TRIGGERnometry - December 06, 2023


How the Media Broke the World - Liv Boeree


Episode Stats

Length

1 hour and 4 minutes

Words per Minute

179.41527

Word Count

11,494

Sentence Count

715

Misogynist Sentences

3

Hate Speech Sentences

4


Summary

Summaries generated with gmurro/bart-large-finetuned-filtered-spotify-podcast-summ .

In this episode of the podcast, I sit down with Dr. Andrew Yang to talk about his new book, "Moloch: The New World Order." It's a book that explores the role of a demon god called Moloch, and the role that he plays in shaping the way we understand the world.

Transcript

Transcript generated with Whisper (turbo).
Misogyny classifications generated with MilaNLProc/bert-base-uncased-ear-misogyny .
Hate speech classifications generated with facebook/roberta-hate-speech-dynabench-r4-target .
00:00:00.760 This incentive structure is a big part of why we're seeing such incredible polarization.
00:00:06.440 Even the really respectable papers are leaning more and more into click-baity, rage-baity
00:00:11.560 tactics in order to maintain their market share.
00:00:15.540 On average, the average person just doesn't know where to go to get reliable information
00:00:19.080 anymore.
00:00:20.080 People don't tune into the news to find out what the facts are.
00:00:23.180 They find out to get the emotional hit.
00:00:26.600 It just feels like there's this force, like a razor blade coming up through the fabric
00:00:31.720 of reality, of shared reality, that is trying to bifurcate everything.
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00:01:59.800 What's this Moloch concept that you've come up with to describe where our media and new
00:02:04.220 media ecosystem is going wrong?
00:02:06.480 Well, I didn't come up with the Moloch concept.
00:02:08.980 It actually comes from an old, originally it comes from this old Bible story about this
00:02:13.520 horrible cult that was so obsessed with winning wars.
00:02:18.800 They were willing to sacrifice more and more of the things they cared about, up to and
00:02:25.420 including their children, who they would sacrifice in a bonfire in this burning effigy of this
00:02:30.580 demon god thing called Moloch, in the belief that it would then reward them with all the
00:02:37.020 military power they could want.
00:02:38.380 And so this sort of story became a kind of like synonymous with this idea of sacrificing
00:02:46.840 too much in the name of winning and like the forces of when competition goes wrong, essentially.
00:02:56.760 And then in 2014, Scott Alexander of Slate Style Codex, or now Astral Codex 10, wrote this
00:03:04.300 amazing blog post called Meditations on Moloch, where he's like, he basically connects the
00:03:11.360 dots between all of these like mentions of Moloch throughout history and put it into like
00:03:15.940 modern game theory terms.
00:03:17.840 Because he noticed, he's like, it seems like there's this like mechanism where, the same
00:03:25.260 sort of mechanism that is driving a lot of different problems in the world.
00:03:28.440 You know, whether it's like tragedy of the commons type problems, where companies will
00:03:35.100 take, you know, shortcuts to get, you know, to keep their share of the market or whatever,
00:03:39.740 you know, like use cheap plastic packaging or something like that, because that's the most
00:03:44.160 cost efficient thing they can do.
00:03:46.420 But then it's like creating all these negative externalities, you know, for the future, or
00:03:52.980 deforestation.
00:03:54.500 All of these sort of tragedy of the commons type situations are created by these like
00:03:58.460 misaligned game theoretic incentives, as well as things like arms races, you know, the fact
00:04:05.580 that we ended up with 60,000 nuclear weapons on earth, far more than we would ever need
00:04:10.440 to like maintain mutually assured destruction, is again, because it's like, the game theory
00:04:15.260 dictates it.
00:04:16.220 If your opponent does, you know, builds up a stronger arsenal, now you've got to do it,
00:04:20.780 and now they've got to do it, and so on.
00:04:22.020 So it's like, it's these like, screwed up short term incentives that each individual
00:04:28.100 person is technically rational for following, but if everyone does them, creates these like
00:04:32.680 bad outcomes for the world.
00:04:34.860 That's kind of what this moloch thing is.
00:04:37.440 And that's what it sort of becomes synonymous with.
00:04:40.680 And I was, you know, I'm sure like you guys just generally appalled at the direction that
00:04:46.340 the media has been taking over the last few years.
00:04:49.060 I mean, I mean, it's, if it bleeds, it leads has been like a strategy they've been using
00:04:53.920 since whenever, right?
00:04:55.760 But it feels like since the internet, and certainly since social media, that the competition
00:05:04.080 dial has been turned up, and it feels like even the really respectable papers are leaning
00:05:10.800 more and more into like clickbaity, ragebaity tactics in order to maintain their market share,
00:05:17.480 essentially.
00:05:17.780 And so it's the same kind of mechanism.
00:05:21.360 Like, you know, you're an editor, and you notice that your user, you know, your readership numbers
00:05:27.680 are like waning compared to your competitors.
00:05:29.360 And you notice all your competitors are now doing like more like slightly more clickbaity
00:05:32.720 stuff.
00:05:33.440 Well, now you kind of have to do it too, right?
00:05:35.980 Because if you don't, you're going to get left behind them.
00:05:38.100 And this is, again, the same moloch mechanism.
00:05:40.980 So yeah, I made like a whole little short film about it.
00:05:43.740 It's very good.
00:05:44.420 I really enjoyed watching it.
00:05:46.000 And the interesting thing to me is that for a while, there was the narrative, well, the
00:05:52.540 mainstream media is dying, corrupt, blah, blah, blah, blah, blah, which is true.
00:05:57.320 The new media is the answer.
00:05:59.280 And I think there's an element of that that can potentially be true.
00:06:03.240 But new media also is subject to various algorithms and various incentives that clearly
00:06:09.700 I mean, I look at some very popular YouTubers who comment in our space on stuff, just the
00:06:15.200 titles and thumbnails.
00:06:16.340 And I'm like, if I just ingested that for a week, I don't think I'd be a very happy,
00:06:22.040 emotionally stable person.
00:06:23.480 Right.
00:06:23.800 You know, they are doing, you know, and every now and again, we'll have a thumbnail that
00:06:27.800 says something along those lines.
00:06:29.360 But I'm just saying it seems to me like while the new media potentially offers a solution,
00:06:34.100 it is subject to many of the same flaws and perverse incentives.
00:06:38.040 Yeah, it's just a big old attention game, right?
00:06:41.360 Everyone is trying to compete for each other's attention, whether it's big media companies,
00:06:47.260 whether it's individual influencers, people, even like government orgs, you know, NGOs that
00:06:53.660 everyone is trying to get their voice heard.
00:06:56.220 And so it incentivizes people to do whatever tactics are best at doing that.
00:07:01.320 And it seems like the best emotions for going viral.
00:07:06.160 I mean, they're certainly not like cool-headedness or nuance, right?
00:07:10.520 It's fear, rage, and then the occasional like really like sort of exciting, happy story.
00:07:18.000 But rage in particular, even more than fear, is like a sort of action-triggering emotion.
00:07:27.060 And because the business models, not only of, you know, influencers, but also mainstream
00:07:34.220 media now is more like, how can you maximize impressions?
00:07:38.540 You want an active emotion that encourages people to go out and like share and comment.
00:07:43.800 And that's why rage is just so useful.
00:07:46.600 And the most effective way of triggering rage is like getting people well, you know, whipped
00:07:51.980 up into a tribal frenzy.
00:07:53.240 And so it's this, I think, you know, this like incentive structure is a big part of why
00:07:58.660 we're seeing such incredible polarization.
00:08:01.760 You know, it's hard to say, where did the polarization start?
00:08:04.720 It's been, there was this really cool like chart that was posted, I'll try and send it
00:08:11.280 to you guys, that showed how, it looked like, I called it the mitosis of Congress.
00:08:16.340 I don't know if you saw it.
00:08:17.100 It's like-
00:08:17.720 No, but do send it to us.
00:08:18.660 We'll put it in.
00:08:19.160 Yeah, it's like Democrats and Republicans over the years, like how much sort of overlap
00:08:23.120 there was in like opinion and, you know, it was in aggregate and just over time, it's
00:08:27.520 become more and more and more polarized until the point now it's like, there's basically
00:08:31.040 no overlap ever.
00:08:32.700 And what's interesting though, is that this process started before the internet.
00:08:37.120 So I don't think the internet is the cause, but it's basically just turned up the acceleration
00:08:43.480 because it's, you know, the tails were already coming apart.
00:08:46.700 It's just that, yeah, it's like it's turned up the competition dial and everyone's leaning
00:08:52.900 into it harder and harder.
00:08:54.520 It's really interesting that you say that because if I think back to our country of the UK and
00:09:00.700 we're talking about generating rage, I mean, who did that better than the tabloid press
00:09:05.400 in the 80s and the 90s?
00:09:07.040 I mean, they were masters of it.
00:09:08.180 There's a Netflix series out about David Beckham and David Beckham during the World Cup, he
00:09:12.660 got sent off for basically a little kick out at an Argentine player who then made a meal
00:09:19.480 out of it.
00:09:20.620 And then he became a national hate figure.
00:09:23.640 The Daily Mirror put a dartboard with his face on it and they generated this campaign
00:09:29.320 against him where he became the most hated man in the UK.
00:09:34.120 So it's been going on for a long time.
00:09:37.160 I just, what I find interesting is how, in a way, these mainstream media outlets are doing
00:09:43.140 this even more because they realise they're becoming less and less relevant.
00:09:47.060 Yeah, I completely agree.
00:09:48.820 They, I mean, that's the thing.
00:09:52.040 Like, I'm angry at them for doing it, you know, when it, particularly like the BBC, right?
00:09:56.540 And to be fair, I think they have held on perhaps the longest out of all the outlets.
00:10:02.960 But, you know, there are certain things, particularly like I see them make articles around the tech
00:10:09.640 space or something like that, areas that I know.
00:10:12.000 And I'm like, OK, it's very clear that you have a particular political slant.
00:10:15.400 Usually they lean left, not always, but...
00:10:18.400 That interview between Elon Musk and the BBC journalist, where the BBC journalist ran out of questions.
00:10:25.880 Like, I'm like, we will spend the next year working incredibly hard to get Elon on the show.
00:10:31.380 And we would, like, be desperate for every extra minute of time.
00:10:35.020 And this guy just wanted to attack him.
00:10:36.880 And then he ran out of attack questions.
00:10:38.600 Well, OK, I'm bored now.
00:10:40.300 It was unbelievable.
00:10:41.540 You've got one of the most relevant men on the planet, and you run out of things to say.
00:10:46.280 Yeah.
00:10:46.580 Yeah, it's not ideal.
00:10:47.480 No.
00:10:48.640 Well said.
00:10:49.580 But more generally, like, yeah, it just feels like there's this force, like a razor blade
00:10:57.920 coming up through the fabric of reality, of, like, shared reality, that is trying to, like,
00:11:01.860 bifurcate everything.
00:11:03.520 That's what this, again, I keep calling it Moloch, you know, it's helpful to almost think
00:11:08.460 of it as a kind of agentic entity.
00:11:11.560 What does that mean, sorry?
00:11:12.620 Like, something, I'm not saying actually there is a force that wants us to fight, but
00:11:18.360 it's almost helpful to think of it as there is this, like, demon that is, like, one, it
00:11:23.920 just, its lifeblood is people being at war and people arguing and people fighting and
00:11:29.540 the world doing badly because we aren't able to coordinate.
00:11:32.160 And that's the sort of outcome of this, because, like, we're, the type of problems the civilization
00:11:38.860 is moving into, you know, I have a background in philanthropy and, like, you know, global
00:11:42.480 catastrophic risk.
00:11:43.440 I've sort of worked in, like, semi in research and that, but certainly in, like, communicating
00:11:46.900 about it.
00:11:47.680 And almost all these problems, whether it's, you know, future pandemics, and there will
00:11:53.940 be worse ones than COVID, or climate change, or any of these big, really big problems, they're
00:12:00.540 all a result of us not being able to really coordinate effectively.
00:12:03.380 If we could coordinate well, then they would be relatively trivial.
00:12:06.640 Like, we've known roughly what we need to do to mitigate climate change, you know, or
00:12:10.460 at least temper it, but we haven't been able to get our act together to do it because there's
00:12:15.200 so many incentives for everyone to defect each time.
00:12:18.040 It's like, well, okay, you know, you're a poor country who's trying to get, grow their
00:12:22.540 GDP, and they've got a bunch of coal.
00:12:25.120 Of course, like, what are they meant to do?
00:12:26.700 Like, you know, this is the fastest ways to lift our people out of poverty.
00:12:29.280 But technically, they are defecting from, like, the global optimum, which is no one
00:12:33.660 uses coal, right?
00:12:34.640 And, like, uses perhaps a slightly more expensive but cleaner source of energy.
00:12:39.940 And so the problem with this, like, media issue in particular, the fact that, like, the media
00:12:45.840 are becoming increasingly polarized, everything is more optimized towards, like, rage and, like,
00:12:50.680 volatility and hype, unnecessary, like, hyperbole and that kind of stuff, is that now, you know,
00:12:58.620 okay, yes, you'll get, like, little echo chambers where people really, really trust their particular
00:13:02.540 news source.
00:13:03.300 But on average, the average person just doesn't know where to go to get reliable information
00:13:07.640 anymore.
00:13:08.320 It's really, really hard.
00:13:09.660 And if we can't, like, collectively make sense of these difficult problems, how the fuck
00:13:14.280 are we going to then, like, communicate and coordinate on actual reasonable solutions?
00:13:17.820 Which is one of the reasons why, like, you know, I think COVID was always going to be
00:13:21.400 too, it was so transmissible.
00:13:25.180 That was, the cat was out the bag, really, as soon as that, you know, it took them too
00:13:29.440 long to, it took governments too long to realize they needed to do something.
00:13:32.980 And then in the end, they ended up going crazy.
00:13:35.760 You know, they acted too slowly in the beginning, and then they lingered with stupid solutions
00:13:39.820 solutions for too long.
00:13:42.420 But if we can't have a shared understanding of reality, and we have a media system, which
00:13:50.000 is meant to, like, the purpose of the media is to, you know, in an ideal world, inform
00:13:53.700 people about the nature of reality so that you can get, like, a healthy parallax of views
00:13:58.460 and come to, like, sane conclusions, kind of as a hive mind.
00:14:01.180 If the media are doing the exact opposite of that, like, making people whipped up into frenzies
00:14:07.420 and splitting them apart, then we can't coordinate on these problems, so.
00:14:10.660 Well, you make really good points there.
00:14:11.980 I mean, one of the things you said, though, that I think probably isn't true, though, is
00:14:15.160 I don't think the function of the media, at least in terms of observable behavior, is to
00:14:21.320 inform people.
00:14:22.540 I think politics, culture, and everything to do with those things has now become entertainment.
00:14:30.220 The media is entertainment.
00:14:32.260 The news is entertainment.
00:14:33.900 People don't tune into the news to find out what the facts are.
00:14:37.900 They find out to get the emotional hit.
00:14:41.440 Right.
00:14:41.860 It's like a dopamine source.
00:14:42.960 Yes.
00:14:43.740 You know, and the tribal rage that comes with it, obviously, is a very powerful, you know,
00:14:48.240 it's a drug.
00:14:49.640 But I'm curious to talk about this concept of shared reality, because I suppose we've got
00:14:55.680 to a point where, wherever you think, I mean, there's, you know, this is why the trans debate
00:15:01.640 has become so prominent, because you're just going, it's two groups of people who can't
00:15:07.520 even agree on something as basic as biology, right?
00:15:12.980 And so, I mean, how do we have a shared reality if there are people who can't define what a
00:15:19.160 woman is, and there's other people who think it's the...
00:15:21.140 Do you see what I'm saying?
00:15:22.660 Right.
00:15:23.120 I mean, I don't know.
00:15:25.600 I think with issues like that, like, almost every cultural issue is the reason why it's
00:15:32.780 so front and centre, even though, in theory, it shouldn't be, you know, like, there's far
00:15:36.900 bigger issues in the world about, like, you know, trying to define what is or what isn't
00:15:40.820 a woman.
00:15:41.460 Like, it's...
00:15:42.780 Not to some people, Liv.
00:15:43.960 No, the feminists would disagree with you.
00:15:47.760 But the thing is, I agree with you that in terms of the issue itself, it's insignificant
00:15:55.080 compared to the problems we face.
00:15:57.140 However, I would argue if you have a disagreement about the very concept of truth at that basic
00:16:03.280 level, that is like, whoa.
00:16:05.900 Yeah.
00:16:06.160 No, and you're right.
00:16:07.280 It points to, and this is the thing.
00:16:09.240 So whether it's trans stuff, whether it's the debate over capitalism, all of these
00:16:14.240 different, like, cultural hot topics, that I think the reason why they are so successful
00:16:20.240 in meme space, again, if each, like, war topic is in its own, like, entity, is because there
00:16:25.700 are genuinely, like, valid perspectives from both sides.
00:16:29.960 And, like, any that which is going to create tension, like, where, because the system, like,
00:16:35.600 because the media, the way their incentive structures are set up, they are, you know,
00:16:41.640 they are being funneled into focusing on whatever topic will get the most clicks and views.
00:16:47.780 And thus, anything that has the maximum amount of tension, because there are conflicting arguments
00:16:52.900 and viewpoints, they are, like, messy things.
00:16:54.740 Like, you know, yes, I am someone who believes strongly in, you know, I think biology is the
00:17:00.320 closest thing, you know, it's one of our solid paths to reality.
00:17:03.840 At the same time, I very fundamentally believe that people should be free to live and choose
00:17:09.300 how they express themselves.
00:17:10.860 As long as they don't hurt other people.
00:17:12.100 As long as they don't, yeah, sure.
00:17:13.060 But, like, so these are two fundamental things, but they are, like, you know, that creates
00:17:17.980 tension, you know?
00:17:19.440 There will be certain things where someone's choice, like, butts up against the rights of
00:17:24.240 someone else's.
00:17:24.880 And it's like, what do we do in these?
00:17:26.280 And I think in part why these issues have taken off so much is because, let's think,
00:17:36.500 like, you know, like the trans issue thing, it became...
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00:18:12.780 Because it's not like it's a new concept, right?
00:18:15.400 The concept of trans people have been around for at least, you know, there's been, like,
00:18:18.480 writings of it for, like, certainly the last century.
00:18:21.800 But it's like the media latched onto it, because it was like, the media machine, this entity
00:18:27.720 that wants to just, like, keep the wheels churning and maximize profit, noticed, oh, this
00:18:32.200 is a thing, this is a potential trigger point.
00:18:34.160 Let's lean into this.
00:18:35.100 And then it became more and more inflamed than it needed to be.
00:18:38.580 Is that so...
00:18:39.920 I'm really curious to explore this with you.
00:18:42.040 So this is why I'm pushing back.
00:18:44.480 We are kind of in the media, and we talk about that issue quite a lot.
00:18:48.380 Now, I can tell you from a personal perspective why I am interested in it.
00:18:52.740 I'm interested in it because I think truth matters.
00:18:55.020 And what we are trying to optimize for here is the truth.
00:18:58.760 So when someone says, you know, abracadabra, Stacey, I'm now a different person, I respect
00:19:06.120 your right to call yourself whatever the hell you want.
00:19:07.880 But as you say, it butts up against the rights of other people.
00:19:10.440 And also, there are truth claims being made in that discussion.
00:19:15.500 And I'm like, if we can't even agree about truth at this basic level, how are we going
00:19:22.100 to solve any problem?
00:19:23.080 So to me, I understand your perspective, and I bet you there's lots of media outlets
00:19:28.080 that have focused in on it because they're like, this is where you get the clicks.
00:19:31.200 But for me, it's like, while, you know, some children are being hurt by this process, and
00:19:36.060 while we can't agree on truth, we have to get somewhere on this issue.
00:19:41.040 We have to find a way to resolve those tensions which are right exist.
00:19:45.380 But truth matters.
00:19:46.860 Right.
00:19:47.000 The thing that I would want to talk about when we're talking about the media is personal
00:19:52.320 responsibility.
00:19:53.480 And look, you can argue that these corporations, these organizations are evil, you know, they're
00:19:58.840 manipulating us.
00:19:59.980 And that very well may, that may very well be true.
00:20:02.660 But there's also a part of it is you have agency and you are allowing yourself to be manipulated.
00:20:08.880 No, that's a very good point.
00:20:09.720 Um, the this guy, Patrick Ryan, came up with this term psychosecurity.
00:20:16.640 And he's been saying like, the biggest issue of this decade, in his opinion, I'm not sure
00:20:22.320 if I would completely agree, but that we all need to be thinking about and working on is
00:20:27.020 this idea of psychosecurity, same as you'd have cybersecurity for your computer or your
00:20:32.360 physical security for your house or whatever.
00:20:34.300 We need psychosecurity to protect ourselves from the increasingly powerful manipulation
00:20:40.880 tools that are flying about on the Internet.
00:20:44.740 And whether these tools are being used because someone is evil or whether these tools are
00:20:48.240 being used because they're simply stuck in a like, you know, a for profit incentive game
00:20:53.200 that makes you, you know, they're funneling, they're trying to just maximize their profits.
00:20:57.280 So it's like more the game that's evil.
00:20:59.100 It doesn't really matter.
00:21:00.020 The point is, we're spending more and more time on these devices.
00:21:04.900 And these devices have not really been built for our like mental health.
00:21:08.000 They've been built for, again, kind of either, you know, maximizing profits or maximizing,
00:21:14.260 you know, just getting people to stay on them for as long as possible.
00:21:16.620 And so how do we build these psychological defenses against these various things?
00:21:21.020 Whether it's like TikTok trying to just turn you into a fucking drooling moron, just scrolling
00:21:27.940 a thing or the media trying to turn you into a like foaming at the mouth, politically polarized,
00:21:35.120 rabid person.
00:21:36.300 It's how do we build up these sort of psychological defenses without going full Amish and going
00:21:42.140 like, OK, no more phones for me.
00:21:44.700 It might be that's right.
00:21:45.600 And the thing is, is that AI is going to make this more like speed all this up because,
00:21:49.760 you know, AI is like, it's such a broadly useful technology.
00:21:55.520 If you can hack intelligence itself, then anything that, anything that there's an incentive
00:22:02.020 to use intelligence for, it will get used for.
00:22:06.260 And that includes all the really good stuff, solving all these big problems, but also speeding
00:22:10.400 up the existing problems we have.
00:22:11.980 Like, it'd be terrifying to think, you know, if like all the really partisan news outlets
00:22:18.400 suddenly got AI, you know, really personalized AIs for each individual user to get them to
00:22:23.760 keep getting even more and more angry.
00:22:25.520 That's the way things are trending.
00:22:27.120 Wow.
00:22:27.920 Yeah.
00:22:29.080 Like every company on earth is waking up to the fact that AI is like, there's going to
00:22:32.540 be an AI tool to speed up their company.
00:22:34.380 And that means all the good ones, but also all the like bad ones and even the criminal ones.
00:22:38.300 Criminal enterprises will soon have access to AI for whatever crappy thing is they want.
00:22:41.960 Casinos wanting to addict people to slot machines.
00:22:45.420 Like, I mean, those are already sort of dopamine hijacking enough, but that kind of thing.
00:22:51.180 I mean, arguably that's what social media is.
00:22:53.160 It's our first like interaction on a broad scale with like rudimentary AI, because it's,
00:23:00.400 you know, they might have started out really basic algorithms, but these things are getting
00:23:03.760 more and more intelligent, more and more personalized.
00:23:06.940 Like my Twitter feed, damn, that shit knows exactly.
00:23:10.540 Same with my Instagram as well.
00:23:11.580 My Instagram is like my, Twitter is what makes me all like fired up and like intellectually
00:23:15.600 interested in something.
00:23:16.680 And Instagram is all the things that just like, when I just want to chill out and like, you
00:23:21.200 know, I want to be entertained on the toilet.
00:23:23.020 It's just, here's funny, here's funny animal doing that.
00:23:25.620 Here's silly thing there.
00:23:27.940 They're so tailored to my brain because I've been freely giving them my information all this
00:23:33.480 time.
00:23:33.820 And it's AI is just, as AI gets better, this is going to get stronger and stronger and
00:23:37.760 stronger.
00:23:38.380 And that does not sound like a good thing.
00:23:41.720 Doesn't seem like it.
00:23:42.720 No.
00:23:44.140 We'll get back to the episode in a minute.
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00:25:35.540 Back to the interview.
00:25:36.540 And this is the thing that I'm worried about because I think it was a few months ago when
00:25:43.320 Elon and a few people, they signed a document requesting that there's a moratorium on AI
00:25:48.920 and as noble as that is, and I would like that, the reality is that's simply not realistic.
00:25:56.740 No, it's going to, well again, it's like a coordination problem.
00:25:59.260 Um, because also like, how do you, you know, where do you draw the line?
00:26:03.500 Technically Google Maps is an AI.
00:26:05.880 AI is so broad as a term.
00:26:07.940 So you need to like, they, I think the purpose of that letter was just to like raise attention.
00:26:13.860 Um, and it did a good job.
00:26:15.120 Definitely did a good job.
00:26:16.380 Um, you know, the type of regulation that I think makes the most sense in the, in the interim
00:26:22.060 while we're figuring this out is like regulation on front, what are called frontier models,
00:26:26.900 which are like the, just the leading most powerful ones.
00:26:29.000 So like technically GPT-4 was a frontier model six months ago, whatever is currently being
00:26:33.600 worked on now, that's the upgrade to that is now a frontier model.
00:26:36.840 And the thing is with these types of things where like, you know, I, I think it was pretty
00:26:42.280 irresponsible for open AI to go and just release or even like, uh, Microsoft and they were using
00:26:48.440 Bing, they did that first actually to, there's no way they could know what the downstream,
00:26:53.280 and we still don't know what the downstream effects are of having such a powerful language
00:26:57.860 manipulation tool released to the internet, released to a billion people, nine, you know,
00:27:02.280 eight billion people.
00:27:03.600 Um, and to be fair, there is no way they can know until they do it.
00:27:07.820 So like these companies are going to be just running real time experiments on humanity.
00:27:12.640 And if it turns out that these experiments are actually have a bunch of unintended consequences,
00:27:16.200 we won't know until it's, you know, either too late.
00:27:19.820 I'm not saying that like the current models are a risk of extinction, they're not, but
00:27:23.320 there's maybe like downstream second, third order effects, again, contributing to like
00:27:28.340 not knowing, you know, polluting the information ecosystem, this kind of stuff, um, that we won't
00:27:33.460 know until they've become so integrated into the economy that they're almost impossible
00:27:37.020 to extract again.
00:27:38.380 And that's the thing, our economy is getting more and more integrated into AI or vice, sorry,
00:27:42.680 vice versa.
00:27:43.160 So some like one, one like sane thing that could be done is like more regulation on frontier
00:27:50.120 models, because that will, a, that sort of make it, it's putting the responsibility on
00:27:56.420 the most powerful people within AI, the big, the biggest companies.
00:27:59.520 So minimizes the risk of regulatory capture.
00:28:02.260 It's only really affecting the big boys, not the little, the little guys can still carry on
00:28:05.480 developing.
00:28:06.520 Um, and those are also the models that are most likely to have like unseen risks and big,
00:28:12.620 big, big, big consequences.
00:28:14.460 But in terms of this like wider question of like AI, like speeding up the misalignment
00:28:21.700 that's already inherent within our sort of economic system, I don't know, like it's just
00:28:27.240 so hard because it's like, it's like, it's like a game of whack-a-mole, but instead of like
00:28:33.340 20 little things, it's like 20,000.
00:28:36.460 And it's, it's also from a personal point of view, more and more, I've just had the realization
00:28:43.180 that the, the amount of time that I spend online is also proportionate to the, the amount
00:28:51.840 of misery that I feel.
00:28:53.840 I've realized as I get older that the more, the less time I spend online, the happier that
00:29:00.120 I am because life really is all about connection.
00:29:02.820 It is.
00:29:03.460 That's why people love podcasts because it's about people connecting in a way that we rarely
00:29:08.660 do anymore.
00:29:09.940 Sometimes because our lives are so busy.
00:29:12.560 The only time in my day when I actually get to sit and have a conversation with another
00:29:17.540 human being for a prolonged period of time where my phone is off is to do this.
00:29:22.160 Wow.
00:29:22.300 And that's fundamentally unnatural.
00:29:24.760 Yeah.
00:29:25.700 And I think more and more that in order for us to be happier, we need to kind of just take
00:29:34.200 a step back and have that personal responsibility.
00:29:37.420 Yeah.
00:29:37.600 And there's like genuine wisdom in the saying, go out and touch grass.
00:29:40.620 Yeah.
00:29:41.120 Like truly everyone laughs about it, but like, no, people are so disconnected, not only from
00:29:45.740 each other physically, just from the physical, physical reality.
00:29:50.260 The digital realm is, it is a universe of sorts, but it's not a universe that we evolved out
00:29:56.500 of.
00:29:56.980 Yeah.
00:29:57.800 And it almost feels to me like it's like this reality that's growing stronger, that's
00:30:03.580 like feeding off our consciousness in some way.
00:30:06.380 I like in my video, I did this thing, like, because that's like how I feel sometimes when
00:30:10.020 I'm just like on my phone and I'm sitting with my friends.
00:30:13.360 Then I remember like 15 years ago, we'd be sitting around and we'd be all like up in each
00:30:17.620 other's stuff, you know, talking or whatever.
00:30:19.720 And now half the time, like these things are like, like, they're like an appendage on our
00:30:24.080 arm that is just like a parasite sucking all of our attention into.
00:30:28.400 And we're just like, they're feeding them as opposed to them adding to us.
00:30:31.620 That's, that's the thing.
00:30:32.740 It's like, how do we, it feels like that's the trend.
00:30:35.960 Would you not also agree that I think we, we love to bang on about how evil social media
00:30:42.620 is, but it's also fucking great.
00:30:45.040 It's fucking great.
00:30:46.620 So how many friendships do we have, all of us, because we're on social media?
00:30:50.520 How many amazing people have we connected with?
00:30:52.980 How many amazing things have we learned?
00:30:55.180 How have we improved our understanding of the world?
00:30:57.840 Right.
00:30:58.520 And I think the same thing is the case with, with AI.
00:31:01.860 AI, I'd be curious to hear kind of what you think are the biggest risks, but also the
00:31:06.340 biggest rewards that will come from that.
00:31:08.960 Yeah.
00:31:09.200 So, I mean, there's, there's like kind of four different categories of risk.
00:31:13.400 There's the, um, the unintended consequences type stuff.
00:31:20.160 So like you build such a, like an incredibly powerful model that it, you know, especially
00:31:24.580 let's say it learns to, or you don't even have to learn to, people are like already trying
00:31:28.980 to build models, which can edit their own code and like recursively learn.
00:31:33.560 So like that opens up like a pretty obvious can of worms, at least to me, you know, it's
00:31:37.740 like now something can basically evolve itself.
00:31:40.840 It's going to be doing it at a faster, faster rate than any form of biology.
00:31:44.080 So that's like the whole sort of like Darwinian type thing.
00:31:47.280 And it doesn't have to turn evil and want to kill us.
00:31:49.360 It's just like, it might be so good and fast, you know, its goals might not be perfectly
00:31:55.480 aligned with ours and it would therefore perhaps just use all the resources that we
00:32:00.260 need, you know, or our environment is not suitable to its and it wouldn't intend to kill
00:32:05.180 us.
00:32:05.400 It just, we would be a by-product of whatever it continues to do.
00:32:08.700 That's like one category.
00:32:10.220 That's like the most like classic, um, extinction risk type thing.
00:32:13.720 Um, and I'm lots of sci-fi when in my youth about this, which is a benevolent AI realizes
00:32:19.760 that the root of human misery is humans.
00:32:22.360 Yeah.
00:32:22.840 I mean, that's a very like anthropomorphized version of it.
00:32:24.920 I think like that's less plausible than just the idea of like an unintended consequence of
00:32:29.660 like, it's like it wants more compute.
00:32:33.340 And the best way to get more compute is to turn every little bit of silicon it can find
00:32:37.720 into chips and that we need, we need that silicon for other stuff, you know, um, just, you
00:32:42.660 know, just biosphere changes, that kind of stuff.
00:32:45.160 That's, that's like the extreme sci-fi type thing.
00:32:47.320 But then there's the more near-term things again, like, uh, speeding up the misalignment
00:32:53.300 in the system, like basically bad, not bad companies, but like companies that are just
00:32:57.560 wanting to do their thing, maximizing for profits or whatever.
00:33:01.080 And now are made even faster and more efficient at doing that at like, you know, cutting down
00:33:05.800 the rainforest or all these things.
00:33:07.320 And then there's like the bad actor problem.
00:33:08.900 So, you know, cause like one, one argument people put out for like open sourcing is
00:33:16.700 like, well, if we open source and we can get, um, more people to like be thinking about
00:33:20.580 how to build, incorporate safety, we can hive mind this, which seems nice in principle.
00:33:24.560 But the trouble is if you completely open source a very powerful model, um, a model that had
00:33:30.140 been kept closed source, you'd put all these safety measures in.
00:33:32.380 Well, now any bad guy, and the thing is, is that we do have a 1% rate of psychopaths
00:33:37.800 on this planet and it only take a, even like a percent of a percent of them, you know, if
00:33:43.380 they found a way to make these things, you know, to truly cause the max damage they could,
00:33:47.840 you know, like, think, think like ISIS type mentality people, something like that.
00:33:52.220 Now, like, how do you protect against them?
00:33:54.380 You can't.
00:33:54.980 So there's that sort of category of risk.
00:33:57.740 And then you've got the fourth one, which is, uh, sort of structural type problems that
00:34:03.900 might come from like basically the sudden shock of such a powerful new technology becoming
00:34:09.740 ubiquitous.
00:34:10.420 So like mass unemployment is a classic one.
00:34:12.840 Yes.
00:34:13.300 Um, you know, we're already starting to see signs of it and I'm not convinced by the arguments
00:34:19.060 that it will be able to create new jobs fast enough to, um, fill in the gaps of all the
00:34:28.200 ones it's displacing.
00:34:29.320 Like, it doesn't seem obvious to me that that will be the case.
00:34:31.920 Um, so there's those kinds of risks too.
00:34:34.040 And this, sorry.
00:34:34.800 Sorry, I just wanted to finish on the benefits because, you know, in your video, you talk
00:34:40.340 about negativity bias, right?
00:34:42.400 Human beings have, we prioritize negative information.
00:34:45.080 And I said to you, what are the risks?
00:34:46.400 What are the benefits?
00:34:47.040 You know, like risk, risk, risk, risk, risk, let's move on.
00:34:50.100 No, you're absolutely right.
00:34:50.940 You're right.
00:34:51.180 No, you're totally right.
00:34:52.100 And, and, and that's the difficult thing because there are so many problems that AI can
00:34:59.460 help to solve.
00:35:00.240 Right.
00:35:01.000 You know, like a lot of the environmental issues we have because we haven't figured out
00:35:05.100 how to have a like more abundant, clean source of energy.
00:35:08.040 AI could help us figure out nuclear fusion.
00:35:11.080 So we need it for that.
00:35:12.020 It could help us do with drug discovery.
00:35:14.500 So it, you know, especially if like there are all these new potential pandemics on the,
00:35:19.280 on the, um, on the timeline, because that's the thing again, with AI, it's what you call
00:35:23.660 a dual use technology.
00:35:25.480 Not, not all of the different flavors of it are, but certain categories of AI tend to
00:35:29.380 be dual use.
00:35:30.020 They can be used for good or for bad.
00:35:31.380 But the, I kind of, I'm like bipolar on the topic almost because, you know, when I spend
00:35:37.740 a lot of time thinking about these coordination issues, you know, like how do we coordinate
00:35:43.200 to, for climate change or whatever, we almost need some kind of super intelligence to help
00:35:48.640 us better coordinate on these things in a way that doesn't also then just leave us like
00:35:53.200 vulnerable to tyranny or nightmarish like type top-down scenarios.
00:35:56.520 So, you know, the, the bull argument for like going all in on AI as quickly as possible
00:36:02.560 is that we won't be able to solve these other problems without it, but then it opens up new
00:36:06.760 cans of worms that might make these existing problems or even brand new ones worse.
00:36:09.920 So it's like, it feels like it's like this minefield we have to navigate to get through.
00:36:15.300 But if we get through, then it's like, ah.
00:36:17.020 Yeah, and it's also as well, the reality is, is that there are people who, I mean, we don't
00:36:23.380 live in a unipolar world, we live in a multipolar world.
00:36:26.240 And the reality is, is that if we don't invest in AI, China, Russia will do.
00:36:31.840 So that's the classic, yeah, the moloch trap, as you call it.
00:36:34.640 Yeah, exactly.
00:36:35.160 You're totally right.
00:36:35.780 Yeah, so we're right back into that.
00:36:37.920 Yeah.
00:36:38.440 But one thing that I really wanted to talk to you about, Liv, moving on is poker and in
00:36:43.780 particular strategy.
00:36:45.120 Firstly, how did you get into poker?
00:36:47.460 Because you'd studied astrophysics at university and then you became a poker player.
00:36:52.220 Are those connected?
00:36:53.180 Is it mathematics?
00:36:54.420 No, it was very, very random.
00:36:56.860 I graduated, really didn't want to get a real job.
00:37:01.640 I was trying to do anything I could.
00:37:05.200 And I started applying for game shows in the UK.
00:37:09.580 What type of game shows?
00:37:10.920 Just any of them that would accept me, basically.
00:37:13.340 I was on Golden Balls.
00:37:16.520 Oh, really?
00:37:17.200 Okay, that type of game show.
00:37:19.220 That one, I defected.
00:37:23.260 I stole.
00:37:25.000 Yeah, I feel bad about that one.
00:37:27.640 What else?
00:37:29.460 Codex with Tony Robinson.
00:37:31.160 Okay, yeah.
00:37:31.840 That was great.
00:37:33.380 They locked you in the British Museum overnight and you had to solve all these clues.
00:37:35.940 But anyway, one of the first shows, in fact, the first show I got on was one that said,
00:37:40.500 could you use your powers of skill and deception to win £100,000?
00:37:43.560 I was like, that's a lot of money.
00:37:45.040 Yes, please.
00:37:46.840 So, yeah.
00:37:47.760 And I got selected as one of the five contestants.
00:37:50.040 And then they did this big reveal that they were actually going to teach us how to play poker.
00:37:53.580 And, like, the loose premise was, like, which personality type is best suited for the game.
00:37:59.120 And I was the professor, as they called me.
00:38:02.040 And I didn't win the show, but I just absolutely fell in love with the game.
00:38:08.660 You know, at the time, I was really into metal music and wanted to be a rock star.
00:38:15.200 And I was like, oh, wait, this is probably easier in many ways because I wasn't that good at guitar.
00:38:22.200 A way to, like, I wanted to travel the world, basically, and live a very ridiculous life.
00:38:26.880 And poker seemed like a fun way to do that.
00:38:29.160 Wow.
00:38:29.460 Okay.
00:38:30.140 So, how much of it is luck?
00:38:33.020 How much of it is strategy in order to become a good poker player?
00:38:38.340 So, it depends on the time horizon you're talking about.
00:38:41.740 Like, if the three of us sat and played for half an hour, it's basically all luck.
00:38:48.240 Assuming you know roughly how to play.
00:38:52.200 But if we played for a week, I'm going to win probably 98% of the time, something like that.
00:38:59.820 Again, I don't know how good you guys are.
00:39:01.540 Maybe one of you are very good.
00:39:02.380 No, no.
00:39:02.760 I think you underestimate your success rate in that scenario.
00:39:06.840 I think it'd be closer to 100%.
00:39:08.180 Right.
00:39:08.360 So, basically, there's a lot of luck in, you know, any given hand, there's a lot of luck
00:39:12.400 and randomness because the deck is shuffled between each hand, et cetera.
00:39:15.460 You can't control what cards you get.
00:39:17.480 But the more you play, the more decision points there are, the more any edge that the better
00:39:23.840 player has accumulates.
00:39:25.240 And how much of it is about reading people's emotional cues, tells, et cetera?
00:39:31.540 How important is that?
00:39:32.780 If you're just some purely analytical nerd that can't read people at all, can you be
00:39:39.860 a successful poker player?
00:39:41.020 Yeah.
00:39:41.380 So, let's put it this way.
00:39:44.100 The best poker player on earth is the most analytical nerd you can imagine because it's
00:39:48.800 an AI.
00:39:49.420 It's an AI that doesn't know human emotion.
00:39:52.520 It doesn't read people in that way.
00:39:54.420 It's just so good at calculating the game theory, basically, these Nash equilibria.
00:40:01.260 It's so good at that that it is able to beat the very best humans on earth consistently.
00:40:05.220 If they were to sit and click buttons against this thing for infinity, this thing would crush
00:40:09.640 them.
00:40:10.620 So, what that says is that the game really at its core is a game of maths.
00:40:14.380 Wow.
00:40:14.680 Now, that's not to say that there isn't this level of meta information that you can use.
00:40:22.120 And what's interesting is how the games changed.
00:40:23.840 When I first learned to play, and certainly the decade before, like in the 90s, the best
00:40:28.520 players in the world were incredibly...
00:40:32.000 They were like these old school hustler type guys, you know, like the classic in the casino
00:40:37.020 with the cigar.
00:40:38.560 They would make these sort of inspired, intuitive plays that they couldn't even explain why they
00:40:43.160 did them.
00:40:43.440 They just had really strong gut feelings.
00:40:44.940 And their gut feelings were really, like, very accurate, at least more accurate to everyone
00:40:50.380 else.
00:40:50.960 So, that's why they were so good.
00:40:52.500 But as, you know, the game moved into online poker more, and we started having like more
00:40:57.940 data, basically, to synthesize and analyze, and then we started building software to analyze
00:41:02.120 that data, the game became more and more of a science and less of an art.
00:41:06.240 And this is sort of trended towards this very mathematical style.
00:41:09.620 Now, that's not to say that good, very, you know, the very best players these days know
00:41:14.940 how to do both types.
00:41:16.560 They are very mathematical.
00:41:17.980 They understand all the game theory.
00:41:19.240 But they're also great, like, readers of human behavior.
00:41:23.400 Those are the very best players.
00:41:24.700 But still, technically, they would lose to the machine.
00:41:30.160 That's how good it is.
00:41:31.140 And how useful is that ability to read other people in poker to normal life?
00:41:36.180 Like, can you tell what we're thinking now?
00:41:38.300 I mean, I can't tell what you're thinking.
00:41:40.020 Like, what you learn in poker, and I think this is true in almost anything, any kind of...
00:41:44.400 Oh, there's the fly.
00:41:45.020 What you're really looking for is figuring out what someone's baseline behavior is when
00:41:52.660 they are not, like, doing the activity, so they're not in a poker hand or they're not
00:41:56.920 in a negotiation.
00:41:58.600 You know, are they a naturally relaxed person?
00:42:01.040 Are they quite tense?
00:42:02.480 Are they extroverted, introverted, etc.?
00:42:05.260 And then you want to see how they deviate from their baseline when you're actually in play.
00:42:11.040 So, some people are naturally, like, very intense when they're playing, and then all
00:42:19.820 of a sudden they become more languid and something.
00:42:21.760 That can be sometimes some relevant information.
00:42:25.060 But the trouble is, as well, is that fear and excitement present themselves very similarly.
00:42:30.660 So that's a real tricky one.
00:42:32.360 When you're like, you know, we're playing and you go all in, put me to the test, and I
00:42:37.500 can see your heart is going, and you're breathing fast, and your mouth is clearly dry, that could
00:42:43.320 be excitement or fear.
00:42:44.740 So one little thing I've found helpful is sometimes to, like, just, like, make someone
00:42:49.700 sit there and sweat it for a few minutes.
00:42:51.440 Like, pay attention to how they are after three minutes or two minutes, however long I can
00:42:55.360 stretch it out for.
00:42:56.680 Because if they are excited, you know, if they have a good hand, typically that excitement
00:43:03.920 will wane.
00:43:04.440 You know, they've made their big action, and now they're just waiting to see what you
00:43:07.620 do.
00:43:08.500 And they don't really, there's nothing more they have to worry about.
00:43:11.600 So they'll typically calm down.
00:43:13.340 But if someone is bluffing, their heart's still going after two minutes, and that's still,
00:43:18.340 you know, they're still very, very stressed.
00:43:19.620 So that can be one way of discerning.
00:43:22.360 But again, like, the main thing is that there's no one-size-fits-all.
00:43:26.600 And you just have to be, it's something that you really can't explain.
00:43:32.820 People just have to gather through experience.
00:43:35.440 And I was going to say, Liv, how does mathematics work with poker?
00:43:39.860 You get given your hand.
00:43:42.220 How do you then discern what the best play is with your hand?
00:43:46.620 Because obviously you don't know the hands of other people.
00:43:49.680 Right.
00:43:49.800 So it's all about this concept called, like, ranges.
00:43:55.220 We're going to get quite specific here.
00:43:56.820 So, you know, you're playing Texas Hold'em.
00:43:58.920 Yeah.
00:43:59.280 You get two cards out of a deck of 52.
00:44:01.940 There's 1,326 possible combinations of two cards that you could get.
00:44:06.900 I hope those numbers are right.
00:44:08.060 It's been a long time.
00:44:10.260 If they're not, they're not.
00:44:11.320 I'm pretty sure that's the number.
00:44:13.060 And so all you know, so to begin with, you know, I have two cards out of a possible combination of, that's one combination out of 1,326.
00:44:22.120 So that's, like, right now my range is 100% of uncertainty to you.
00:44:26.060 But then let's say, you know, you raise and I now re-raise.
00:44:30.780 Well, now you can narrow down that range because I'm probably not going to be re-raising with, like, let's say, the bottom 40% of those cards.
00:44:38.860 Right.
00:44:40.180 There might be some and so on.
00:44:41.840 But as the hand progresses, your job is to try and extract as much information out of me as you can, while at the same time giving as little to me as possible.
00:44:50.780 Because I'm trying to do the same thing.
00:44:51.840 Right.
00:44:52.180 So you're trying to narrow down the range of cards your opponent could conceivably have by, you know, putting them to the test or seeing how they behave.
00:44:59.140 Um, while keeping the range of perceived cards that you have as wide as possible.
00:45:05.540 So that's what you're trying to do in fundamental, you know, fundamental terms.
00:45:10.240 And then there's basically sort of mathematics you can do within that.
00:45:13.720 Let's say I bet, um, 100 into a pot of 100, you know, existing 100.
00:45:21.940 So now you have to call 100 to win 200.
00:45:24.000 So you're getting two to one.
00:45:25.600 Right.
00:45:26.040 And now you can see this stuff like basically pot odds and then like these combinatorial, combinatorial, um, calculations you can do to see if you're getting the right kind of price.
00:45:36.660 Um, I won't go into the minutia of that, but that's the kind of stuff.
00:45:40.380 So, yeah.
00:45:41.260 So there's a real strategy behind it.
00:45:43.320 And the question I think that is really relevant for everybody watching this and particularly people who aren't interested in poker is, has that helped you to strategize in life?
00:45:55.920 And also, what are the best poker strategies that you can take for real life and that people can implement?
00:46:04.920 Um, I would like to think it has because, like, one of the main things poker teaches you to do is to just, like, be comfortable with uncertainty.
00:46:14.780 Be comfortable with just seeing things probabilistically.
00:46:16.900 Which actually leans into, kind of brings us full circle back to the, the, the, this, this issue that we have with today's modern media.
00:46:23.780 Right.
00:46:24.240 We don't know what's quite true.
00:46:25.920 You'll, some, you know, oh, they found aliens.
00:46:28.400 You know, the Mexican Congress are being shown this, this alien shape.
00:46:32.380 Well, what's the likelihood that it's real?
00:46:34.600 What's the likelihood it's not?
00:46:35.460 Okay.
00:46:35.580 That's maybe a silly example because that was pretty obvious that it was not real.
00:46:38.460 But, you know, some of these things you truly can't know and you might never find out what the truth is.
00:46:43.900 And so you, what poker teaches you is to be like, okay, well, I'm like, I feel like 30% of the time they have this kind of hand and then 40% of the time this, so then 30% of the time they have that or whatever.
00:46:59.160 You know, you're, you're very used to thinking about things probabilistically with this, like, gray scale.
00:47:05.460 And that's the most useful skill by far because, I mean, even things like trying to take it, you know, decide whether to park illegally somewhere.
00:47:17.780 Not that I would advocate that, but, you know, you're running late for a meeting.
00:47:21.800 Shit, I don't want to get a parking ticket, but I don't want to be late for my meeting.
00:47:25.500 What I would do is go, okay, well, what's the probability I'll get a ticket while I'm parked here?
00:47:29.520 Okay, it's probably like, you know, I'm here for half an hour.
00:47:32.240 It's probably only like 10%.
00:47:33.280 Okay, how much is the ticket if I get it?
00:47:35.760 It's $100.
00:47:36.580 All right, so that's an expected loss of $10.
00:47:39.680 Would I be willing to pay $10 to park right now and be on time for my meeting?
00:47:42.520 Yes.
00:47:42.840 Okay, I'll park.
00:47:43.820 You know, that's the kind of thing, these expected value calculations, which you don't learn in school.
00:47:49.360 And they're so useful.
00:47:50.480 They're so important.
00:47:52.500 So, yeah, living with just gray scale and probability is probably the number one thing.
00:47:58.920 We'll be back with our guest in a minute.
00:48:01.120 But first, we want to take a moment to talk about our partners, GiveSendGo.
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00:49:29.420 And now, back to the interview.
00:49:32.260 The next thing is learning how to deal with luck and randomness.
00:49:39.760 Because one of the hardest things in life is when, you know, let's say we have a big success at something.
00:49:43.860 Is it because we did a really good job?
00:49:46.460 You know, we were just better than everyone else?
00:49:48.920 Or was it more because we got lucky?
00:49:50.780 Or some combination of those two?
00:49:52.660 And again, like poker, it's like I won very early on in my career this huge tournament,
00:49:58.880 this European Poker Tour tournament.
00:50:01.500 And after that, basically, for a period of time, for the next six months,
00:50:07.660 because it was such a big tournament, I got so much attention for winning it.
00:50:10.900 I just assumed I was God's gift.
00:50:13.160 And I stopped studying the game as hard.
00:50:15.560 I started playing in bigger tournaments, like riskier tournaments, etc.
00:50:18.860 And my win rate just went, like, absolutely plummeted to the floor.
00:50:22.960 And that's because I got fooled by randomness a little bit.
00:50:25.420 Like, I obviously did a lot of stuff right to win that tournament.
00:50:27.620 But I also had so much luck on my side.
00:50:31.540 And our egos have a tendency, you know, the narrative we tell ourselves is we like to take credit for our successes
00:50:40.060 and outsource blame on luck.
00:50:43.800 You know, oh, I just got unlucky when things don't go well.
00:50:46.760 And poker teaches you to basically be, like, honest with yourself.
00:50:50.120 You have to be epistemically humble and, like, really scrutinize, you know, okay, what was the cause of this?
00:50:58.980 Was it because I did things right or because I got lucky?
00:51:01.700 And therefore, it trains you to be more focused on process as opposed to outcome and results.
00:51:06.060 Like, if you develop a good process that's kind of agnostic to whether luck is on your side or not,
00:51:10.920 then that's the benchmark you should measure yourself against.
00:51:13.500 So that's the other one.
00:51:14.200 And then the third one is, like, don't overprivilege your intuition in situations where your intuition is not best suited.
00:51:23.080 Because, again, like, the natural thing if I'm playing in a, if I was playing poker and I couldn't, you know,
00:51:31.480 my brain wasn't working well and I couldn't think through all these combinations and so on is go,
00:51:35.000 well, I'll just go with my gut.
00:51:37.080 And after 15 years of playing, my gut was fairly reliable.
00:51:41.640 But certainly for the first 5-10 years of playing, my gut was not very good.
00:51:46.340 And so that would be, I would often use my intuition as an excuse to just not do the boring number crunching.
00:51:54.140 And again, people, I've noticed that's a trend that a lot, that seems to be widespread in the world.
00:52:00.500 You know, you look at these memes online, if you search for, like, intuition, everything,
00:52:05.740 the internet says, oh, trust your intuition 100% of the time.
00:52:08.220 It's always right.
00:52:08.980 And it's like, that's just bullshit.
00:52:10.100 You know, after even 15 years of playing poker and thinking I have great intuitions,
00:52:14.520 I would still have an error rate.
00:52:16.040 I'd be so sure that someone was bluffing me.
00:52:18.200 And then it turns out that actually they had a really good hand.
00:52:20.340 But my gut was, like, screaming, no, cool, cool.
00:52:23.020 And it was wrong.
00:52:24.160 So that's the other one.
00:52:25.800 Be careful of, like, over-relying on intuition and instinct in situations where really you just need to do the, like,
00:52:33.040 the boring number crunching.
00:52:34.360 And it's such a powerful message because so many people make decisions that are emotional,
00:52:38.980 not based in rationality.
00:52:40.400 And then it turns out that they're terrible decisions because you're not making an objective choice.
00:52:46.760 Because you're letting your emotions hijack your decision-making process.
00:52:51.820 Yeah.
00:52:52.160 And the reason, you know, if you're just doing stuff purely on instinct all the time,
00:52:55.740 you can't go in and then scrutinize what your thought process was.
00:52:59.800 At least if it's, like, you're doing something, like, logically, you can, like, look back at it and go,
00:53:03.480 okay, that's probably where my bias and my emotion clouded this bit.
00:53:06.580 But when it's, like, pure intuition stuff, it's a black box.
00:53:11.440 You don't know what's going on in there.
00:53:12.700 And they're still vulnerable to emotional bias and that kind of stuff.
00:53:17.640 So, yeah, it's, I don't know.
00:53:20.640 I wish I had, like, a clean answer to, like, how you do it.
00:53:23.340 It was a clean answer.
00:53:23.600 It was.
00:53:24.260 I'm curious, is it possible to control your own tells?
00:53:29.800 Is that something poker players work on?
00:53:32.640 You do.
00:53:35.200 I mean, again, like, I should caveat this.
00:53:36.980 I haven't, I quit poker, like, four years ago, you know, properly now.
00:53:40.540 I'm not sure what the, like, latest strategies people are doing.
00:53:45.580 You definitely, like, I would practice.
00:53:48.620 It's not like I would sit in front of the mirror or anything like that.
00:53:50.640 Because I would watch videos of myself.
00:53:52.840 Like, you know, if I played a final table, I would then go back and watch it afterwards if it was televised to see,
00:53:57.220 oh, okay, so this is how I was behaving there.
00:53:58.880 Good to know.
00:53:59.740 I'm gulping a lot.
00:54:00.760 And I'm clearly, you know, when I was running a huge bluff.
00:54:05.160 But, you know, a good poker face is basically something that's just, it doesn't have to be a deadpan.
00:54:14.440 It's just something that is natural to you.
00:54:17.580 Some people are naturally very animated.
00:54:19.260 So you just want to train yourself.
00:54:21.740 Basically, it's through exposure therapy of being in, like, these stressful high-stakes situations.
00:54:25.360 The more you're in them, the less you're going to have the flight or fight response.
00:54:29.700 So that's really the training you can do.
00:54:32.180 You know, you can't train your poker face if you're, like, for a huge final table until you've actually just been there and done it and felt how it felt and dealt with all the physiological annoyances that your body throws at you.
00:54:44.780 I remember the first time I did Question Time, I was completely calm on my way there.
00:54:51.600 The drive Francis came with me.
00:54:53.220 Completely calm when we got there.
00:54:54.760 Completely calm as we did the warm-up.
00:54:56.880 And then when it came to the actual show, I suddenly couldn't move my body for, like, five minutes.
00:55:01.300 I could just do this.
00:55:02.320 And the rest of my body was just, like, rigidly stuck in one place.
00:55:07.240 But then as the show went on, I relaxed into it.
00:55:09.780 But it's amazing how, like, it just flips.
00:55:13.860 And it's not something that you truly control.
00:55:16.800 Second time you do it, you are actually relaxed.
00:55:19.480 Yeah.
00:55:19.660 I still, you know, I do a lot of public speaking these days and I still get, like, incredible straight fright each time.
00:55:29.160 I did just for the first time try beta blockers, you know, which are, like, they're meant to help just, like, slow down the heart rate and so on.
00:55:36.200 Just, like, to help with the physiological symptoms and they did actually really help.
00:55:39.400 So I kind of wish I'd discovered these long ago when I was playing poker.
00:55:43.800 But, yeah, it's, I don't know.
00:55:46.620 So I think some people's bodies, there's a lot of variation between people as well.
00:55:52.660 You know, practice obviously helps.
00:55:54.800 But a big thing I learned is just, like, I learned to accept that I'm just always going to have a high heart rate when I'm stressed.
00:56:01.740 And that's just how my body responds.
00:56:04.280 I, having long hair would actually help in poker.
00:56:06.620 I would do this a lot to just try and hide it.
00:56:10.260 But, yeah, just, it's kind of get comfortable with the fact that you are going to be stressed sometimes.
00:56:15.680 And there's just, like, the worst thing you can do is being stressed about being stressed, right?
00:56:20.080 Yeah, it's practicing acceptance.
00:56:22.620 I think that's the most important thing.
00:56:24.500 When you are in a situation and you feel stressed, you go, okay, why am I feeling stressed?
00:56:30.660 And most of the time, it's because you're catastrophizing.
00:56:35.420 And actually, once you analyze it and you take a step back and go, this is just an emotion, that's all it is.
00:56:40.760 And that's a really, well, it's certainly with me, that's a really good way I've found to deal with that.
00:56:46.180 That realizing that you're not your emotions, you know?
00:56:48.820 This is just a thing that is temperate.
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00:57:17.560 What's the biggest amount of money you won in a tournament?
00:57:25.640 It was that European Poker Tour.
00:57:27.820 Yeah, it was 1.25 million euros.
00:57:30.480 That's incredible.
00:57:31.420 It was a good week.
00:57:32.840 It was a good week.
00:57:33.520 I was 25.
00:57:34.480 You were 25?
00:57:35.500 25.
00:57:36.400 Thank God you weren't a 25-year-old man.
00:57:38.760 Yeah.
00:57:39.700 I was much better.
00:57:42.380 What did you do with it?
00:57:43.740 No, I was actually pretty reasonable.
00:57:45.980 I bought a flat in London and then put a bunch of it back into poker.
00:57:54.380 As I said, probably a bunch of it into that six months after where I wasn't playing very well.
00:57:57.940 Did you think like, this is the beginning, this is it now, I'm going to be winning like this every few months or every week or whatever?
00:58:04.840 I thought I was God's gift.
00:58:06.480 I mean, so would anyone, really.
00:58:09.320 I mean, to be fair to you, if I was 25 years old and I won a poker tournament where I won 1.25 million euros...
00:58:17.020 You'd be dead.
00:58:17.860 Oh, yeah.
00:58:18.480 And before my inevitable death, I would be a raging dickhead.
00:58:22.740 Yeah, I mean, I didn't do anything too nuts in terms of lavish spending.
00:58:33.840 I mean, I just, it was more just like, so after winning that, the British press, speaking of tabloids, got hold of it.
00:58:42.020 Daily Mail turned up at my parents' house.
00:58:44.120 My mum didn't know, so she let them in.
00:58:45.740 They were taking photos of my childhood pictures.
00:58:48.260 They're all on there now.
00:58:50.680 Yeah, I was on the front page of like a bunch of tabloids that week because it was, you know, there was some angle there.
00:58:57.500 I don't know quite what their angle was.
00:58:58.720 I guess it was just like I was a young, cutish girl who had an interesting story.
00:59:03.520 And that was, I mean, it was the highest high that week.
00:59:08.520 Talk about dopamine spikes.
00:59:09.740 My God.
00:59:10.560 And then it like, once it all sort of settled down, I think I probably had like a big crash as well.
00:59:14.200 And I remember wanting that, having that taste of fame.
00:59:19.860 That was definitely a thing that like, there was a part of my brain I wanted to get back to.
00:59:23.720 It was like, okay, well, I need the next win so I can keep that going.
00:59:25.980 And then when it didn't come as easily, that was interesting to adjust to.
00:59:32.500 And why did you stop?
00:59:35.280 In the end, combination of things.
00:59:38.660 A, the game has gotten so much harder.
00:59:40.960 Really?
00:59:41.260 So much harder.
00:59:42.520 Yeah.
00:59:42.720 Well, again, so AI, big part of that.
00:59:47.300 Like online poker is basically done for high stakes money.
00:59:50.660 You can play low stakes or whatever and that's fine.
00:59:53.000 But because you can now have an AI that is playing effectively in real time,
01:00:00.260 that's far better than anyone else.
01:00:02.480 It's just, there's incentive for people to cheat and use them.
01:00:06.640 And so there's that.
01:00:08.000 And then also the average player is just so much better than they used to be because all this like strategy information has been very democratized.
01:00:16.820 You know, these tools are very easy for anyone to work with now.
01:00:19.140 So the average Joe is just much better at poker.
01:00:23.600 And then thirdly, I just kind of got bored of it as well.
01:00:26.320 I've been doing it for a long time and felt, you know, various forms of itchy feet.
01:00:31.980 Also, it's like, you know, the ultimate zero sum game by definition.
01:00:36.440 And I wanted, I felt like I should probably do something else than just that for the rest of my life.
01:00:43.160 It's a little bit more positive sum, a bit more win-win.
01:00:46.300 And plus, you got a taste of the sort of the celebrity and now you make content.
01:00:51.740 Now I'm one of those people.
01:00:54.900 I try and justify it to myself that I'm doing, you know, I really, really believe in the content I'm making.
01:01:01.260 Let's put it that way.
01:01:01.920 Yeah, perfect.
01:01:03.840 That's a good reason to make content.
01:01:05.560 Explaining these concepts of like shitty game theory, you know, the like competition gone wrong in society and like trying to think of like get more people thinking about it to like hopefully we'll then hive mind a solution to this.
01:01:20.620 Definitely feels like my calling.
01:01:24.740 I hate that phrase, but.
01:01:27.140 Why do you hate that phrase?
01:01:28.060 I don't know.
01:01:28.480 It feels.
01:01:29.060 Because you're British.
01:01:30.040 Yeah.
01:01:30.360 Yeah, because here everyone's like, it's my mission.
01:01:32.580 Right.
01:01:33.900 And I'm so blessed.
01:01:35.840 I can hear my mum, stop boasting, stop bragging.
01:01:39.880 But no, I really, really believe in finding ways to defeat Moloch.
01:01:45.360 And I think this is my best way of doing that.
01:01:49.700 I seem to be good at making these little films about it.
01:01:52.000 And I've, not to pimp my podcast too much, I just launched this podcast called Win Win,
01:01:55.740 which is about finding win-wins in seemingly win-lose situations.
01:02:00.340 Yeah.
01:02:00.580 And I'm so excited to see the type of guests.
01:02:02.580 I saw the announcement and instantly retweeted it because it's going to be great.
01:02:06.460 On that happy note, before we go to locals where we ask you some of the questions from our supporters,
01:02:11.140 the last question we always end with is what's the one thing we're not talking about as a society that we really should be?
01:02:18.920 The one thing we are not talking about enough is whether you want to call it Moloch,
01:02:25.200 whether you want to call it coordination problems, multipolar traps, inadequate national equilibrium,
01:02:29.480 whatever word means the most to you, these forces of short-term incentives that are misaligned with what the world actually needs
01:02:41.000 and are creating these race-to-the-bottom spirals within industries or within little sections.
01:02:46.160 We aren't talking about the meta-level stuff, the actual fundamental structures of these systems sufficiently.
01:02:55.540 Everyone's just too busy pointing fingers going, you did that and therefore you're bad.
01:03:00.460 And it's like, let's focus more on the, you know, it's like basically don't hate the players, hate the game.
01:03:05.740 And how do we fix the game?
01:03:08.620 That's what we're not talking about enough.
01:03:11.760 Livbury, thanks for coming on.
01:03:13.600 Thank you.
01:03:14.120 Head on over to Locals where we continue the conversation with your questions.
01:03:18.720 Why do you think women are so bad at poker?
01:03:20.760 I mean, I think it's a joke, but serious question.
01:03:23.100 Women do underperform in every available metric.
01:03:25.820 I'd like to know what you think are a mix of factors that are responsible for this.
01:03:28.620 We'll see you next time.
01:03:58.620 Get tickets at Mirvish.com.