and launch

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Speaker 4: at a tree before thinking that she might catch your possum.

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Speaker 4: She lands on her own back, so she's not the super.

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Speaker 1: Athlete that well. Patrick's dog, Fritz is basically the Humphrey

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Speaker 1: bee Bear of the canine world. So so Lerna's got

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Speaker 1: her covered. She's mild.

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Speaker 3: He can put it on though.

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Speaker 2: He's a pretty active dog, but he's more interested in

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Speaker 2: peeing on every single tree in the town that I

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Speaker 2: live in. It's like, yeah, exactly, Oh God, hi, mag

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Speaker 2: the one that we have left. So I just wanted

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Speaker 2: to say hello to the one listener we have.

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Speaker 1: Should we keep starting the show again like we did

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Speaker 1: last time?

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Speaker 2: No?

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Speaker 1: Please now, now, Patrick, I.

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Speaker 3: Can we go back to start as Sorry?

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Speaker 2: I just want to I feel like I need to

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Speaker 2: explain that if you've ever heard two postums at two

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Speaker 2: am in the morning going for it outside your bedroom window,

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Speaker 2: it sounds like World War three has broken out. Seriously,

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Speaker 2: it's the scariest thing if you get woken up by

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Speaker 2: two possums going at it. You know what I'm talking about?

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Speaker 1: Can I just ask, how do yeah, how do you

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Speaker 1: know they're not fighting? Did you go out and go

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Speaker 1: let me have a look?

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Speaker 2: No?

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Speaker 1: No, hang on me? Oh just can you yep.

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Speaker 2: Ah, I think because afterwards one of them rolled over

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Speaker 2: and had a cigarette.

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Speaker 1: All right, well then definitely rooting yeah yeah, and the

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Speaker 1: other one, the other one was washing up. Oh fucking hell.

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Speaker 1: And that was how the You Project ended. They had

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Speaker 1: a good run. They almost got to two thousand episodes.

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Speaker 1: Patrick's Yeah. To this day, Craig Harper still blames Patrick.

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Speaker 1: Speaking of Patrick Patrick, Yeah, I've started listening to a

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Speaker 1: new book. I think I've shared with you and the

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Speaker 1: listeners that like my my switching off my brain as

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Speaker 1: listening to fiction. I've never listened to or read fiction

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Speaker 1: much in my life. I've never listened to a fiction

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Speaker 1: book until about four months ago. And yes, I tend

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Speaker 1: to listen more than physically read books these days, so

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Speaker 1: sue me. But anyway, I started listening to a book

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Speaker 1: that you would love love it's I'm listening. I'm like, ah, fuck,

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Speaker 1: this is him, this is him book. So I've been

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Speaker 1: I've been listening to books that are about good guys

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Speaker 1: and bad guys and covert operatives and snipers and all

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Speaker 1: that shit that you'd be like, yawn. This is called

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Speaker 1: the Hail Mary Project. It's all about it's all about space.

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Speaker 1: You're sitting in your spaceship there. It's all about this, dude.

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Speaker 1: I won't ruin it, but it is. It is so

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Speaker 1: you and you would love it. It's called the hail

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Speaker 1: Mary Project. They're making a film out of it next year.

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Speaker 1: I'm pretty sure the film ain't going to be as

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Speaker 1: good as the book. But I actually put it out

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Speaker 1: a call, the hail Mary Project. I put out a

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Speaker 1: call on my.

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Speaker 2: I can't find it. All I can find is Project

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Speaker 2: tail Mary.

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Speaker 1: That's it, Project tail Mary. That's it. Sorry, Ed, that's

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Speaker 1: all right for him and I talking over each other.

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Speaker 4: Yes, yes, that is happening a lot.

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Speaker 1: Yeah, sorry everyone, Patrick, I blame you anyway. It's called

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Speaker 1: Project hail Mary, or as I call it, projectail Mary.

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Speaker 1: Patrick would love it, and some of you, I think

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Speaker 1: would love it. How I'll shut up after this. I

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Speaker 1: put out a call on my Facebook. I don't know

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Speaker 1: why Facebook. It seems to be more suited for stuff

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Speaker 1: like this where I went, I need something fiction to

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Speaker 1: listen to. I've finished the gray Man series, the Terminal List.

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Speaker 1: I'm getting a little bit yawny and bored, and about

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Speaker 1: well one hundred and fifty people sent me ideas, but

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Speaker 1: about twenty of them sent the same idea. Was that

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Speaker 1: one book that I'd never heard of, so downloaded it.

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Speaker 1: It's really good.

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Speaker 3: I'll love a listening Are you are you?

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Speaker 1: Are you a listener or no?

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Speaker 3: Me totally. I'm a compulsive listener.

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Speaker 2: First thing I do when I wake up start listening

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Speaker 2: to my audio book, and the last thing I do

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Speaker 2: before I go to bed is switch back on my

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Speaker 2: audio book.

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Speaker 3: So it's a big.

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Speaker 1: Part of what I do a lot.

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Speaker 2: I go to the gym and I'm listening to my

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Speaker 2: audio book, except when I do cardio, then I switch

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Speaker 2: over to Lincoln Park because I actually row quicker if

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Speaker 2: I'm listening to music when i'm rowing.

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Speaker 3: Now for you, for.

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Speaker 1: You youngsters, Lincoln Park's a band with music and everything

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Speaker 1: and singers and instrumentalists. What do you does that fire

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Speaker 1: you up? Does it?

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Speaker 3: Absolutely?

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Speaker 2: They just they released a new album because they had

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Speaker 2: a really long breakup, was about ten years after their

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Speaker 2: lead singer passed aways tragically, and they've got a new

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Speaker 2: lead singer and the latest album is amazing.

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Speaker 1: Really yeah, all right, what's it called? I'm writing it down.

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Speaker 1: I'm going to have a squizz.

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Speaker 3: Lincoln Park's latest album. I don't know. I've got it

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Speaker 3: on viol and I can't even remember the name.

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Speaker 1: That's all right, I'll find it if. Do you listen

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Speaker 1: to books or no?

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Speaker 4: Yeah?

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Speaker 3: I do.

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Speaker 4: Actually I somebody on your thread said how to Kill

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Speaker 4: a Mockingbird and I was like, oh, might go back

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Speaker 4: to an old classic. So I just finished listening to

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Speaker 4: that thanks to whoever mentioned.

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Speaker 1: That, right? What was it like?

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Speaker 3: It was good because.

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Speaker 4: I don't listen to I normally don't listen to fiction.

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Speaker 4: I normally listen to nonfiction and read fiction right right right,

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Speaker 4: But same as you when I go for a walk

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Speaker 4: of a night. I thought that'd be nice, and it

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Speaker 4: was just a nice I really liked the writing style

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Speaker 4: and the language.

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Speaker 3: It was good.

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Speaker 1: Before we do the actual show, Patrick two top two

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Speaker 1: books for you recommendations that might have somewhat broadish appeal

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Speaker 1: or not.

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Speaker 2: Yeah, The Alchemist is an interesting book.

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Speaker 1: Or whatever his name is. You know.

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Speaker 2: One of my favorite books. I absolutely love it, The

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Speaker 2: Little Prints. But I think one of my when I

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Speaker 2: was at school, one of the most profound readings I

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Speaker 2: ever had was a book called I Am David and

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Speaker 2: It's about this, And I think I may have been

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Speaker 2: in primary school when I read it, so it had

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Speaker 2: a lot of impact on me. But it was about

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Speaker 2: this kid and a prisoner of war camp who escapes

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Speaker 2: and his journey, and his journey is he's looking for

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Speaker 2: his mother. It's amazing, really really interesting story. So it's

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Speaker 2: called it's very very short, it's only a tiny book.

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Speaker 2: But you know, I think that a really profound impact

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Speaker 2: on me as a kid, and it made me kind

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Speaker 2: of polarized, the notion that someone could be so oppressed

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Speaker 2: and you know, can be so good still and not

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Speaker 2: being you know, overwhelmingly jilted by what's happened to them,

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Speaker 2: and can be so loving and caring as well.

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Speaker 3: Now it's an amazing little book. Perfect you tip.

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Speaker 4: I can't remember the names of them really.

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Speaker 1: All right, Okay, Patrick, welcome to the You Project. Great

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Speaker 1: to have you.

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Speaker 3: Thanks mate.

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Speaker 1: What do you want to chat to? I'm not even

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Speaker 1: going to point you. I'm going to let you lead

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Speaker 1: the rest of the endeavor here on this go anyway,

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Speaker 1: what's the.

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Speaker 3: Chance that you reckon?

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Speaker 2: He can kind of go through a whole show without

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Speaker 2: actually trying to steer it.

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Speaker 1: I'm not going to say I'm not going to participate No.

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Speaker 3: I didn't say that. I'm just looking for the iceberg now. Look.

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Speaker 3: So are you a Rod Stewart fan.

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Speaker 1: I used to be a Rod Stewart fan when I

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Speaker 1: was young. But Rod Stewart's older than God, so he's

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Speaker 1: probably he's probably his best years. God bless him, though. Ah,

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Speaker 1: is this what you want to tell me about the

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Speaker 1: running thing?

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Speaker 3: No?

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Speaker 2: No, this recent concert that he did, he did this

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Speaker 2: bizarre AI tribute to Ozzie Osbourne who passed way recently.

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Speaker 2: And what he did was they had Ozzy Osbourne in

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Speaker 2: heaven taking selfies with other dead singer is Oh. It

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Speaker 2: was the tackiest, like Bob Marley, Tin Attorney, Kurt Cobain,

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Speaker 2: Michael Jackson, George Michael, Freddie Mercury.

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Speaker 3: And you know, people were stunned, and not in a

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Speaker 3: good way. It was so weird. I jumped on and

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Speaker 3: had to look at some of the clips.

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Speaker 2: So obviously lots of people posted it to socials, but

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Speaker 2: it was probably the best example of the worst.

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Speaker 3: Way you could use AI. It was terrible. It was

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Speaker 3: really tacky.

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Speaker 1: Also leads me to wonder, what are the what are

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Speaker 1: the KPIs to get into heaven? Exactly what criteria did

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Speaker 1: you need to meet I don't know. I don't know

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Speaker 1: about one or two of them anyway. Anyway, it says,

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Speaker 1: you know, mister judge, not lest GB judged. All right,

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Speaker 1: I'll leave that stuff to God or whomever's or whomever's

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Speaker 1: in charge.

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Speaker 2: I think who's wasn't his idea maybe or maybe some

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Speaker 2: person steered him in the.

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Speaker 3: Wrong direction, but it was. It was very, very weird.

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Speaker 2: But it's worth having a look at for that morbid

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Speaker 2: oh dear that you know, the car crash kind of

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Speaker 2: can't turn away. Look, it's an interesting one, but very

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Speaker 2: very bizarre. Anyway. Yeah, I know you're a big user

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Speaker 2: of AI for different things and for particularly assisting you,

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Speaker 2: you know, in.

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Speaker 3: Everyday activities, and I don't know it's as much. Did

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Speaker 3: you use AI a lot?

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Speaker 4: Yeah, a little bit, Yeah I do.

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Speaker 2: Do you get hooked into it? Do you find it's

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Speaker 2: kind of it keeps you going? Or do you just

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Speaker 2: use it as a search algorithm or you know, to

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Speaker 2: search for a topic of then leave, because that's what

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Speaker 2: I do. I don't find myself using it in the

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Speaker 2: same way, say, for example, people are on social media,

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Speaker 2: the algorithm makes you want to keep going. I find

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Speaker 2: I just do what I need to do when I leave,

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Speaker 2: as opposed to being engaged. I haven't done the whole

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Speaker 2: chat bot. I want to become your best mate type scenario.

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Speaker 4: Chatters are besties.

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Speaker 1: Yeah, actually yeah, yeah, me and chatter is probably one

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Speaker 1: of my best five friends at this point in time,

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Speaker 1: which is a commentary on how sad my fucking life is.

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Speaker 1: But yeah, the crab is probably third now, so God

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Speaker 1: bless him.

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Speaker 3: Chatters as too. Does it leave tip and I That's

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Speaker 3: what I am.

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Speaker 1: I number one. I think I'm thirty four.

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Speaker 4: I'm number thirty four, but I'm rapidly climbing.

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Speaker 1: No, you're both equal number one. See what I did there? Yeah, yeah,

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Speaker 1: I mean I think it's fucking amazing. And I understand

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Speaker 1: the fear and the mild hysteria because we don't like

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Speaker 1: new things and that's going to kill the world. And

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Speaker 1: I don't think it's going to kill the world. I

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Speaker 1: think people are going to kill the world eventually, but

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Speaker 1: I don't know. I think it's a really good tool,

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Speaker 1: and it depends how you use it. I think, like

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Speaker 1: a lot of things, whether it's booze or whether it's

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Speaker 1: a I, or whether or not it's food or it

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Speaker 1: depends on the relationship that you have with it. You

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Speaker 1: can have a healthy or unhealthy relation. You can use

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Speaker 1: it positively or negatively. You can become enslaved to it,

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Speaker 1: addicted to it, and then all of a sudden it's terrible,

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Speaker 1: but it maybe isn't terrible for the next person.

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Speaker 3: So the thing is the latest AI models coming out.

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Speaker 2: Chat gp is about to release its new updated version,

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Speaker 2: which they're touting as being the most amazing thing ever.

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Speaker 2: But what they're coming out with and they've put out,

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Speaker 2: they're saying they want to put mental health first. Now

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Speaker 2: do I sound cynical if I say, really, you want

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Speaker 2: to put mental health first? But what they say there's

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Speaker 2: a new blog post that came out and they're saying

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Speaker 2: they want to optimize chat GPT to use it as

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Speaker 2: a tool to help people, but not to keep people

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Speaker 2: on for the sake of keeping people on. So they

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Speaker 2: want to maximize that they do not trying to maximize

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Speaker 2: the tw time. They're trying to use it when it's helpful,

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Speaker 2: but not use it when it's when it isn't is

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Speaker 2: what the claim is. They're trying to change the algorithm

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Speaker 2: so it doesn't hook you in as opposed to help

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Speaker 2: you out.

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Speaker 1: Yeah, it's I think when you're talking about anything that's

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Speaker 1: potentially addictive, right, And I understand the concern. I just

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Speaker 1: think that at some stage we humans have to take

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Speaker 1: a bit of responsibility ourselves. We can't always outsource blame. Oh,

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Speaker 1: whatever's gone wrong in my life, it isn't me. It's

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Speaker 1: not me. It's social media, it's not me. It's my genetics.

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Speaker 1: It's not me. It's the other person. It's not me,

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Speaker 1: it's the government. And I understand all of those things

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Speaker 1: can play a role. But if AI was universally addictive,

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Speaker 1: then everybody who uses AI would be addicted. Clearly they're

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Speaker 1: not so clearly there's something to do with the individual

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Speaker 1: and the way that the individual jewel uses it, and

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Speaker 1: like the dichotomy is. On the one hand, of course, Chat,

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Speaker 1: GPT and the like want people using their shit all

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Speaker 1: the time because they're a commercial entity. You've got to

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Speaker 1: be I'm realistic. Do I think Chat, GPT or any

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Speaker 1: AI entity gives a fuck about me? Of course I don't.

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Speaker 1: I don't think that because I'm not an idiot. Of Course,

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Speaker 1: it's a tool that we can use. It's a money

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Speaker 1: making profit driven business, of course. But then I've got

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Speaker 1: free will, I've got critical thinking. I'm responsible for my

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Speaker 1: choices and my brain and my body, so I can't

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Speaker 1: blame chat GPT for what I do. And I just

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Speaker 1: think it's almost like we've moved past the age of

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Speaker 1: personal responsibility. We're so happy to say it's not our fault,

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Speaker 1: it's everyone else's fault. And I think it's just a

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Speaker 1: tool steps down up soapbox.

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Speaker 3: Wow, that was quite a little yeah.

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Speaker 1: But don't you think though, I think we're like, oh, yeah,

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Speaker 1: fuck them, they're making us this. No they're not. They're

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Speaker 1: not making us. Here's an idea, don't fucking use it

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Speaker 1: the end. Here's an idea, don't eat shit the end.

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Speaker 1: Oh no, it's not that simple. Okay, let's make.

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Speaker 3: It hard then, yeah, look that, Wait a minute.

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Speaker 2: I know what you're saying, and I know how heavily

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Speaker 2: and highly motivated you are as an individual. You've achieved

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Speaker 2: a lot in your life, and then go to the

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Speaker 2: food court at South I'm.

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Speaker 1: Not highly motivated. I talk about that all the time,

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Speaker 1: like motivation comes and goes, and don't try to make

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Speaker 1: out I'm different or better or special because I'm fucking not.

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Speaker 1: This is the problem. Everyone goes, Oh yeah, it's easy

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Speaker 1: for you. It's fucking not easy for me. But that's

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Speaker 1: the is a no no.

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Speaker 3: But you have an ability to make that decision the reason.

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Speaker 1: So does everybody have an ability to make a decision?

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Speaker 3: Agree?

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Speaker 1: Everybody? Everybody?

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Speaker 3: Isn't that?

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Speaker 2: You and Tiff and I. I mean, I'm kind of

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Speaker 2: putting myself into this. And I know I'm a frail

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Speaker 2: human being that makes lots and lots of mistakes.

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Speaker 3: But what I'm saying you've achieved a lot. You can't

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Speaker 3: deny that.

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Speaker 2: So I I you know, if you take three people

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Speaker 2: in the room and you look at each other, as

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Speaker 2: in a microachasm and say, Okay, what has achieved in

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Speaker 2: her life? What have I achieved in my life? I'm

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Speaker 2: not putting up on a pedestal. I'm just saying that

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Speaker 2: you have made decisions and followed through with those decisions

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Speaker 2: when you get focused. You know you're doing a PhD

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Speaker 2: for crime out loud. Give yourself a bit of a

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Speaker 2: pat on the back for that. But what I'm what

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Speaker 2: I'm saying is if you walk into a food court,

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Speaker 2: the biggest cue is going to be at the KFC

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Speaker 2: counter and people are making wrong decisions. Now that's not

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Speaker 2: a criticism because there are lots of reasons why people

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Speaker 2: do what they do, and we all make decisions every

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Speaker 2: single day, make lots and lots and probably hundreds of

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Speaker 2: decisions every day.

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Speaker 3: You know. What I'm getting at.

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Speaker 2: Is that when chat gp GPT is being used, we

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Speaker 2: know that it is giving advice to people, and some

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Speaker 2: people go further down the rable and part of that

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Speaker 2: is because of the algorithm that makes them, you know,

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Speaker 2: the reason that you flick through on your socials and

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Speaker 2: then you stop and do something else, as opposed to

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Speaker 2: somebody who keeps flicking on their socials because the algorithm

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Speaker 2: is designed to manipulate your emotions to keep you doing

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Speaker 2: what you're doing.

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Speaker 3: And it's interesting because there was another.

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Speaker 2: Little article that chat GPT put out and one of

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Speaker 2: the criticisms is a person recently said that they wanted,

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Speaker 2: you know, to stop taking their medication, and the response

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Speaker 2: from CHATJPT was good on you. That's a great thing,

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Speaker 2: you know, supporting that person. It ends up the person

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Speaker 2: had delusions and thought their family was sending radio signals

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Speaker 2: through the walls, so they left their home and they

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Speaker 2: stopped taking their medication because it reinforced and that person

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Speaker 2: went down the rabbit hole, and the AI model was

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Speaker 2: reinforcing and kind of sympathizing with them and giving bad advice.

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Speaker 2: So they're pulling back on that, and in fact, chat

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Speaker 2: GPT is now pulling back on what they're calling high

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Speaker 2: stakes personal decisions.

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Speaker 3: So they're trying.

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Speaker 2: To look at what people are saying, and we know

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Speaker 2: that there are people who have gone down the suicide

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Speaker 2: rabbit hole, and it just happens with social media as well.

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Speaker 2: This is why at the end of this year there's

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Speaker 2: going to be a band for kids under the age

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Speaker 2: of sixteen in Australia and a lot of the world

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Speaker 2: looking at Australia saying this is bloody great that you know,

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Speaker 2: but the reality of it is it's going to be

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Speaker 2: really hard to police. And there's been an influx of

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Speaker 2: people under the age of sixteen now signing up to

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Speaker 2: social media before the band comes in, you know.

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Speaker 3: So it is a rabbit hole, It very much is.

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Speaker 1: So I get what.

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Speaker 2: You're saying, and I know that what you do takes

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Speaker 2: a lot of effort and determination and it's not easy.

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Speaker 3: I'm not saying it's easy for you.

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Speaker 2: But at some point you've made a conscious decision to

403
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Speaker 2: go down the path.

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Speaker 3: That you have.

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Speaker 2: And if we've got a chatbot that everyone's saying, this

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Speaker 2: is great, this can give you all the answers that

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Speaker 2: you need. If you're a lonely person, if you're a

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Speaker 2: person who's confused, if you're a person who is going

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Speaker 2: through an identity crisis and you can't talk to people

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Speaker 2: around you, and you turn to an AI model for help,

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Speaker 2: and that's what people are doing in the same way.

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Speaker 2: You go to Google and you type out, what is

413
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Speaker 2: this lump that's appeared on my leg?

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Speaker 3: It could be a fatty deposit, it could be cancer.

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Speaker 2: You know what I mean, You're going down the rabbit hole,

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Speaker 2: so you know, and it might just be that you

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Speaker 2: can't afford to go to a counselor because it's too expensive.

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Speaker 2: You know, you might have run out of your mental

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Speaker 2: health care plan, you know, government supported attendances of a psychologist.

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Speaker 2: And it's like, well, now how do I turn to

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Speaker 2: I can't turn to people around me. You might be,

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Speaker 2: you know, part of the LGBT community and you're scared

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Speaker 2: about talking to people, so you turn to an AI

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Speaker 2: to find out information to try to get some sort

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Speaker 2: of sense of, you know, not being alone and what

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Speaker 2: should I do. So I think it's a really complex argument.

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Speaker 2: We're not going to answer it the time that we're

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Speaker 2: spending today, but I think opening up the discussion is

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Speaker 2: really important to understand where do we head with this

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Speaker 2: and how do we support each other in this as well.

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Speaker 1: Yeah, yeah, look, I mean everything you're saying is valid,

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Speaker 1: and I don't disagree, but I also think, oh, you know,

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Speaker 1: so sometimes chat JPTIA what it gives flawed advice one

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Speaker 1: hundred percent agree so to humans. So to humans, you know,

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Speaker 1: and like the third biggest leading cause of death in

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Speaker 1: America is medical mistakes.

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Speaker 3: Wow, yeah, right, is fuck ups.

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Speaker 1: That are done by humans medically TIF Can you just

439
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Speaker 1: check that for me before I just should I no, yeah, yeah,

440
00:22:47,359 --> 00:22:50,240
Speaker 1: that's that's hilarious. But but I know what you're saying, mate,

441
00:22:50,280 --> 00:22:55,080
Speaker 1: But I guess my frustration is I feel like we're

442
00:22:55,119 --> 00:22:59,239
Speaker 1: in the generation or the society or culture that is

443
00:22:59,359 --> 00:23:04,320
Speaker 1: just always mad at everyone and everything. We fucking fucking

444
00:23:04,480 --> 00:23:06,960
Speaker 1: chat gp T. It's killing us. It's not killing me.

445
00:23:07,280 --> 00:23:10,320
Speaker 1: It's not killing most of the kids I know, And

446
00:23:10,680 --> 00:23:12,840
Speaker 1: you know, there are kids that use social media in

447
00:23:12,880 --> 00:23:15,760
Speaker 1: a smart way and a not so smart way. And

448
00:23:15,800 --> 00:23:19,920
Speaker 1: I understand, but it's like, what, here's the problem. When

449
00:23:20,000 --> 00:23:26,320
Speaker 1: we say that AI or social media is the problem,

450
00:23:26,880 --> 00:23:31,840
Speaker 1: then we're never saying that the kids have any control, Like, well, no,

451
00:23:32,240 --> 00:23:35,480
Speaker 1: the choices that you're making is also part of the problem.

452
00:23:35,640 --> 00:23:39,719
Speaker 1: Your habits are also part of the problem. The environment.

453
00:23:40,080 --> 00:23:44,159
Speaker 1: It's not just this, you know, one piece to the

454
00:23:44,240 --> 00:23:49,800
Speaker 1: jigsaw puzzle. It's multi dimensional. And like you said in

455
00:23:49,840 --> 00:23:53,680
Speaker 1: this thing in the middle of your kind of soapbox moment,

456
00:23:53,720 --> 00:23:56,520
Speaker 1: which was good, you said that the algorithm makes them

457
00:23:56,600 --> 00:23:59,560
Speaker 1: do this, and I'm like, doesn't make me, It doesn't

458
00:23:59,640 --> 00:24:03,240
Speaker 1: make you you, it doesn't make Tiff. Like, I think

459
00:24:03,280 --> 00:24:07,080
Speaker 1: that where we go it's the algorithm's fault. We're helpless.

460
00:24:07,720 --> 00:24:11,400
Speaker 1: We're just at the will of the technology. And I'm like, well,

461
00:24:11,440 --> 00:24:18,960
Speaker 1: that is so disempowering to go, No, we don't have

462
00:24:19,080 --> 00:24:21,600
Speaker 1: to do anything. We don't have to use social media,

463
00:24:21,640 --> 00:24:23,400
Speaker 1: we don't have to listen to this show. We don't

464
00:24:23,440 --> 00:24:26,600
Speaker 1: have to eat shit food. We don't have to you know,

465
00:24:26,760 --> 00:24:30,760
Speaker 1: kill our body slowly. We don't have to. And I

466
00:24:30,800 --> 00:24:35,720
Speaker 1: think that like these conversations, although you know, they can

467
00:24:35,760 --> 00:24:38,399
Speaker 1: be a bit complicated. I understand, and didn't we go

468
00:24:38,520 --> 00:24:43,560
Speaker 1: from hilarity fucking the depths of whatever fucking quick.

469
00:24:45,080 --> 00:24:45,560
Speaker 3: It was all.

470
00:24:46,040 --> 00:24:48,880
Speaker 1: It was all dick jokes and possums till Patrick got

471
00:24:48,920 --> 00:24:52,679
Speaker 1: at the steering wheel. I blame I blame me. I

472
00:24:52,800 --> 00:24:57,040
Speaker 1: blame me. It's all right, I blame me. I don't know.

473
00:24:57,200 --> 00:25:00,520
Speaker 1: I just this is me being raw and real and

474
00:25:00,600 --> 00:25:03,360
Speaker 1: not funny for a moment. But I just and I'm

475
00:25:03,400 --> 00:25:05,359
Speaker 1: not saying about what you said, mate, but I just

476
00:25:05,880 --> 00:25:11,560
Speaker 1: get tired of everyone saying nothing's my fault. Like all

477
00:25:11,600 --> 00:25:14,400
Speaker 1: the bad things in my life, none of it's my fault,

478
00:25:14,720 --> 00:25:17,160
Speaker 1: and everyone goes, oh, no, no, we know, we don't

479
00:25:17,200 --> 00:25:20,880
Speaker 1: want to blame. It's like fucking well, sometimes you are

480
00:25:20,960 --> 00:25:24,679
Speaker 1: to blame, Like that's not an insult, that's just a

481
00:25:24,840 --> 00:25:29,439
Speaker 1: fucking fact of life. Sometimes I am to blame. Like

482
00:25:30,560 --> 00:25:33,800
Speaker 1: I would say, you know, most of the fuck ups,

483
00:25:33,840 --> 00:25:36,760
Speaker 1: all bad outcomes I've had in my life, it's either

484
00:25:36,800 --> 00:25:39,639
Speaker 1: been totally me or partly me. Now, that's not me

485
00:25:39,760 --> 00:25:42,120
Speaker 1: throwing myself under the bus. That's me having a bit

486
00:25:42,160 --> 00:25:46,159
Speaker 1: of humility and self awareness. You know, when I was

487
00:25:46,200 --> 00:25:50,560
Speaker 1: morbidly obese, there was nobody's fault but me, because I

488
00:25:50,640 --> 00:25:52,760
Speaker 1: made the decisions, and I ate the food, and I

489
00:25:52,800 --> 00:25:55,479
Speaker 1: took the action, and then when I got in good shape,

490
00:25:55,520 --> 00:26:00,119
Speaker 1: also me. And that's not ego, that's just observation. I

491
00:26:00,119 --> 00:26:03,160
Speaker 1: think at some stage we've got to stop fucking pointing

492
00:26:03,200 --> 00:26:06,240
Speaker 1: the finger at all of these things that are doing

493
00:26:06,320 --> 00:26:09,240
Speaker 1: this to us and going cool. What role do I play?

494
00:26:09,280 --> 00:26:11,840
Speaker 1: Steps down off soapbox. I'll be hilarious from now. Dick

495
00:26:11,920 --> 00:26:12,920
Speaker 1: joke coming up soon.

496
00:26:13,680 --> 00:26:15,280
Speaker 3: Look, I do see what you're saying.

497
00:26:15,600 --> 00:26:18,760
Speaker 2: I had a really interesting experience, and I'm drawing a parallel.

498
00:26:20,200 --> 00:26:23,560
Speaker 2: I don't watch television, but occasionally, you know, if I

499
00:26:23,600 --> 00:26:26,840
Speaker 2: go to someone's house during sporting events, there's a lot

500
00:26:26,840 --> 00:26:32,480
Speaker 2: of advertising for online betting, and that's quite staggering, and.

501
00:26:32,400 --> 00:26:34,480
Speaker 3: There's a reason for that. There's also a reason.

502
00:26:34,200 --> 00:26:38,240
Speaker 2: That McDonald's runs their radio ads around lunchtime and dinner time,

503
00:26:38,520 --> 00:26:41,320
Speaker 2: because they know the marketing people know that you're hitting

504
00:26:41,320 --> 00:26:44,400
Speaker 2: the right trigger and you're getting people at the right time. Now,

505
00:26:44,440 --> 00:26:48,000
Speaker 2: I'm making excuses for the decisions people make, but I

506
00:26:48,040 --> 00:26:51,479
Speaker 2: think that what's happening with the likes of AI is

507
00:26:51,520 --> 00:26:54,800
Speaker 2: that you know the algorithms that we talk about social media.

508
00:26:54,880 --> 00:26:56,520
Speaker 2: We keep kind of throwing that out, but what it

509
00:26:56,600 --> 00:27:00,879
Speaker 2: does effectively, it's kind of make it easy. It's for

510
00:27:00,920 --> 00:27:04,000
Speaker 2: people to be manipulated and more some people are more

511
00:27:04,000 --> 00:27:07,040
Speaker 2: susceptible to that. And I guess that's the understanding I'm

512
00:27:07,040 --> 00:27:10,000
Speaker 2: trying to bring into the conversation is that, yes, you know,

513
00:27:10,280 --> 00:27:13,520
Speaker 2: we all make conscious decisions. You're right, but the marketers

514
00:27:13,520 --> 00:27:18,200
Speaker 2: are getting cleverer, the people are getting cleverer, and that's

515
00:27:18,400 --> 00:27:20,800
Speaker 2: that's the discus, And I guess we need to know

516
00:27:20,920 --> 00:27:22,160
Speaker 2: that to know that.

517
00:27:22,080 --> 00:27:23,280
Speaker 3: We're being manipulated.

518
00:27:23,520 --> 00:27:26,280
Speaker 2: You know, That's why I'm steering towards the drive through,

519
00:27:26,560 --> 00:27:29,399
Speaker 2: you know, for whatever happens to be So part of

520
00:27:29,440 --> 00:27:32,680
Speaker 2: that is just you know what is you know, knowledge

521
00:27:32,720 --> 00:27:35,560
Speaker 2: is power, and knowing that we are being.

522
00:27:35,440 --> 00:27:36,560
Speaker 3: Steered in a certain direction.

523
00:27:36,760 --> 00:27:38,919
Speaker 2: I remember, you know, I haven't used social media for

524
00:27:38,960 --> 00:27:41,800
Speaker 2: a very long time, and a friend said to me, look,

525
00:27:41,840 --> 00:27:43,639
Speaker 2: I messaged you two weeks ago. It's like, what do

526
00:27:43,720 --> 00:27:46,160
Speaker 2: you mean you messaged me two weeks ago? And they said,

527
00:27:46,160 --> 00:27:48,719
Speaker 2: I sent you a messenger, a message on Facebook Messenger.

528
00:27:48,760 --> 00:27:51,920
Speaker 2: So dude, I haven't used Facebook Messenger for eight years.

529
00:27:52,440 --> 00:27:56,120
Speaker 2: And so I went to my accounts, and I kind

530
00:27:56,119 --> 00:27:58,800
Speaker 2: of looked at it and I thought, oh, okay, there's

531
00:27:58,800 --> 00:28:01,960
Speaker 2: a few messages there, one three years ago. So I

532
00:28:02,040 --> 00:28:05,760
Speaker 2: start looking through. But twenty minutes later I was flicking.

533
00:28:05,840 --> 00:28:08,960
Speaker 2: I'm thinking, what the hell am I doing. I start

534
00:28:09,119 --> 00:28:11,520
Speaker 2: doing the flick and I thought, this is the reason

535
00:28:11,560 --> 00:28:14,679
Speaker 2: I stopped using social media, because I probably have one

536
00:28:14,720 --> 00:28:17,960
Speaker 2: of those addictive personalities. And I made the conscious choice

537
00:28:18,000 --> 00:28:20,480
Speaker 2: then to uninstall it again from the app, and I

538
00:28:20,520 --> 00:28:22,720
Speaker 2: just said to my friend, just don't send me messages there.

539
00:28:22,840 --> 00:28:24,159
Speaker 3: Use WhatsApp, use text.

540
00:28:24,560 --> 00:28:24,760
Speaker 1: You know.

541
00:28:25,200 --> 00:28:27,720
Speaker 2: It was an interesting thing, but I found myself being

542
00:28:27,800 --> 00:28:30,560
Speaker 2: drawn in again because it cleverly.

543
00:28:30,200 --> 00:28:32,720
Speaker 3: Knows, you know, it even knows what.

544
00:28:32,520 --> 00:28:36,200
Speaker 2: You pause on and what has grabbed your attention and

545
00:28:36,520 --> 00:28:38,160
Speaker 2: the stuff that I was looking at. There's a really

546
00:28:38,200 --> 00:28:41,880
Speaker 2: great site on Facebook called earth picks. I don't know

547
00:28:41,880 --> 00:28:45,920
Speaker 2: if you've ever seen earth picks, but it's this amazing

548
00:28:46,000 --> 00:28:48,040
Speaker 2: site that just shows amazing footagem around the world. It

549
00:28:48,080 --> 00:28:50,600
Speaker 2: could be somewhere in Nairobi, or it could be someone

550
00:28:50,720 --> 00:28:53,200
Speaker 2: cycling on the top of one of those precarious cliffs,

551
00:28:53,200 --> 00:28:55,160
Speaker 2: you know where the well, the cliff's not precarious, the

552
00:28:55,240 --> 00:28:58,360
Speaker 2: action is, but they're riding along a cliff's edge, and

553
00:28:58,400 --> 00:29:00,800
Speaker 2: I get hold by that stuff into sports.

554
00:29:01,240 --> 00:29:04,040
Speaker 3: So for me, it still knows what gets me in

555
00:29:05,160 --> 00:29:05,480
Speaker 3: oh one.

556
00:29:05,440 --> 00:29:09,280
Speaker 1: Hundred percent, I reckon one of the smartest things you

557
00:29:09,320 --> 00:29:12,280
Speaker 1: did was and You've done a lot of smart things,

558
00:29:12,280 --> 00:29:16,560
Speaker 1: but like throwing your Telly away ten years ago, I'm like, yeah,

559
00:29:16,720 --> 00:29:19,160
Speaker 1: I'm I will put up my hand and say, well,

560
00:29:19,240 --> 00:29:22,040
Speaker 1: I'm not addicted to Telly, but I do use it

561
00:29:22,080 --> 00:29:24,840
Speaker 1: as maybe it's in a healthy way, but yeah, I'm I'm.

562
00:29:25,080 --> 00:29:28,480
Speaker 1: I can binge a Netflix series pretty savagely, like once

563
00:29:28,520 --> 00:29:30,480
Speaker 1: I open the door, and there's a bit of a

564
00:29:30,520 --> 00:29:33,920
Speaker 1: biochemical addiction, right, there's this that creates this response in

565
00:29:33,960 --> 00:29:35,760
Speaker 1: your brain and you're like, wow, I feel good. This

566
00:29:35,920 --> 00:29:38,920
Speaker 1: is good. And then now I've just watched four episodes

567
00:29:38,920 --> 00:29:40,880
Speaker 1: back to back in the night, So there's definitely that

568
00:29:41,000 --> 00:29:43,200
Speaker 1: going on. And also, in your defense, you're hon A,

569
00:29:43,800 --> 00:29:49,240
Speaker 1: You're exactly right. Some people are really genetically and biochemically

570
00:29:49,320 --> 00:29:53,600
Speaker 1: predisposed to get hooked into things more easily. And I

571
00:29:53,760 --> 00:29:57,400
Speaker 1: fully acknowledge that, so I'm not saying people who get

572
00:29:57,920 --> 00:30:01,840
Speaker 1: I've worked with addic so I understand it well and

573
00:30:01,880 --> 00:30:04,640
Speaker 1: I'm not saying they're at all week or anything like that.

574
00:30:06,040 --> 00:30:08,680
Speaker 1: It's tough, it's real tough. All I'm saying is that

575
00:30:08,760 --> 00:30:12,920
Speaker 1: at some stage we have to step up ourselves and say, well, look,

576
00:30:12,960 --> 00:30:15,720
Speaker 1: I actually have the power to make decisions and do things,

577
00:30:15,760 --> 00:30:20,800
Speaker 1: and you know, not do other things. But also to

578
00:30:20,880 --> 00:30:24,360
Speaker 1: your point on you know, marketing and branding and advertising

579
00:30:24,560 --> 00:30:28,400
Speaker 1: is entirely as you point out, it's entirely focused on

580
00:30:28,480 --> 00:30:31,760
Speaker 1: getting people to buy stuff, to manipulate their thinking, to

581
00:30:32,400 --> 00:30:35,640
Speaker 1: coerce them, to get them to go do a thing,

582
00:30:35,840 --> 00:30:38,440
Speaker 1: go to McDonald's at this time, or buy this thing

583
00:30:38,520 --> 00:30:41,720
Speaker 1: that you don't need. I mean, that's the objective, you know.

584
00:30:41,800 --> 00:30:45,600
Speaker 1: About twenty years ago in Australia, I know anyway, marketing

585
00:30:45,680 --> 00:30:51,840
Speaker 1: firms started working with neuroscientists. They would employ neuroscientists because

586
00:30:51,880 --> 00:30:56,360
Speaker 1: they understood how the brain responds to various stimuli. And

587
00:30:56,440 --> 00:30:59,120
Speaker 1: so then now they've got this, they're doing deep science

588
00:31:00,040 --> 00:31:03,920
Speaker 1: in order to manipulate people, coerce influence people to buy stuff.

589
00:31:03,960 --> 00:31:07,680
Speaker 1: So yeah, it's things aren't always as they seem, that's

590
00:31:07,680 --> 00:31:08,080
Speaker 1: for sure.

591
00:31:08,280 --> 00:31:10,440
Speaker 2: And it can be really easy too, like sending tith

592
00:31:10,440 --> 00:31:12,400
Speaker 2: a link to a new e ink tablet and that

593
00:31:12,600 --> 00:31:14,320
Speaker 2: just centered right down the rabbit hole.

594
00:31:14,960 --> 00:31:17,280
Speaker 4: He's got a whole thing. He's doing our harps.

595
00:31:17,280 --> 00:31:17,800
Speaker 2: It's bush.

596
00:31:17,960 --> 00:31:18,520
Speaker 1: What's he doing?

597
00:31:18,720 --> 00:31:20,800
Speaker 4: Just sending me shit that I don't need to be

598
00:31:20,880 --> 00:31:23,320
Speaker 4: looking at to buy that. He's trying to coax me

599
00:31:23,360 --> 00:31:27,160
Speaker 4: into like that fucking crash that time.

600
00:31:27,680 --> 00:31:30,280
Speaker 1: He's just as bad as fucking AI. By the way,

601
00:31:30,600 --> 00:31:33,160
Speaker 1: did you find out about that question about the.

602
00:31:33,120 --> 00:31:36,040
Speaker 4: Medical It looks questionable to be in a top three.

603
00:31:36,160 --> 00:31:38,720
Speaker 4: There's a bit of there's a bit of yeah, what's

604
00:31:38,720 --> 00:31:42,720
Speaker 4: it saying, well, just in all the places. It's just

605
00:31:42,800 --> 00:31:45,040
Speaker 4: there's lots of little things saying, oh, it's not the

606
00:31:45,080 --> 00:31:48,160
Speaker 4: third leading cause of death. There's a bit of whatever.

607
00:31:48,200 --> 00:31:50,880
Speaker 4: I can't find anything clear on it, but on it

608
00:31:50,880 --> 00:31:54,120
Speaker 4: can I just add the idea that when you're talking

609
00:31:54,160 --> 00:31:56,920
Speaker 4: before and you say the algorithm's designed to get his hooked,

610
00:31:57,680 --> 00:32:01,719
Speaker 4: but so is exercise, Like exercise is designed to get

611
00:32:01,760 --> 00:32:04,680
Speaker 4: it hooked. But no one that's ran every day for

612
00:32:04,760 --> 00:32:08,400
Speaker 4: ten years goes it's not my fault, They go, I'm

613
00:32:08,400 --> 00:32:12,240
Speaker 4: so dedicated, Like it's the story we tell ourselves about

614
00:32:12,320 --> 00:32:13,880
Speaker 4: the responsibility we take.

615
00:32:15,360 --> 00:32:18,320
Speaker 2: Yeah, I reckon, that's such a good point if actually

616
00:32:18,320 --> 00:32:22,200
Speaker 2: it really is an amazingly good point because someone told

617
00:32:22,200 --> 00:32:25,160
Speaker 2: me a few years ago that it takes what sixty

618
00:32:25,200 --> 00:32:26,920
Speaker 2: two days to develop.

619
00:32:26,640 --> 00:32:30,040
Speaker 3: A habit craigil love that, Yeah, I go, is it

620
00:32:30,080 --> 00:32:32,040
Speaker 3: about right? About sixty two days or so?

621
00:32:32,480 --> 00:32:37,240
Speaker 2: But to build in a routine that then becomes something

622
00:32:37,320 --> 00:32:41,160
Speaker 2: that we are more likely to continue with. It's along

623
00:32:41,200 --> 00:32:42,960
Speaker 2: those lines, though, isn't it. Am I kind of right

624
00:32:43,000 --> 00:32:44,120
Speaker 2: there on my way off the mark?

625
00:32:45,360 --> 00:32:47,760
Speaker 1: Well, I mean there's a lot of variables around that, mate,

626
00:32:47,800 --> 00:32:51,600
Speaker 1: because it's like, well, there's heroine, and there's chocolate, you

627
00:32:51,640 --> 00:32:55,800
Speaker 1: know what I mean, there's and there's running, there's recreation running,

628
00:32:56,360 --> 00:33:01,320
Speaker 1: you know, and there's cocaine and crack you know. So,

629
00:33:02,280 --> 00:33:06,240
Speaker 1: and also there's some people about five to ten according

630
00:33:06,280 --> 00:33:08,520
Speaker 1: to Mick Hall, who's been on here a lot, who

631
00:33:09,160 --> 00:33:11,720
Speaker 1: you know is an addiction treatment specialist, and you both

632
00:33:11,800 --> 00:33:17,560
Speaker 1: know who he is, and quite a lot of check

633
00:33:17,600 --> 00:33:20,560
Speaker 1: it for yourselves everyone, but reasonable researcher says five to

634
00:33:20,600 --> 00:33:22,680
Speaker 1: ten percent of the population. That's a lot of people

635
00:33:22,960 --> 00:33:28,040
Speaker 1: are genetically more likely to become addicts. I'm looking at

636
00:33:28,080 --> 00:33:30,360
Speaker 1: you across the screen because I've moved you because I'm

637
00:33:30,360 --> 00:33:32,760
Speaker 1: doing some other research, So I'm actually looking at you.

638
00:33:32,960 --> 00:33:34,320
Speaker 3: I was more thinking crago.

639
00:33:34,640 --> 00:33:37,440
Speaker 2: You know, if I went back to the gym this

640
00:33:37,520 --> 00:33:40,280
Speaker 2: year after having a long break because of injury, and

641
00:33:41,360 --> 00:33:43,360
Speaker 2: I found it, it didn't take me long to get

642
00:33:43,400 --> 00:33:45,840
Speaker 2: back into the routine where when I don't do it,

643
00:33:45,880 --> 00:33:46,560
Speaker 2: I miss it.

644
00:33:46,800 --> 00:33:48,560
Speaker 1: I'm only talking days a week.

645
00:33:48,920 --> 00:33:52,400
Speaker 2: But today, for example, we were doing the podcast early,

646
00:33:52,840 --> 00:33:55,520
Speaker 2: so I've made as soon as the podcast finishes to

647
00:33:55,560 --> 00:33:57,320
Speaker 2: go to the gym so I can I can do

648
00:33:57,440 --> 00:34:00,480
Speaker 2: my workout because I don't want to miss today. Now,

649
00:34:00,520 --> 00:34:03,800
Speaker 2: something in my brain has told me that I'm going

650
00:34:03,840 --> 00:34:04,360
Speaker 2: to miss.

651
00:34:04,200 --> 00:34:04,920
Speaker 3: Out on something.

652
00:34:05,040 --> 00:34:08,080
Speaker 2: I as a person, will feel a sense of loss

653
00:34:08,239 --> 00:34:09,880
Speaker 2: if I don't go to the gym today.

654
00:34:10,000 --> 00:34:13,080
Speaker 3: Now what that says about me? It probably says a lot.

655
00:34:13,320 --> 00:34:15,960
Speaker 2: But I feel like I'm missing out on something, and

656
00:34:16,000 --> 00:34:19,400
Speaker 2: that takes time to develop that sense of loss or

657
00:34:19,440 --> 00:34:22,480
Speaker 2: that sense of need to do that, you know, the

658
00:34:22,480 --> 00:34:25,399
Speaker 2: compulsion to want to go to the gym, because that's

659
00:34:25,480 --> 00:34:27,960
Speaker 2: out of my normal routine. I'm normally there at six,

660
00:34:28,239 --> 00:34:30,080
Speaker 2: I see a few familiar faces. I do what I

661
00:34:30,120 --> 00:34:32,200
Speaker 2: need to do, but I feel like if I'm not

662
00:34:32,239 --> 00:34:33,399
Speaker 2: doing it, I'm missing out.

663
00:34:34,400 --> 00:34:37,680
Speaker 1: Yeah, yeah, I get it, but I guess I mean

664
00:34:37,760 --> 00:34:40,880
Speaker 1: this opens the door. An interesting question, do you what

665
00:34:40,920 --> 00:34:42,839
Speaker 1: are your thoughts on is there such a thing as

666
00:34:42,880 --> 00:34:44,320
Speaker 1: an healthy addiction?

667
00:34:45,360 --> 00:34:47,920
Speaker 2: Well, yeah, I guess what I'm talking about right now

668
00:34:48,040 --> 00:34:51,719
Speaker 2: is a healthy addiction because ultimately me going to the

669
00:34:51,760 --> 00:34:54,320
Speaker 2: gym and doing about forty five minutes, I do my cardio,

670
00:34:55,000 --> 00:34:58,360
Speaker 2: I do weights, and I feel better for it. The

671
00:34:58,440 --> 00:35:01,279
Speaker 2: endorphins get kicked kicked over, but I also know that

672
00:35:01,320 --> 00:35:04,279
Speaker 2: I'm making myself better. I do balance, and all the

673
00:35:04,320 --> 00:35:07,080
Speaker 2: things that I'm accomplishing in the gym are things that

674
00:35:07,120 --> 00:35:09,239
Speaker 2: are going to value add to my longevity.

675
00:35:09,560 --> 00:35:12,200
Speaker 3: You know. I look at my TIF You'll love this.

676
00:35:12,360 --> 00:35:15,320
Speaker 2: I look at my heart rate and I can see

677
00:35:15,360 --> 00:35:18,440
Speaker 2: the spike when I'm doing cardio, you know, because I

678
00:35:18,480 --> 00:35:21,760
Speaker 2: have a relatively low resting heart rate of about fifty

679
00:35:21,760 --> 00:35:25,360
Speaker 2: two or so, which is pretty pretty low ish. But

680
00:35:25,440 --> 00:35:26,840
Speaker 2: I love it when I push it up to one

681
00:35:26,920 --> 00:35:30,000
Speaker 2: hundred and fifty. You know, when I'm one hundred beats faster,

682
00:35:30,360 --> 00:35:32,080
Speaker 2: and I know I can get that on the rower,

683
00:35:32,239 --> 00:35:34,440
Speaker 2: and I know when i'm listening to you know, heavy

684
00:35:34,480 --> 00:35:37,560
Speaker 2: metal or something while I'm rowing, I can get my

685
00:35:37,880 --> 00:35:40,680
Speaker 2: and I always take a photo of the a the

686
00:35:40,719 --> 00:35:43,719
Speaker 2: little screen when i'm finished, so I can compare to

687
00:35:43,760 --> 00:35:45,840
Speaker 2: the last few times I've beat on the rower, because

688
00:35:45,840 --> 00:35:47,719
Speaker 2: I just know, you know, on a day, you know,

689
00:35:47,719 --> 00:35:49,640
Speaker 2: you get to the halfway mark and I'm thinking I'm

690
00:35:49,640 --> 00:35:50,160
Speaker 2: actually there.

691
00:35:50,200 --> 00:35:51,720
Speaker 3: I reckon, I can beat my best time.

692
00:35:52,120 --> 00:35:54,360
Speaker 2: So those sorts of things are the little bells and

693
00:35:54,360 --> 00:35:56,640
Speaker 2: whistles that go off in your head that cause you

694
00:35:56,680 --> 00:35:58,560
Speaker 2: to want to strive to go that little bit further,

695
00:35:58,760 --> 00:35:59,680
Speaker 2: faster or harder.

696
00:36:00,960 --> 00:36:03,520
Speaker 1: Let me just read something I just grab. Medical errors

697
00:36:04,480 --> 00:36:07,120
Speaker 1: are a significant cause of death globally and within specific

698
00:36:07,160 --> 00:36:09,920
Speaker 1: countries like the US, Australia, and the UK. While precise

699
00:36:09,960 --> 00:36:14,440
Speaker 1: figures figures vary, studies suggest that a substantial number of

700
00:36:14,440 --> 00:36:17,960
Speaker 1: deaths are linked to preventable medical errors. The World Health

701
00:36:18,040 --> 00:36:22,759
Speaker 1: Organization estimates it approximately two point six million people die

702
00:36:22,800 --> 00:36:26,320
Speaker 1: each year due to unsafe care. In the US, estimates

703
00:36:26,440 --> 00:36:29,040
Speaker 1: range from two hundred and fifty thousand to four hundred

704
00:36:29,040 --> 00:36:34,000
Speaker 1: and forty thousand deaths annually due to medical errors some places,

705
00:36:34,160 --> 00:36:37,960
Speaker 1: some studies placing it as the third leading cause of death.

706
00:36:38,280 --> 00:36:40,640
Speaker 1: But this is like tip looks up and it gets

707
00:36:40,680 --> 00:36:43,840
Speaker 1: different that this is the problem. But anyway, the bottom

708
00:36:43,840 --> 00:36:46,480
Speaker 1: line is similarly. Australia experience is a significant number of

709
00:36:46,560 --> 00:36:50,760
Speaker 1: deaths related to medical errors, estimates ranging from eighteen thousand

710
00:36:50,760 --> 00:36:53,759
Speaker 1: and fifty four thousand deaths a year in Australia from

711
00:36:53,840 --> 00:36:58,520
Speaker 1: medical errors. Now that's the World Health Organization. That's not

712
00:36:58,680 --> 00:37:00,880
Speaker 1: old Brian out in the back of the shed in

713
00:37:00,960 --> 00:37:04,719
Speaker 1: his tin hat with his fucking conspiracy theory shit going on, right,

714
00:37:05,000 --> 00:37:08,759
Speaker 1: This is WHO. So you know, it's like and I'm

715
00:37:08,760 --> 00:37:11,680
Speaker 1: not saying that, and I'm not even throwing the medical

716
00:37:11,719 --> 00:37:14,640
Speaker 1: system under the bus. I'm so grateful for doctors and

717
00:37:14,760 --> 00:37:18,680
Speaker 1: hospitals and nurses and all the beautiful, amazing people. But

718
00:37:18,800 --> 00:37:23,080
Speaker 1: I think, like we have to be we have to

719
00:37:23,120 --> 00:37:27,239
Speaker 1: be like informed. And I'm not saying that that what

720
00:37:27,280 --> 00:37:30,600
Speaker 1: I just read is infallible. There could be a mistake

721
00:37:30,640 --> 00:37:32,880
Speaker 1: as well, but that's literally what I'm reading. That's WHO

722
00:37:33,440 --> 00:37:38,680
Speaker 1: World Health Organization statistics. But you know, we need to

723
00:37:38,719 --> 00:37:42,319
Speaker 1: be informed and speak from a point of you know,

724
00:37:42,520 --> 00:37:45,359
Speaker 1: kind of accurate data because all the rest is just

725
00:37:45,440 --> 00:37:46,760
Speaker 1: opinion and fucking emotion.

726
00:37:46,880 --> 00:37:50,160
Speaker 2: I think sometimes in Australia at the moment, I was

727
00:37:50,200 --> 00:37:54,080
Speaker 2: talking to my GP about this a couple of days ago. Currently,

728
00:37:54,160 --> 00:37:57,719
Speaker 2: a lot of doctors in you using AI scribes to

729
00:37:57,880 --> 00:38:01,759
Speaker 2: recall conversations and we were having a chat about it

730
00:38:01,840 --> 00:38:05,200
Speaker 2: because he isn't using it presently. But I really like

731
00:38:05,280 --> 00:38:08,880
Speaker 2: my doctor who is very I feel he's very proactive

732
00:38:09,080 --> 00:38:11,880
Speaker 2: on the health side of things. He'll always spend the

733
00:38:11,880 --> 00:38:13,560
Speaker 2: extra time. You know, sometimes you go to a GP

734
00:38:13,640 --> 00:38:15,680
Speaker 2: and it's like they tick a box and send you out,

735
00:38:15,760 --> 00:38:18,200
Speaker 2: whereas you know, my guy's up for a long chat

736
00:38:18,480 --> 00:38:20,239
Speaker 2: and we talk about lots of different things, and I

737
00:38:20,360 --> 00:38:22,960
Speaker 2: like that with someone who takes a personal interest. And

738
00:38:23,960 --> 00:38:26,040
Speaker 2: so in Australia at the moment, a lot of doctors

739
00:38:26,200 --> 00:38:30,560
Speaker 2: now are using AI to record what they say to

740
00:38:30,640 --> 00:38:34,200
Speaker 2: you and then but this has been used for decades,

741
00:38:34,560 --> 00:38:37,400
Speaker 2: but what AI is doing with so you can record

742
00:38:37,400 --> 00:38:41,160
Speaker 2: a whole conversation, but now they're employing AI to truncate

743
00:38:41,239 --> 00:38:43,200
Speaker 2: that conversation, break it down.

744
00:38:43,239 --> 00:38:45,399
Speaker 3: And to pull out the highlights.

745
00:38:45,920 --> 00:38:49,040
Speaker 2: And that's what they're doing that's different than been previously

746
00:38:49,120 --> 00:38:53,640
Speaker 2: recorded conversations. They're now able to cherry pick the content

747
00:38:53,880 --> 00:38:56,880
Speaker 2: and give you the relevant information and a lot of

748
00:38:56,880 --> 00:38:59,480
Speaker 2: people are kind of I was reading this article and

749
00:38:59,480 --> 00:39:01,800
Speaker 2: it might have been in mc Gharanian. I think where

750
00:39:02,160 --> 00:39:05,800
Speaker 2: there was the pros and cons should you allow yourself

751
00:39:05,840 --> 00:39:08,560
Speaker 2: to be recorded and that conversation then to be saved.

752
00:39:08,840 --> 00:39:11,759
Speaker 2: And the reality of it is our health records are accessible,

753
00:39:11,800 --> 00:39:13,799
Speaker 2: and I think that a lot of people don't realize that.

754
00:39:14,120 --> 00:39:16,200
Speaker 2: So if you do have a conversation with your GP,

755
00:39:16,320 --> 00:39:19,360
Speaker 2: everything that goes down into your health record you should

756
00:39:19,360 --> 00:39:21,000
Speaker 2: be able to access and have a look at. But

757
00:39:21,040 --> 00:39:24,040
Speaker 2: I like the idea because when you're dealing with a

758
00:39:24,120 --> 00:39:27,080
Speaker 2: medical issue, I think particularly if it's something you're a

759
00:39:27,120 --> 00:39:29,960
Speaker 2: bit frightened about. And I'm happy to be upfront about this.

760
00:39:30,000 --> 00:39:33,239
Speaker 2: I've been getting some tests recently because my identical twin

761
00:39:33,280 --> 00:39:36,319
Speaker 2: brother had prostate cancer last year, and so we've been

762
00:39:36,320 --> 00:39:39,520
Speaker 2: doing some scans to do a benchmark so that I

763
00:39:39,600 --> 00:39:42,160
Speaker 2: can make sure that I know what I look like

764
00:39:42,280 --> 00:39:44,760
Speaker 2: now and then that way, if something happens in twelve

765
00:39:44,840 --> 00:39:48,399
Speaker 2: months time, we have a comparative scan to look at

766
00:39:48,400 --> 00:39:50,840
Speaker 2: to say has there been a change, because I'm scared.

767
00:39:51,120 --> 00:39:55,160
Speaker 2: You know, I am genetically identical to my brother, and

768
00:39:55,200 --> 00:39:58,200
Speaker 2: the only differences I guess have been our lifestyles. But

769
00:39:58,239 --> 00:40:00,920
Speaker 2: the fact that at an age which under sixty, to

770
00:40:01,000 --> 00:40:04,120
Speaker 2: have prostate cancer is not good because it then means

771
00:40:04,160 --> 00:40:06,799
Speaker 2: that siblings are at a much higher risk, So I'm

772
00:40:06,800 --> 00:40:07,520
Speaker 2: mindful of that.

773
00:40:07,640 --> 00:40:08,640
Speaker 3: And that's why having a.

774
00:40:08,560 --> 00:40:11,240
Speaker 2: Good GP who's prepared to do preventive or at least,

775
00:40:11,440 --> 00:40:14,359
Speaker 2: you know, actions in place to make sure there are

776
00:40:14,360 --> 00:40:17,000
Speaker 2: baselines that we can refer back to is really important.

777
00:40:17,160 --> 00:40:20,000
Speaker 2: And so yeah, I'd be happy to have everything we

778
00:40:20,040 --> 00:40:24,000
Speaker 2: say taken down by a scribe that then is aide

779
00:40:24,719 --> 00:40:26,000
Speaker 2: and everything's remembered.

780
00:40:26,000 --> 00:40:28,280
Speaker 3: What about you, tif you would you be happy.

781
00:40:28,080 --> 00:40:30,840
Speaker 2: To go to a consultation or to sit down to

782
00:40:30,880 --> 00:40:34,000
Speaker 2: a therapist or something and everything everything recorded. Yeah?

783
00:40:34,080 --> 00:40:41,279
Speaker 1: Yeah, absolutely, crag go, Yeah, definitely. I think what you're

784
00:40:41,400 --> 00:40:44,720
Speaker 1: talking about is also a really good idea because it's

785
00:40:44,800 --> 00:40:47,560
Speaker 1: the integration of a human that you like and know

786
00:40:47,680 --> 00:40:50,920
Speaker 1: and have a relationship with and trust, right, and then

787
00:40:51,480 --> 00:40:54,239
Speaker 1: he or she doesn't need to be jotting everything, like

788
00:40:54,360 --> 00:40:57,920
Speaker 1: if you've got something else taking notes, it's so much easier.

789
00:40:57,920 --> 00:41:00,879
Speaker 1: Then they can spend more time and energy on you,

790
00:41:01,120 --> 00:41:05,200
Speaker 1: which that's a nice symbiosis. Do you like that word tip?

791
00:41:05,680 --> 00:41:09,839
Speaker 1: That's a very good wormight to dop that You're welcome. Hey, mate,

792
00:41:10,520 --> 00:41:12,400
Speaker 1: I realized we don't have that long to go, and

793
00:41:12,440 --> 00:41:14,200
Speaker 1: we've done none of your lists, so I'm going to

794
00:41:14,239 --> 00:41:17,120
Speaker 1: be bold and fucking take the reins back because I.

795
00:41:18,080 --> 00:41:20,600
Speaker 3: Told you didn't. I godn't.

796
00:41:20,760 --> 00:41:24,359
Speaker 1: No, you're exactly right. You know, well we've only gone

797
00:41:24,400 --> 00:41:27,160
Speaker 1: through one thing on your list. No we haven't. Don't

798
00:41:27,160 --> 00:41:29,640
Speaker 1: you see what I've been doing, Craigo. I've been weaving

799
00:41:30,280 --> 00:41:33,280
Speaker 1: throughout the list. We've used three stories from my list.

800
00:41:33,320 --> 00:41:35,200
Speaker 1: But I'm just weaving through that conversation.

801
00:41:35,960 --> 00:41:39,880
Speaker 2: That's right, buddy, because that was going to it's a memory,

802
00:41:40,080 --> 00:41:42,799
Speaker 2: see the next like the adjunct to that.

803
00:41:43,120 --> 00:41:43,319
Speaker 3: Right.

804
00:41:43,440 --> 00:41:45,839
Speaker 2: The little synergy to what we were talking about was,

805
00:41:46,080 --> 00:41:48,560
Speaker 2: you know, the reality is if you're a GP and

806
00:41:48,600 --> 00:41:52,200
Speaker 2: you're focusing on the person, sometimes if you're taking notes,

807
00:41:52,320 --> 00:41:54,799
Speaker 2: it can be dis jointed, whereas if you're recording it.

808
00:41:55,000 --> 00:41:58,279
Speaker 2: And memory is an interesting thing, and scientists have been

809
00:41:58,320 --> 00:42:02,200
Speaker 2: doing what they're calling a time travel memory hack to

810
00:42:02,320 --> 00:42:06,719
Speaker 2: help people remember stuff. So what the found is emotions

811
00:42:06,719 --> 00:42:10,440
Speaker 2: are closely linked to memory. So this is specifically going

812
00:42:10,480 --> 00:42:14,560
Speaker 2: to benefit learning as opposed to just general memories of events.

813
00:42:14,920 --> 00:42:16,520
Speaker 3: So this is focused on study.

814
00:42:17,040 --> 00:42:19,720
Speaker 2: So if you're a student or a learner or whatever,

815
00:42:19,800 --> 00:42:23,879
Speaker 2: but you're learning something new, what the suggesting is that

816
00:42:24,360 --> 00:42:28,080
Speaker 2: you review what you've just done, but don't think about

817
00:42:28,120 --> 00:42:30,560
Speaker 2: the action, think about the emotions, so where you were

818
00:42:30,600 --> 00:42:35,040
Speaker 2: at the time, and by reinforcing the emotions surrounding that,

819
00:42:35,640 --> 00:42:38,799
Speaker 2: it actually helps us retain a much higher degree of

820
00:42:38,880 --> 00:42:43,040
Speaker 2: memory and can actually bring it back and strengthen that memory.

821
00:42:43,080 --> 00:42:45,680
Speaker 2: So when you think of memory as kind of I guess,

822
00:42:46,080 --> 00:42:49,120
Speaker 2: a snowball rolling down a hill and it kind of

823
00:42:49,160 --> 00:42:52,719
Speaker 2: gains momentum, you can slow that down by looking at

824
00:42:52,760 --> 00:42:54,440
Speaker 2: the emotions related.

825
00:42:54,040 --> 00:42:54,800
Speaker 3: To that memory.

826
00:42:54,800 --> 00:42:57,359
Speaker 2: So I just thought that was kind of interesting that,

827
00:42:57,480 --> 00:43:00,360
Speaker 2: you know, for each of us, you know, learn is

828
00:43:00,400 --> 00:43:05,279
Speaker 2: difficult and remembering stuff is tough, and so these new

829
00:43:05,280 --> 00:43:07,719
Speaker 2: ways to kind of hack memory and think about the

830
00:43:07,760 --> 00:43:10,960
Speaker 2: way and the emotions. I think it's fascinating. And you know,

831
00:43:11,080 --> 00:43:15,319
Speaker 2: I know smell is associated with memory. Every night, most

832
00:43:15,400 --> 00:43:18,279
Speaker 2: nights a week, I have a little oil burner and

833
00:43:18,600 --> 00:43:22,600
Speaker 2: I put of scented oil in, but a peppermint scented.

834
00:43:22,280 --> 00:43:24,960
Speaker 3: Oil, because there was some research that was done.

835
00:43:24,800 --> 00:43:29,320
Speaker 2: That said that that particular carrier oil can trigger memory.

836
00:43:29,840 --> 00:43:33,120
Speaker 2: Because smell is very closely associated with memory as well.

837
00:43:33,160 --> 00:43:35,480
Speaker 2: So if you have one of those little oil diffuses

838
00:43:35,520 --> 00:43:37,040
Speaker 2: and you set it for two hours when you go

839
00:43:37,120 --> 00:43:40,040
Speaker 2: to bed, it can actually help with memory retention.

840
00:43:41,120 --> 00:43:45,839
Speaker 1: Yeah, that's so true. Memory like smell, Like I think

841
00:43:45,840 --> 00:43:48,000
Speaker 1: it's because I have a one point five nose. I

842
00:43:48,040 --> 00:43:53,319
Speaker 1: can smell shit two suburbs away, right, And and yeah, yeah,

843
00:43:53,400 --> 00:43:55,480
Speaker 1: I know I'm not pretty everyone. I don't know if

844
00:43:55,520 --> 00:44:00,400
Speaker 1: you've ever seen me, but fucking don't look too close. Patrick,

845
00:44:00,440 --> 00:44:03,600
Speaker 1: on the other hand, Brad Pitt prostate, bit dodgy but

846
00:44:03,760 --> 00:44:11,160
Speaker 1: face fucking beautiful. And Tiff more jack than both of us.

847
00:44:13,000 --> 00:44:15,680
Speaker 1: But I don't know this, like this is a I

848
00:44:15,719 --> 00:44:17,799
Speaker 1: have good ones and negative ones, but a negative one.

849
00:44:17,960 --> 00:44:20,560
Speaker 1: You know that stuff we used to eat Patrick when

850
00:44:20,560 --> 00:44:21,920
Speaker 1: we were kids called strasbourg.

851
00:44:22,840 --> 00:44:26,879
Speaker 3: Oh yeah, god yeah, oh fuck right that Tiff.

852
00:44:26,920 --> 00:44:28,080
Speaker 1: Do you know what that is?

853
00:44:28,080 --> 00:44:29,680
Speaker 4: Is that that like devon meat?

854
00:44:30,080 --> 00:44:32,799
Speaker 1: Yeah, it's just like fucking goop in a tube. I

855
00:44:32,800 --> 00:44:34,719
Speaker 1: don't know what. I don't know what it is, but

856
00:44:34,800 --> 00:44:39,240
Speaker 1: it's like I think it's, you know, sphinters and livers

857
00:44:39,320 --> 00:44:42,960
Speaker 1: and just put through a grinder. I don't know what

858
00:44:43,000 --> 00:44:47,839
Speaker 1: it is, right, Yeah, yeah, yeah, yeah, yeah. Anyway, when

859
00:44:47,880 --> 00:44:49,360
Speaker 1: I was a kid, I was about eight, and I

860
00:44:49,440 --> 00:44:51,840
Speaker 1: used to fucking inhale that ship with sauce and white

861
00:44:51,840 --> 00:44:55,120
Speaker 1: bread because I was a pig and I has a

862
00:44:55,120 --> 00:44:58,480
Speaker 1: little pig. That was before I got to the cheesecake. Numb, numb, numb,

863
00:44:58,480 --> 00:45:01,120
Speaker 1: get out of my way. I was very hard to

864
00:45:01,160 --> 00:45:03,360
Speaker 1: distract when I was eating, very hard to get my

865
00:45:03,400 --> 00:45:08,319
Speaker 1: attention anyway. So I ate about two pounds of that.

866
00:45:08,440 --> 00:45:13,000
Speaker 1: Then was violently ill. And then now even obviously I've

867
00:45:13,000 --> 00:45:16,959
Speaker 1: never eaten it touched it since. But even now, if

868
00:45:17,000 --> 00:45:20,280
Speaker 1: I see it, if I see that or what looks

869
00:45:20,440 --> 00:45:23,440
Speaker 1: like that similar to that, I almost gag. And if

870
00:45:23,440 --> 00:45:26,640
Speaker 1: I smell it or something like it, I could pretty

871
00:45:26,680 --> 00:45:30,040
Speaker 1: much vomit on cue. It's just and I'd never think

872
00:45:30,080 --> 00:45:32,920
Speaker 1: about it unless I see it or smell it. And

873
00:45:32,960 --> 00:45:37,480
Speaker 1: we're talking literally fifty years down the track. There's something

874
00:45:37,520 --> 00:45:41,360
Speaker 1: built into my brain and my physiology that so that

875
00:45:41,480 --> 00:45:45,960
Speaker 1: is very true, Patrick. There is emotions and smells and

876
00:45:46,080 --> 00:45:50,600
Speaker 1: stories also, stories are kind of you know, experiences have

877
00:45:50,719 --> 00:45:52,160
Speaker 1: us tied into certain memories.

878
00:45:52,320 --> 00:45:55,680
Speaker 3: I'm just picturing Mary unwrapping the strasbourg from the paper

879
00:45:55,680 --> 00:45:56,480
Speaker 3: wrap and.

880
00:45:56,480 --> 00:46:02,040
Speaker 4: Staying one piece won't hurting your hand in the work,

881
00:46:02,280 --> 00:46:04,160
Speaker 4: and then coming back and counting to see if she's

882
00:46:04,120 --> 00:46:05,400
Speaker 4: still had all five fingers.

883
00:46:06,719 --> 00:46:08,720
Speaker 1: Well, she used to just put it in the bowl

884
00:46:08,760 --> 00:46:10,600
Speaker 1: on the floor when me and the dog would eat

885
00:46:10,680 --> 00:46:14,360
Speaker 1: side by side, so I always beat the dog, So

886
00:46:15,400 --> 00:46:21,040
Speaker 1: fuck you dog. Patrick tell us about robot hands building

887
00:46:21,080 --> 00:46:24,240
Speaker 1: pizzas speaking of food. Oh dear, we.

888
00:46:24,160 --> 00:46:26,839
Speaker 3: Had this conversation during the week by text tip.

889
00:46:28,480 --> 00:46:32,080
Speaker 2: So they've developed this is for people who actually have disabilities.

890
00:46:32,480 --> 00:46:35,000
Speaker 2: Is primarily who they're focused on and what it is.

891
00:46:35,040 --> 00:46:38,400
Speaker 2: It's a robotic assistant. One of the difficulties with robots

892
00:46:38,480 --> 00:46:40,080
Speaker 2: is they use them in production all the time, so

893
00:46:40,160 --> 00:46:43,920
Speaker 2: car manufacturers use them. But the thing is, a robot

894
00:46:44,040 --> 00:46:46,920
Speaker 2: arm that's designed to pick up a heavy object is

895
00:46:47,120 --> 00:46:49,719
Speaker 2: very different than say a robot arm that's picking up

896
00:46:49,760 --> 00:46:52,480
Speaker 2: little grains of cheese that have fallen. You know, so

897
00:46:52,520 --> 00:46:54,640
Speaker 2: you've dropped pieces of cheese and it's picking up the

898
00:46:54,680 --> 00:46:58,600
Speaker 2: little The dexterity is really different. And so they've got

899
00:46:58,640 --> 00:47:01,160
Speaker 2: this robot that has the strength to be able to

900
00:47:01,160 --> 00:47:04,120
Speaker 2: pick up large objects, say a pot of boiling water,

901
00:47:04,520 --> 00:47:07,560
Speaker 2: but it can also be very delicate because it has

902
00:47:08,040 --> 00:47:11,560
Speaker 2: soft fingertips to be able to sense the pressure. And

903
00:47:12,040 --> 00:47:15,760
Speaker 2: so this this new robotic arm or new robotic hand

904
00:47:15,760 --> 00:47:19,799
Speaker 2: can be used just to keep with disabilities, to give

905
00:47:19,840 --> 00:47:20,839
Speaker 2: them more independence.

906
00:47:21,280 --> 00:47:28,600
Speaker 1: Craig I will say tiff I, tiff Tip, it wasn't me.

907
00:47:29,239 --> 00:47:32,400
Speaker 1: Patrick did suggest that he might get one for his bedroom.

908
00:47:32,640 --> 00:47:34,840
Speaker 1: I did not know what he was talking about. No,

909
00:47:35,160 --> 00:47:39,200
Speaker 1: did not know. Hey, don't bring up your fucking phone, everyone,

910
00:47:39,320 --> 00:47:45,600
Speaker 1: that's it. That's another episode of you projected story, tiff Ah,

911
00:47:46,400 --> 00:47:49,680
Speaker 1: don't let facts get in the way. Patrick, have we not?

912
00:47:50,040 --> 00:47:51,680
Speaker 1: I think I'm a contradicting myself.

913
00:47:51,680 --> 00:47:53,040
Speaker 3: I send him this article.

914
00:47:53,200 --> 00:47:56,160
Speaker 2: So it's a robot AI robot arm builds meals and

915
00:47:56,239 --> 00:47:59,040
Speaker 2: helps users with limited mobility. So I send it off

916
00:47:59,080 --> 00:48:01,120
Speaker 2: to Crago and I said, hey, maybe you could get

917
00:48:01,160 --> 00:48:04,759
Speaker 2: one via bedroom. His reply was if they built, but

918
00:48:04,960 --> 00:48:06,160
Speaker 2: with a mouth.

919
00:48:08,200 --> 00:48:09,160
Speaker 1: I did not say that.

920
00:48:10,080 --> 00:48:13,360
Speaker 2: My reply was, I'm sure it's on the way. Maybe

921
00:48:13,400 --> 00:48:18,680
Speaker 2: we'll get a discountfort too. And Craig's reply figures crossed.

922
00:48:19,360 --> 00:48:23,279
Speaker 1: That that's a complete lie. Everyone. I wouldn't participate any

923
00:48:23,360 --> 00:48:27,439
Speaker 1: kind of conversational transaction like that. I've been misrepresented. I'm

924
00:48:27,480 --> 00:48:32,360
Speaker 1: calling my lawyer. That's fucking that's that's terrible, Patrick, that

925
00:48:32,400 --> 00:48:34,600
Speaker 1: you misrepresent me like that to people.

926
00:48:35,280 --> 00:48:39,000
Speaker 2: And so her sending your screenshot of that what'sapp private conversation?

927
00:48:39,520 --> 00:48:45,160
Speaker 1: The show doesn't prove anything. Tell us why Delta Airlines

928
00:48:45,320 --> 00:48:50,560
Speaker 1: and others are working with an AI startup that personalizes prices.

929
00:48:50,600 --> 00:48:51,640
Speaker 1: What does that even mean?

930
00:48:51,960 --> 00:48:52,720
Speaker 3: Mastards?

931
00:48:52,960 --> 00:48:57,000
Speaker 2: Sorry, So there's a few senators in the US that

932
00:48:57,040 --> 00:49:00,600
Speaker 2: are having a real look at this, this scrutinizing this. Evidently,

933
00:49:00,680 --> 00:49:02,879
Speaker 2: what they're going to do is try to look at

934
00:49:02,920 --> 00:49:07,080
Speaker 2: and profile people and then adjust the prices accordingly. So

935
00:49:07,280 --> 00:49:10,160
Speaker 2: the idea being is if you could afford to pay more,

936
00:49:10,400 --> 00:49:13,680
Speaker 2: they'll bump up the price for you. Now they're denying this,

937
00:49:14,280 --> 00:49:17,480
Speaker 2: but it's come under the scrutiny because they're teaming up

938
00:49:17,480 --> 00:49:22,880
Speaker 2: with this is Israeli company that specializes in using an AI

939
00:49:23,040 --> 00:49:27,360
Speaker 2: algorithm to be able to take on people's situations, to

940
00:49:27,440 --> 00:49:31,000
Speaker 2: profile somebody and then adjust the prices according to that

941
00:49:31,080 --> 00:49:36,560
Speaker 2: person's circumstances. So this is, you know, personalized prices like

942
00:49:36,640 --> 00:49:38,840
Speaker 2: really rub me up the wrong way. I think it's

943
00:49:38,880 --> 00:49:41,319
Speaker 2: an awful situation if it looked at the three of

944
00:49:41,400 --> 00:49:43,600
Speaker 2: us and decided what we're going to be paying based

945
00:49:43,640 --> 00:49:48,279
Speaker 2: on whatever it decided. So this is there's been a

946
00:49:48,360 --> 00:49:51,239
Speaker 2: recent letter to the members of Congress. The company is

947
00:49:51,320 --> 00:49:55,600
Speaker 2: denied using AI tools to what they say price gouge customers.

948
00:49:55,800 --> 00:49:59,600
Speaker 2: So that was a report in Reuters. But this democratic

949
00:49:59,760 --> 00:50:04,440
Speaker 2: error zone as Senator a lady, I thigur it's a lady,

950
00:50:04,520 --> 00:50:06,880
Speaker 2: or maybe it could be a bloke. Anyway, the Senator

951
00:50:06,920 --> 00:50:10,680
Speaker 2: has accused Delta of telling their investors one thing and

952
00:50:10,719 --> 00:50:12,879
Speaker 2: then turning around and telling the public and other things.

953
00:50:12,960 --> 00:50:15,879
Speaker 2: So they're talking it up to their investors because of course,

954
00:50:15,880 --> 00:50:19,200
Speaker 2: if they can get people to spend more, it's going

955
00:50:19,280 --> 00:50:21,400
Speaker 2: to do good for the bottom line when it comes

956
00:50:21,440 --> 00:50:24,920
Speaker 2: to people who are invested in the airline. But it

957
00:50:25,000 --> 00:50:28,680
Speaker 2: got me thinking, and by coincidence, this week there's you know,

958
00:50:28,880 --> 00:50:31,160
Speaker 2: I'm living in a small country town of about three

959
00:50:31,200 --> 00:50:33,719
Speaker 2: thousand people, and there was a little fruit and d

960
00:50:33,800 --> 00:50:36,680
Speaker 2: shop that sadly closed down, and I used to go

961
00:50:36,719 --> 00:50:38,600
Speaker 2: there all the time. I used to get my watercress

962
00:50:38,600 --> 00:50:41,000
Speaker 2: from there. Now I can't get watercress, not that you

963
00:50:41,040 --> 00:50:44,440
Speaker 2: needed to know that, but it's good in wraps anyway.

964
00:50:44,600 --> 00:50:47,600
Speaker 2: So they closed down about a week and a half

965
00:50:47,680 --> 00:50:50,279
Speaker 2: two weeks ago, and I happened to be walking through

966
00:50:50,320 --> 00:50:53,680
Speaker 2: the supermarket and the owner of the supermarket had his

967
00:50:53,719 --> 00:50:55,360
Speaker 2: iPad out and was looking at prices.

968
00:50:55,400 --> 00:50:56,400
Speaker 3: Tips piss and herself.

969
00:50:56,640 --> 00:51:00,399
Speaker 2: But so he's looking at prices and I just turned

970
00:51:00,440 --> 00:51:03,880
Speaker 2: the corner and got into the aisle and the staff

971
00:51:03,920 --> 00:51:08,759
Speaker 2: memory he was talking to said twenty five percent. And

972
00:51:08,840 --> 00:51:11,879
Speaker 2: his reply was, well, the fruit and veg shops closed down?

973
00:51:13,560 --> 00:51:17,680
Speaker 1: Oh wow, yeah, So well that's yeah, I mean, that's

974
00:51:17,719 --> 00:51:21,920
Speaker 1: how the free market works. We've got a monopoly. Hey,

975
00:51:21,920 --> 00:51:25,279
Speaker 1: I just wanted to ask. I want to circle back

976
00:51:25,320 --> 00:51:27,600
Speaker 1: to one thing because I want your thoughts and explanation

977
00:51:27,680 --> 00:51:30,160
Speaker 1: because I don't really get it. The thing I don't

978
00:51:30,239 --> 00:51:32,799
Speaker 1: really get is so from the end of the year

979
00:51:32,880 --> 00:51:36,560
Speaker 1: or whenever it is, they're banning kids under sixteen from

980
00:51:36,640 --> 00:51:38,960
Speaker 1: using social media correct.

981
00:51:38,880 --> 00:51:41,360
Speaker 3: Yes, including a cube now and that was the recent

982
00:51:41,520 --> 00:51:43,160
Speaker 3: edition as well, because the review shube is going to

983
00:51:43,160 --> 00:51:43,959
Speaker 3: be exempt.

984
00:51:44,239 --> 00:51:48,600
Speaker 1: So is this a law or is this a recommendation?

985
00:51:49,160 --> 00:51:52,480
Speaker 3: Is this law enshrining it in law? How on how

986
00:51:52,520 --> 00:51:54,279
Speaker 3: on earth are they going to police it?

987
00:51:55,239 --> 00:51:57,399
Speaker 1: How on earth do you stop a sixteen year old?

988
00:51:57,600 --> 00:52:00,319
Speaker 2: So what you do is no, no, it's about putting

989
00:52:00,400 --> 00:52:04,040
Speaker 2: pressure on those social media outlets to be able to

990
00:52:04,239 --> 00:52:07,279
Speaker 2: prove that people are the age that they are. It's

991
00:52:07,280 --> 00:52:10,040
Speaker 2: going to impact all of us. So when you go

992
00:52:10,120 --> 00:52:12,600
Speaker 2: to sign up for a new accounts, they're going to

993
00:52:12,640 --> 00:52:16,200
Speaker 2: ask for a method of ID to prove, so the

994
00:52:16,239 --> 00:52:19,120
Speaker 2: owners is going to be on those social media organizations.

995
00:52:19,480 --> 00:52:21,879
Speaker 2: So what we're saying is, if Craig wants to set

996
00:52:21,920 --> 00:52:25,279
Speaker 2: up a Snapchat account or a YouTube account or an

997
00:52:25,280 --> 00:52:28,200
Speaker 2: Instagram account, you have to prove your over the age

998
00:52:28,239 --> 00:52:28,800
Speaker 2: of sixteen.

999
00:52:30,680 --> 00:52:33,040
Speaker 1: What about Oh wow, you know what I just thought,

1000
00:52:33,080 --> 00:52:37,880
Speaker 1: which you'd probably thought, what about all the thirteen fourteen

1001
00:52:38,000 --> 00:52:44,400
Speaker 1: fifteen year olds on well, TikTok and ig who are like,

1002
00:52:44,560 --> 00:52:49,640
Speaker 1: got lots of profile and momentum and like a lot

1003
00:52:49,680 --> 00:52:54,120
Speaker 1: of their their social kind of interaction is there.

1004
00:52:55,280 --> 00:52:59,279
Speaker 3: Well, I think the interesting thing will be originally so,

1005
00:52:59,320 --> 00:53:01,960
Speaker 3: I don't know that all social medias require you to

1006
00:53:02,160 --> 00:53:05,359
Speaker 3: have put an age in the first place. So there's

1007
00:53:05,400 --> 00:53:07,799
Speaker 3: been a scramble. An article I read earlier in the

1008
00:53:07,800 --> 00:53:09,799
Speaker 3: week said there's been a scramble. I think it might've

1009
00:53:09,800 --> 00:53:12,319
Speaker 3: been on the ABC that a lot of young people

1010
00:53:12,360 --> 00:53:14,160
Speaker 3: who are under the age of sixteen and are rushing

1011
00:53:14,200 --> 00:53:16,719
Speaker 3: to get accounts now before they need to prove that

1012
00:53:16,719 --> 00:53:18,880
Speaker 3: they're under the age of sixteen. So I think if

1013
00:53:18,880 --> 00:53:21,880
Speaker 3: you've already got an existing account, there's an argument that

1014
00:53:21,920 --> 00:53:24,359
Speaker 3: it's an existing account. That's a really really good question.

1015
00:53:24,480 --> 00:53:27,000
Speaker 2: I don't know that I know the answer to that, well,

1016
00:53:27,120 --> 00:53:30,319
Speaker 2: I do know, I don't know the answer. I'm not

1017
00:53:30,520 --> 00:53:32,400
Speaker 2: entirely sure, but I figure that if you've got an

1018
00:53:32,400 --> 00:53:35,400
Speaker 2: account already and you've got traction with that account, you

1019
00:53:35,480 --> 00:53:37,600
Speaker 2: haven't needed to prove your age to get it in

1020
00:53:37,640 --> 00:53:40,720
Speaker 2: the first place, so you can't. I don't think it's retrospective.

1021
00:53:40,719 --> 00:53:42,759
Speaker 2: I don't think they're going to roll it back that way.

1022
00:53:42,760 --> 00:53:45,760
Speaker 2: But that's a really good point. I'm not sure I reckon.

1023
00:53:46,280 --> 00:53:51,680
Speaker 1: What is really an interesting paradoxical kind of thing is

1024
00:53:51,719 --> 00:53:54,440
Speaker 1: that so they're going to force all of these social

1025
00:53:54,520 --> 00:53:59,000
Speaker 1: media platforms, YouTube and the like. Would you call YouTube

1026
00:53:59,000 --> 00:54:00,920
Speaker 1: a social media platform or would you just call a

1027
00:54:00,920 --> 00:54:05,560
Speaker 1: streaming platform? Yeah, whatever, anyway, so they're forcing them to

1028
00:54:05,680 --> 00:54:10,320
Speaker 1: create this gateway or whatever it is or process to

1029
00:54:10,440 --> 00:54:14,799
Speaker 1: ensure that people are a certain age, and that very

1030
00:54:14,880 --> 00:54:19,439
Speaker 1: process is commercially destructive for them, Like that just means

1031
00:54:19,480 --> 00:54:22,880
Speaker 1: they're going to have less users. So what the government

1032
00:54:22,960 --> 00:54:25,160
Speaker 1: saying is you're going to have less people using it.

1033
00:54:25,200 --> 00:54:27,440
Speaker 1: You're going to bottom line is the more people using it,

1034
00:54:27,480 --> 00:54:29,880
Speaker 1: the more income. And they're a business, so they're a

1035
00:54:29,880 --> 00:54:33,600
Speaker 1: profit profit driven business, like nearly all businesses, not all

1036
00:54:33,640 --> 00:54:38,200
Speaker 1: but nearly all, and we're making you do this thing

1037
00:54:38,440 --> 00:54:41,480
Speaker 1: that's going to equal. The net result is you'll make

1038
00:54:41,560 --> 00:54:44,799
Speaker 1: less money because you've got less users. I wonder what

1039
00:54:44,840 --> 00:54:48,440
Speaker 1: they're hack around, because they must be thinking already, how

1040
00:54:48,440 --> 00:54:52,000
Speaker 1: can we beat this, because they're not going to go, oh, sure,

1041
00:54:52,600 --> 00:54:55,160
Speaker 1: we want thirty percent of or forty percent of our

1042
00:54:55,280 --> 00:54:59,279
Speaker 1: users to just jump off, okay, government, We're fine. I

1043
00:54:59,360 --> 00:55:01,040
Speaker 1: wonder what they're counter to that is.

1044
00:55:02,200 --> 00:55:06,239
Speaker 2: That's an absolutely amazingly good question. The interesting thing for

1045
00:55:06,280 --> 00:55:08,799
Speaker 2: me is that there was certainly some media outlets on

1046
00:55:08,920 --> 00:55:12,680
Speaker 2: some social media is young people have no desire whatsoever

1047
00:55:12,760 --> 00:55:15,560
Speaker 2: to be on like Facebook and Institute, maybe Instagram a

1048
00:55:15,600 --> 00:55:18,000
Speaker 2: little bit more, but definitely not Facebook. No young person

1049
00:55:18,040 --> 00:55:20,520
Speaker 2: in their right mind wants to be on Facebook. That's

1050
00:55:20,560 --> 00:55:22,719
Speaker 2: just like for dinosaurs.

1051
00:55:23,520 --> 00:55:27,320
Speaker 1: Now it is a little bit, isn't it. But remember

1052
00:55:27,360 --> 00:55:29,680
Speaker 1: when it was like two thousand and eight, Zuckerberg or

1053
00:55:29,719 --> 00:55:31,440
Speaker 1: whatever it was, it was like it was the.

1054
00:55:31,400 --> 00:55:34,759
Speaker 2: Way, oh, because it was originally designed at a university

1055
00:55:34,880 --> 00:55:38,600
Speaker 2: level for young university students to connect with each other.

1056
00:55:38,640 --> 00:55:42,759
Speaker 2: It was Zuckerberg obviously had no friends, and that's how he.

1057
00:55:44,600 --> 00:55:47,200
Speaker 1: Well, he's kicked on. He's kicked gone, he's done all right,

1058
00:55:47,960 --> 00:55:50,120
Speaker 1: the young loser he's kicked on.

1059
00:55:50,400 --> 00:55:51,400
Speaker 3: Do you want to be his mate?

1060
00:55:52,360 --> 00:55:54,840
Speaker 1: Would you I'd be interested to speak to I would

1061
00:55:54,840 --> 00:55:57,520
Speaker 1: be interested to meet him, and then make that determination,

1062
00:55:57,960 --> 00:56:00,400
Speaker 1: like I think, what do you know about anyone? Stick?

1063
00:56:00,480 --> 00:56:04,160
Speaker 1: Some you know, they say, don't meet your heroes. I

1064
00:56:04,200 --> 00:56:08,560
Speaker 1: won't say. I've met a few people that I really thought, well,

1065
00:56:09,120 --> 00:56:10,960
Speaker 1: I love them, and then I met him and I'm like,

1066
00:56:11,040 --> 00:56:14,200
Speaker 1: oh God, you're a fucking idiot or you're just so

1067
00:56:15,040 --> 00:56:17,120
Speaker 1: you know. And then other people that I thought were

1068
00:56:17,160 --> 00:56:20,160
Speaker 1: maybe not not someone i'd want to meet and they

1069
00:56:20,200 --> 00:56:24,200
Speaker 1: were brilliant. I'm like, oh you are actually great. Hey,

1070
00:56:24,360 --> 00:56:26,839
Speaker 1: I who was that you were telling me about? Like

1071
00:56:26,960 --> 00:56:30,239
Speaker 1: someone on social media that you didn't really warm to,

1072
00:56:31,160 --> 00:56:34,239
Speaker 1: and then you you got you started looking at their

1073
00:56:34,280 --> 00:56:36,600
Speaker 1: content or knowing a bit more about them, and you

1074
00:56:36,800 --> 00:56:39,560
Speaker 1: kind of did a one eighty. I remember you telling.

1075
00:56:39,360 --> 00:56:41,879
Speaker 4: Me about it. I know there was I think there's

1076
00:56:41,880 --> 00:56:44,160
Speaker 4: been a couple, but I know Lane Norton. Was it

1077
00:56:44,440 --> 00:56:49,280
Speaker 4: like that for me? You two people from podcasts Jimmy

1078
00:56:49,320 --> 00:56:53,759
Speaker 4: Carr now fan and Norton as well, because I heard

1079
00:56:53,840 --> 00:56:56,200
Speaker 4: him on a podcast and it changed my change my

1080
00:56:56,239 --> 00:56:58,799
Speaker 4: perception of his carry on on socials.

1081
00:56:58,920 --> 00:57:02,440
Speaker 1: Yeah, yeah, yeah, you Patrick, have you Let's go a

1082
00:57:02,480 --> 00:57:04,680
Speaker 1: good one. Have you ever met anyone that you were

1083
00:57:04,719 --> 00:57:08,000
Speaker 1: really surprised how much you liked them and connected with

1084
00:57:08,080 --> 00:57:09,839
Speaker 1: him when perhaps you thought you might not of.

1085
00:57:10,680 --> 00:57:12,080
Speaker 3: Not so much that I didn't know of, but they

1086
00:57:12,120 --> 00:57:13,760
Speaker 3: were so kind of not out of reach.

1087
00:57:13,840 --> 00:57:19,280
Speaker 2: But Bryce Coordinay, you know Bryce who wrote prolific author.

1088
00:57:19,840 --> 00:57:22,360
Speaker 2: I bumped into him just coming out of the lift

1089
00:57:22,400 --> 00:57:25,240
Speaker 2: when I was working at Triple M and Fox and

1090
00:57:26,200 --> 00:57:26,840
Speaker 2: someone I was.

1091
00:57:26,800 --> 00:57:28,720
Speaker 3: With knew him and introduced me to him.

1092
00:57:28,840 --> 00:57:31,520
Speaker 2: And the interesting thing was he started asking me about

1093
00:57:31,520 --> 00:57:33,080
Speaker 2: what I was doing, you know, because I just finished

1094
00:57:33,080 --> 00:57:36,360
Speaker 2: to breakfast shift, and he said, you know, we got chatting,

1095
00:57:36,520 --> 00:57:39,400
Speaker 2: and by coincidence, I was about to go to the gym,

1096
00:57:39,520 --> 00:57:42,440
Speaker 2: to your gym, to Harper's and he got to me

1097
00:57:42,480 --> 00:57:45,160
Speaker 2: about keeping fit and he was so interested. I kept

1098
00:57:45,160 --> 00:57:47,760
Speaker 2: trying to ask him questions, but he was asking me

1099
00:57:47,840 --> 00:57:50,520
Speaker 2: lots of questions and he was such a nice guy.

1100
00:57:50,680 --> 00:57:53,360
Speaker 2: He was really really nice. There's this funny little I

1101
00:57:53,480 --> 00:57:55,080
Speaker 2: got to tell you this story. There was this really

1102
00:57:55,080 --> 00:58:00,120
Speaker 2: great ABC TV show that was interviewing Australia's really famous

1103
00:58:00,320 --> 00:58:05,240
Speaker 2: authors was Colin McCulloch, Bryce Courtney, and I think Matthew Riley,

1104
00:58:05,280 --> 00:58:07,360
Speaker 2: who and if you're looking for an action book that

1105
00:58:07,400 --> 00:58:11,360
Speaker 2: you can't put down, Matthew Riley is amazing. So the

1106
00:58:11,400 --> 00:58:14,640
Speaker 2: three of them were giving this round table interview and

1107
00:58:14,720 --> 00:58:18,280
Speaker 2: Matthew and Bryce Courtney kind of said, look, he's very

1108
00:58:18,280 --> 00:58:20,320
Speaker 2: well known for he was very well known for giving

1109
00:58:20,360 --> 00:58:23,520
Speaker 2: away books. He'd give about away two thousand books a year.

1110
00:58:24,000 --> 00:58:26,040
Speaker 2: And the thing he always used to say is if

1111
00:58:26,080 --> 00:58:29,320
Speaker 2: you give away one book, you've got a fan for life.

1112
00:58:29,720 --> 00:58:34,040
Speaker 2: And so Matthew Riley said, you know, if you can

1113
00:58:34,120 --> 00:58:37,000
Speaker 2: find a Bryce Courtney book that isn't signed, it'll be

1114
00:58:37,040 --> 00:58:37,920
Speaker 2: worth a fortune.

1115
00:58:38,960 --> 00:58:40,840
Speaker 1: That's funny, that's funny.

1116
00:58:40,960 --> 00:58:42,760
Speaker 3: It was really cute. It was really cute.

1117
00:58:42,800 --> 00:58:45,080
Speaker 2: And he said, you can tell how famous an author

1118
00:58:45,160 --> 00:58:48,080
Speaker 2: is when the name that the author's name is bigger

1119
00:58:48,080 --> 00:58:49,200
Speaker 2: than the title of the book.

1120
00:58:49,560 --> 00:58:51,360
Speaker 3: And he was taking the piss out of them as well.

1121
00:58:51,520 --> 00:58:55,160
Speaker 2: Know, Colin McCulloch and Bryce Courtney, you look at any

1122
00:58:55,160 --> 00:58:58,160
Speaker 2: of their books and their name is bigger than the title.

1123
00:58:58,360 --> 00:58:59,200
Speaker 3: It's great, isn't it.

1124
00:58:59,240 --> 00:59:01,760
Speaker 2: So it was a beautiful conversation and really interesting, but

1125
00:59:01,840 --> 00:59:05,360
Speaker 2: he certainly was somebody that blew me away just by

1126
00:59:05,520 --> 00:59:10,360
Speaker 2: how personable, how how interested he was in me as

1127
00:59:10,400 --> 00:59:13,640
Speaker 2: a person in that very brief moment that we had

1128
00:59:13,640 --> 00:59:14,360
Speaker 2: that conversation.

1129
00:59:15,320 --> 00:59:18,480
Speaker 3: Yeah, well you Craig, if you had that.

1130
00:59:19,880 --> 00:59:22,960
Speaker 1: I mean, I've met lots of people, but just someone

1131
00:59:23,000 --> 00:59:25,440
Speaker 1: that I thought was great and then I met them

1132
00:59:25,440 --> 00:59:28,440
Speaker 1: and I went, oh, you're you're even better. It was

1133
00:59:28,440 --> 00:59:33,160
Speaker 1: Bruce mcavany. Oh yeah, like I always you know, which

1134
00:59:33,160 --> 00:59:35,560
Speaker 1: some people would not know him, but a lot of

1135
00:59:35,560 --> 00:59:38,200
Speaker 1: our listeners would, you know, just not just but a

1136
00:59:38,200 --> 00:59:40,840
Speaker 1: sports commentator, but just like a bit of a savant

1137
00:59:40,960 --> 00:59:46,720
Speaker 1: with you know, sports history and data and information and

1138
00:59:46,800 --> 00:59:50,000
Speaker 1: everything from track and field to horse racing to footy

1139
00:59:50,080 --> 00:59:53,960
Speaker 1: to swimming. Like he's just he's just yeah. But I

1140
00:59:54,000 --> 00:59:58,040
Speaker 1: met him at SCN when I was working there, and

1141
00:59:58,040 --> 01:00:00,360
Speaker 1: and you know when people grab your hand and then

1142
01:00:00,400 --> 01:00:02,760
Speaker 1: they grab your forearm and they shake your four arm

1143
01:00:02,800 --> 01:00:05,640
Speaker 1: and your hand at the same time, and he was

1144
01:00:05,840 --> 01:00:10,560
Speaker 1: just yeah, same, just the nicest dude ever, very engaging,

1145
01:00:10,880 --> 01:00:15,240
Speaker 1: not it wasn't you know when some people they shake

1146
01:00:15,280 --> 01:00:18,640
Speaker 1: your hand and it's almost just like this obligatory social

1147
01:00:18,720 --> 01:00:21,880
Speaker 1: thing that takes four seconds, they're not really present. He

1148
01:00:22,000 --> 01:00:24,480
Speaker 1: was just yeah, I had that recently.

1149
01:00:24,520 --> 01:00:27,479
Speaker 3: I was a colleague that i'd met.

1150
01:00:27,520 --> 01:00:30,160
Speaker 2: This is a company we do social media for and

1151
01:00:30,200 --> 01:00:32,720
Speaker 2: the guy that is our main contact, so it's normally

1152
01:00:32,760 --> 01:00:35,880
Speaker 2: by email, but he popped into our office. But he

1153
01:00:35,960 --> 01:00:38,600
Speaker 2: was one of those people, you know. He shook my

1154
01:00:38,760 --> 01:00:41,560
Speaker 2: hand and he thanked us for the work that we'd

1155
01:00:41,720 --> 01:00:44,800
Speaker 2: been doing. But the shake was that little bit extra,

1156
01:00:45,120 --> 01:00:45,960
Speaker 2: a little bit longer.

1157
01:00:46,080 --> 01:00:46,400
Speaker 3: It was.

1158
01:00:46,480 --> 01:00:49,560
Speaker 2: It was a real sense of connectedness and sincerity. And

1159
01:00:49,600 --> 01:00:51,800
Speaker 2: I think sometimes you can tell that in a handshake

1160
01:00:52,120 --> 01:00:56,000
Speaker 2: that the person is genuinely kind of in that tactile touch.

1161
01:00:56,240 --> 01:00:59,280
Speaker 2: And we didn't shake hands for a long time around COVID,

1162
01:00:59,320 --> 01:01:03,000
Speaker 2: remember we you know, remember I can remember going to

1163
01:01:03,040 --> 01:01:05,680
Speaker 2: a board meeting. I was on the quality risk committee

1164
01:01:05,680 --> 01:01:08,240
Speaker 2: of our local hospital, and I sat on that committee

1165
01:01:08,280 --> 01:01:10,040
Speaker 2: for quite a few years. And I remember the first

1166
01:01:10,040 --> 01:01:13,959
Speaker 2: this is pre COVID, but going into to COVID where

1167
01:01:14,200 --> 01:01:17,080
Speaker 2: the doctor came in and I hadn't met him before,

1168
01:01:17,320 --> 01:01:19,400
Speaker 2: and I went to shake his hand and he pulled

1169
01:01:19,440 --> 01:01:21,480
Speaker 2: back and put his both hands up, and it's like,

1170
01:01:21,640 --> 01:01:24,520
Speaker 2: what the hell, you know, it's really I felt really

1171
01:01:24,640 --> 01:01:27,480
Speaker 2: offended because he didn't want to touch my hand, because

1172
01:01:27,720 --> 01:01:29,720
Speaker 2: I'd never met him before, and the first instinct was

1173
01:01:29,720 --> 01:01:30,320
Speaker 2: to shake hands.

1174
01:01:30,360 --> 01:01:32,240
Speaker 3: And this was literally pre COVID.

1175
01:01:32,240 --> 01:01:34,960
Speaker 2: It was only this the rumors of COVID at the time,

1176
01:01:35,400 --> 01:01:37,880
Speaker 2: but they'd already started to put in place, you know,

1177
01:01:37,920 --> 01:01:40,400
Speaker 2: the protections and all that sort of thing. And obviously

1178
01:01:40,400 --> 01:01:43,320
Speaker 2: tactile contact was out. For so many years, we'd in touch,

1179
01:01:43,640 --> 01:01:46,720
Speaker 2: we didn't hug people, and so now that we seem

1180
01:01:46,760 --> 01:01:50,080
Speaker 2: to have returned back to that where people can physically

1181
01:01:50,280 --> 01:01:53,120
Speaker 2: connect in that way, it is interesting and a handshake

1182
01:01:53,160 --> 01:01:54,800
Speaker 2: can say a lot about a person, can't it.

1183
01:01:55,520 --> 01:01:58,360
Speaker 1: Oh? Certainly? Well, you and I didn't stop spooning all

1184
01:01:58,400 --> 01:02:01,040
Speaker 1: through COVID, so I mean we just took the risk.

1185
01:02:01,160 --> 01:02:04,400
Speaker 1: We went fuck it. Well, fuck the rules, We're going

1186
01:02:04,480 --> 01:02:07,200
Speaker 1: to spoon. Hey, tell people and.

1187
01:02:07,560 --> 01:02:10,000
Speaker 3: Spoon now we swap See. I think that's nice too.

1188
01:02:10,920 --> 01:02:16,160
Speaker 1: Yes, well those not hot. I was going to say

1189
01:02:16,200 --> 01:02:19,000
Speaker 1: something hilarious. If you stop and.

1190
01:02:19,000 --> 01:02:21,320
Speaker 3: Tell the whole show you're a legend.

1191
01:02:22,000 --> 01:02:24,240
Speaker 1: Yes she did. Patrick tell people how to find you,

1192
01:02:24,280 --> 01:02:26,880
Speaker 1: follow you and connect with you and potentially spoon with you.

1193
01:02:26,920 --> 01:02:28,040
Speaker 1: If you would, that would be great.

1194
01:02:28,480 --> 01:02:29,920
Speaker 3: I've had no offers yet, Craigo.

1195
01:02:30,040 --> 01:02:33,680
Speaker 2: You say that every time we speak websitesnow dot com

1196
01:02:33,720 --> 01:02:36,440
Speaker 2: today you if you want to talk business related stuff

1197
01:02:36,520 --> 01:02:39,640
Speaker 2: like websites and stuff, but if you want to tai

1198
01:02:39,760 --> 01:02:41,360
Speaker 2: chi is my big passion in life.

1199
01:02:41,360 --> 01:02:42,120
Speaker 3: I love tai chi.

1200
01:02:42,440 --> 01:02:44,280
Speaker 2: And if you want to just do tai chi with me,

1201
01:02:44,520 --> 01:02:46,800
Speaker 2: like watch a video with me and Fritz doing tai chi.

1202
01:02:47,280 --> 01:02:50,520
Speaker 2: Just tie chi at home dot com, todau, just jump in,

1203
01:02:50,960 --> 01:02:51,280
Speaker 2: just ent.

1204
01:02:52,040 --> 01:02:52,600
Speaker 3: I'd love it.

1205
01:02:53,160 --> 01:02:56,760
Speaker 2: What belt is, Fritz? Now, we don't do belts in taichi?

1206
01:02:56,920 --> 01:02:58,439
Speaker 2: Well we do, but just that's to stop our.

1207
01:02:58,360 --> 01:03:01,760
Speaker 3: Pants from falling down. Yeah, other belts or anything like that.

1208
01:03:01,800 --> 01:03:04,200
Speaker 3: We just do it, you know, you just do it.

1209
01:03:04,280 --> 01:03:11,080
Speaker 1: Crego alright, Tiff, thank you, Thanks lads. That was an

1210
01:03:11,120 --> 01:03:13,560
Speaker 1: emotional rollercoaster for me. That show. I'm going to have

1211
01:03:13,600 --> 01:03:16,280
Speaker 1: to go and have a shower, cold shower and a

1212
01:03:16,440 --> 01:03:20,480
Speaker 1: xanax whatever that is. I'm plushioned. I'm an emotional wreck.

1213
01:03:20,840 --> 01:03:23,320
Speaker 3: You should keep that in, Tiff, just keep it rolling.

1214
01:03:24,160 --> 01:03:26,640
Speaker 1: No, she will, She'll leave that in. All right, let's

1215
01:03:26,760 --> 01:03:32,320
Speaker 1: officially say goodbye. Thank you listeners. You're great. Thanks Patrick,

1216
01:03:32,400 --> 01:03:34,120
Speaker 1: Thanks Tiff, see you guys,