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Speaker 1: I'll get a team. Welcome to another installment of your

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Speaker 1: favorite show, with your favorite people. David, John Ken, Patrick Gillespie,

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Speaker 1: Tiffany and Margaret, Woman of Veronica. Two dogs, Cook cloak Cookie?

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Speaker 2: Can they two dogs?

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Speaker 1: Are you all right?

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Speaker 3: I'm great?

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Speaker 1: Thanks great? Great, dog's good, dog, good, cat, good, motorbike good.

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Speaker 2: Everything's good.

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Speaker 1: To get rid of the cat, the motorbike or the dog.

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Speaker 1: What would go first?

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Speaker 2: One of them? None of them. We'd all live homeless

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Speaker 2: on food stamps if we had two meat, the cat,

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Speaker 2: the dog and the motorbike.

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Speaker 1: A food stamp still a thing.

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Speaker 3: I don't know. Never were in Australia, but I think

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Speaker 3: they are in the US. Yeah.

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Speaker 1: I think you've been watching too many Disney movies. Tiff. Hello,

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Speaker 1: Professor Gillespie, how are you?

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Speaker 2: Yeah?

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Speaker 1: Good?

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Speaker 3: Good to be here. I got to ask. So, last

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Speaker 3: time we talked, Tiff had bought an accessory for her

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Speaker 3: bike to make it really really noisy. That now fitted, Tiff.

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Speaker 2: It's been fitted. It's so good. I am so obsessed.

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Speaker 2: Now you've got no idea, David. We'll talk about it later.

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Speaker 1: No, talk about it, talk about it now, because I

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Speaker 1: want people to know what I have to contend with.

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Speaker 3: So you were frustrated at writing around on the equivalent

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Speaker 3: of a singer sewing machine, and now it's a singer

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Speaker 3: sewing machine that sounds like a Harley is it? It

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Speaker 3: really is?

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Speaker 2: And it's like I can't even describe. It has transformed

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Speaker 2: my relationship with the bike. I cannot ride it enough.

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Speaker 1: There aren't too many women that I know that are

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Speaker 1: I mean, in fact, you might be the only one

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Speaker 1: that's totally enamored with a motorbike that's loud and obnoxious.

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Speaker 1: So how good is it? Though? It is good? It

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Speaker 1: is good. It does so, I mean, but I'm a bogan.

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Speaker 3: So you're going to have to get a sound clip

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Speaker 3: and edit it in here, Tiff, so that people know

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Speaker 3: what we're talking about.

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Speaker 2: I'll go give it a few revs. Maybe next week

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Speaker 2: I'll get out on it, give it a few revs,

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Speaker 2: and pop it in for the listeners.

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Speaker 1: You could just go out record it to your phone.

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Speaker 1: Could you do that? Could you literally record it on

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Speaker 1: your phone and insert it into this episode.

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Speaker 3: I could do that. I could do it, Tiff.

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Speaker 1: Let's hear your motorbike now, boom, And that was TIFF's motorbike. Everyone,

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Speaker 1: I've just created some more. Every woman listens to the

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Speaker 1: show will be like, not every woman, but a lot

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Speaker 1: will be like, I don't get it. I didn't get it.

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Speaker 3: What it?

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Speaker 1: What didn't you get? What do you get now? Sorry, David,

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Speaker 1: this is really this is very inappropriate. But what do

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Speaker 1: you get now that you didn't get?

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Speaker 2: Well, I didn't get how much it was going to

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Speaker 2: change the entire riding experience, not just the ah everyone's

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Speaker 2: bad bokes louder than mine. And I'm on a Junomi

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Speaker 2: sewing machine, so I go the long way home. I

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Speaker 2: couldn't be bothered getting it, getting it unpacked, to bring

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Speaker 2: it fifteen minutes to the gym before. Now, I, oh,

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Speaker 2: I don't know something, something happens. It's very visceral. It's

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Speaker 2: it's the sound, it's the feeling. And do you know what,

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Speaker 2: I've got a comms unit the communications for other writers,

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Speaker 2: and I don't like it because it takes me away

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Speaker 2: from the presence of the sensation of the whole bike experience.

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Speaker 3: Yeah, I know what, I know what you're talking about.

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Speaker 3: You know my first car was a Gemini, Yeah, which

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Speaker 3: was you know, it's a singer sewing routine with four

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Speaker 3: wheels and it. It became a lot faster and better

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Speaker 3: when I went and bought some speech stripes and put

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Speaker 3: you stuck them down the side of it.

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Speaker 1: It's it's it's an indictment on you that you owned

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Speaker 1: a Gemini and then but that you are brave enough

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Speaker 1: to say that you.

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Speaker 3: Are under Gemini a long time ago.

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Speaker 1: Although back in the day they were they were kind

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Speaker 1: of okay.

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Speaker 3: It wasn't that kind of Gemini. It was a blue

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Speaker 3: nurse's car. So it was a lovely hell blue.

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Speaker 1: Had kind of baby powder blue. All right, Now, we're

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Speaker 1: not here to talk about bloody motorbikes or forty year

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Speaker 1: old geminis. We're here to talk about the things that

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Speaker 1: you've been sticking your nose into, because you fucking stick

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Speaker 1: your nose in a lot of places.

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Speaker 3: You do.

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Speaker 1: You do open doors that nobody asked you to open.

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Speaker 1: Let's just say that. But you do it with gay

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Speaker 1: abandon You just you just throw it open and just

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Speaker 1: cartwheel in there. And so one of that. By the way, everyone,

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Speaker 1: David who please help him get some more followers on

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Speaker 1: Buddy LinkedIn. He's up to two thousand, but my nana's

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Speaker 1: on two and a half thousand and she's dead. So

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Speaker 1: if you could give him, if you could give him

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Speaker 1: a chop out, follow him on LinkedIn. And also, if

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Speaker 1: you're not a member or if you're not following on

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Speaker 1: the U Project podcast Facebook page where he posts every

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Speaker 1: second or third one of his articles, jump in there.

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Speaker 1: Also follow on there. But you put up something this

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Speaker 1: week around an AI kind of let's call it a

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Speaker 1: resource that was developed. Do you want to I won't.

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Speaker 1: I won't spoil the I won't spoil the show. Tell

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Speaker 1: us what was developed and what it's for.

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Speaker 3: Okay. So O two, which is a British telecommunications company,

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Speaker 3: decided that rather than just blocking scammer numbers as they're

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Speaker 3: coming through their servers, they would prefer to waste the

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Speaker 3: scammer's time, figuring that that's actually a more powerful this

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Speaker 3: incentive to phone scammers because just blocking their numbers just

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Speaker 3: means that the computer moves on to the next number,

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Speaker 3: and you know, they haven't really harmed the scammer at all.

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Speaker 3: So what they developed was an AI that imitates your

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Speaker 3: grant and this AI will have a really lengthy conversation

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Speaker 3: with anyone that rings them, and it's really interesting. I

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Speaker 3: think you've got some audio here, Tiff, and I whack

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Speaker 3: it in because listening to this is your You're now

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Speaker 3: going to listen to the actual AI having a real

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Speaker 3: conversation with real phone scammers.

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Speaker 4: So W is than a dot W. And then Dodd,

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Speaker 4: I think you're perfectly bothering people, right, I'm just trying

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Speaker 4: to have a little chat. Gosh, our time fly is

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Speaker 4: it's showing me a picture of my cat Fluffy.

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Speaker 3: It's showing you a picture of your cat Fluffy.

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Speaker 1: It's not stupid, got it.

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Speaker 4: Dear, Because while they're busy talking to me, they can't

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Speaker 4: be scamming you. And let's face it, dear, I've got

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Speaker 4: all the time in the world.

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Speaker 3: So you know, she's got a bit of a sense

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Speaker 3: of humor as well. You know that one of fellow

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Speaker 3: saying has been nearly an hour and she's saying, oh,

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Speaker 3: how time flies. So it's an interesting approach to the

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Speaker 3: problem in that they figured, well, we haven't just got

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Speaker 3: one Grannie we can put on the phone. You know,

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Speaker 3: got one AI grannie, You've got a billion of them,

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Speaker 3: so you know, run them all simultaneously. And so that's

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Speaker 3: their plan, is to just waste the scammer's time and

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Speaker 3: clog up their calling networks with conversations with not very

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Speaker 3: real grannies.

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Speaker 1: Is is it? It must be bloody great AI. If

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Speaker 1: they can keep someone on the phone for an hour

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Speaker 1: thinking that they're actually having a real conversation with the

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Speaker 1: real person, well.

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Speaker 3: They've got a strong motivation to stay on the phone.

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Speaker 3: So you're remembering that, you know, it's a fairly unrewarding job,

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Speaker 3: I guess, in the sense that you know, ninety nine

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Speaker 3: percent of people are to speak hang up with in

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Speaker 3: the first second. So they want to stay on the phone.

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Speaker 3: They want to think that they're making progress. They want

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Speaker 3: to talk to someone and see if they can get

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Speaker 3: them too interested in what they're doing. And the interesting

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Speaker 3: thing about an AI is that it can adapt. It

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Speaker 3: can have a genuine conversation with you. It can talk

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Speaker 3: to you about what you've said, it can listen to

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Speaker 3: what you've said, it can engage in it. And this

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Speaker 3: one has been told programmed to keep the conversation going

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Speaker 3: whatever it takes. And as you heard from those examples,

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Speaker 3: it was managing to do it for an hour, which now, look,

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Speaker 3: I suspect this is a fairly short term solution and

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Speaker 3: that you know pretty soon these scammers will be AIS

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Speaker 3: themselves and see AI is talking to our eyes, and

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Speaker 3: no one will waste anyone's time. But I guess a

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Speaker 3: few within megacycles of computing time might go down the drain.

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Speaker 3: But it's an interesting use of AI at the moment,

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Speaker 3: and it shows how far it's gone that you could

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Speaker 3: be talking to what you think as a person in

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Speaker 3: real time and in fact you're not.

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Speaker 1: It is getting It's getting harder and harder to identify

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Speaker 1: what is real and what is not. Like I got

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Speaker 1: sent something today through one of the speaking agencies that

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Speaker 1: I do some work for, and I didn't open it,

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Speaker 1: but it looked legit. It was from there, had they

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Speaker 1: had everything that looks like the other emails I get

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Speaker 1: from them, But it had a file to open, which

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Speaker 1: didn't make sense, so I didn't open it. And I'm

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Speaker 1: nine to nine point nine, I'm sent. Sure it was

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Speaker 1: a virus or something, but I just nearly automatically opened

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Speaker 1: it because I've opened things from them many times and

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Speaker 1: it just came in and it's like, oh, there's a

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Speaker 1: file here, blah blah blah about that, and then I

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Speaker 1: read what it was about, and I'm like, what is

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Speaker 1: what is that, but you I think if you're not

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Speaker 1: ever vigilant, you know we're going to get in trouble

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Speaker 1: because the quality. I mean, there's also some ridiculously terrible

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Speaker 1: kind of you know, scams, but some of them are

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Speaker 1: pretty high level, aren't they.

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Speaker 3: Yeah, But I guess on the flip side of this

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Speaker 3: is it's worth thinking about where it could be useful.

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Speaker 3: If you've got AI capable of holding a reasonable conversation

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Speaker 3: with you, but also with access to a significant amount

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Speaker 3: of data about the organization it works for, then wouldn't

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Speaker 3: you rather be talking to an AI like that than

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Speaker 3: sitting on hold for two days waiting for your bank

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Speaker 3: to talk to you, or for your Telcoe to talk

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Speaker 3: to you, or for cent a Link to talk to you,

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Speaker 3: which is the alternative at the moment, which is press

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Speaker 3: this button and then go on hold for three days.

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Speaker 3: Wouldn't you rather be answered every single time, even if

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Speaker 3: it's by an AI that you can actually have a

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Speaker 3: conversation with and who probably has a pretty good chance

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Speaker 3: of giving you the information you're after.

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Speaker 1: And also you're not talking to anything that gets pissed

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Speaker 1: off or impatient or frustrated or has emotions or is

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Speaker 1: going to judge you or you know.

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Speaker 3: So in the example we just played the grandess, they

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Speaker 3: were swearing at her. It's perfectly calm, just keeps the

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Speaker 3: conversation going.

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Speaker 1: Yeah, yeah, that is, that is.

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Speaker 3: Yeah.

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Speaker 1: There are a range of applications even with I don't

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Speaker 1: use chat GPT for any of my writing or obviously

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Speaker 1: for my research because it's irrelevant. But sometimes I'll look

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Speaker 1: up something just to see what it says about something

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Speaker 1: I already understand, to see if what they bring up

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Speaker 1: is similar to what I would write or what I

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Speaker 1: would say. And I was thinking the other day about

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Speaker 1: what I call in personal intelligence, like how the ability

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Speaker 1: to be able to you know, understand others, all that communicates,

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Speaker 1: solve problems, work alongside other people, that kind of social intelligence.

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Speaker 1: And I thought, I've never heard the term into personal intelligence.

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Speaker 1: I wonder if it's actually a term and an area

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Speaker 1: of research. And I pulled it up and I said,

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Speaker 1: what is inter personal intelligence? On chat GPT? And it

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Speaker 1: brought it up and A Blowke wrote a book Come

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Speaker 1: on Boy you forty years ago, whole thesis, whole and

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Speaker 1: a guy at a Harvard a psychologist and a professor,

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Speaker 1: and yeah, it's one of eight kinds of intelligence he describes.

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Speaker 1: But anyways, so it finished, and then at the end,

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Speaker 1: unprompted by me chat, GPT goes, I hope you find

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Speaker 1: that valuable, Craig, because it's interesting because that intersects with

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Speaker 1: your research and probably something you could talk about in

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Speaker 1: your workshops and on your podcast. Like it gave me

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Speaker 1: a whole paragraph of just general advice around how I

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Speaker 1: could potentially use this information in different capacities and context

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Speaker 1: and I didn't ask it any of that. I'm like,

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Speaker 1: this motherfucker has been studying me, like what it's like,

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Speaker 1: it knows me.

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Speaker 3: Well, that's a nice segue to the next bit that

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Speaker 3: we want to talk about, Craig, which is you would

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Speaker 3: have seen the things about Bunnings getting a slap over

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Speaker 3: the wrist with a damp piece of lettuce by the

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Speaker 3: Privacy Commissioner saying, oh, you'ren aughty folks, you shouldn't have

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Speaker 3: done that. And what Bunnings were doing was for three

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Speaker 3: years they ran profiling software in their stores without telling

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Speaker 3: anyone they were doing it. So this was facial recognition

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Speaker 3: and the reason that Bunnings said they were doing it

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Speaker 3: was to because they wanted to identify criminals in, known shoplifters,

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Speaker 3: potential trouble makers, etc. In their stores. They say seventy

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Speaker 3: percent of problems in their stores come from a very

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Speaker 3: very small group of people that they would use this

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Speaker 3: software to identify, and the privacy commissioner said, wow, you

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Speaker 3: can't do that. They didn't have a problem with them

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Speaker 3: using the software, they had a problem with them doing

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Speaker 3: it without telling one. So and this sort of thing

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Speaker 3: is increasingly becoming part of retail. I don't know if

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Speaker 3: you've ever paid close attention to the self checkout kiosks

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Speaker 3: in the supermarket, but if you have, you would have

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Speaker 3: noticed a real time video of yourself operating the machine.

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Speaker 3: And there's no guarantees around any of this stuff, you know.

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Speaker 3: Bunning said, Look, it was deleted as soon as it

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Speaker 3: wasn't a match, like you know, in less than a second,

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Speaker 3: your photo was off the system. No one was keeping anything,

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Speaker 3: And maybe that's true, probably is, But the fact that

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Speaker 3: it's being recorded at all and is being used for identification,

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Speaker 3: I think gives pause for thought. Because profiling software like that,

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Speaker 3: which well facial recognition software all of us use all

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Speaker 3: the time, use it probably every morning to unlock your phone,

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Speaker 3: every five minutes to unlock your phone and is using

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Speaker 3: facial recognition software. It's used at the airports to you know,

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Speaker 3: get you through customs all that sort of stuff. The

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Speaker 3: question then comes, is it okay for to just be

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Speaker 3: being used everywhere all the time, for us to be

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Speaker 3: able to be identified, particularly in places where it can

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Speaker 3: be matched to other information about us, like our credit

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Speaker 3: card or our flyby's number, or a rewards number which

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Speaker 3: records every purchase we've ever made and our preferences, you know,

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Speaker 3: whether we happen to like the full fat milk or

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Speaker 3: the trim All that kind of stuff starts to be

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Speaker 3: then being associated with stuff that can be picked out

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Speaker 3: immediately by software that's automatically identifying you. Because if you

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Speaker 3: all had a number plate stable to your forehead, So

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Speaker 3: how comfortable are we with that? So taking the example

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Speaker 3: that you just gave with chat GPT, what if you

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Speaker 3: you know, you were browsing the women's little lingerie section

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Speaker 3: at Target, you know, as you do, and you know,

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Speaker 3: the facial recognitions software says, oh, Frank, it's got an

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Speaker 3: interest in women's underwear, and pops onto Instagram, does a

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Speaker 3: complete search of Instagram. You know, the reverse image search

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Speaker 3: of Instagram with your face identifies your Instagram account and

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Speaker 3: then starts popping ads for women's underwear in your Instagram.

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Speaker 3: So that's the sort of thing that can be used

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Speaker 3: commercially and is all doable now with existing technology, And

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Speaker 3: who's to say it isn't. I mean, how did chat

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Speaker 3: GPT know so much about you? He is a good

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Speaker 3: question to ask, But the question is how much of

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Speaker 3: this are we prepared to allow have happening. It's all

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Speaker 3: a bit amusing when it's about your lingerie shopping habits,

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Speaker 3: but it's less amusing when you get a fine in

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Speaker 3: the post for jaywalking at two am and Mount Iseres

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Speaker 3: because you know, a camera picked you up, identified your face,

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Speaker 3: it reported you to authorities and sent you a fine.

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Speaker 3: Or when your car, as we've talked before, you know,

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Speaker 3: shoots a letter off to the to the to the

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Speaker 3: coppers and says, oh, by the way, Harps was doing

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Speaker 3: five k over the limit and he's photographic proof of it.

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Speaker 5: You know, even what you were saying with at Woolworths,

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Speaker 5: I was thinking that because well, where I shop anyway,

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Speaker 5: there's I think there's two cameras, so there's one that

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Speaker 5: is straight on and my face.

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Speaker 1: But then there's one above me where it can see

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Speaker 1: what you're doing. It can see you scanning things. So

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Speaker 1: it's above my head looking at me, scanning things, looking

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Speaker 1: at me taking things out of the basket, scanning them,

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Speaker 1: then putting them into my bag. So it's this kind

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Speaker 1: of overhead view and I think, I mean, honestly, I

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Speaker 1: guess it doesn't bother me because I've never thought about

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Speaker 1: it too much. But no, no, I mean, maybe it's there,

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Speaker 1: but I've never seen this anywhere where it says, by

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Speaker 1: the way, you're being filmed right now.

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Speaker 3: Yeah, And that was the problem that the Privacy Commissioner

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Speaker 3: had with what Bunning's were doing. Like I said, they

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Speaker 3: didn't have a problem with the fact they were doing it.

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Speaker 3: The problem was they didn't tell people they were doing

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Speaker 3: it and give people the opportunity not to consent.

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Speaker 1: So what would be then if they if they told everyone?

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Speaker 1: I mean, what would you do tif if they went, hey,

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Speaker 1: if you shop here, we're going to film you, would

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Speaker 1: you still shop there? I mean probably, I guess I

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Speaker 1: get like, I know I'm being filmed, but then do

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Speaker 1: we know what they'd do with that footage? David or

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Speaker 1: like a.

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Speaker 3: Big problem, isn't it. No, we don't we know what

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Speaker 3: they say they do with it when the Privacy Commissioner

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Speaker 3: hauls them up before them. But do we really know

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Speaker 3: what they'd do with it and what guarantees we've got.

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Speaker 3: And last time when we talked about this with the cars,

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Speaker 3: and this data was being sent off to Chinese and

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Speaker 3: South Korean companies, and there was no explanation as to

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Speaker 3: what was being done with it other than it was

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Speaker 3: being used to train ais well to do what you know,

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Speaker 3: there's just no real detail about this stuff, and I

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Speaker 3: don't think anyone can with confidence say they know what's

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Speaker 3: being done. I guess that coming back to the question

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Speaker 3: you asked about, would TIFFs still go into Bunnings, Well,

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Speaker 3: she might, but I reckon there'd probably be a roaring

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Speaker 3: trade in those face masks. Things you can buy that

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Speaker 3: make it really, really difficult for these detection softwares to work.

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Speaker 3: So there's these ones that they sort of blur your features.

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Speaker 3: They're still basically see through, but they blur your features

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Speaker 3: and the software struggles with it. They were very very

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Speaker 3: popular in Hong Kong, by the way, during the democracy

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Speaker 3: riots because they knew that this technology was being used there,

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Speaker 3: and so they sold a lot of those masks. You

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Speaker 3: might see a lot of that sort of thing happening

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Speaker 3: if people are being told what's going on and deciding, actually,

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Speaker 3: I'd really rather not be identified. You know, when I

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Speaker 3: go in and buy a lawnmower.

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Speaker 1: I wonder if in some not too distant dystopian future

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Speaker 1: they are selling so they're filming us and then selling

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Speaker 1: that too. I mean, unless there was some commercial upside

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Speaker 1: for them, there'd be no reason for them to record

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Speaker 1: it unless they were going.

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Speaker 3: To there's a lot of commercial upside. So just the

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Speaker 3: example I gave you before, where you know, if it

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Speaker 3: noticed that you're hanging around in the linger section, then

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Speaker 3: that day not.

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Speaker 1: Just stop saying that. Please, could you find another example

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Speaker 1: or another example? Could it not be the fresh produce

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Speaker 1: section or something?

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Speaker 3: To be really really clear, listeners, I have no evidence

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Speaker 3: to hang around in the lingerie section. It is just

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Speaker 3: a hopothetical.

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Speaker 1: But target do though that.

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Speaker 3: But but I guess there's an instant commercial upside to that,

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Speaker 3: which is that information is valuable to an advertiser of

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Speaker 3: lingerie products, and there's other commercial applications as well, because

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Speaker 3: then they've got that information linked to the other things

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Speaker 3: that you purchase. So you may never purchase lingerie, but

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Speaker 3: it now knows something about you that it didn't know before,

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Speaker 3: which it would have only gotten from your purchase history,

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Speaker 3: and so it can cater the advertising to you, It

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Speaker 3: can target things to you, it can sell that targeting information.

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Speaker 3: I'm not suggesting anyone is doing this, It's just possible.

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Speaker 3: And whenever something is possible, there's likely to be someone

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Speaker 3: pushing the envelope.

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Speaker 1: If you look like you wanted to jump in, well.

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Speaker 2: I feel like if this, why is this a thing

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Speaker 2: around these sorts of things and not people that are

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Speaker 2: doing child trafficking and pornography, And like, if this sort

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Speaker 2: of stuff exists, is on their better uses than trying

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Speaker 2: to catch someone fucking scanning a roma tomato or something else.

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Speaker 3: It's probably, Yeah, it's probably because law enforcement often lags

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Speaker 3: be in terms of its access to technology. And then

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Speaker 3: the other problem is giving these sorts of capabilities to

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Speaker 3: law enforcement is a whole new level as well, in

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Speaker 3: the sense that it's people are almost okay with it.

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Speaker 3: If all it's going to happen is they're going to

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Speaker 3: sell you a new pair of shoes with it, but

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Speaker 3: they're less okay with it if someone who can throw

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Speaker 3: you in the slammer has access to this information.

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Speaker 1: Oh, there is so much stuff to sort through with this.

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Speaker 1: All right, let's do one more before we close the

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Speaker 1: Gillespie door. So you wrote an article the other day. Well,

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Speaker 1: there was an article that you commented on from the

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Speaker 1: New York Times called is being busy good for people

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Speaker 1: with ADHD?

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Speaker 3: Yeah?

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Speaker 1: What tell us about that? Because I'm I don't know

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Speaker 1: the answer. I'm suspecting it might be.

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Speaker 3: It is so interesting study, big study done in the

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Speaker 3: United States tracking people over sixteen years to see whether

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Speaker 3: there're ADHD symptoms, you know, stayed the same, got worse,

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Speaker 3: got better, whatever. And what they discovered along the way

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Speaker 3: was that it went in and out with adults, and

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Speaker 3: that the thing that most accurately predicted the ADHD symptoms

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Speaker 3: or the severity of them. And remembering what ADHD is,

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Speaker 3: and that the primary symptom is lack of focus, you know,

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Speaker 3: lack of an ability to focus, particularly in an adult.

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Speaker 3: That can have severe consequences because you can't get anything done.

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Speaker 3: You're a bit study at work and in general. And

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Speaker 3: so they were tracking this and they found it really

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Speaker 3: was affected by how busy you were. So the busier

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Speaker 3: you were, the more you had on the more stress

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Speaker 3: you were under, which is a little bit paradoxical, the

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Speaker 3: more stress you were under, the less likely you were

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Speaker 3: to have ADHD symptoms. So and in fact, for many people,

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Speaker 3: the more stress they became, the more likely they were

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Speaker 3: to be completely in remission from those symptoms. So that's

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Speaker 3: an interesting finding and it backs up some of the

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Speaker 3: things that we've talked about sort of over many episodes,

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Speaker 3: which is find a way to generate dopamine if what

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Speaker 3: you want to do is address ADHD symptoms. ADHD is

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Speaker 3: a lack of dopamine. You do not have enough dopamine

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Speaker 3: to keep you focused. And the definition of enough is

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Speaker 3: what your brain says is enough, and the level of

435
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Speaker 3: that is dependent on how addicted or stressed you are.

436
00:24:24,080 --> 00:24:27,080
Speaker 3: The higher your addiction or stress levels, the higher it

437
00:24:27,119 --> 00:24:29,679
Speaker 3: says you need. And so even a normal level in

438
00:24:29,760 --> 00:24:32,439
Speaker 3: someone else is not enough to keep you focused. So

439
00:24:33,080 --> 00:24:35,720
Speaker 3: the way ADHD medication works is to give you a

440
00:24:35,720 --> 00:24:39,320
Speaker 3: dopamine spike. They're stimulants, so not that people would be

441
00:24:39,320 --> 00:24:41,560
Speaker 3: prescribing it, but you could give someone cocaine. It will

442
00:24:41,600 --> 00:24:44,280
Speaker 3: give them a dopamine spike, and it would fix their dopamines,

443
00:24:44,400 --> 00:24:49,600
Speaker 3: the their ADHD symptoms. So the interesting thing is this

444
00:24:49,640 --> 00:24:53,800
Speaker 3: is entirely predictable, which is make someone busy, make them

445
00:24:53,880 --> 00:24:57,119
Speaker 3: really really have to focus, have to stay on task

446
00:24:57,200 --> 00:24:59,760
Speaker 3: all the time. They're having to generate their own dopamine

447
00:25:00,040 --> 00:25:03,480
Speaker 3: because they're so busy, put them under stress. Stress generates

448
00:25:03,520 --> 00:25:07,600
Speaker 3: dopamine just as well. So make someone busy, time poor,

449
00:25:07,720 --> 00:25:12,000
Speaker 3: under stress, they are likely to not have ADHD symptoms,

450
00:25:12,040 --> 00:25:15,240
Speaker 3: is what this study is saying. And the reason is

451
00:25:15,280 --> 00:25:17,679
Speaker 3: because of that, because they're generating their own dopamine. And

452
00:25:17,680 --> 00:25:19,480
Speaker 3: this lines up with the stuff we've talked about in

453
00:25:19,480 --> 00:25:22,399
Speaker 3: the past about ice baths, for example, how do you

454
00:25:22,440 --> 00:25:24,920
Speaker 3: address something like this jump in an ice bath because

455
00:25:24,920 --> 00:25:28,960
Speaker 3: an ice bath is a massive dose of stress and

456
00:25:29,040 --> 00:25:32,040
Speaker 3: it gives you a huge dopamine hit. So that's what

457
00:25:32,080 --> 00:25:34,520
Speaker 3: this found. The interesting thing is also backed up with

458
00:25:34,560 --> 00:25:39,040
Speaker 3: some earlier studies on students which found, okay, but what

459
00:25:39,359 --> 00:25:43,040
Speaker 3: they're busy doing matters. So you have to be interested

460
00:25:43,280 --> 00:25:46,119
Speaker 3: in the thing you are doing or that's keeping you busy,

461
00:25:46,760 --> 00:25:48,800
Speaker 3: or you won't get any dopamine from it. So being

462
00:25:48,840 --> 00:25:52,359
Speaker 3: busy doing housework, for example, did not have any effect

463
00:25:52,400 --> 00:25:57,880
Speaker 3: on students' ability to focus, but being busy playing sport did.

464
00:25:58,880 --> 00:26:01,960
Speaker 1: Oh right. It's not just any busy, it's a certain

465
00:26:02,080 --> 00:26:02,720
Speaker 1: kind of busy.

466
00:26:02,840 --> 00:26:05,159
Speaker 3: It has to be something you want to do, like

467
00:26:05,200 --> 00:26:07,639
Speaker 3: so it's got to be something that you enjoy or

468
00:26:07,680 --> 00:26:09,840
Speaker 3: else you're not going to keep up motivation to stay

469
00:26:09,880 --> 00:26:13,120
Speaker 3: busy with it anyway. But also it's not actually giving

470
00:26:13,160 --> 00:26:14,480
Speaker 3: you a dopen mean hit because you don't want to

471
00:26:14,480 --> 00:26:15,320
Speaker 3: do it in the first place.

472
00:26:16,000 --> 00:26:19,760
Speaker 1: That is very interesting. I wonder if I wonder if

473
00:26:19,840 --> 00:26:23,240
Speaker 1: knowing that in the education system, they could do something

474
00:26:23,320 --> 00:26:24,800
Speaker 1: with that insight.

475
00:26:25,480 --> 00:26:28,080
Speaker 3: I think a lot of teachers know this sort of

476
00:26:29,200 --> 00:26:33,040
Speaker 3: without any official science behind it. They know if I

477
00:26:33,119 --> 00:26:35,199
Speaker 3: want these boys in my class that are bouncing off

478
00:26:35,240 --> 00:26:38,280
Speaker 3: the walls to focus, I'll let them go outside and

479
00:26:38,280 --> 00:26:40,320
Speaker 3: bounce around for a bit and then I'll get more

480
00:26:40,359 --> 00:26:43,360
Speaker 3: out of them.

481
00:26:43,400 --> 00:26:45,479
Speaker 1: Well, t if it looks like you've got some editing

482
00:26:45,560 --> 00:26:48,119
Speaker 1: to do, because you've got to insert you may have

483
00:26:48,240 --> 00:26:51,040
Speaker 1: to reinsert that lady's audio because I don't know how

484
00:26:51,080 --> 00:26:54,359
Speaker 1: good that was, and you have to it was bloody awful,

485
00:26:55,320 --> 00:26:57,280
Speaker 1: and because yeah, that was a bit dodgy. So you

486
00:26:57,359 --> 00:26:59,320
Speaker 1: might have to figure that out, but you're a whiz.

487
00:26:59,320 --> 00:27:03,359
Speaker 1: And then you've got to insert the MT seven with

488
00:27:03,520 --> 00:27:08,359
Speaker 1: the Akropovich System on it, which that means nothing to

489
00:27:08,440 --> 00:27:09,800
Speaker 1: our listeners, but just.

490
00:27:09,760 --> 00:27:12,440
Speaker 2: Trust me, it means something to some of them.

491
00:27:12,440 --> 00:27:15,879
Speaker 1: It means something too much to the twelve Bogans that

492
00:27:15,960 --> 00:27:18,320
Speaker 1: listen to the show. Shout out to the Bogans and

493
00:27:18,359 --> 00:27:22,159
Speaker 1: Glespo's like, what's in Akropovich full system just makes it

494
00:27:22,200 --> 00:27:23,800
Speaker 1: sound good? Mate with the baffle out.

495
00:27:24,280 --> 00:27:26,879
Speaker 3: Yeah, I'm going to have to do something I've never

496
00:27:26,920 --> 00:27:28,200
Speaker 3: done before. I'm going to have to go and listen

497
00:27:28,200 --> 00:27:30,040
Speaker 3: to one of these episodes so I can hear it.

498
00:27:30,520 --> 00:27:32,679
Speaker 1: Yeah, you'll hear it, So it'll be out, not tomorrow,

499
00:27:32,760 --> 00:27:35,240
Speaker 1: the next day. I'm able to say goodbye, Affair, but

500
00:27:35,320 --> 00:27:38,320
Speaker 1: as always, we appreciate you. Thank you sir, right out

501
00:27:38,400 --> 00:27:38,760
Speaker 1: see ya