Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas - 6 | Liv Boeree on Poker, Aliens, and Thinking in Probabilities
Episode Date: July 23, 2018Poker, like life, is a game of incomplete information. To do well in such a game, we have to think in terms of probabilities, unpredictable strategies, and Bayesian inference. These are ideas that pla...y a central role in physics and rationality as well as in poker, which makes Liv Boeree such a great person to talk about them. Liv is a professional poker player who studied physics as a university student, and maintains an active interest in science generally and astrophysics in particular. We talk about poker, probability, the likelihood that aliens exist elsewhere in the universe, and how to be rational when it comes to charitable giving. [smart_track_player url="http://traffic.libsyn.com/seancarroll/liv-boeree.mp3" social_gplus="false" social_linkedin="true" social_email="true" hashtag="mindscapepodcast" ] Liv Boeree earned a First Class Honours degree in Physics from the University of Manchester, before becoming a professional poker player. She has won well over $3 million on the poker circuit, including taking First Place at the 2010 European Poker Tour Main Event in San Remo, Italy. She is the co-founder of the charity organization Raising for Effective Giving, which has raised millions of dollars (largely from fellow poker players) for good causes. Home page Wikipedia page TEDx talk on probabilities Vox article on the Fermi paradox Raising for Effective Giving Twitter Download Episode
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Hello everyone and welcome to the Mindscape podcast.
I'm your host, Sean Carroll.
Before jumping into today's episode, let me just talk about some meta-commentary, the state of the podcast.
As we all know, this is a new project for me.
We're all learning what's going on.
I'm having fun.
I hope that you're having fun.
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recommending it to your friends, iTunes reviews, or make me just as happy as any other podcaster.
Some of you might know that Libson, the host that I use for the actual podcast episodes,
has an automatic thing. Well, they will put the podcast on YouTube. It's just a still image.
It's not really a video. It's just the Minescape banner logo there, but the audio is the same
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discuss further. The YouTube comments have been awesome, but a more centralized place to go is
on Reddit where people are talking about these things. So I think that's all that I wanted to say
for the commentary stuff. So let's get into today's episode. The theme of which is that we don't know
everything as we go through life, but we still have to make choices. We still have to act
in the world somehow, but we live in a situation of incomplete information. We don't know what's
going to happen in the future. We also don't even know everything about the world right now.
So what we do is we attach probabilities to things. We say there's a certain chance that's a
something's going to happen. A credence is how much weight we put on one possibility versus another,
and then we act accordingly. Formalizing this idea of placing probabilities on things and then
acting accordingly is called betting. And nowhere is the idea of betting made more explicit and
formalized than in the game of poker. Poker is one of my favorite games. It's a game of skill that
has luck involved because you don't know what the other players have, but you can make choices. And some
of those choices you can win. There are people who make money over the long term very regularly
playing poker. Those are called professional poker players. They really exist. There's no professional
slot machine players because there you're just losing money overall. But poker is a game of
skill. And today's guest, Liv Boree, is a perfect person to talk to about this stuff. Live was a physics
major as an undergraduate at the University of Manchester. And she was quite good at that, but she
decided instead to add a little spice of excitement to her life by becoming a professional
poker player. And she's done pretty well. I can't say it was a bad choice. She's made almost
$4 million in winnings at the poker table. And so we're going to talk about what you learn
from being a poker player, what that helps you do in terms of your everyday life, making choices
about one thing to do or another in conditions of incomplete information, where probabilities are
Central. Liv is also still remains interested in science and is developing TV projects to help
popularize science. She also has become interested in altruism and charitable giving within the
umbrella of effective altruism, trying to use empirical data to maximize our impact as charitable
givers. She's the co-founder of an organization called Raising for Effective Giving,
which funnels money to organizations that have shown that they really have gotten good
bang for their buck in terms of the charitable dollars.
So we're going to talk about poker, we're going to about altruism.
We're also going to talk about how to think about the existence of aliens.
Whether or not aliens exist out there in the world turns out to be something that's
at the intersection of science and also probability.
How do you reason about something like that when you have so little data?
So let's go.
Libri, welcome to the Mindscape podcast.
Thank you very much.
So now you were trained, at least undergraduate education.
as a physicist, astrophysicist.
Now you are a professional poker player.
Correct.
So just to set the stage, I think for a lot of people, if you say professional poker player,
they know exactly what that means.
I bet a lot of people in the audience are unclear that there are such a thing as professional
poker players.
Is that even legal?
Are you like in downstairs?
Is it like rounders?
Are you getting in trouble?
What is the situation?
What is your lifestyle like?
How does this work being a professional poker player?
So it depends obviously from person to person.
There are different types of professional poker players,
but I for the most part play a type of poker called tournament poker
where everyone puts up an equal amount of money
and in exchange for that you'll get a certain amount of chips
and basically everyone keeps playing until someone,
until everyone else is knocked out and one person has all the chips
and wins either all the money or certain sort of distribution of the prize ball.
capitalism. Exactly. Yes. A very, very aggressive, zero-sum form of capitalism. And, yeah, so I got into it
in a very random way. As you said, I studied physics. I fully intended to carry on in physics.
I loved it. But at the same time, I had been in education. I was 21. I also had ambitions
of being a rock star. I was very into heavy metal and disturbing my neighbors late at night, playing
guitar. And so I was like, you know what, I'm going to take the summer off after my graduation
and start, I need to make some money somehow. So I'm going to apply for TV game shows,
because I felt like that made, as a contestant. As a contestant, I'm always like playing games.
Long story short, I learned how, I learned to play poker on one of these game shows, and I
love the game. And I was like, you know what? I think I want to take a few years and throw myself
into this game. I think I have an aptitude for it. It seems like a lot of fun. I want to travel the
world and get some life experience. Still in the back of my
mind saying, I'll come back to, I'll come back to physics.
Right. Once we've made our pile,
we can, go think about the universe.
Pay back my student debt, etc.
And now, 10 years later,
still here.
The debt has long since been refuted.
Yeah, exactly.
Well, things just turned out pretty well in the poker sense.
And yeah, so like in terms of sort of lifestyle,
it's a lot of, for me, at least traveling to different tournaments.
So, like, there's a big stop in Barcelona every August.
or there's a big stop in Vegas, which I've just come from, the World Series.
And you'll sort of travel around to these, you know, it's not the pro tour because anyone can play them.
Right.
But the professionals tend to like, that's their lifestyle going from event to event and playing in these tours.
So literally anyone listening right now, as long as they have the right amount of money, can show up, they have the tournament, say, here I am.
And want to play.
It's not like a golf tournament or basketball.
You know, anyone is welcome.
And it's a meritocracy once you're there.
Exactly.
Yeah.
So anyone can play.
It doesn't mean you necessarily should play.
but if you want to and you have the money and the desire,
then you absolutely can.
And I mean,
I think that's what sort of obviously separates poker a little bit
from something like golf,
because golf is, you know,
the results of a golfer are very closely correlated to their skill level.
Whereas with poker,
particularly over like a small sample size of maybe 10,
even 100 tournaments,
the worst players could be vastly outperforming the best players.
And so to say,
oh, well, we're only going to let in the,
the people who've had the best results over the last six months.
That's stupid.
And people would just get very annoyed with it because, A, first of all, everyone thinks they're the best.
That's why poker exists.
But B, it wouldn't actually be correlated to necessarily being the best players getting in.
And C, the ones who are good would like the money from the people who are not good to be in the tournament.
Yeah.
Yeah, it's this constant battle between, well, I want to be playing against the best.
I want to say I'm the best.
But at the same time, I don't want to scare people off.
And so, yeah, you need a.
the weaker players you want to be playing against in an ideal world.
But it is a game of, it's a combination of luck and skill, right?
I mean, like everything in life.
But it's not just luck.
There's a certain element of randomness.
You're dealt the cards, but then you play them in a certain way.
So it's not like playing blackjack or craps where there's really no way to win
without some kind of cheating.
Yeah, exactly.
I mean, with those games, yeah, the casino, you know, it's built its big golden halls
and amazing rooms and specials.
because they have this small edge that over time they make money from.
And the longer you play, unless you know how to count cards,
which again the casinos will kick you out for doing,
you can't make money playing blackjack and roulette.
Whereas poker, because you're playing against other people,
and the casino host it basically because I think casinos don't really want to host poker.
They're not really making great money from it, basically,
just like a small percentage of each pot.
But yeah, with poker, you're playing against other people.
if you are consistently making better decisions than your opponents, then you are going to be making
a profit in the long run.
I do get the feeling, though, that the casinos enjoy having poker players around.
Some of them are very good at playing poker, but then are perfectly willing to go blow it
at the Baccarat table, right?
That's a very, very correct observation, yeah.
I mean, I've known many, many poker players who were some of the best in the world and yet
had no money to their name because they were the worst in the world at walking past the roulette
table.
It's just another game, just walking past it.
Yeah.
Who's the best at walking past it?
And they know that they should lose on average.
Yeah, but they just love it.
Like that's, you know, it's, yeah.
I mean, there's, I think to be a good poker player,
you have to obviously have a willingness to,
you cannot be a risk of us human.
Like you have to be willing to gamble,
to take risks to have those like heart in the throat moments.
But at the same time,
you need to be able to do that in an intelligent,
moderated way.
And some, certainly not the best players you see around now.
Most of them actually don't have what we call sort of the degenerate gambler streak in them as much.
But there are still some who do struggle with it.
And it's quite a tragedy to see someone who's like worked so hard at being so good at one particular game.
Right.
But then have this sort of life, we call it a life leak, a leak in the bottom of their pocket.
Yeah.
Which is some other form of gambling.
But, I mean, it makes for great stories, though.
It does.
And it's, it also contributes to this.
that the game has of being slightly
disreputable, right? No matter how
much money and TV exposure
and everything, and you still, to this day,
do, as you allude to, hear stories
of some of the world's best players just disappearing.
Like, they're hiding.
Right.
They come back, oh, they just lost $5 million over the weekend.
And it therefore must be a very different kind of
lifestyle than maybe you thought you were signing up for
when you went to university as an astrophysics major.
Yeah, I mean, like, I've seen it sort of
had some insights,
insights into like the world of, you know, the top chess players, for example.
And it is for the most part a very different sort of, um, social dynamic, because the best
chess players, like they really have to, I mean, they just study and study and study and study.
And I mean, they're, they're brilliant, obviously, at what they do.
But I don't know, like many, I think, but I think poker players have a little bit more of, um,
the wild, the sort of, not free spirit, but you know what I mean?
Like this, this wildness to them.
Right.
They, you know, there's this, these urges, I guess, that they want to fulfill.
They get thrills for many other things as well, whereas chess players tend to, you know,
they have to be so laser focused on what they do.
Sorry, but also, but sorry, but just continue exactly in that line.
The thing that you're doing when you're playing poker is fundamentally different than the
thing that you're doing when you're playing chess.
When you're playing chess, both players see the board.
Right.
100%.
When you're playing poker, you don't know.
what the other person's cards are.
And so they put out a big bet.
They go, all right, here it is.
This is all your stack.
This is for your tournament life.
You have a pretty good hand, but not the metaphysically perfect hand.
And you need to, I mean, ideally say, well, there's a certain chance that they're bluffing.
There's a certain chance that they're not.
And I'm just going to risk it.
Yeah, exactly.
I mean, like with chess, you have all the information out there.
There is no hidden information.
I mean, sure, you can't directly see into the other person's brain to see what specific strategies.
But you usually have a pretty good idea and there's not like a very definite bits of information that you don't have.
Whereas poker, yeah, it's incomplete.
And so that's why you have to think probabilistically.
And yeah, so then it becomes sort of this, I mean, largely a science of being able to quantify these uncertainties that you have.
Like, okay, well, what is the range of hands that they could conceive of be playing here?
okay it's from pocket twos to um
ace king or something like that and and what also what is the
but then I have the piece of information that they they bet this particular card but not this one
and they bet this size and and then on top of that there's there's the even harder to quantify
things like oh the pulse in their neck seems to be going really really strongly here when I
wouldn't expect it to this is inconsistent with the story they're telling with the with their
chips so you know how what do I do with that like
and so it's this
there's all these like little bits of
variables of information of some of
which are you're extremely
confident about and others you're really not
and you've got to sort of
evaluate all of these somehow
and put them together to come out to one
one answer that is most likely
to be the correct decision
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I don't know.
You know Ed Witten, the physicist?
Who?
Ed Witten, the famous string theorist.
I've heard of, yes.
Yeah, he is, you know, he would probably win the poll of U.S.
most theoretical physicists in the world today,
who's the smartest theoretical physicists.
Oh, really?
Yeah.
He doesn't like poker because he says, like,
I don't know what the other person has.
Like in chess, I could outthink everybody,
but in poker, you have to make up these...
Like heuristics, basically.
Heuristics, models, right, of the opponent.
And, of course, the counter to that
would be that John von Neumann helped invent game theory
because he wanted to become a better poker player, literally, right?
He was playing poker.
I'm surprised Ed Whitten and it doesn't like it so much
because, I mean, it's still ultimately a mathematical game.
It is.
But there's also psychology, so I'm sure one of the classic questions you're asked is what is the balance of doing math versus doing psychology when you're literally at the table?
So the answer to that is it entirely depends.
But to throw, I hate throwing probabilities out there when it really does wildly depend.
I would say like 90%.
And so if, say, for example, I wanted to make you into the very best poker player in the world.
I would want to sit with you and make sure that you have,
like, put 90% of our effort into making sure that you understand the game theory.
The math, right, yeah.
The math, the actual, like, the building blocks of the game,
so that your strategies are built upon that,
because it's ultimately a mathematical game.
Then on top of that, if I can teach you some of the, like,
the psychology and the harder to quantify parts, you know, these, like, sort of, I guess,
build your,
intuitions up so that you are able to sort of intuit from people's behaviors what they're thinking.
But that's just more really just a matter of experience, I think, ultimately. Some people are
more inclined, you know, are just better at reading people than others naturally, but I still think
it's ultimately a learnable skill. And again, some of the best poker players still find ways to
almost like quantify their uncertainty about these like very psychological human characteristics.
You'll know what they're correct.
You know I should be calling 40% of the time
according to game theory.
And then I have a piece of evidence
that suggests that actually the opponent's bluffing
very far more rarely than that.
Well, how confident am I in that?
And then I might waver the needle
to say so I'm down to 35% I'll call instead.
But it's still something that you can quantify.
Yeah, I once went to a movie premiere
with a bunch of people and one of the people
was Phil Locke, the poker player,
the famous poker player.
He calls himself a time.
scientist. A time scientist? I did not know that. We didn't talk about that, but we're like chit-chatting
a whole bunch of us in the lobby before the movie starts, and Phil suddenly says, there's an 83% chance
that I'm going to have to pee before the movie ends, so I should go to the bathroom right now.
And I didn't know whether or not that sort of silly precision of 83% was a joke, or whether he's
just that good at estimating things like that. Knowing Phil, he is pretty good. He does like to think in
terms of probabilities, but that degree of granularity over-desimated. He's just having fun.
Yeah. Yeah. So obviously there's math in the sense of, okay, I need a heart to come down.
I only have one card. There's some elementary math. What is the percentage chance a heart will come down.
Right. But there's also higher level math. In particular, the game theory situation with sort of optimal
strategies and dominant strategies and exploitative strategies. Do you study that as part of your
education training as a professional poker player? Yeah. Ideally, you, you,
you want to sort of familiarize yourself with,
so, I mean, well, you're lucky in this day and age,
there's, there are these solvers out there that you can basically
will run Monte Carlo simulations in different,
you can go, okay, what should I do with Jack 9 suited
on a 10, 7,4, one suit board, you know, of the same suit.
And, you know, similar scenarios like that.
put them into the solver, let it run for a few hours,
and it'll show you what the game theory optimal strategies
with the range of hands that you conceivably have in that situation would be.
So there would usually be like a percentage of those hands
that you would want to check raise because they're really good, for example,
because they have a lot of equity,
but there's a percentage that you would want to check cool
because they're kind of in the middle of the road.
And then there's a percentage that you would then want to bluff
because you need to balance out your range.
You can't just check raise.
with the strongest hands,
you need to have some bluffs in there
so that you can get called.
You need to have the appearance
of having a balanced range of hands,
bluffs and weak hands,
when you make an aggressive action.
And so anyway, you can literally find out
what is the, you know,
as mathematically close
to the perfect game theory optimal solution is now
in these different scenarios.
And so the very best players
will sit and work with these solvers.
You can't use them in real time,
but you can go away
and just study for hours.
and sort of try to basically build a mental model that emulates these game theory optimal solutions.
And then once you have this mental model of game theory optimal,
then you can go out there and play using this style as a sort of as a base.
But then you would then deviate from it as when you come across an opponent who is playing not in a game theory optimal style.
Because a good way to think about it is like if you and I were to play rock paper scissors and you don't know anything about me,
what would you be the strategy, the best strategy that you would employ?
I believe the best strategy is randomly do, one-third, one-third, one-third.
Exactly, yeah, exactly.
You want to perfectly randomize because you don't have any information about me.
So in response to that, the best case that I can do is to also randomize perfectly.
Because if I don't do anything other than that, you're going to be exploiting,
you'll be taking advantage of me.
So that's like an Nash equilibrium, basically.
Sorry, explain what that is for the people out there in,
podcast land. So a Nashick equilibrium is basically a state strategy where it's unprofitable for
either competitor or any competitor, it can be multiple competitors as well, like more than two,
to deviate from that strategy. If you deviate from it, you're only going to be losing
on average in the long run. So it's the equilibrium where everyone is doing as best they can.
As best they can and breaking even. In this situation, you're breaking even against each other.
Like if we both play...
Zero-some game for it.
Exactly, yes.
However, if you now notice that I start throwing rock, I know, every time.
Yeah.
Should you continue playing this preview?
I could have a better strategy.
Exactly.
You wouldn't want it, you'd be stupid to carry on just playing this perfect 33% randomized thing.
No, you'd want to start playing paper far more often or like 100%.
And so that is what you'd call then an exploit.
You exploit my bad play by deviating from the previous game theory optimal.
And so that same kind of thing applies in poker.
You'll be playing, you'll start off maybe ideally playing this game theory optimal strategy.
And if your opponent's equally good, they'll hopefully try and match that and you'll be in the long run breaking even against each other.
But because basically no human in the world can play perfectly game theory optimal, there are these rooms.
You want to see over the course of time, you'll observe what these mistakes are people are playing.
And so you'll deviate and start exploiting those.
I was highly amused to learn that there were competitive.
rock, paper, scissors, leagues.
I did not know that they exist.
They do, because people are not good at randomizing, right?
Right.
And in fact, this is a very educational moment for me also.
The New York Times had an app where you could go and play rock paper scissors against the app.
And basically, it had trained as an AI sort of thing, on millions of real life human being
rock paper scissors players and realized what the tendencies were.
what the deviations from randomness were,
and it would beat you.
And I went in there...
With what kind of edge over...
It was small.
It was not large, but noticeable.
Like over 20 hands, you could definitely tell you.
You were losing.
Yeah, yeah, that was my experience.
But then what I realized,
like, so I went in there, cocky, I'm like,
I know how this is working.
I'm going to beat it, and it destroyed me.
So then I realized
there was something that I felt I should be doing.
Like, I played rock two times in a row.
I should play scissors or something.
something like that, right?
And I would tend to do that and I was losing.
You don't do these same thing in the row many times.
Yeah, that's right.
That's hard to do because you don't realize how many times those sequences come up randomly, right?
But what I realized was if I figured out what my impulse was and had the strategy that the New York Times app would
probably play a dominant strategy against my tendency, then I should play the one that would beat that.
And suddenly I kicked its ass.
I really did.
So it's just a matter of...
Over how many iterations, you know?
It's not the most exciting game in the world, right?
So, you know, dozens but not hundreds of iterations.
Let's put it that way.
I want to do that.
So we can find that.
But another thing that I, along these lines,
I remember the first time I learned about in the realm of Nash's equilibrium and game theory,
the fact that in games like this,
mixed strategies will generally be the dominant or the equivalent.
will there be an optimal strategies. In other words, there's no one action you should ever take every time in that situation. And it's perfectly obvious in rock, paper, scissors. It's also true in poker. If you have pocket aces in some position, the best possible strategy is not to do the same thing every time, no matter what you have. It's almost always true. And then, so you have to, if the strategy is to do one thing 90% of the time and something else 10% of the time, it's really hard to ever do that 10% thing. You know you're not doing the best thing. Right. Well, so what some of the, again, the
top players have started doing now because like everyone everyone knows that you need to be able to
basically be a perfect randomizer machine to have these not only sort of to remember what the these
ratios you need to have you know in certain situations where you want to be bluffing with say
10% of your hands and and and betting for value with 90% how do you randomize that well people have
started looking like watches like yours you've taken it off but with the second hand right old analog
watches have become popular again. Why? Because it's a really good randomizer. If you're, if you go,
okay, you just use where the second hand is on the clock face. Okay, if it's between zero and if,
if you know you want to check raise 25% of the time, is it between zero and 15? Oh, yes it is. Okay,
this is a check raise situation. If it's not, okay, I check call. Do you do that? Um,
not as much as I should. I've done it, I've done it a few times. Um, but A, I always forget
my watch. And other players do it by actually just like shuffling their chips all the time.
Because usually the chip will have, you know, the word written on it and just where it lands.
Yeah, that's a way. And even if you're, this is a thing, people think, oh, you need to then
keep it secret that you're doing this. No. Even if your opponent knows, they just go, oh, shit.
The optimal strategy. They're playing GTO against me. Okay. I need to, it's just an unsettling
thing to know, basically. Yeah. But part of me thinks that it's less important to actually to
actually play the game theoretical optimal strategy than to make your opponent think you're playing it,
right? Because they're not perfect optimizers or randomizers either. So if you're supposed to do something
two-thirds of the time and something else one-third of the time and your randomizer makes you do the
one-third of the time thing three times in a row, then I would definitely do the other thing,
no matter what the randomizer told me the next time, because I'm not actually, my opponent is
not building the correct model of me. That is true to an extent, yes. Um,
But at the same time, if your opponent is also then playing this perfectly sort of, you know, randomized in the right way style, their style will not be losing out to the, because they're playing this, this unexploitable style, then arguably you're going to still be playing less, less perfectly than they are.
And so in the long run, again, it's always down, you know, in the long run, you'll still be playing a less profitable style than them.
Or sorry, a more exploitable style than them.
But when it comes to poker at a table with six or ten people,
we don't know the game theoretical optimal.
No. Pocair has not been solved.
In fact, as far as like, no, artificial intelligence cannot win at a 10-hand,
10-player table against top player.
There's been the AI that successfully beat humans' heads up one-on-one.
One-on-one, yeah.
But I don't even know if anyone's trying to do the three-person and higher game,
because, I mean, the game tree just gets ridiculous, the decision tree.
And yet we poor humans do it.
Exactly. Yeah, we're really, really good at building these sort of heuristics.
These, I don't know why we're so good at it, but we're able to sort of condense this down into these rules of thumb that work out really well.
I mean, I think it kind of makes sense. That is what we're good at, right?
Thinking fast and slow, Daniel Kahneman would explain, you know, we don't think in terms of rational, logical choices generally.
We think in terms of heuristics. We think in terms of rules of thumb.
we're really good at coming up with models of the world that are pretty good.
Yes, good approximations that get us by.
Yeah.
Yeah.
I mean, do you use Bayesian analysis or something like that very much?
Why don't we explain what Bayesian analysis is?
Sure.
So Bayesian analysis is basically updating our model of the world based upon new information,
incorporating new evidence based on sort of the weight,
the strength of this evidence, whether it's proving or disproving our beliefs. And then,
you know, when we see, when we see that thing happen, we'll go, okay, well, this means I should
change my mind by this amount. It's like shifts the needle. You know, if you think, um, all,
all trees are green, all leaves are green. Um, you'll go around, but then if you see,
you'll go around assuming that, but then if you see a tree with purple leaves, well, now
that's evidence to suggest that's not so true. So you now shift towards, okay, maybe not all
trees are green, etc. And you, then you,
a way you can actually model that mathematically using Bayes theorem.
Do I do it mathematically in game?
Absolutely not.
I don't have likelihood ratios and so on in my head.
But no, I mean, ultimately our brains are Bayesian machines, right?
That's what we're doing naturally without really realizing it.
And, I mean, at least to me, it seems like it's a sort of fundamental law of,
not a physical law, but it is, you know, it's, would you call it a psychological law?
It is some kind of law of the world.
live in, right?
Basis theorem?
I mean, it's a math theorem.
It's the correct way to update your model of the world, I think.
Yeah, it seems like it.
It's a rational way to behave, right?
And so my impression is, this is my amateur poker player's way of thinking about it.
You can tell me what that makes sense.
You know, you sit down at the table and you more or less assume everyone is the same in some
way.
And then as you see how they play, your model of each individual player becomes more sophisticated.
Yes.
So we have ways in poker of sort of.
of describing that, right? There are tight players and loose players and aggressive players and so
forth. And maybe then you say, well, oh, this person is tight before the flop and then they
become loose afterward. And is that more or less what's going through your mind? Yeah, I mean,
not that I would ever advocate stereotyping people at all, but when you sit down at a poker
table, like I just played the World Series of Poker Main Event, for example, where it's generally
against a lot of amateur players who, you know, pony up their $10,000 once a year and it's,
you know, it's the best tournament of the year. It's really good.
it was profitable for you right yeah it worked out pretty well this time um and and so when you
first sit down i will immediately look around the table and create basically of of first impressions
of how someone looks you know literally their gender their age the way they're sitting in their
chair the clothes they're wearing the way they look at me you know their their appearance of confidence
or not confident um and so i'll immediately create a sort of some kind of
of stereotype.
A prior, a prior, exactly, a prior.
But then in an ideal world, I'll still just try and, you know, not let that influence
my play too much, just a little bit.
But as soon as you start getting real information, after like 20, 30 hands, well, now
I've seen, okay, this person hasn't played a single hand over 30 hands.
Did I think they were type beforehand?
Actually, yes.
And does the evidence continue to confirm that?
Yes, it does.
okay, so I can shift the needle a little bit more to strengthen that belief.
But if I notice actually the person who, you know, like the old guy who seemed kind of
conservative and timid has played every single hand and is raising and re-raising everyone,
okay.
Better update.
It's time to update.
This is very strong evidence.
Let's shift the needle more towards it.
He's an aggressive player.
And so, yeah, you'll sort of start building these models of people.
And then by the end of the day, if you've been at the same table, now you've got probably
multiple hundreds of hands
where you've seen
a lot of information of people's tendencies
with increasing degrees
of nuance and so you'll build up a very accurate mental
model of players over
a given period of time.
So do you take this way of thinking
mixed strategies, game theory, optimal
et cetera, basis theorem
and updating your priors, do you extend
it from poker to the rest of your life?
Has being a professional poker player changed
how you go about buying a house?
or getting a boyfriend or choosing where to go for dinner?
Yeah, I would say so.
In terms of just like thinking about things in terms of probabilities
and uncertainties.
You know, beforehand I was very black and white in my thinking.
It'll either happen or it won't.
You know, I certainly wasn't comfortable with any kind of granularity.
And now I'll sort of look at something and be like, okay, do I think,
am I going to make it in time for this podcast?
judging by the LA traffic,
it doesn't seem, yeah,
the probability has gone down
and I'll estimate at least mentally
and hopefully I'll try and communicate it to people as well
what I think the likelihood is
in terms of a percentage.
I'm 30% to be there on time.
That kind of thing.
And I mean, in terms of picking boyfriends,
well, yeah, I mean, Igor.
He picked a poker player, so what does that tell you?
It's hard when you're playing on the poker circuit
not to also have a significant other
who's sharing the same lifestyle.
But yeah, funny story.
Igor and I actually,
what Igor asked me now about half a year ago,
randomly, he's like,
what do you think the likelihood is
that we'll still be together in three years' time?
Because we were like talking about moving cities
and should be by a house.
And he said, well, what do you think the likelihood is
will actually be together in three years' time?
I was like, oh, good question.
Sorry, that's a question
that would only be asked by number one,
a poker player and number two,
someone who is pretty secure in the relationship already.
Yeah, well, yes. Well, yeah, that's a reasonable thing to assume. And luckily, our numbers came out fairly similarly. I think it was like 92 and 94% or something like that.
Excellent. Yeah. Because there's a non-linearity there. Like getting the wrong answer could change the probability.
Oh, absolutely. Yeah. There can be. But at the same time, it's really useful to know, even if you don't end up being honest with each other, the fact that it asks you to reflect on that.
Right.
and you come away and think, oh, actually the number's 60%,
but I found myself the word 90% coming out my mouth.
Well, if nothing else, that's information for yourself.
That's right.
Right?
Like, oh, there's something not quite right here.
Fortunately, like I did genuinely.
I was like, no, I think it's definitely over 90%.
It's definitely under 100%.
You know, stuff can still happen, therefore,
and luckily we were pretty much aligned.
Yeah, so it definitely, I found it has bled into my thinking in all sorts of ways.
And in general, you just
become more strategic.
I don't know.
I mean, I don't think that's a bad thing.
I know that people,
sometimes when people ask,
oh, what do you do?
And like, particularly if I'm in some kind of negotiation,
they're like, oh, you're a poker player.
Well, I don't believe anything you say.
And it's like, oh, come on.
Because I think poker is all about massive crazy bluffs, right?
Not about strategic thinking.
Exactly.
Yeah.
It's like, no, it's about choosing when to bluff,
to actually minimizing your risk when you bluff.
Like, I've found that, like,
bluffing is stressful.
Like, it can be very fun when you get away with it,
but it's really not fun when you get caught.
Oh, yeah.
And having, you know, when you,
poker players know what it's like to get your bluffs caught,
be caught in a lie.
It's, A, it's embarrassing,
and B, it actually just financially hurts
and it can knock your confidence and so on.
And so away from the table,
I don't, like, lying isn't really very fun.
Like, I get, I get to scratch that itch at the table.
And it just creates complications.
And unless there's really, really, really, really,
good reason for it. I tend to try and avoid it. And it is embarrassing, even at the poker table,
but it shouldn't be, right? I mean, you're just playing the game theoretical optimal strategy.
Yes. Why should I be sad about my bluff called? Yeah, no, that's definitely a thing. I try to,
you know, anyone I'm teaching poker, I say, like, the first time you get caught in a bluff,
turn those cards over and slam them down and have a big smile on your face and be proud of
yourself. That's very good advice. It's a big part of the game. And you have to get used to that sort of
getting your fingers caught in the cookie jar.
Because if you don't ever get caught,
then you're probably not doing it often enough.
So, yeah, there's so many, like, different facets of the game
that sort of bleed over into life.
I mean, just the emotional control part of it.
Poker, you learn to get used to bad luck very fast
because, I mean, you play 10,000 hands in a week.
You're going to have one percenters, you know,
where you should win the hand 99% of the time,
but you don't. You'll have multiple of those happen, and they really sting.
But probabilities they compound over time. And if there's many, many instances of bad luck
things that can happen, then eventually one of those will happen to you. And so if you sort
remember that, I find you get less emotionally attached. And it's less of a shock.
Yeah, I mean, what do you said about the granularity of probabilities, I think is very true. I mean,
I have this idea that almost everyone thinks there are only three probabilities for anything. It's
either zero percent, 100 percent or 50 percent.
You know nothing.
The idea of something being 70-30 is just really hard for human beings to latch on to.
And maybe this is those heuristics that we grew up with in the wild, in the Velt of Africa,
like you better make a decision right away under conditions of stress and you don't get
to do things over and over again.
So you would really say that your experience as a poker player has given you a better
ability to correctly handle those 70-30 situations.
Yeah, I think so.
I think you, you know, I mean, you're familiar with the term scope and sensitivity in terms of
you, humans, we evolved in sort of tribes of probably up to 150 or so people.
And so beyond that, numbers weren't that useful in terms of, we didn't have to count
much beyond that.
And, you know, the classic example of, oh, there's, there's, there's, there's,
a thousand birds dying in oil, dying from an oil spill somewhere, you'll feel some degree
of sadness about that. If I say there's a million birds dying from oil, you don't feel
a thousand times sadder. You feel probably a little bit sadder, but not a thousand times. And so
we have this, like, our brains aren't intuitively equipped to think accurately around really large
numbers or really, really small numbers. We just work on this sort of like little macroscopic level
that's in our everyday lives.
And so that, I would say that's really in realms of probabilities
that sorts us out between the sort of 30% and the 70%.
But beyond that, things just feel really,
oh, it happens 10% of the time.
Oh, that's a never.
Yeah, that's a never.
Oh, 85% time, pretty much always.
And I don't know, like, I think on the most part,
we don't have an intuitive understanding of what actually like a 5%
feels like or a 7% or a 10%.
but poker you play enough you will like I find my emotions genuinely correlate with like when I turn the cards up on the flop you know we get a big all in and I'm a I'm a 12% underdog so I'm yeah I've only got a 12% chance to win well I'm just not going to get excited I'm like okay I've lost I'm yeah and and or if I have a 1% chance of winning then my emotions are even less you know I just don't feel anything I mean I'm just annoyed that I got it in so bad and but if it's a coin flip my
heart will genuinely be racing because I'm like wow I will win this 50% of the time and who knows
what's going to happen and so yeah you you you sort of become well calibrated to what these actually
these these probabilities mean because we've just seen we've seen these situations so many times over
does that therefore apply to the everyday world I mean yeah like if I'm someone says oh you're
I don't know 10% to to make a flight I think or if I can figure out that I'm roughly
10% to make a flight, then I will be, you know, I would be extremely pleasantly surprised if I did
make it, whereas I think, but at the same time, I don't think I'm that well calibrated as I am
in poker. It's hard, yeah, it's hard. So just to change gears a little bit, I was pleased to see that
you had an article in Vox recently. You went back to your sort of astrophysics training, and, you
know, it was a story about the application of probabilities to interesting questions about the nature
of the universe. So why don't you fill us in on what?
that was.
Yeah.
So recently,
some of the researchers
at the Future of Humanity Institute
in Oxford
published a paper
on,
called dissolving the Fermi paradox,
which I imagine most viewers
know what the Fermi paradox is.
Let's not imagine that.
Let's tell them what it is.
Okay, Fermi is basically,
well, Enrico Fermi back in,
when was it, 1960-ish, 53?
50s.
Yeah, he...
He didn't live into the 60s.
He didn't.
very radioactive, yeah.
Bad.
But yeah, basically he, you know, he looked up, he was like, wait,
there seem to be billions, if not trillions of stars out there.
And we know that the universe is somewhere around 14 billion years old.
If there's so many possible sites for life, why are we not at least, you know,
we've been releasing radio waves now for, you know, a few decades, like relatively easily.
Surely we should be at least hearing or picking up trace signals from other worlds
or seeing aliens all the time.
Like the universe is so old.
There should,
it must be at least a few other thousand civilizations out there
that have got a big head start on us.
So where is everybody?
And so that's the like famous Fermi paradox.
Like the contradiction between the size and age of the universe
and the lack of observed alien life.
And so this paradox is seemingly only gotten stronger with time
as, you know,
we've become more space-faring.
And we've discovered more and more exoplanes.
planets and, you know, it seems like there are, you know, universes even sort of more,
more capable of hosting life than we imagined.
Certainly a lot of places out there where it could be.
Right.
And yet, and yet we've still seen nothing and we've been, you know, really looking hard.
And anyway, so this paper that they published uses the Drake equation, which was sort of this
equation that sort of is the best way we could try and estimate the number of.
of intelligent civilizations within the Milky Way.
And it does a novel form of analysis on it
that hadn't been really done before.
And the answers that sort of came out of the back of that
is that we are somewhere around 75%
to be the only intelligent civilization within the galaxy
and somewhere around a coin flip,
about 50-50,
to be the only intelligent civilization
in the entire observable universe,
which is pretty astonishing stuff.
Right.
counterintuitive to many people.
Extremely counterintuitive, agreed.
Also quite disappointing because I'd love there to be some aliens out there.
I mean, at least from curiosity standpoint.
But yeah, nonetheless, pretty groundbreaking claim.
And so the article was sort of discussing how they came to that claim,
what are the actual processes that they did, the methods of analysis.
But then I wanted to make a sort of larger point from that,
which is, okay, well, we don't know for certain that this.
is actually the case. But let's assume that it is based upon our current best state of knowledge.
It seems like we're, if nothing else, life is extremely, intelligent life is extremely rare in the
universe. What does that mean philosophically speaking? For us, if we really are the only
intelligent civilization out there and may well be for the rest of the universe's future, what does
that mean? You know, should we do anything with that information? Should we change any of the
behaviors that we're currently exhibiting and the trajectories that we seem to be putting ourselves
onto. And I think, yes, I think it speaks that we have a greater responsibility to not blow
ourselves up. I do want to get into that, but first I want to dig into this probability stuff,
because the Drake equation is something that has been, you know, batted around ad nauseum, right?
Like people not talking about the Drake equation. And so for the two of you out there in
podcast land who have not heard about it, the Drake equation is a way of estimating the number of
intelligent civilizations by saying, well, how many planets are there, times what's the fraction
of planets on which life develops, times what's the fraction on which the life becomes intelligent?
It's different ways of breaking it down. But as far as I can tell, there's quite two things in the new
paper that are kind of interesting. One is they take seriously the idea of rather than finding just
our best fit number for the fraction of times life comes into existence and then becomes
multicellular, they say, what's the uncertainty, or what is the probability distribution?
So taking those probabilities a bit more seriously.
And secondly, it is a matter of being good Bayesian and updating our priors, right?
I mean, they're not saying just based on the laws of physics were probably the only intelligent civilization in the galaxy.
They're saying based on the fact that we haven't seen it yet, right?
That in some sense, Fermi was right.
It would have been very, very easy to run into another civilization if they were out there.
We haven't seen them.
They don't seem to be out there.
And therefore, from that, we draw the conclusions.
that probably the simplest explanation is they're just not there.
Maybe it's just way more unlikely that intelligent civilizations exist and continue to exist
than we thought it might have been.
Right, exactly.
The fact that we haven't found any evidence of aliens is evidence unto itself
and should be incorporated into sort of the Bayesian model that we have of the situation.
Were they able to pinpoint one of the factors and say this is probably the tiny one?
in terms of which one has the...
The smallest probability, is it that life doesn't usually form?
Yeah, so the one that has the biggest number of range of uncertainty on it is a fraction of planets that develop life.
Okay. Which makes perfect sense. What do we know about that?
Exactly. Like, we still haven't really figured out how life started on Earth, the process of abigenesis is just really not well understood yet.
and so the difficulty that we've had with the Drake equation is that
we're sort of plugging in numbers like the rate of stellar genesis within
the number of stars that develop per year
that's an astronomical number we have a reasonably accurate number for that
exactly we have data for that but then something like the fraction of planets that
developed life it could literally be the uncertainties they have like 200 orders
magnitude of uncertainty.
Oh my goodness.
Yeah.
It's that, it's that much.
Yeah.
And the thing is, is that because like that's those, any number between that is actually
completely plausible by saying, oh, well, yeah, but let's ignore the fringe parts of it.
That's making a statement, that's making a claim of knowledge that we can't make.
You know, say, oh, well, it's probably somewhere in the middle.
No.
Like it's as, you know, the probability distribution is like fat-tailed all the way down.
And so to cut these off is, is, is.
is just doing bad math, basically.
Yeah, I'm glad the paper came out
because I've run into great resistance.
I've always felt basically this.
Like, we don't know how likely it is
that life's going to exist.
The other obvious bottleneck is multicellular life,
which, again, we don't know how that exists.
Maybe, I tend to think that once we get
multicellular life, intelligence is probably not far behind.
Yes.
But both the existence of life itself
and multicellularity seem like very mysterious.
maybe the chances are just 10 to the minus 100, right?
And people say, there are so many planets out there.
And there's no number n such that I cannot find another number that multiplies it and gives us a small number.
Tiny, tiny, tiny number, exactly.
Yeah.
I mean, it's sort of the idea of like this great filter where there's some kind of insurmountable barrier that exists somewhere in the chain of evolution that for whatever reason most planets can't get past.
And for some reason, Earth managed to get past it.
Like, I hate to even, like, hazard a guess at where it is, but, like, intuitively, you know,
the intuition is really applied to this.
It feels to me that it's somewhere in the step from singular, sorry, prokaryotic to eukaryotic life, somewhere around there.
But, again, that's just my...
That's true.
So not just multilularity, but just the idea of having a nucleus.
Exactly.
Having a nucleus within a cell.
That seems to be...
Yeah.
Somewhere around that.
And there's some other work that Future of Manity Institute are doing right now on the similar analysis,
but looking at the transitionary time, the rates it takes to go from each step to each step.
And it just seems quite likely that the reason why the Earth, the reason why life isn't everywhere is because it just takes such a long time for it to actually get to the stage where intelligent civilizations then actually spring up.
Right.
We made it on Earth 5, 6th of the way through of Earth's lifespan.
In about 750 million years.
Life came into being relatively quickly.
Right.
But then it sat around in this boring...
Nothing state for ages and ages.
And then suddenly, there was this explosion where evolution got, you know,
kickstarted faster and things, interesting things started appearing.
But that wasn't basically until 5, 6th of the way through of Earth's lifespan.
Had it just been a little bit longer, we would not have existed.
because Earth would have been gobbled up by the sun.
And so that's a reasonably plausible explanation
as to why life is incredibly rare.
I suspect that's the right explanation.
My other favorite one is that there are plenty of civilizations.
They all become highly advanced.
They upload their consciousness into computers
and then they become bored and they don't go space traveling anymore.
Yes, that's a good one.
Also the Ace Divation hypothesis.
Do you know that one?
I don't know that one.
You'll be better to explain the exact.
reason why. But because computation is expensive in higher temperatures, and you would expect a
rational civilization that would want to maximize the number of computations it can do over time.
So it would make sense for them to hibernate or estivate until the general temperature of the
universe, until far far in the future and the ambient temperature of the universe is much lower
and therefore it's much cheaper
and I think it's something like
10 to the 30 more computations a second you could achieve
or something like that.
I can't remember. It's Anders Sandberg has a very fun paper on it.
I've never heard of that one.
I like the audacity of it.
I don't believe it.
No, I don't.
So I'll tell you why I don't believe it
because the temperature of the universe goes down.
That's fair.
But also the free energy of the universe goes down.
The energy that we have available to run our computation goes down.
So I presume someone smarter than me
has actually done the calculation and said it's still better to wait, but there's clearly a
competition.
Yeah, I'm pretty sure he factors that in, but I'm not versed enough to explain why.
Nonetheless, again, it was one that felt intuitive, it was very fun, but intuitively, I'm like,
nah.
Probably because it only takes one, you know, plucky counter example, right?
Only one civilization has to not buy into that.
Yeah.
But it does remind me of John Wheeler used to say, when he mixed cream into coffee, he always felt
sad because he was increasing the entropy of the universe, irretrievably.
But you do bring up this question of,
What does it mean?
What implication?
So what if we are the only civilization, only intelligent life forms, it makes you think,
you know, for better or for worse, but making you think is good.
Why are we here?
What is the point?
And you actually been thinking about things like this, right?
Yeah, I mean, I was just having a conversation with my partner, Igor, about sort of moral,
realism.
I know that you're very much a non-moral realist in terms of...
The human constructivist, yes.
Yes, and I'm of the same mindset.
But that said, if you want to sort of, if nothing else, maintain optionality,
us going extinct is definitely going against that.
Like now the options have disappeared to zero,
and it seems, it definitely appears like there is a very real risk
that we can go extinct by even 2100.
And by real risk, the estimate somewhere between, anywhere between,
like 2 and 20%.
I'm a moral constructivist,
but the morals I construct do say
that human extinction would be bad.
It would be bad, yes.
That's okay.
I don't need an objective
story to tell myself about it.
Right, exactly.
And yeah, it just seems like
it would be a terribly big shame
if, you know, all this,
these little pockets of low entropy
have managed to appear us,
you know, basically go and get
to second law of thermodynamics to a degree.
Are we actually going against
a second law of thermodynamics?
No, we're not.
goes against the second law of thermodynamics.
So how, this is what I've never wrapped my head around,
how do pockets of low entropy so successfully exist then?
Well, it's actually an outgrowth of the second law of thermodynamics.
Because if we think about it, if it weren't,
what would it mean to not have the second law of thermodynamics, right?
What would it mean is that we were already in thermally equilibrium, right?
We were already at a maximal entropy state, right?
Once you say the early universe started with low entropy,
that's all you need to say, then entropy increases and that's the second law.
The only way out of that is,
to say you were already in high entropy, and then there would never be any life. There would never be
any complex structures. There would never be anything like that. I see. We are not creating pockets of
low entropy. We are leaching off of the fact that the early universe had an extraordinarily
low entropy. We're increasing the entropy of the universe willy-nilly, right? There's a separate
question, related but separate, which is why are we complicated? Why are there complex structures
in the universe? And that's something that it makes sense that complexity develops along the way
from low entropy to high entropy,
but the details of how it actually happens
is an ongoing fun research problem.
And life is certainly just an example of exactly that.
Right.
And so, yeah, I think it would be arguably a tragedy
on a universal scale in terms of just lost utility
and lost potential and lost optionality
if, you know, even from just a,
looking from an expected value standpoint,
If we were to go extinct, even if it's a 0.001% chance,
there's still going to be 10 to the, I don't know,
how many possible lives, you know,
and it's obviously very happy lives in the future.
I have met people who argue that the human race should go extinct.
That would be a moral good,
that the rest of the planet would be better off without us.
Right. I assume they're extreme negative utilitarians in terms of the thing.
No, no, no. It's just that the utility goes to the plants and the animals, not to us.
We're a net negative they claim.
I don't believe them.
I'm just saying, you know, it is out there.
What's their main argument as to why we are a net negative?
Just because we create suffering upon...
Yeah, we're highly distorting the ecosystem.
And, you know, so much of the biomass is devoted to keeping us happy.
And it's not a natural state of being.
Right.
But define natural.
Well, yes.
That's the thing.
Now I get into the semantics of that.
I don't want to defend to this.
I'm just laying it out there.
No, I mean, it's definitely an interesting viewpoint to discuss.
And I have to say, intuit my intuitions are very...
I grew up in nature.
I love nature more than anything
and nothing upsets me more than seeing
images of the rainforest
this millions and millions of years old,
beautiful, unbelievably complex rainforest
a tree being cut down into planks of wood
something that's so unbelievably complex
and sustains this intricate
framework of an ecosystem around it
or the insects and animals and fungi
and everything that grows off it and relies upon it
is reduced to more planks of wood
that people then put, you know, we put our coffee mugs on.
You know, that's put down into this complicated ecological,
sorry, economic system out of this complex.
And I think they're two very different things.
Complex ecologicalism.
So like intuitively, it seems like a huge tragedy that we are doing that.
Nonetheless, I also think intuitively is a huge tragedy that this,
you know, human consciousness that does seem, I don't know, inherently special,
but there's definitely something inherently unique.
that we're not seeing elsewhere in the natural world as much.
And for that to go out.
And the thing is, if we go extinct,
well, chances are probably most of the other big animals will go extinct too as well.
I just wanted on the record that we are having this conversation at a concrete table,
not a rainforest wood table.
With metal legs, yes, very good.
So we're very morally correct in our living room here.
But it doesn't, we probably probably.
don't really think that it affects that calculation whether or not we're the only civilization.
I mean, maybe it makes it more poignant, right?
Right.
But we still don't want human beings to go extinct even if there's 100 million others out there.
I mean, there are plenty of people who think that there are 100 million others out there,
and they're waiting for us to grow up a little bit, right?
Right.
I have my suspicions that that's crazy also, but it is at least one of the options on the table.
Yeah, I, it's definitely, I mean, you can't, you can't rule anything out.
that's the thing when we're dealing with something of such uncertainty like this.
And certainly humanity has a lot of growing up to do.
But that said, there's a lot of beauty and goodness in the things that we are doing.
And it would be nice if we were given the opportunity to try and grow up.
And you have put your money where your mouth is, quite literally,
becoming interested not only in these philosophical questions,
but the applied questions of how to be better people,
how to make the world a better place,
and in the effective altruism movement in particular.
And you don't just talk it,
but you've like started an organization?
Yeah.
So tell people what effective altruism even is.
Yeah. So effective altruism is basically
the combining the head and the heart
when it comes to philanthropy and doing good.
You know, we all, well, the vast majority of us,
we want to do good in the world.
You know, if we see someone,
suffering, we'll try and help them. You know, you see someone passed out in the street.
The actual human instinct is to usually go and check on them or a dog yelping or whatever it is,
someone is screaming fire. You know, we're all, for the most part, naturally altruistic.
And that's a great thing. But at the same time, there will also be, you know, different ways.
There will be some ways which are more effective at getting a certain problem alleviated.
And so effective altruism is basically applying science to.
to philanthropy, to altruism, doing good as effectively and efficiently as possible.
And so, I remember like hearing about this, that, you know, I wanted to give money to,
for example, environmental charities.
But I often just felt lost.
I was like, well, where do I start?
What's, you know, I want, I'm concerned about climate change.
I'm concerned about biodiversity loss, et cetera, et cetera, all these different things,
which, how do I weigh these off against each other?
When I give my money to one charity, that means I'm actively not giving my money to another.
You know, we only have limited resources ever to give.
And so it's imperative that we do as much research we can,
or at least consult people who have done the research,
to figure out where we can have the biggest positive impact with whatever we give.
Whether it's not just money as well, time.
If you choose to work for a charity, you want to make sure that it's,
the actions that you are taking in your line of work are achieving the most good.
Because you won't get those hours back.
time is also a scarce resource.
And so after hearing all these arguments, I was like,
oh, this makes a lot of sense.
And a team of full-time effect of altruists,
they suggested, well, look, we think poker players will get this.
They're very used to thinking in numbers about uncomfortable things.
They're comfortable with the idea of sort of thinking about expected value and uncertainty.
Variants, yeah, variance, quantifying things.
And they're also, you know, poker players, I think, are willing to,
despite sort of the impression, you know, that we're all like dark degenerate money grabbing.
Yeah, gamblers.
Actually, you know, like I think a lot of poker players are aware of sort of a unique position
that they have in terms of we have sort of time and we can make good money and it'd be nice
to contribute to society in some way.
And so we decided to start this organization called Raising for Effective Giving, reg-charrity.org.
raising is a pun.
Raise it, exactly, pun on the old chips thing.
Igor and I have many arguments about who came up with a name.
That's why there's a 4% chance that it's not going to have to.
Yeah, well, no one will ever know.
And yeah, so four of us poker players started it alongside these Swiss effect of altruists.
And we, yeah, we were encouraging poker players to give 2% of their profits, sorry, 2% of their net, no, gross winnings every quarter.
And some people sort of continue on that model.
Others just sort of, because poker's a very all or nothing kind of game.
Often you'll have a big win followed by months of losing.
Months and so generally people just tend to donate when they have a big win,
a percentage.
And yeah, it's been extraordinarily well received.
I had no idea that poker players would like get it as much as they did and it's raised
over $6 million now.
And we, so the charities are specifically,
we either use givewell who you might know
givewell.org which is a very...
Gibwell is usually where I go when I...
Yeah, they're fantastic.
In terms of human suffering reduction,
they are the go-to in terms of you want to find out
how you can help human lives right now as best as possible.
So we use their top three recommended charities
which are almost always against malaria foundation
and sort of something deworming
and direct poverty alleviation with like give directly.
And that's because like,
the cost to save a human life, like it or hate it, unfortunately, is just many hundreds of times cheaper,
like around 100 times cheaper in the developing world than it is here, say, in the US or in the UK.
You know, in the US, there are, you know, the government more up to, spend up to around a million dollars to, to save a life on, if you look at sort of cross-health care and that kind of thing.
And yet you can demonstrate, demonstratively, uh,
a life in some parts of sub-Saharan Africa for around $7,000.
So, like, that's a huge, huge difference.
And even if you think that an American life is worth more than someone, say, from Malawi,
do you really think that they're worth 100 X?
Would you, like, would you press that button to say, I will kill 100 Malawians to save
one random American?
And it's not talking about an American you know.
Like, someone random from America in a part you've never been to.
would you really say they're worth 100 mothers are worth one mother here? No. And so yeah, it's about
this sort of idea. Unfortunately, you do. You have to like put a price effect. It's not putting a price
on a human life, but it's about saying my actions, I can help someone with the money that I give.
And so I want to help as many people as possible with that. And so yeah, so we've got some,
we've got the best charities in human suffering alleviation, the best ones in
animal suffering alleviation. By best I mean most cost effective. And the animal ones almost always
are to do with anti-factory farming. Just because it's pretty tragic what's going on out there.
And it's very, very cheap just to save very sentient animals from a life of misery. And then we also
have neglected research areas, specifically ones looking into things like global catastrophic risk.
Okay, cool. So, yeah, like people looking into risk from biosecernic.
Because even if it's a tiny chance.
Exactly.
Even as it's a 0.1% chance, you know, if you factor that over the 100 billion or so lives
that are going to exist over the next century, and that's roughly what the number is,
even over the next century, that's a lot of people.
I mean, it seems kind of obvious that we should try to be efficient and spend our charitable
givings as effectively as possible, but there has been pushback, right?
I mean, some people don't like it.
I mean, personally, I'll confess, I'm not a utilitarian.
I think that it's hard to be a consistent utilitarian,
but still, I take the effective altruism
to be a good nudge in the right direction, right?
I mean, we certainly do value the things we see right in front of our eyes
more than the things we know are going on out there in the world,
and this is an excellent reminder that there's ways to make a huge impact
elsewhere in the world that might not be quite as obvious to us.
Exactly. It's not just, it's taking, you know,
it's not saying that if you, you know, react to something immediately happening in front
you that that's not a good way of doing good. Of course it's good. Like, it's there. And a big
part of when you do good, you're trying to do something altruistic and help, it's fine to also
feel good about it. You know, I think people go, oh, you know, you shouldn't have any
positive emotions that come out of it or you shouldn't be doing it that way. I think that's silly. Like,
no, like you want to do whatever continues to motivate you. Yeah, get that dopamine from
Absolutely. And so it's about, like I said, it's about balancing not just the head but also the heart.
The heart is a big part of any kind of charity giving and so on.
And I think it's a mistake to try and remove that out of it.
But at the same time, we have to be aware that just purely acting emotionally,
when we know that we have these big biases in terms of like we randomly will sort of value people
who happen to live in the same town as from someone who lives in a town 100 miles away.
even though we don't know either of them
just because that's just the way
human intuitions are sort of built
and that can then be
a mistake in terms of our sort of narrow
resources that we have to allocate.
Maybe from what we said earlier there'd be a good
charity that could
give everyone free poker lessons
because it would help them think in probabilistic
ways about the world.
I wouldn't specifically say that
but yeah I mean like there is a
there is a charity who, I mean, they're at least a sort of 5013C, but who train young people
in applied rationality.
So quantifying things, which is basically applied poker.
Doesn't at all talk about poker, but they training promising young people who are looking
to get into sort of research, politics, you name it, the art of rationality, which is
incredibly important because these are going to be the future leaders.
And, you know, I think we want leaders who are.
aware of human biases and aren't afraid to think in sort of scientific terms, you know,
to give them to tools to understand their own emotions and so on, and therefore be better equipped
decision makers.
And I think that's an incredibly valuable thing.
And that's one, these kind of organizations that are looking into teaching nationality
classes in schools, I think these are incredibly promising area to donate to.
because, you know, they can create a, like, there's definitely a huge lack in our current education system.
And like, how many kids are taught to, you know, think through their feelings, for example, or, yeah, like, oh, it's okay to be uncertain.
Let's see if we can estimate our probabilities. Like, these basic rationality tools that you and I take for granted, like, we only take, we only know them because we learn them as adults, either through poker or through another means.
But imagine if you were just taught these, these basic things or, like, learning to think through the counterfactuals, something like that.
I wish I'd learn that when I was 10.
It would save me so much time.
Yeah, just like looking up the probabilities of,
I used to be a huge hypochondriac.
The amount of worrying time I've spent,
you know, going always my headache and brain tumour,
if I'd just learn to, like, do a bit of Bayesian updating,
that would have saved me a lot of misery over, you know, in my late teens.
And so, yeah, it's, I think it's a big shame that these areas are neglected.
Well, I think it's a perfect place to end because you basically encapsulated
the mission statement of this podcast, trying to get people to think a little bit more rationally,
a little bit more cognizantly of their biases and a little bit thinking in different ways than
they usually do. So, Lib Boree, thanks so much for coming on the podcast. Thank you, John.
