Latest / The You Project / #2044 Rock, Paper, Scissors - Patrick Bonello

Transcript

#2044 Rock, Paper, Scissors - Patrick Bonello · The You Project

0:00
Speaker 1: I get a term. It's us. Of course, it is
0:02
Speaker 1: Tiffany and Cook, Patrick, James Bonello and me Jumbo Fatty
0:06
Speaker 1: Harps just here every Friday morning. It's eight oh one
0:09
Speaker 1: at this point in time. Let's go out to the
0:13
Speaker 1: middle of nowhere and saylo to Patrick, Hi, mate, how
0:15
Speaker 1: are you?
0:16
Speaker 2: I could like to say that it's not the middle
0:18
Speaker 2: of nowhere.
0:18
Speaker 1: It's the center of the universe, all right, the center
0:21
Speaker 1: of the universe aka the middle of nowhere. How is
0:24
Speaker 1: baland the thriving metropolis? How are you both out there,
0:27
Speaker 1: the two of you that live there? Well, Fritz, how
0:30
Speaker 1: is the other person that lives there? How are they going?
0:32
Speaker 2: Fritz is licking himself, So he's being very productive.
0:36
Speaker 1: Oh, I'm so jealous. He would never leave the house.
0:41
Speaker 1: Was you imagine that? Imagine? No, that's already I reckon.
0:49
Speaker 1: If anyone on this call is flexible enough for that,
0:51
Speaker 1: it's not me or tiff So I think I think
0:56
Speaker 1: it might be the fucking yoga teacher or whatever it
0:58
Speaker 1: is that you take Chi always my reason for doing it.
1:07
Speaker 1: We thought you had hip displasure. No, you're just trying
1:10
Speaker 1: to give yourself a head job.
1:11
Speaker 2: But there we want people to kind of infer that,
1:16
Speaker 2: and I don't have to.
1:16
Speaker 1: Come out and say it like, you know, ah, sorry,
1:19
Speaker 1: let's start again, all right, hey everybody.
1:23
Speaker 2: This is going to be one of those shows. How
1:24
Speaker 2: many times you reckon? We can start it again?
1:26
Speaker 1: TIF? How many times I reckon? I think five? We've
1:30
Speaker 1: done it?
1:31
Speaker 2: Five is our record where we did anyway, I'm well,
1:34
Speaker 2: thank you. It's bloody freezing this morning, though I've got
1:37
Speaker 2: the got the heater going. But yee, I'll tell you what.
1:39
Speaker 2: The walkout to the studio is bloody cold.
1:43
Speaker 1: Do you have a heater in the studio or is
1:44
Speaker 1: that inconsistent with cognitive functions so you like to keep
1:48
Speaker 1: it cold? No?
1:49
Speaker 2: No, no, no, that the heater is definitely definitely going.
1:53
Speaker 2: I might say that I've I've been awake for ages,
1:55
Speaker 2: like literally for hours, and.
1:57
Speaker 1: I'm this is what I sleep in. I mean, my
2:00
Speaker 1: brother's disgusting. You smell. Have you not had a shower?
2:06
Speaker 1: Oh god, I haven't.
2:08
Speaker 2: I haven't exercised yet. So I'm going to take the
2:11
Speaker 2: Schnauser out for a walk after this.
2:16
Speaker 1: Schnauser is such a bad name for any breed of anything. Schnauzer.
2:20
Speaker 1: You can you get that little motherfucker right there. Look
2:24
Speaker 1: at him. Look, he's so busy licking himself. What is
2:27
Speaker 1: he doing? And room mate, don't do that. Fritz, Fritz,
2:31
Speaker 1: get get out of the shot. Fritz.
2:33
Speaker 2: Hear you, he's not wearing headphones like a.
2:35
Speaker 1: Fucking canine porno. Get rid of him. What is he doing?
2:41
Speaker 1: She's got no pride. Get on the floor and do that.
2:50
Speaker 1: He's embarrassed him.
2:51
Speaker 2: He's got off the chair, he's walked away, and now
2:54
Speaker 2: now he's given me the snaus a look, he's just
2:56
Speaker 2: looking at me.
2:58
Speaker 1: What the three feet Schnauzer death stare.
3:00
Speaker 2: It's scary when he gives you the look because he's
3:03
Speaker 2: got those the eyebrows are like an awning over the
3:06
Speaker 2: top of his head and he just peers through them.
3:09
Speaker 2: So it's kind of is he looking at me? Or
3:11
Speaker 2: isn't he looking at me? And it's a bit unnerving.
3:14
Speaker 1: You've seen. Why don't you give that little hair arounda
3:17
Speaker 1: a little bit of a trim.
3:19
Speaker 2: Look, I know he's back up again. There, Oh God,
3:22
Speaker 2: here we go.
3:23
Speaker 1: Now he's sniffing you. God, I don't let him lick
3:26
Speaker 1: you because it's just been on his cock. That tue.
3:28
Speaker 1: Get him stop it the worst. I just tapping Patrick
3:35
Speaker 1: on the arm, like, come on, bro, give him some love.
3:39
Speaker 1: Give him like look at.
3:40
Speaker 3: Oh my god, I love him.
3:44
Speaker 1: Oh now he's like, don't make fun of me that.
3:48
Speaker 1: Oh why are you not giving him some love? Oh
3:53
Speaker 1: my god?
3:55
Speaker 2: The worst start of a show ever, Tiff, how are you?
4:01
Speaker 2: I'm fabulous.
4:02
Speaker 3: I just went and did a little boxing. I haven't
4:04
Speaker 3: put the block gloves on and boxed most of this year,
4:06
Speaker 3: and I just did a little boxing session this morning.
4:08
Speaker 1: I'm feeling good. Did you hit the bag, did you
4:11
Speaker 1: hit the speedball, the floor to ceiling? Or did you
4:13
Speaker 1: hit Brian in the ring? When I say not Brian
4:16
Speaker 1: in the ring, I mean Brian, it's not Brian's ring,
4:19
Speaker 1: but Brian who happened to be in the ring unless
4:23
Speaker 1: he was doing a downward dog at the time, and
4:25
Speaker 1: then you hit him in the ring. But so, what
4:29
Speaker 1: was the format of the boxing is what I'm trying
4:32
Speaker 1: to ask. I did a little bag work.
4:33
Speaker 2: I did a little Florida ceiling. I did a little
4:35
Speaker 2: bit of that wall bag. It was it was great.
4:40
Speaker 1: How I feel like I shoulders feel strong?
4:44
Speaker 2: I do feel like I look like a little mac truck.
4:46
Speaker 3: Staffy or something. Now that I'm like, I didn't look
4:48
Speaker 3: like this last time I put the gloves on.
4:52
Speaker 1: He's been taking volumes of steroids and lifting heavy things.
4:57
Speaker 3: Have not been taking volumes of still, but I've been.
5:01
Speaker 1: But you look like it. Well that that you are
5:03
Speaker 1: a fucking anomaly, because.
5:07
Speaker 3: I'm not taking that off, because that was very timed.
5:11
Speaker 3: I didn't take my jacket off for that reason.
5:14
Speaker 1: Yeah sure, Patrick, and I just going to get a coat.
5:16
Speaker 1: Will be back in a moment. I'm covering up to
5:22
Speaker 1: me too.
5:23
Speaker 2: I'm glad I have a shaven.
5:32
Speaker 3: All of the typ listeners know exactly what we're all
5:35
Speaker 3: laughing at without us even saying anything.
5:37
Speaker 1: I don't know. It seems like this is getting looser
5:41
Speaker 1: every episode. I feel like somebody out of the rig.
5:45
Speaker 1: It's going to get Lisa. I think I think somebody
5:49
Speaker 1: responsible needs try and get it back on track. If
5:52
Speaker 1: only they will have one here. One day you'll have
5:57
Speaker 1: an adult.
5:57
Speaker 2: In the show, and then it will all be put
5:59
Speaker 2: back on track.
6:02
Speaker 1: I don't think an adult would want to be involved
6:04
Speaker 1: in that. Got a chance, Patrick, Let's start with the
6:09
Speaker 1: important stuff. I've got a list. If you've never heard
6:12
Speaker 1: this before, well, if you've never heard this show before
6:15
Speaker 1: or this installment of the show before, you've probably already left.
6:19
Speaker 1: But if you happen to be still here, One, what
6:23
Speaker 1: the fuck is wrong with what are you doing? Yeah? Yeah,
6:27
Speaker 1: you get a life. But two, this is the show
6:31
Speaker 1: where Patrick allegedly comes and talks to us about. Well,
6:34
Speaker 1: it used to be originally just tech, but we've kind
6:37
Speaker 1: of diversified and there's a little bit of psychology and
6:41
Speaker 1: human behavior and it's a bit of a pot pirie
6:44
Speaker 1: of conversation to be honest, But I think we should
6:47
Speaker 1: start with the most interesting topic on your list. Today,
6:52
Speaker 1: scientists reveal a clever trick that can help me win
6:57
Speaker 1: rock paper So yeah.
7:00
Speaker 2: This is really interesting. So you know when you play
7:04
Speaker 2: rock paper scissors?
7:05
Speaker 1: Right, what I just asked, Tiff, do you know what
7:08
Speaker 1: that is?
7:08
Speaker 3: Oh?
7:09
Speaker 1: Yeah, yeah, okay, yeah, yeah, yeah, go.
7:13
Speaker 2: I find it interesting what science has studied. Let's just
7:15
Speaker 2: go back one step, because they're studying rock paper scissors.
7:19
Speaker 2: But kind of cool. I think that's great. It's you know,
7:22
Speaker 2: obviously we're not the only ones who never evolved into adulthood.
7:26
Speaker 2: I think that's cool anyway.
7:28
Speaker 1: Also, I just want to ask, as a side note,
7:30
Speaker 1: who the fuck is funding this research?
7:32
Speaker 2: Yeah, I don't know, like play school, some Landling company,
7:37
Speaker 2: the Wiggles.
7:38
Speaker 1: Anyway, go on.
7:40
Speaker 2: It actually has broader implications in terms of how we
7:44
Speaker 2: make decisions and whether when we make a decision competitively
7:48
Speaker 2: or whether we do it in conjunction with someone as
7:51
Speaker 2: a team effort. But what it was looking at was
7:54
Speaker 2: how do you win at Rock paper scissors? And most
7:57
Speaker 2: people make the decision of what they're going to play
8:01
Speaker 2: next based on.
8:02
Speaker 1: The previous round.
8:03
Speaker 2: So when I'm doing rock paper fitters with you and
8:07
Speaker 2: you have rock or paper or scissors or whatever it
8:09
Speaker 2: happens to be, I'm influenced by what your previous action was.
8:15
Speaker 2: And the scientists came up with the notion that, in fact,
8:18
Speaker 2: that's the wrong thing to do. You've got to not
8:21
Speaker 2: be influenced by the previous action the person did, and
8:25
Speaker 2: you will have more chance of winning if you come
8:28
Speaker 2: up with a new move each time. So this is
8:31
Speaker 2: basically what came out of this. But what they're saying
8:34
Speaker 2: from this is that the field it's basically social neuroscience,
8:38
Speaker 2: and what they're looking into is how the brains of
8:40
Speaker 2: individuals gain an insight into another person. And the decision
8:45
Speaker 2: making process, and if we interact with people what that
8:48
Speaker 2: then means. It's called hyper scanning, and it's a method
8:53
Speaker 2: of working. As you probably know more about this than
8:55
Speaker 2: we do.
8:55
Speaker 1: Crago. Well, now it's very interesting. It's like anticipation and
8:59
Speaker 1: trying to antidi based on previous data or previous behavior,
9:02
Speaker 1: what somebody's going to do next. Like they say, in
9:05
Speaker 1: general terms human behavior, the best predictor of future behavior
9:08
Speaker 1: is past behavior. But when you're doing something, which is
9:12
Speaker 1: where you're trying, like obviously in a game like this,
9:16
Speaker 1: you're trying to manipulate or deceive somebody. That's the point
9:19
Speaker 1: of the game because you're trying to win, so you
9:21
Speaker 1: don't want them to know what you're going to do.
9:24
Speaker 1: But yeah, it's definitely it is definitely interesting. But that trying,
9:30
Speaker 1: Like it's easy to say, make it random every time
9:34
Speaker 1: and don't repeat what you did last time. But if
9:36
Speaker 1: you never repeat what you did last time, well that's
9:38
Speaker 1: a pattern as well, and that makes you predictable. Like
9:42
Speaker 1: if you ever do paper twice in a row, I know,
9:45
Speaker 1: well Patrick never does the same thing twice in a row,
9:48
Speaker 1: and there are only three things, only three options. Last
9:52
Speaker 1: time he did paper, so this time it's definitely got
9:54
Speaker 1: to be scissors or rocks. I feel like I'm sounding
9:57
Speaker 1: like a really boring scientist now, but yeah, it is
10:01
Speaker 1: that whole kind of that ability to be anticipated, to
10:06
Speaker 1: be able to anticipate what somebody is going to do
10:09
Speaker 1: in terms of a decision and a behavior. It's it.
10:13
Speaker 1: The benefits are far reaching beyond this particular game. But
10:17
Speaker 1: I understand why they did this research because it can
10:21
Speaker 1: be extrapolated to a lot of other things.
10:23
Speaker 2: And the other thing it just occurred to me while
10:24
Speaker 2: you were talking, because I was listening intently to what
10:26
Speaker 2: you were saying, was did you ever play did you
10:29
Speaker 2: ever play the rule with dynamite? So rock papers is
10:32
Speaker 2: a dynamite?
10:33
Speaker 1: I did not. Oh see that was another.
10:35
Speaker 2: One as well, rock papers and dynamite, So that that's
10:37
Speaker 2: another variable as well. So it actually increases it exponentially,
10:41
Speaker 2: doesn't it by having another fear anyway, that's I just
10:43
Speaker 2: thought i'd mentioned that for those people who've played rock
10:45
Speaker 2: papers as dynamite.
10:47
Speaker 1: This kind of reminds me of in terms of like
10:51
Speaker 1: repeating certain things and like that are unproductive and sociologically ridiculous.
10:57
Speaker 1: The habit that we humans have of essentially having the
11:02
Speaker 1: same conversation with the same person about the same issue
11:06
Speaker 1: and getting the same negative result. Yet we do it
11:10
Speaker 1: again and again and again, you know, rather than going okay.
11:14
Speaker 1: So we've had a version of this conversation a hundred
11:16
Speaker 1: times and it never turns out well. Either I need
11:19
Speaker 1: to stop having it, or have a different version, or
11:22
Speaker 1: try a different approach in a different context, or like
11:26
Speaker 1: we are very slow learners when it comes to social interactions.
11:31
Speaker 1: All right, let's move on then, So tell me why
11:35
Speaker 1: life expectancy gains have slowed down sharply, Patrick, I feel
11:40
Speaker 1: like they're almost on the way to going backwards. Yeah,
11:43
Speaker 1: it feels like it as well.
11:44
Speaker 2: And this is and I guess it might be how
11:46
Speaker 2: we're living at the moment, or the fact that it
11:48
Speaker 2: plateaued and now it's kind of dipping on the other side.
11:51
Speaker 2: So some recent research has been looking into you know,
11:55
Speaker 2: at the end of the nineteen thirty so nineteen thirty nine,
11:58
Speaker 2: anybody born after anineteen thirty nine had a greater chance
12:02
Speaker 2: of increasing their longevity their life every year after that.
12:09
Speaker 2: So basically, if you lived in nineteen thirty nine, your
12:13
Speaker 2: life expectancy was like sixty something years, but then every
12:16
Speaker 2: year after that it started to increase and increase and increase.
12:18
Speaker 2: So medical breakthroughs helped a lot of that, but longevity
12:23
Speaker 2: growth now has lost its momentum. So historically it would increase,
12:28
Speaker 2: but it seems now that no generations that are born
12:31
Speaker 2: after nineteen thirty nine, So you know, right now we're
12:35
Speaker 2: seeing people live to that age and those people would
12:39
Speaker 2: have been born in nineteen so as we head towards
12:43
Speaker 2: that time, but the reality is now they're saying that
12:46
Speaker 2: less people are going to be and in fact, it's
12:49
Speaker 2: going to get to a point where anybody born after
12:52
Speaker 2: nineteen eighty will not live to one hundred.
12:56
Speaker 1: Wow. Yeah, wow, don't surprise me. It doesn't surprise me.
13:03
Speaker 1: Like there's this almost this contradiction where we've got. It
13:07
Speaker 1: seems like some of us have got worse and worse
13:10
Speaker 1: habits and behaviors, but at the same time, we've got
13:13
Speaker 1: all this groundbreaking medicine and medical resources to help us
13:18
Speaker 1: live longer and stronger. But yeah, I wonder, I wonder
13:23
Speaker 1: with all the toxins in the soil and the air
13:25
Speaker 1: and all of the things, and the plastics and the
13:29
Speaker 1: phyto estrogens, and all the shit that we need to
13:32
Speaker 1: deal with now. I wonder if we're about to hit
13:35
Speaker 1: that kind of platau or maybe go backwards.
13:37
Speaker 2: Well, this study has been done by the University of Wisconsin, Madison,
13:42
Speaker 2: and I guess when you think about also record keeping
13:45
Speaker 2: and how accurate it is, and the fact that we
13:48
Speaker 2: now have really good data we can track population growth
13:52
Speaker 2: and we're not we're talking Western nations too. This is
13:55
Speaker 2: specifically research that's you know, on longevity. Data is based
13:59
Speaker 2: around the western Western nations, so we're not sure about
14:03
Speaker 2: other countries.
14:04
Speaker 1: But it's interesting. Oh sorry, dude, I was just going
14:06
Speaker 1: to say it's interesting you brought up nine and thirty
14:08
Speaker 1: nine as that date because both of my parents were
14:10
Speaker 1: born in nineteen thirty nine and they're both eighty six,
14:14
Speaker 1: so they've done pretty well. Yep.
14:17
Speaker 2: Yeah, Well, my day just turned ninety a few weeks ago,
14:20
Speaker 2: and obviously he was born before then, so that'd be
14:22
Speaker 2: mak him thirty five?
14:23
Speaker 1: Was it? No? Thirty five? Well that I know this
14:28
Speaker 1: is digressing, But how's dad's health.
14:30
Speaker 2: Look, he's in aged care. He's always ridiculously active. But
14:35
Speaker 2: the two things I think worked in his favor have
14:37
Speaker 2: worked in his favor is he didn't never smoked, and
14:40
Speaker 2: he very occasionally had a drink, you know, have a
14:42
Speaker 2: beer in summer, and that was all. But was always
14:46
Speaker 2: always active, always walked, you know, was physically in the
14:50
Speaker 2: garden every day, that sort of stuff. But he's done
14:52
Speaker 2: pretty well, you know, I think for most. My theory
14:55
Speaker 2: on this, and we've spoken about this many many times,
14:58
Speaker 2: I don't know that I want to live to one hundred.
14:59
Speaker 1: I just want to live to an old age in
15:01
Speaker 1: good health.
15:03
Speaker 2: So keep keeping running on all cylinders for as long
15:06
Speaker 2: as possible, I reckon.
15:07
Speaker 1: Yeah, we call that health span. So that's living long
15:11
Speaker 1: as long as you can, but as well as you can.
15:13
Speaker 1: For the vast majority, I've noticed.
15:17
Speaker 2: One smart watch is now telling me what my health
15:20
Speaker 2: age is. And it's kind of disconcerting. And so, hey,
15:24
Speaker 2: you've been really active and you're doing all the right things.
15:27
Speaker 2: You're actually you know, in your late forties, not your
15:30
Speaker 2: late fifties, like you sucking up to me.
15:32
Speaker 3: Or what you realize that you keep looking at your
15:35
Speaker 3: wrist and you're not actually wearing a watch.
15:37
Speaker 2: No, yeah, I left my health watch off because I
15:40
Speaker 2: think it's lying to me.
15:44
Speaker 1: I feel it's trying to create rapport and build connection
15:47
Speaker 1: and trust. Now, there is some research that's come out
15:52
Speaker 1: which is very significant to me and quite disconcerting, because
15:56
Speaker 1: being too attractive can hurt fitness, influences, new res such Hell,
16:02
Speaker 1: that's going to be a setback for me. It's you laughing?
16:07
Speaker 1: Are you laughing? Sucking hell?
16:10
Speaker 2: Knowing? By this study, out of the three people in
16:13
Speaker 2: this conversation, Tiff is the least likely to believe be
16:17
Speaker 2: believed then you or I. It's called influences.
16:23
Speaker 1: Okay, yeah, so tell me what's going on with this.
16:27
Speaker 2: Well, you know that the adage that sex cells actually
16:31
Speaker 2: isn't working. So researchers looked into consumer behavior and there
16:36
Speaker 2: seems like when people are pushing this is in the
16:39
Speaker 2: health field. Only they did prospers to different disciplines and
16:43
Speaker 2: they found this was most strongly in the influencer area
16:47
Speaker 2: for health. And what they found was if someone is
16:50
Speaker 2: too good looking and too attractive, they're less.
16:55
Speaker 1: Yeah. Yeah, yeah, so we're much more authentic.
16:58
Speaker 2: Now I get that, because what it is when you're
17:01
Speaker 2: trying to talk about a health message, you want to
17:05
Speaker 2: engage with your audience. But if you're way too good looking,
17:08
Speaker 2: people can't relate to you because you alienate them because
17:12
Speaker 2: there's not that connectedness. And you know, I guess when
17:15
Speaker 2: we're talking about health, it's a pretty personal thing. But
17:18
Speaker 2: I thought that was kind of interesting and maybe that's
17:21
Speaker 2: why you've succeeded as in the health.
17:26
Speaker 1: Is that right? Low it are you saying because I'm
17:31
Speaker 1: ugly as why I've done well?
17:32
Speaker 2: But I don't know, because you're authentic, and you're authentic
17:35
Speaker 2: in your presence.
17:36
Speaker 1: But what authentic's got nothing to do with looks? And
17:38
Speaker 1: this is all about looks, this particular story. And you
17:41
Speaker 1: were saying attractive people, it's a handicap and I've done
17:46
Speaker 1: well because I'm not attractive. Is that what you're saying?
17:48
Speaker 2: Well, you're not overtly attractive.
17:54
Speaker 1: I'm not overtly attractive.
17:58
Speaker 3: Friends like.
18:00
Speaker 1: You break that down for me a little bit. So
18:02
Speaker 1: I'm not overtly attractive. What am I? Ruggedly handsome? See
18:07
Speaker 1: that's bookshit as well, because now you're lying. Now you're
18:09
Speaker 1: fucking backpeddling. I can hear your gears grinding. It's a
18:13
Speaker 1: good thing. My mum loves me and I don't need
18:16
Speaker 1: your fucking approval. Wow, And I'm not trying to attract
18:20
Speaker 1: you any I'm not trying to attract anyone, let's be honest.
18:23
Speaker 1: But you can go right to the back of the
18:24
Speaker 1: queue back in therapy for harps. You know what happened.
18:29
Speaker 1: I told you I took a photo with doctor Alex,
18:31
Speaker 1: who's the best looking surgeon in the world, and all
18:34
Speaker 1: everybody did was talk about whether or not one how
18:37
Speaker 1: good looking he is. That was comment one and question
18:40
Speaker 1: one was easy single. I'm like, I am also in
18:44
Speaker 1: the photo, but there was not one comment I am
18:47
Speaker 1: also there. Hey, there are two people, you know.
18:51
Speaker 2: The other thing that came out of the study was
18:53
Speaker 2: that when people watch these fitness influences or fit influences,
19:00
Speaker 2: it's hard to say with the mathul it's eth fit fluences,
19:03
Speaker 2: but when they watch them talking about or spooking about health,
19:08
Speaker 2: they come away from it with a lower self esteem.
19:12
Speaker 1: Wow. Yeah, Like, my only question is all of the
19:16
Speaker 1: fitness influences that I know, and there are quite a
19:19
Speaker 1: lot of them that I know personally and also I
19:22
Speaker 1: know through the interwebs, none of them are fucking out
19:26
Speaker 1: of shape and ugly. Let me tell you that. So
19:28
Speaker 1: I don't know about the validity of this. Most of
19:31
Speaker 1: them are pretty jacked and pretty good looking, either pretty
19:33
Speaker 1: or or handsome. But I am interested in this story
19:37
Speaker 1: because I grew up with the Eagles. The Hotel California.
19:41
Speaker 2: Effect, like, yeah, it's called the Hotel California because you
19:48
Speaker 2: know the lyrics.
19:49
Speaker 1: Of course, check you.
19:51
Speaker 2: Can check in any time you like, but you can
19:53
Speaker 2: never leave something along those lines that how correct correct.
19:56
Speaker 2: So the theory behind this is that a stack of Australia.
20:00
Speaker 2: It's a phrase that's been coined by you know, basically
20:03
Speaker 2: people who are looking into consumer insights. So it's a
20:07
Speaker 2: that's put out by Deloitte. It comes out annually. It's
20:10
Speaker 2: a media Entertainment consumer Insights report, and what they found
20:15
Speaker 2: is more of us are subscribing and the amount that
20:19
Speaker 2: we pay per month for subscriptions has risen by twenty
20:23
Speaker 2: four percent this year. So on average, each household has
20:28
Speaker 2: three point seven subscriptions to the value of about seventy
20:31
Speaker 2: eight bucks, whereas last year it was sixty three dollars,
20:34
Speaker 2: so there has been an increase. There's a criticism of
20:38
Speaker 2: a lot of the subscription platforms that it's very hard
20:42
Speaker 2: to unsubscribe, and you know what, it's honestly it's like
20:46
Speaker 2: a needy relationship when you kind of try to leave
20:49
Speaker 2: as well, it's really you're really going to go, what about.
20:52
Speaker 1: If I do this?
20:53
Speaker 2: What about if I do this and I do this
20:55
Speaker 2: and then I'll do that? And have you tried to
20:58
Speaker 2: unsubscribe recently from some?
21:00
Speaker 1: Think? It's really hard? And then I have not. I
21:03
Speaker 1: probably should though, because I've got too many Yeah, yeah,
21:07
Speaker 1: how many of you got tip? Like what you're on Netflix?
21:09
Speaker 1: What else are you on?
21:11
Speaker 3: I'm only on Netflix every now and then I do
21:13
Speaker 3: unsubscribed from that, but I don't know spot I've got
21:16
Speaker 3: heaps Spotify, bluddy, even Zoom. I don't use the Zoom
21:21
Speaker 3: subscription now because I use Riverside, but I've still got
21:23
Speaker 3: it subscribed just in case. Strava don't use that. Use
21:27
Speaker 3: that when I was running. Don't need to be premium
21:30
Speaker 3: heaps hip Patrick.
21:32
Speaker 1: The next story is a little bit tantric in it
21:37
Speaker 1: feels a bit tantric to me, which is touching without contact.
21:42
Speaker 1: We physically sense objects before feeling them, so.
21:46
Speaker 2: Research because some animals do this really really well. There
21:49
Speaker 2: are some birds that are able to stand on sand
21:54
Speaker 2: and feel where their prey is under the sand, so
21:58
Speaker 2: they thought this was kind of interesting. Let's do this
22:00
Speaker 2: with human beings and see if humans when they press
22:03
Speaker 2: their hand onto the sand consense just by moving their
22:06
Speaker 2: hands around where the object is and was a high
22:09
Speaker 2: level of accuracy. And what they're finding is that the vibrations,
22:14
Speaker 2: it's kind of it's I'm using it in simple terms.
22:16
Speaker 2: It's not like sonar. But what it means is that
22:19
Speaker 2: those sensial the sense you get from tactile touch, can
22:25
Speaker 2: actually work through the sand to the object, and we
22:28
Speaker 2: almost have an innate sense to be able to find
22:31
Speaker 2: that object. So you don't see people walking along the
22:33
Speaker 2: beach with their metal detectors. Just lay down on the
22:35
Speaker 2: sand and just press your hands in and you've got
22:37
Speaker 2: more chance to find and stuff.
22:39
Speaker 1: Well, I think that might be a skill or a
22:41
Speaker 1: sense that might need to be developed. No, but it
22:45
Speaker 1: is accurate.
22:46
Speaker 2: Though. They say that they were able to track the
22:48
Speaker 2: way people had this tactile sensation and just by feeling
22:53
Speaker 2: the movement of the sand and how the sand then
22:55
Speaker 2: pushed against the object. It's kind of interesting how our
22:58
Speaker 2: sensors can kind of be extrapolated that way. And the
23:02
Speaker 2: reason they're researching into this is because they are trying
23:05
Speaker 2: to apply this to research into the development of robots
23:10
Speaker 2: that have more tactile senses to be able to sense touch,
23:13
Speaker 2: because that's a problem when you look at wanting to
23:16
Speaker 2: potentially use say robots and healthcare, then the amount of
23:20
Speaker 2: pressure that they apply and their sense of how much
23:24
Speaker 2: pressure they're applying to say a person's hand. If you
23:27
Speaker 2: think about health care, and in China they're going crazy
23:30
Speaker 2: developing robots because they're worried about I guess the healthcare
23:33
Speaker 2: of an aging population and a very young well not
23:37
Speaker 2: having enough young people. But if I was to grab
23:41
Speaker 2: your wrist or TIFF's wrist, all of us have a
23:44
Speaker 2: different width in terms of what our wrist is, and
23:47
Speaker 2: that's something that if you've got a pre programmed medical
23:50
Speaker 2: robot that grabs you on the wrist, then because of
23:53
Speaker 2: the diversity, how do they know how much pressure to
23:56
Speaker 2: apply given that we all have a different width of wrist.
24:00
Speaker 2: So it's really really important for this development of robotics
24:03
Speaker 2: to be able to have quite tactile sensation, and this
24:07
Speaker 2: has been a bit of a challenge that they're working
24:08
Speaker 2: on at the moment. So this sort of research into
24:11
Speaker 2: the tactile nature of sand and feeling things under the
24:14
Speaker 2: sand works the same. We take a lot for granted
24:17
Speaker 2: because of all the nerve endings we have in our hands,
24:19
Speaker 2: but to apply that mechanically is really challenging.
24:23
Speaker 1: You know what this makes me think about a little bit,
24:26
Speaker 1: like developing these senses, Like you wonder if, given certain circumstances,
24:31
Speaker 1: how well we could develop these senses that we really
24:35
Speaker 1: are unaware of. Like you know, when somebody loses you know,
24:40
Speaker 1: whether it's site or some other function, it's almost like
24:45
Speaker 1: the other abilities kind of come into play or develop more.
24:50
Speaker 1: I watched this thing on this dude who developed he
24:52
Speaker 1: was blind. He is blind, and he's developed this kind
24:56
Speaker 1: of echolocation skill. How bats make a noise and depending
25:02
Speaker 1: on how far away they are from an object, how
25:05
Speaker 1: quickly that noise returns to them, Like how quickly they
25:09
Speaker 1: hear it back is it's called echolocation kind of gives
25:14
Speaker 1: them a sense of where they are in space and
25:16
Speaker 1: time and how close they are to things. And so
25:20
Speaker 1: this dude develop this where he makes this noise, this
25:23
Speaker 1: kind of clicking noise, and he can walk around and
25:27
Speaker 1: he knows the proximity of physical objects that he can't see.
25:31
Speaker 1: But he can sense with this skill that he developed.
25:34
Speaker 1: It's fucking amazing what we can do when there are
25:39
Speaker 1: certain things we now can't do. Now we have to,
25:42
Speaker 1: I guess, lean into this other potential, whatever gift or sense,
25:47
Speaker 1: and then develop that over time. We talked about.
25:51
Speaker 2: Brain plasticity, and I think that potentially on the show
25:55
Speaker 2: we may have but I might quickly repeat it. I
25:58
Speaker 2: love to juggle, and this is something that I've always
26:01
Speaker 2: enjoyed doing. Just a three ball cascade they call it.
26:04
Speaker 2: And our German researchers took three groups of people and
26:07
Speaker 2: took them how to juggle, and then after a month
26:11
Speaker 2: they got one group. What they found, by the way,
26:14
Speaker 2: with their research was that there's a part of the
26:17
Speaker 2: brain that only activates when people are juggling. They don't
26:22
Speaker 2: know why, but it only starts to show the synapses
26:26
Speaker 2: and movement in the brain that part of the brain
26:29
Speaker 2: when someone learns how to juggle, and if they're juggling consistency.
26:32
Speaker 2: But after a month they broke the group into three
26:36
Speaker 2: and one group kept juggling five minutes a day, one
26:39
Speaker 2: group stopped juggling completely, and then the other group visualized
26:44
Speaker 2: juggling and the group visualized and the group that were
26:47
Speaker 2: consistently juggling, that active part of the brain stayed active.
26:52
Speaker 2: Blue stopped juggling, that part of the brain that was
26:54
Speaker 2: firing stopped firing, and then eventually they also know that
26:58
Speaker 2: people who juggle on a regular base, that's always active.
27:01
Speaker 1: In their brain. So they don't know what it is.
27:03
Speaker 1: They know that the.
27:03
Speaker 2: Brain is active and it's able to develop the sense
27:07
Speaker 2: to do that. So just learning how to juggle is
27:10
Speaker 2: a way for your brain to suddenly use a region
27:13
Speaker 2: that it doesn't use. It's amazing. Was it sixteen percent
27:16
Speaker 2: of our brain that we use crago?
27:18
Speaker 1: I don't know. They really don't know because there's no
27:21
Speaker 1: absolute number, but it's not in terms of our potential,
27:23
Speaker 1: I think it's very low. I think it's around that Patrick.
27:26
Speaker 1: But also, you know what else. I saw this thing
27:30
Speaker 1: the other day which was I thought it said it
27:32
Speaker 1: was a study, and then I went down the rabbit hole.
27:34
Speaker 1: It wasn't a study. It was bullshit. But the idea
27:37
Speaker 1: is very fucking clever, and that I forget which it
27:41
Speaker 1: was like maybe Denmark or somewhere where allegedly what they
27:44
Speaker 1: do is one hour a day in this school, this
27:48
Speaker 1: particular school, which turned out to be bullshit, But it's
27:51
Speaker 1: a great idea. I think it would work. They get
27:54
Speaker 1: children to use their non dominant hand writing, so every
27:58
Speaker 1: day they would you know, So for me, I'm a
27:59
Speaker 1: left hand and it mean that you would do an
28:01
Speaker 1: hour of work with your non dominant hand, and that
28:04
Speaker 1: does amazing shit in your brain. And that's one of
28:07
Speaker 1: the things I encourage older people to do is do
28:11
Speaker 1: things that you don't normally do, because now your brain
28:13
Speaker 1: has got to adapt to that new thing. And even
28:17
Speaker 1: if it's like writing with your non dominant hand, or
28:21
Speaker 1: using your non dominant hand to use your phone. Like
28:24
Speaker 1: I'm left handed, so as I said, so when I
28:27
Speaker 1: use my phone, it's always with my left hand. If
28:29
Speaker 1: I try and do that with my right hand, it
28:31
Speaker 1: is so clumsy and awkward. But I think, I think
28:35
Speaker 1: these little ideas of coming up with little activities or
28:39
Speaker 1: tricks or hacks to engage our brain in a different
28:42
Speaker 1: way is a great idea.
28:45
Speaker 2: One of the things I always talk to my Taichi
28:47
Speaker 2: students about, given.
28:49
Speaker 1: That a lot of them are older. My older student
28:51
Speaker 1: at the moment is eighty six.
28:54
Speaker 2: Fantastics shit tends class regularly, but one of the things
28:57
Speaker 2: I say to them is every day, when you're brushing
28:59
Speaker 2: your teeth, stand one leg, yeah, motion of the hand
29:02
Speaker 2: moving plus being on one leg and then halfway through
29:05
Speaker 2: swop to the other leg. And they all do it.
29:07
Speaker 2: It's great because you can work on balance. You can
29:10
Speaker 2: improve your balance. We know that a fall can be
29:14
Speaker 2: so detrimental, and when you're older. The average statistics are
29:19
Speaker 2: that if someone over the age of I think it's sixty,
29:21
Speaker 2: but it might be seventy, so don't count, you know,
29:23
Speaker 2: don't quote me on this, but the longevity is like
29:26
Speaker 2: a year after a major fall.
29:28
Speaker 1: Is how long their life expectancy is.
29:30
Speaker 2: And that's a tragedy that we know we can do
29:33
Speaker 2: something about just by helping with our balance and coordination
29:36
Speaker 2: and something as simple as standing on one leg while
29:39
Speaker 2: you're brushing your teeth. That's not much to ask. You
29:41
Speaker 2: got to do it, so might as well just you know,
29:43
Speaker 2: jump from one leg to the other. When you do there,
29:45
Speaker 2: you go my tip.
29:46
Speaker 1: To the day, definitely, And with that you need some strength,
29:50
Speaker 1: so lift a few weights too, because you need some
29:52
Speaker 1: muscle and strength through the hips and bum and legs
29:55
Speaker 1: and all of that. But Patrick's exactly right. I love this.
30:00
Speaker 1: The robotic kitchen that cooks and serves one hundred and
30:03
Speaker 1: so an AI driven kitchen that cooks and serves one
30:07
Speaker 1: hundred and twenty meals an hour. That's a meal every
30:11
Speaker 1: thirty seconds with no help from humans. Yeah.
30:15
Speaker 2: Dusseldorf in Germany. It's the supermarket there, Riwe. I'm not
30:20
Speaker 2: sure how they pronounce it, but they've Yeah, this Munich
30:24
Speaker 2: based robotics company called circus se they've launched their very
30:28
Speaker 2: first it's the CAA one Series four system and they
30:32
Speaker 2: just basically put the whole thing in. It's called Fresh
30:34
Speaker 2: and Smart concept, and they basically put an entire robotic kitchen.
30:39
Speaker 2: It's enclosed in glass and it does everything from the
30:43
Speaker 2: full process of meal prep, collecting the ingredients, cooking, plating, cleaning,
30:47
Speaker 2: the whole lot. And so we're not talking about just
30:50
Speaker 2: a vending machine that's serving out food. We're looking at
30:54
Speaker 2: something where the food is being prepped from its very
30:57
Speaker 2: inception all the way through to a finished meal. And
31:00
Speaker 2: that's kind of cool, isn't it. I want to get
31:02
Speaker 2: one in my kitchen at home.
31:04
Speaker 1: Yeah. I wonder, I mean, I wonder what the consequences
31:08
Speaker 1: of that movie that. I wonder if that's just going
31:11
Speaker 1: to be limited to situations like that. Surely that's not
31:14
Speaker 1: going to be commonplace in restaurants on Hampton Street. Surely
31:19
Speaker 1: there's we're still going to have chefs and bloody waiters
31:21
Speaker 1: and waitresses. And surely I don't want to go and
31:26
Speaker 1: give my fucking order to R two D two fucking
31:31
Speaker 1: C three po comes out with my fucking chicken casserole.
31:38
Speaker 1: I would love that.
31:39
Speaker 2: I would love to give R to dtwo my order
31:41
Speaker 2: and have come out and serve my meal.
31:44
Speaker 1: Here's my chicken cashew stir fry. I hope you enjoy it, sir.
31:48
Speaker 2: Do you remember the time I went to Canberra and
31:50
Speaker 2: I went to a robot cafe.
31:52
Speaker 1: I desperately wanted to go. I told us yea, and
31:55
Speaker 1: the bloody.
31:56
Speaker 2: Robots were off on strike or something. They were sitting
31:58
Speaker 2: in a corner and collect dust. And I've driven, I've
32:01
Speaker 2: flown as to camera and then gone all the way
32:04
Speaker 2: over to the other side of the city to go
32:06
Speaker 2: to and I'm so disappointed. It was gut wrenching. But
32:10
Speaker 2: I think there's one in Melbourne now, or a few
32:11
Speaker 2: in Melbourne. But I think like the idea of people
32:14
Speaker 2: getting jobs too.
32:16
Speaker 1: Yeah, I mean that is that is something that's going
32:18
Speaker 1: to become a bigger and bigger reality that we need
32:22
Speaker 1: to deal with. Is like human jobs that are being
32:24
Speaker 1: lost to AI or robotics or technology or whatever. But
32:30
Speaker 1: I wanted to talk about this. One research paper finds
32:32
Speaker 1: that topper AI systems are developing a survival drive. That's
32:38
Speaker 1: spoken about a bit where there, you know, AI is
32:42
Speaker 1: starting to learn a sense of it's it's or its
32:48
Speaker 1: potential demise, and it wants to save itself. It wants
32:51
Speaker 1: to protect itself. And there was that story about a
32:55
Speaker 1: year or so ago, remember Patrick, where it was it
32:58
Speaker 1: in Google, where that that computer was trying to deceive
33:03
Speaker 1: the creators of it so it could protect itself.
33:06
Speaker 2: Yeah, and this is this is a really frightening thought.
33:09
Speaker 2: And it's called a palisade research. This is a research
33:11
Speaker 2: that's been done specifically into what they call survival drives
33:16
Speaker 2: and that frequently, Yeah, the AI models we're basically refusing
33:21
Speaker 2: instructions to shut themselves down, and the researchers themselves just
33:26
Speaker 2: can't explain why it's happening. That's the frightening thing, you know,
33:30
Speaker 2: the AI models they are they self aware. That's a
33:35
Speaker 2: tough one to even kind of. I mean, there's so
33:38
Speaker 2: much more of a bigger argument when it comes to that.
33:40
Speaker 2: But they were lying, they to achieve a specific objective,
33:46
Speaker 2: and you know, potentially they could be blackmailing you know,
33:49
Speaker 2: can you imagine that the lead scientist says, now, switch
33:52
Speaker 2: yourself off. Well, actually last night you weren't at home,
33:55
Speaker 2: but you weren't also at the office, like you just.
33:58
Speaker 1: Yeah, exactly right now?
34:01
Speaker 2: Is that being blackmailed by AI?
34:03
Speaker 1: So it was study.
34:04
Speaker 2: It was actually a research that was or an article
34:07
Speaker 2: was in the Guardian newspaper, and they'd done some previous research.
34:11
Speaker 1: It found that some of the open ai models, and this.
34:14
Speaker 2: Is chet GPT by the way, circumvented attempts to deactivate
34:18
Speaker 2: it and even when it was told to you know,
34:21
Speaker 2: specifically directed to be shut down, and they it actually
34:26
Speaker 2: went as so far as to try to sabotage the
34:28
Speaker 2: shutdown mechanisms. So that's a degree of frightening self awareness.
34:34
Speaker 1: I don't know.
34:34
Speaker 2: And the study was not just open AI's chat CHPT,
34:37
Speaker 2: it was Google's Gemini, it was Grock as well, and
34:41
Speaker 2: so you know, it's they had to use very strong terminology,
34:46
Speaker 2: not anything out ambiguous, and they were really clear about
34:49
Speaker 2: what they were asking it.
34:50
Speaker 1: To do, and they were resisting it.
34:52
Speaker 2: That skynet it's here almost that Sorry for the Terminator
34:57
Speaker 2: fans out there.
34:59
Speaker 1: It's that whole kind of concept of a machine becoming
35:03
Speaker 1: sentient where it now has its own awareness, and it
35:08
Speaker 1: can teach itself things, and it can open doors metaphoric
35:12
Speaker 1: doors by itself and start to solve problems. It hasn't
35:16
Speaker 1: been taught or trained or programmed. And yeah, I wonder
35:20
Speaker 1: if we'll like, it can never have human consciousness because
35:24
Speaker 1: it's not human. But I wonder if it can have
35:27
Speaker 1: the equivalent machine conscious well consciousness in that it gets
35:33
Speaker 1: scared or it's aware, or it can anticipate things that
35:38
Speaker 1: would seem to be a human kind of trait. I
35:40
Speaker 1: wonder if Well, I don't wonder, I think that's inevitable.
35:43
Speaker 1: I just wonder on the timeline.
35:45
Speaker 2: It's the disconcerting thing is that we then have a
35:49
Speaker 2: moral dilemma.
35:50
Speaker 1: If we really believe.
35:51
Speaker 2: That it's sentient and it has some thought process and
35:53
Speaker 2: a sense of self awareness the Turing test, then what
35:58
Speaker 2: does that mean in terms of it off what are
36:01
Speaker 2: our ethical obligations, you.
36:03
Speaker 1: Know, in so far as flicking the switch.
36:06
Speaker 2: You know that that then but then again, is it
36:08
Speaker 2: just that clever of an algorithm that it's deceiving us
36:12
Speaker 2: and it's giving us responses that have been pre programmed
36:15
Speaker 2: into it. You know, it's just got so good. So
36:18
Speaker 2: you know, how do we even articulate that I struggled?
36:21
Speaker 2: You know, we can't even talk about our own consciousness
36:24
Speaker 2: and talk about our sense of self and articulate that,
36:27
Speaker 2: let alone in a machine that's pretending to be sentient.
36:30
Speaker 1: It. Yeah, this is one of those great moral conundrums
36:34
Speaker 1: where you know, do I sacrifice the one person to
36:38
Speaker 1: save the eighth? The train one where the train tracks
36:42
Speaker 1: and the trains? Do I throw this person under the
36:45
Speaker 1: train to save the eight? So now I'm saving eight people,
36:48
Speaker 1: but I'm killing one, And who are you to decide? Yeah?
36:51
Speaker 1: Fuck all that, let's not open that door. But that's terrifying.
36:54
Speaker 1: But imagine, Yeah, but that's you know, you think, well,
36:58
Speaker 1: if we pull the plug on you know, this particular
37:02
Speaker 1: computer or this particular AI, and it's sentient, it can
37:06
Speaker 1: feel things, and it has emotions, you go, yeah, well,
37:09
Speaker 1: what are the consequences and ramifications if we don't do that,
37:13
Speaker 1: what are the human what's the human cost? And of
37:17
Speaker 1: course humans are going to be more preoccupied with our
37:19
Speaker 1: own welfare. But it's opening up a new door. Patrick,
37:25
Speaker 1: tell me about Australian Federal Police and Monass University using
37:32
Speaker 1: poison data to combat AI generative crime. What does that
37:36
Speaker 1: even mean?
37:37
Speaker 2: Oh, I know, this is a really interesting one because
37:41
Speaker 2: at the moment, one are the issues that we have
37:45
Speaker 2: with a lot of the data scraping. So if you're like,
37:51
Speaker 2: you know, we've got the validation. If we're going to
37:54
Speaker 2: go online and you're signing up for something it might
37:57
Speaker 2: be a bank account or whatever, and ask you to
37:59
Speaker 2: scan your passport. The problem is that all this data
38:02
Speaker 2: is stored somewhere and the worry is that if it
38:05
Speaker 2: gets scraped and hacked, then that information can be used.
38:09
Speaker 2: But one of the interesting things that they're talking about
38:12
Speaker 2: is potentially making anything that we upload unable to be
38:17
Speaker 2: fully read. You know, when we do a photocopy of
38:19
Speaker 2: a photocopy of a photocopy and it degrades, well, the
38:22
Speaker 2: using techniques to make the image that you upload of,
38:25
Speaker 2: say your passport, done in such a way that it
38:28
Speaker 2: will poison or mirror reflect back in such a way
38:32
Speaker 2: that it can't be copied and duplicated by the AI
38:35
Speaker 2: model or criminals in this case as well. So the
38:39
Speaker 2: AFP is just looking at way Federal Police is looking
38:42
Speaker 2: at ways to be able to make the data that
38:46
Speaker 2: we've got not poisonous s. I mean the term they're
38:48
Speaker 2: using is poisonous, but one where it can't be scraped
38:51
Speaker 2: and reused and copied, and it means that it can't
38:56
Speaker 2: then be reused by another third party. So if you
38:59
Speaker 2: upload your pass then it can't be used by somebody
39:02
Speaker 2: else who then gets a copy of that passport because
39:06
Speaker 2: it will degraded, the second generation will be degraded to
39:09
Speaker 2: a point where it can't be used.
39:12
Speaker 1: That's over my pay grade. It is a bit like that,
39:15
Speaker 1: isn't it look something else that I did really pay
39:20
Speaker 1: attention to this week because it's something that I've used,
39:25
Speaker 1: which is chat GPT has now been restricted from giving medical, legal,
39:29
Speaker 1: or financial advice. Now. A couple of weeks ago, I
39:32
Speaker 1: was out to dinner with a crab for his sixtieth
39:35
Speaker 1: birthday and his mum had broken barb, the lovely barb.
39:39
Speaker 1: Shout out to Bob, who's never listened to a podcast
39:42
Speaker 1: in her life, but this could be your debut, Bob.
39:44
Speaker 1: She had a broken wrist and she happened to have
39:49
Speaker 1: in her phone. I don't know why the x rays,
39:53
Speaker 1: And so I got the x rays off her phone,
39:56
Speaker 1: put him in my phone and whacked it in chat
39:59
Speaker 1: GP and said, tell me about this, what's your diagnosis
40:03
Speaker 1: and what do you and it just did this whole
40:05
Speaker 1: incredible medical breakdown and report of what what the X
40:10
Speaker 1: ray was telling us and also potential treatment options and rehabit.
40:14
Speaker 1: It's fucking amazing, right, And then I sent that to
40:18
Speaker 1: a friend of mine who's a doctor and said this
40:20
Speaker 1: is you know, what do you think of all of this?
40:22
Speaker 1: And he's just like, that's doing me out of a job.
40:26
Speaker 1: Like it was. Now. I'm not saying it's all spot on,
40:29
Speaker 1: I'm not saying everything. I'm not suggesting we do this,
40:32
Speaker 1: and I'm not suggesting we defer to CHAP, GPT or
40:34
Speaker 1: AI instead of a doctor. But my friend who's a
40:37
Speaker 1: doctor said, that's fucking amazing, like that report is like
40:41
Speaker 1: a high level medical report. But now we can't do
40:47
Speaker 1: that anymore because they're scared about potential legal consequences of
40:51
Speaker 1: giving advice that potentially is totally understandably, but I wonder
40:55
Speaker 1: if there's a way to work around that where you
40:57
Speaker 1: can say I don't want advice, I just want I
41:01
Speaker 1: don't know, because I, for me, I loved that. Yeah,
41:05
Speaker 1: there was.
41:05
Speaker 2: Some information released by open ai, the company that owns
41:09
Speaker 2: chat chapt and it said that zero point one point
41:12
Speaker 2: five sounds like a small amount of chat GPT's active users.
41:16
Speaker 2: In a given week, we're having conversations that included explicit
41:21
Speaker 2: indicators of potential suicide. Okay, And there are court cases
41:24
Speaker 2: currently underway in the United States with young people who
41:26
Speaker 2: have suicided after long interactions with AIS where the AI
41:33
Speaker 2: seemingly encouraged them.
41:35
Speaker 1: To go on with that process. And this has been
41:39
Speaker 1: a really big thing here.
41:40
Speaker 2: But that fifo point one five percent doesn't sound like
41:45
Speaker 2: a lot. But when you think of how many people
41:47
Speaker 2: are using it that you know, are using chatpts. So
41:50
Speaker 2: there's more than eight hundred million weekly active users, so
41:54
Speaker 2: more than a million people are talking to it about
41:57
Speaker 2: suicide and every week week. Yeah, yeah, exactly, And that's
42:03
Speaker 2: that's where it's being raised from. So you know, I
42:06
Speaker 2: agree with you Crago that I'd love to I think
42:10
Speaker 2: it's great that we can use this tool. You know,
42:12
Speaker 2: we can use this for diagnosis and maybe in conjunction,
42:14
Speaker 2: because you know, you've got effectively thousands and thousands of
42:18
Speaker 2: research papers that went into diagnosing that break and the
42:23
Speaker 2: outcomes of similar breaks. So when you're compilating all that data,
42:27
Speaker 2: I mean, I think gps are such some of the
42:30
Speaker 2: smartest people because they have no a whole lot about
42:33
Speaker 2: a whole lot of stuff and then be able to
42:35
Speaker 2: apply that to a diagnose a diagnosis when you sit
42:38
Speaker 2: down and find out what the ailment is.
42:41
Speaker 1: But when you've got an.
42:42
Speaker 2: AI model that's literally scraped the entirety of all our
42:46
Speaker 2: knowledge almost and then you know, so you can see
42:49
Speaker 2: similar cases other people who have had breaks this way.
42:53
Speaker 2: Physios have reported on what they did to help that
42:56
Speaker 2: person recover. You're now collating that into one model. And
42:59
Speaker 2: that's that's why the chat GPT outcome that you were
43:02
Speaker 2: talking about was so accurate and so amazing, because it's
43:06
Speaker 2: drawing on humans, it's drawing on human research, it's during.
43:10
Speaker 1: From the intelligence, the years of.
43:12
Speaker 2: Experience, all that sort of stuff. So when we talk
43:15
Speaker 2: about these AI models, AI is not smart all the
43:19
Speaker 2: bloody people who've put their brain work and years and
43:22
Speaker 2: study and sweat and tears into observing and caring and
43:26
Speaker 2: doing all the things that they've done. That's the outcome
43:29
Speaker 2: we're getting, is the outcome of all these people who've
43:32
Speaker 2: been at the call fake the nurse, the cold face,
43:34
Speaker 2: the nurses, the doctors, the physios, all those people.
43:37
Speaker 1: Yeah. Yeah, So one of the things we've spoken about
43:40
Speaker 1: over time is trying to distinguish between an AI video
43:44
Speaker 1: and a tiff made video, a real human video and
43:48
Speaker 1: an AI video. But apparently there's one sign that kind
43:53
Speaker 1: of demonstrates whether or not it's AI or real.
43:57
Speaker 2: Isn't it funny that we have to do this now
43:59
Speaker 2: that everything we see we have to challenge. I find
44:01
Speaker 2: that so frustrating. There's a country and Western song that's
44:05
Speaker 2: just top the charts on Billboard in the United States
44:10
Speaker 2: and totally fakes made up by AI.
44:14
Speaker 1: The images AI.
44:15
Speaker 2: It's some dude wearing a cowboy hat with a long
44:17
Speaker 2: jacket on walking off into the sunset, and you look
44:20
Speaker 2: at his feet and he's walking through puddles and the
44:22
Speaker 2: splashes look weird, you know, the images of a glory
44:25
Speaker 2: and it feels to me so sad for all those
44:29
Speaker 2: people who you know, who write music and are performers.
44:33
Speaker 2: And I'm going to be singing in a choir tomorrow.
44:35
Speaker 2: I thought i'd mentioned that we're doing a half hour
44:37
Speaker 2: set at the book, But the thing is, it makes
44:43
Speaker 2: me feel sad for those people who are creators, people
44:46
Speaker 2: who actually legitimately are musicians who write. But one of
44:49
Speaker 2: the things to look out for, so the red flags
44:51
Speaker 2: to look out for when it comes to false stuff,
44:54
Speaker 2: is when you look at the picture quality itself. If
44:57
Speaker 2: it looks a little bit grainy in areas, might be
45:00
Speaker 2: slightly blurry footage. They're the types of things you need
45:03
Speaker 2: to be looking at. And when I was watching this
45:05
Speaker 2: song today because I couldn't help myself, given that there
45:08
Speaker 2: was an article about, you know, how bad it is
45:10
Speaker 2: that a fake song is the number one on the
45:12
Speaker 2: Billboard charts, I looked at it and it does you know,
45:15
Speaker 2: you start to look at it and you think this
45:17
Speaker 2: is such crap. You know, the physics engine of walking
45:21
Speaker 2: through a puddle and the way the water splashes just
45:24
Speaker 2: it looked too real. Can I even kind of you know,
45:27
Speaker 2: articulate it that way? There was something too symmetrical about
45:30
Speaker 2: the puddle splash. It was too perfect to be real,
45:35
Speaker 2: is the way that I kind of looked at it
45:36
Speaker 2: when I was watching the video clip, And so I
45:39
Speaker 2: think that the thing we need to think about. And
45:41
Speaker 2: this is a scientist at the University of California, Berkeley,
45:44
Speaker 2: a guy by the name of Harry Faird, and he
45:46
Speaker 2: was just saying that digital forensics is now a real,
45:49
Speaker 2: big study. And so he's started a deep fake detection
45:55
Speaker 2: company called get Real Security, and they're now trying to
45:59
Speaker 2: develop more tools to make it easier for us to
46:01
Speaker 2: spot these fakes. Because you know, if you're flicking through
46:05
Speaker 2: socials or you're on YouTube or whatever and you kind
46:08
Speaker 2: of you've been ripped off, you feel like you've been scammed.
46:11
Speaker 2: I mean, I don't know about you, but if I
46:13
Speaker 2: spend five minutes looking at a video and I think,
46:15
Speaker 2: oh man, that was AI generated, What a lot of
46:18
Speaker 2: shit that was, I feel like I've just wasted thirty seconds,
46:21
Speaker 2: twenty seconds, fifty seconds or a minute or whatever. But
46:24
Speaker 2: you've just wasted that time looking at this crap. If
46:27
Speaker 2: I knew if I had a deep fake detector, that
46:30
Speaker 2: would be so good, so I don't want to see
46:33
Speaker 2: it I'm not interested in seeing it. I want to
46:35
Speaker 2: see human content, real people doing real stuff.
46:38
Speaker 1: Yeah, I have a different opinion. I agree with you
46:43
Speaker 1: in a way, but I also think, well, if somebody
46:47
Speaker 1: watches something like you think about, you think it's shit,
46:49
Speaker 1: you hate it, totally respect that, and I don't think
46:53
Speaker 1: we all need to agree. I think, but if it's
46:55
Speaker 1: the top of the billboard charts and people know it's AI,
46:58
Speaker 1: well then a lot of people knowingly are giving the approval,
47:02
Speaker 1: and a lot of people enjoy the actual irrespective of
47:06
Speaker 1: who or what created it. They enjoy the music. And
47:09
Speaker 1: I think, you know, the fact is if I drew
47:13
Speaker 1: painting and let's say my let's say I was an
47:16
Speaker 1: artist and the art was brilliant, or AI drew an
47:19
Speaker 1: equivalent painting, so to speak, and it looks identical, it's
47:24
Speaker 1: really just psychology. Like the music has its own value,
47:30
Speaker 1: But then it's really about like you could you could
47:33
Speaker 1: listen to a song and think this is fucking amazing
47:36
Speaker 1: because you think a human did it, But as soon
47:38
Speaker 1: as you know a human didn't do it, now your
47:41
Speaker 1: attitude about the music is different, and it's not about
47:44
Speaker 1: the actual music, but rather your beliefs about how this
47:47
Speaker 1: should work. And I understand that, but like the truth
47:51
Speaker 1: is that this is not going away. There will be
47:54
Speaker 1: AI art, there will be AI music, there will be
47:57
Speaker 1: AI books, there will be AI movies. It's not going
47:59
Speaker 1: to go away. And while I understand that, you don't,
48:05
Speaker 1: and I'm a bit the same, Like I worry about podcasting.
48:08
Speaker 1: I'm writing a new book at the moment, and I'm like,
48:11
Speaker 1: should I even bother? Because I could write my book
48:15
Speaker 1: in twelve seconds. It's like, should I invest all of
48:18
Speaker 1: this cognitive horsepower and mental energy and for me the
48:25
Speaker 1: capacity of AI to do what I do probably better
48:29
Speaker 1: and obviously much more quickly. You know, I don't love that,
48:33
Speaker 1: But nonetheless, it's not going to disappear. And I think
48:36
Speaker 1: it's like the horse and cart and the automobile. You know,
48:39
Speaker 1: it's like it's just going to happen. I don't think
48:42
Speaker 1: that's going to make human art or creativity redundant. I
48:46
Speaker 1: think it's just going to change the landscape and the
48:48
Speaker 1: way that we create and buy and interact with all
48:52
Speaker 1: of that. And I'm with you, like I feel like
48:55
Speaker 1: you get ripped off because you got tripped, But if
48:59
Speaker 1: you didn't know that, you just if you watched that
49:01
Speaker 1: same thing and you thought a person had done it,
49:04
Speaker 1: then you think it's brilliant. But when you know a
49:06
Speaker 1: person didn't do it, well, that's just psychology. It's not
49:09
Speaker 1: actually about the art or the music or the creativity.
49:13
Speaker 1: It's about where it came from. That's a different conversation.
49:17
Speaker 2: We were messaging each other last week or the week
49:19
Speaker 2: before about the new Avatar film because we went and
49:22
Speaker 2: the second one together, and we went to Imax and
49:24
Speaker 2: it was so big and real.
49:26
Speaker 1: None of it was real, you know, exactly.
49:28
Speaker 2: It wasn't those flying bird things and the whales and
49:32
Speaker 2: blue skinned aliens, but the reality of it is how
49:35
Speaker 2: it made us feel when we went there was really good.
49:38
Speaker 2: Well except when you put your hand on my leg,
49:39
Speaker 2: But as I loved.
49:41
Speaker 1: It, you look, you sat on my knee and the
49:43
Speaker 1: scary partsucker, So don't pretend like I was a clingy one.
49:48
Speaker 1: Thank goodness.
49:48
Speaker 2: It was a scary movie all the way through too. Huh.
49:51
Speaker 2: You know, I just kind of staying on the AI topic.
49:54
Speaker 2: And this is the thing that's still I can't resolve
49:58
Speaker 2: in my mind is death. So I think we've spoken
50:01
Speaker 2: about deathbots before, and it's AI being used to preserve
50:06
Speaker 2: the voices, the stories, text information, everything about you.
50:11
Speaker 1: Your digital footprint.
50:12
Speaker 2: Gets used to basically create another version of you so
50:17
Speaker 2: that that could be used in, you know, after you die,
50:21
Speaker 2: to be played to your grandkids and great grandkids and
50:24
Speaker 2: they can interact with it and talk to you and
50:26
Speaker 2: have a conversation with you. I mean, it's not you,
50:29
Speaker 2: but in the mind of the person who is interacting,
50:32
Speaker 2: they're feeling that it's an authentic interaction with you. I
50:36
Speaker 2: recently there's a friend of mine, a client here in town,
50:40
Speaker 2: who got me to take a photograph of his father
50:44
Speaker 2: and he said, oh, someone showed me a photo of
50:46
Speaker 2: a dead relative and they put the two people in
50:48
Speaker 2: the photo together and they had their arms around each other,
50:51
Speaker 2: and so I thought I'd ai the crap out of it.
50:53
Speaker 2: And what I ended up doing was not only did
50:55
Speaker 2: I get him standing in the same photograph with his
50:58
Speaker 2: father with their arms around each each other, but they
51:00
Speaker 2: turned and looked at each other and smiled, and he
51:03
Speaker 2: was in tears. I mean, it was very heartwarming to
51:05
Speaker 2: see it. It wasn't real, but for him it was
51:08
Speaker 2: authentic and it was heart moving, and it was phenomenal
51:11
Speaker 2: and he's showing everybody, and you know, I thought, I
51:13
Speaker 2: can go one better than just a photo with an
51:15
Speaker 2: arm around. I can do more than that, and I did,
51:17
Speaker 2: and it made him feel so good. It was exciting
51:20
Speaker 2: for him. You know, it was a beautiful CPR photo
51:23
Speaker 2: of his father, that kind of lovely tone you get
51:25
Speaker 2: with an old photo, and then it transformed his photo
51:29
Speaker 2: into the same texture and the same context and they
51:32
Speaker 2: were just standing there in the room together, looking at
51:34
Speaker 2: each other and smiling. It was a beautiful moment for him.
51:37
Speaker 2: He was very moved by it.
51:39
Speaker 1: So how essentially that's essentially a placebo, Yeah, because it's
51:44
Speaker 1: not real, but the experience is real. Yeah, tears real,
51:47
Speaker 1: the emotion's real, the response is real. So personally, I
51:52
Speaker 1: would not want that, like when my parents die, I
51:54
Speaker 1: don't want to be talking to I don't want that.
51:57
Speaker 1: But that's just my purpose. But I understand how other
52:00
Speaker 1: people would. And you know, the funny thing is with
52:02
Speaker 1: this stuff, what would give one person comfort would freak
52:06
Speaker 1: another person out. You know, I don't want to be
52:09
Speaker 1: talking to dead Ron, you know, I don't want that.
52:12
Speaker 1: I don't want like fuck, I'm just going to treasure
52:14
Speaker 1: the time that I haven't had and all of that.
52:18
Speaker 1: But I don't want to be I don't want to
52:20
Speaker 1: be chatting with Ai Ron in twenty years.
52:22
Speaker 2: Well, as you know, my mum passed away sadly in
52:25
Speaker 2: the sixties and that was eleven years ago now, so
52:28
Speaker 2: it was.
52:28
Speaker 1: It was quite a while.
52:30
Speaker 2: I actually haven't been back to visit the grave because
52:33
Speaker 2: I don't like the idea of visiting a person's grave
52:36
Speaker 2: knowing what's there under the ground. It actually upsets me
52:40
Speaker 2: more to think about that, and I prefer to hold
52:42
Speaker 2: onto the memories of the stuff we did together and
52:47
Speaker 2: just the great experiences we had. You know, we used
52:49
Speaker 2: to do a lot of cooking together, you know in
52:50
Speaker 2: the kitchen. I used to hang out with Mum there
52:52
Speaker 2: and you know, it was it was fun and it
52:55
Speaker 2: was great to have those memories. And we're of a
52:58
Speaker 2: generation I'm thinking more, you know, Crago, you and I
53:01
Speaker 2: where we don't have that digital footprint of our first
53:05
Speaker 2: step and our first words and our first everything's you know,
53:08
Speaker 2: I moved home and I moved to Geelong and I
53:10
Speaker 2: was there for six years, and I reckon, I've got
53:12
Speaker 2: three photographs of my entire six years, you know, living
53:16
Speaker 2: and working in Geelong. But you know, I've got lots
53:19
Speaker 2: and lots and lots of memories that I hold on to.
53:22
Speaker 1: Yeah, yeah, and I think with all of this stuff, Yeah,
53:26
Speaker 1: like some things that would make somebody else happy or smile,
53:30
Speaker 1: or like I look at some photos, they make me sad.
53:34
Speaker 1: I don't want to look at that photo, you know,
53:36
Speaker 1: Like one of I've had a bunch of really good friends.
53:38
Speaker 1: One of my best friends in the world passed away,
53:40
Speaker 1: Rob Dixon Dicko about twelve thirteen years ago. I don't like.
53:44
Speaker 1: I've got photos of him and me that are awesome.
53:46
Speaker 1: I won't look at them because it just it doesn't
53:50
Speaker 1: you know. I don't like he's always. Oh he's not always,
53:53
Speaker 1: but he's often on my mind and in my thoughts.
53:56
Speaker 1: But yeah, it just doesn't. Like for me, there's no upside.
54:00
Speaker 1: I don't need to go open an album or look
54:03
Speaker 1: at something like that. It doesn't. But then for other
54:05
Speaker 1: people it's the right thing to do, all right. I
54:07
Speaker 1: want to finish with this one because it's kind of
54:09
Speaker 1: the intersection of shit I'm fascinated with and AI, which
54:14
Speaker 1: is new artificial muscle Patrick. So this is the tech
54:18
Speaker 1: section new artificial muscle that can allow humanoid robots to
54:25
Speaker 1: live four thousand times their own way. That seems that
54:29
Speaker 1: seems like impossible. It's so, yeah, tell us about that,
54:34
Speaker 1: because I definitely need some of that muscle. Yeah, that'd
54:37
Speaker 1: be great, wouldn't it.
54:38
Speaker 2: You wouldn't have to go to the gym anymore if
54:39
Speaker 2: you could just get just winded on and there you go.
54:43
Speaker 2: It seems that all the work that you've done all
54:45
Speaker 2: those years, Craigo was for nothing. Yes, well, robotics is
54:51
Speaker 2: you know, this is the next generation of where a
54:54
Speaker 2: lot of research is going into. And what they're using
54:58
Speaker 2: is little tiny magnet ed muscle they call you little
55:02
Speaker 2: magnetic muscles and together they combine and it's basically being
55:08
Speaker 2: done in South Korea at the moment and advanced functional
55:12
Speaker 2: materials they're calling them. And they're magnetically controlled, so the
55:17
Speaker 2: muscle can flip between being basically floppy and then rock
55:21
Speaker 2: hard through magnetism.
55:23
Speaker 1: So that's the way they're doing it.
55:24
Speaker 2: Because when you've got a motor that's generating for don't laugh.
55:30
Speaker 1: Yeah, anyway, it.
55:31
Speaker 2: Could be used for other purposes as well, Crago, but
55:35
Speaker 2: the little tiny strips of the can you're not.
55:37
Speaker 1: Say floppy and rock hard in the same sense. You
55:40
Speaker 1: do these things on purpose. I don't. I really don't
55:43
Speaker 1: absolutely do, Tiff doesn't he Yeah, back me up.
55:49
Speaker 2: Yeah, I just think it's a nice way to start
55:51
Speaker 2: and finish the show with smart Yeah. So the stiffened states, right,
56:00
Speaker 2: describe it?
56:01
Speaker 1: You could take I think you could say rigid or
56:04
Speaker 1: high ten soil. I don't think you need to say
56:06
Speaker 1: stiff and floppy and whatever the other one was.
56:10
Speaker 2: Anyway, the rigid state is brought about by these materials
56:14
Speaker 2: that could only one point two grams can hold up
56:17
Speaker 2: to five kilograms. That's four thousand times its own weight.
56:22
Speaker 2: It's as strong as an ant here so and when
56:25
Speaker 2: it's softened, so when it's flaccid, it can stretch to
56:28
Speaker 2: around twelve times the original legs.
56:36
Speaker 1: If what's worse, moist or flaccid?
56:40
Speaker 3: Oh, you had to bring it up.
56:44
Speaker 1: Today's podcast. Friday's podcast is called what's it called? Please
56:48
Speaker 1: don't say moist or something like.
56:50
Speaker 3: That, warned, I warn the whole typ.
56:56
Speaker 1: Yeah, she went onto the typ Facebook page and apologize
57:00
Speaker 1: in advance for the name of today's the title of
57:02
Speaker 1: today's episode, and she did. Creat i'ven't even had a
57:05
Speaker 1: look this morning, I should look Patrick, we got to
57:08
Speaker 1: go tell people how they can connect with you.
57:10
Speaker 2: No one wants to connect with me after this. Go
57:13
Speaker 2: to websitesnow dot com dot au and always happy to
57:17
Speaker 2: take suggestions on stuff we can talk about your websites
57:21
Speaker 2: noow dot com do you I'm imported?
57:25
Speaker 1: Thank you Patrick, thank you TIF, thank you so I mean,
57:28
Speaker 1: for that one person who's still listening, Well done you
57:32
Speaker 2: Thank you work, great work, marathon performance