October 14, 2024 • 48 mins
Tim Harford joined Nate Silver and Maria Konnikova on their podcast Risky Business to discuss two of history’s most compelling swindlers: Sam Israel III and John Law.
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Speaker 1 (00:15):
Pushkin. Over the years, Cautionary Tales has warned you about
Ponzi schemes, dodgy Christmas savings clubs, and promotions that are
too good to be true. So it may come as
a surprise when I urge you to get into Risky Business.
Speaker 2 (00:33):
Don't worry.
Speaker 1 (00:34):
I'm not trying to pull a fast one. I just
want you to try out a podcast I think you'll enjoy.
Risky Business is a weekly show about making better decisions.
The hosts, Maria Konakova and Nate Silver, are both writers
and high stakes poker players. Maria and Nate cover everything
from politics to poker to personal decisions, so when they
(00:55):
asked me to join them for an episode, I was
eager to try. I even got the chance to talk
to Maria about one of the fraudsters featured in Cautionary Tales.
She has met him and he assured her yes, he
was a liar. You can listen to Risky Business wherever
you get your podcasts, But for now, here's the episode
featuring me. I hope you like it. There are duels,
(01:17):
prison breaks, banking bubbles, poetry, and Nate reveals he has
a relative who faked his own death.
Speaker 2 (01:30):
Hi, everyone, Welcome back to Risky Business, our show about
making better decisions. I'm Maria Kanikova.
Speaker 3 (01:36):
And I'm Nate Silver.
Speaker 2 (01:38):
So today we have a slightly different and fun show
for you. We're going to be bringing on a very
special guest, Tim Harford, who hosts another Pushkin podcast, Cautionary Tales,
and we'll be talking about the intersection of risk and
cautionary tales from history. Tim, welcome to the show to
(02:03):
be on the show. Thank you so for listeners of Pushkin,
you're probably familiar with Tim as the host of Cautionary Tales.
I've been lucky enough to be on the show and
to have been a listener of the show. I think
it's wonderful. My episodes are obviously the best, but it's
all pretty good. Tim is an economist, a journalist. He
(02:24):
has a column in the Financial Times, He's written multiple
amazing books. You know, longtime friend of the two of us. Nate,
I don't know if you want to add anything else,
but we're so happy to be here and to do
kind of an episode where Cautionary Tales and Risky Business intersect,
where we talk about cautionary tales that are about risky business.
(02:45):
That are about risk, about taking risks, about how risk
taking can go wrong, and how sometimes you know, the
lines between legitimate risks and cons and deceptions might get
blurred a little bit and cross over into territory that
goes from legitimate to illegitimate very quickly.
Speaker 3 (03:04):
Do you mean to say that campbling doesn't always work out, Maria?
Speaker 2 (03:06):
It's weird, it's so weird.
Speaker 1 (03:08):
The chance of loss is in fact one hundred percent,
which I guess we'll get we'll get to that, but yes, that.
Speaker 2 (03:13):
Is absolutely true. So when we were kind of thinking
about ways to make this episode work, Tim, you thought
about one particular story where you and I have actually
intersected on this because we've both thought about this person
and he's someone who I actually had on my previous podcast,
The Grift, and he is a well, let's let's have
(03:36):
you lay him out. Let us meet Sam Israel, the
first kind of our first subject for today.
Speaker 1 (03:42):
Sam Israel, the third I think is his full name. Third,
absolutely remarkable gentleman if gentlemen is the right term, and
it probably isn't. So we did a Cautionary Tales episode
live on stage about pyramid schemes and Ponzi schemes and
white people fall for them, but also white people set
(04:05):
them up. And this kind of strange snowball of disaster
where the Ponzi scheme becomes increasingly difficult to cover. And
the most amazing example I've ever come across is by
You Capital, which was set up by Sam Israel. I
saw one writer described Sam Israel and by You Capital.
(04:26):
It's like somebody took the Bernie Madoff story but was
told to write a Hollywood script and to punch it
up a bit, make it sing a bit more. And
everything that made made Off's Ponzi scheme notorious applies to
Sam Israel, but it just all gets crazier. So Sam
(04:48):
came from a wealthy family, I think of commodity traders
in Louisiana, but he wanted to show he could make
it himself, and he got into Wall Street at an
early age, absorbed that Wall Street culture, you know, all
that kind of broish culture of Wall Street in the
nineteen eighties. And so he takes all this in, he
(05:11):
keeps his mouth shut. He watches various dubious activities, and
not just the kind of the sex work and the excess,
but also illegality, financial illegality, observes people kind of insider trading,
for example, and then he sets up his own firm,
by You Capital, which is a hedge fund, and very quickly,
(05:32):
by You Capital turns from being a hedge fund into
being a ponzi scheme. And just to remind people what
a ponzi scheme is, it's very simple. Investors give you money,
and then you announce you've made massive profits, and then
more investors give you money, and you announce you made
even more massive profits, and then more investors give you money,
and you keep saying you've made massive profits. And if
(05:53):
anybody ever says, that's great, I'd like my money back, well,
that's easy. You can give them the money back with
the profits because more people keep giving you, keep giving
you their money. And the insight that Sam Israel had
was with a hedge fund, it's kind of open ended.
The money keeps growing, and why would anybody ever want
their money back if you keep telling them they made
(06:14):
another twenty percent this year, they made another twenty five
percent this year, Like no one ever asks for their
money back. They just leave the money with you. And
so the fraud went on for a very long time,
and then things started to unravel. But Maria, you met
Sam so so, and you met Sam in prison, so
a spoiler. So tell us what did you make for
him as a person? How did he get into this?
(06:35):
Why did he get into this?
Speaker 2 (06:36):
Well, it's funny because my interview with him was from
a while back, you know, twenty seventeen something like that.
I honestly don't remember.
Speaker 1 (06:47):
We should say he was arrested, I think in about
two thousand and seven, two thousand and eight something like that.
Speaker 2 (06:53):
Wasn't yeah, exactly exactly, but so I was trying to
refresh my memory, and you know, just looked at some
of the transcripts and then also looked at an interview
that he did with Andrew Ross Sorkin, and he told
us the exact same thing at the beginning, which is like,
don't believe me, I'm a liar. And it's so funny
(07:13):
because I think that he thinks that that absolves him, right,
if he puts that disclaimer up top, then he can
sort of charm his way out and say, but actually,
I'm a good guy, right, I'm not like that bad
guy made off.
Speaker 1 (07:29):
So I should say there's one amazing scene. Gee Lawson
wrote this book The Octopus, which is like the quintessential
account of Sammy's wail. But there's a scene in that
book where his wife walks in and catches him bent
over his desk snorting cocaine through a fifty dollar bill
and says, why are you taking cocaine? And he goes,
(07:49):
how dare you accuse me of taking drugs? So yeah, sorry,
I interrupted, but.
Speaker 2 (07:54):
No, he is. It is the kind of guy he is.
And you know, he was incredibly charismatic, and he said,
I was doing really really well on Wall Street. Right,
he kind of got in. He didn't want to compete
with his siblings, wanted to do it on his own,
so he didn't want to go into the family business. Instead,
he had this opportunity to go into Wall Street, worked
(08:16):
at a very successful hedge fund, and was actually making money.
By the way, this is all according to sam Israel, Right.
I haven't actually looked at his returns. I did not
look at his balance sheets. I don't know how he
did as a trader. He assures me that he was
making millions for people and for himself in his prior
Wall Street days. So let's just we'll take that on faith.
(08:38):
But what I've learned working with con artists is you
can't take anything on faith, so asterisk. But he was
very successful on Wall Street, and I assume he must
have been to a certain degree because he started his
own hedge fund right and he was able to raise
I think about three hundred million to begin with of
outside money, which back then this was nineteen ninety six,
I want to say something around somewhere around there in
(08:59):
ninety so that was a lot of money. And he
went in with a partner who was a close friend
of his, who was a disgraced fund manager whose fund
had just gone under. But Sam believed in him and
thought that, you know, that he was a good guy
and that this would work. So the way Sam told
it to me was that when they started by you
(09:20):
in nineteen ninety six, he kind of relied on this guy,
you know, to be an equal partner, and that this
guy was started losing a lot of money, and Sam said, well,
I'm a good trader, I'm good at this. I'll be
able to kind of work my way out of the hole.
But he couldn't, and the hole kept getting bigger, and
so at some point he realized, you know, shit, we've
(09:42):
lost twelve percent in our first year. You know, it's
even worse in our second year. This is looking bad
and our ability to raise money is going down because
our returns are shit. They're absolutely horrible. And so that's
when it became a Ponzi scheme.
Speaker 1 (09:56):
And his accountant, who was a guy called Dan Marino. Hell,
there is footnote for body. Well if anybody so think
about it, this is nineteen ninety six. If anybody googles
as pre google, right, if anybody who tries to search
on the Internet for Dan Marino, they get the football player.
So he's working with this accountant who is completely invisible
(10:19):
to Internet searches. And the accountants are smart. Yeah, it's
really smart. The accountant's completely crooked and basically sets up
his own fake Uh.
Speaker 4 (10:29):
Sounds like a cricket I've read a stereotype based on
last but Deno sounds like a cricket account accountant or
an NFL quarterback.
Speaker 1 (10:36):
So he sets up his own fake auditing firm. So
he's basically auditing his own accounts. And if anybody sort
of were to really go and check the go the
guy who says that Dan Marino's accounts are genuine is
an uditor called Dan Marino, and they're the same guy,
so that that was kind of an important part of
this fraud. But yeah, Dan Marinos told the author Gey
(10:58):
Lawson that one of the problems was, there's this idea, Oh,
we're going to have a really good year, We're going
to make a lot of money for real. And when
we make a lot of money for real, then it
will no longer be a palmzy scheme. You know, we'll
have you know, it's all genuine, it all come out
good in the end. Dan Marino said. The problem is
sometimes they did have good years, but whenever they had
(11:20):
a good year, they would claim it was an even
better year, and whenever they had a bad year, they
would never admit that they had a bad year. So
there was a you know, whatever it was, vanity, fear
of the consequences, whatever it was. He just made it
completely impossible for him ever to catch up with his
own life.
Speaker 2 (11:37):
And I think that that's very typical of con artists,
right where they say I'll fix it, I'll make it better.
This isn't this is just temporary, but it never is.
But the most incredible thing about Sam Israel is that
once the scheme kind of comes undone, right, which happens
at some point, just like with SBF. Note right, at
(11:58):
some point people are going to ask for their money
and people are going to get spooked. And when they
get spooked, like there's going to be a day of reckoning.
And he had a moment where he said, oh shit,
you know I'm going to jail. And he thought he
would get seven or eight years, which was pretty typical
for white collar criminals. And then they switched judges and
(12:20):
the judge gave him two hundred and forty months, so
twenty years right instead. And he was like, oh shit,
you know I can't do twenty years. I'm going to
be an old man. This is this is not cool.
I was ready for seven I can't do twenty. And
so instead of you know, figuring out how do I
(12:42):
deal with this, he decides to fake his own death.
Speaker 1 (12:44):
Yeah, which he's obviously going to work out really well.
Speaker 2 (12:47):
Oh it's going to work out great, We'll be back
in a minute. He only has a few months to plan, right,
It's not like he has been thinking, oh, I'm going
to fake my own death. This is my exit strategy.
(13:08):
Because a lot of connor is they don't think that
far ahead, right, They don't think of the exit strategy.
They think it's always going to work out. So he says,
I'm gonna I'm gonna fake my own death. I've watched
this really cool movie it's called r V, and I'm
going to buy an RV and I'm going to, you know,
just go around the country and maybe make my way
to go by the way. One of the things he
(13:28):
told me was that as after his sentencing, as he
was walking out, an FBI agent, one of the ones
he'd gotten friendly with, looked at him and said, I
have two words for you, Costa Rica. I find it
very difficult to believe that that actually has.
Speaker 1 (13:44):
Yes, I also doubt.
Speaker 3 (13:48):
Marino Dan Marino two woods to you, Costa Rica. I
don't know what.
Speaker 2 (13:54):
I think.
Speaker 1 (13:54):
You've got a career this so but I'm curious. So, Marie,
you said that this is very this is short term thinking.
He didn't. He wasn't really thinking to the consequences of
his actions, and that that's true. Any Ponzi scheme inevitably
become completely unsustainable. You cannot possibly keep it going. It
will come to an end. So what is the way out?
(14:17):
And then the faking the suicide again like of course
he's gonna get caught. Of course that's not going to work.
Speaker 2 (14:21):
So yeah, he decided he was going to jump off
a bridge.
Speaker 1 (14:24):
Well not just he decided he was going to pretend
that he had jumped off.
Speaker 3 (14:27):
A bridge, right, he actually jumped off a.
Speaker 1 (14:29):
Bridge because he because he then he did actually actually claim.
Speaker 2 (14:35):
Actually he actually jumped off a bridge. He did. So
this is the research he was doing. When you're trying
to fake your own death, and I interviewed this woman,
Elizabeth Greenwood, who wrote about faking your own death, you
have to think very far ahead. You have to figure
out money. You know, how am I going to be
off the grid right these days? Like how am I
going to survive? How am I going to get out
of the country, and you know where where's my cash
(14:58):
going to come from? All of these things. Instead, what
he spends his time thinking is researching all of the
bridges in New York to try to figure out which
one he could conceivably jump off of an die. So
he finds a bridge that's under construction, so there are
nets underneath, and he's like, oh, perfect, Like I'm gonna
(15:19):
jump and I'm going to land in the net and
then I'll use the net to scramble up and get out.
So he does this, not realizing that those nets are
pretty damn hard to climb out of, so he manages
to make the net. By the way, thinking about risk, right,
risk reward if you miss the net, the you know
(15:41):
the risk reward equation there is not great.
Speaker 1 (15:45):
The designed to catch people or just like a span
of that somebody drops.
Speaker 2 (15:49):
I mean that's the right, No, it's I think it
was gonna I think it was designed to catch bricks
and you know, falling debris from construction. So when a
person goes into it, it just like you know, it
goes all the way down. So then he's stuck in it.
And at this point he's like, I think I'm going
to die anyway, except it's going to be much worse
because I'm going to have spent my last minute trying
to scramble up this net. But he actually does manage
(16:12):
to get out, and he has a driver waiting for
him to take him to his RV and he thinks
he's going to drive off into the sunset. Oh, by
the way, another really really important thing, if you're trying
to fake your own death, do not tell your mother,
your girlfriend, your son, and the driver that you're going
(16:34):
to be faking your own death. Don't worry, mom, I'm
not actually going calling uber.
Speaker 3 (16:41):
Do it in style.
Speaker 2 (16:43):
But that's this is what happened. So you know, he's
fucked from the beginning because he has not thought any
of this through. But he does manage to make it
out of the net. He's met by a driver, makes
it to his RV, and for the first few weeks
it actually seems like everything is kind of okay because
even though he's living in an RV, living in RV parks,
(17:06):
you know, he's kind of getting away with it. And
then he walks into a bar one day and he
sees himself on TV on America's Most Wanted, and he
goes and reads about himself on the Internet, which is
a big, big no no if you're faking your own
death to start googling yourself, but he does that, and
he sees that his girlfriend has been arrested as an
(17:28):
accomplice and that they're looking to arrest his mother. He
doesn't realize that this is a trap, that the police
do this kind of thing to try to get people
kind of out of hiding. He thinks this is real,
and so he gets on a motorcycle, goes to the
police department to turn himself in, walks in. He says,
you know, hey, I'm here to turn myself in, and
(17:48):
the police officers like what you know? In for what?
You need to use the bathroom, like it's over there anyway,
there's all of this miscommunication. He says, no, you know,
I turning myself in. I'm wanted and I just don't
want any press here. And at this point the police
officer actually looks at him, realizes who he is, and
that is when he gets caught and gets an additional
(18:12):
two years added on to his sentence for faking his
own death and running away.
Speaker 1 (18:16):
It's astonishing. I'm not one thing you said, Maria. You
said that the craziest thing about him, or the most
amazing thing about him. I'm not even sure that is
the craziest thing about him. But you know, we haven't
got all day, so that there are other stories you
could tell about Sam. But I wanted to ask Nate.
Given that, Nate, you've been thinking about the habits of
(18:37):
risk taking individuals, these people you call Riverians. Is short
termism part of the or kind of a side effect
or a glitch in the Riverian thinking system. So on
the one hand, you need that ability to think probabilistically,
you need that ability to take calculated risks. But I mean,
(18:59):
Sam as Weel just seems to have never been able
to see past the It had no problem taking risks,
but just couldn't see past the end of his nose.
Speaker 4 (19:07):
Yeah. No, look, I think the better investors and gamblers
have a longer time horizon. That's kind of one of
one of Silicon Valley's secrets, despite their mini flaws, that
they do kind of think ten years ahead. But yeah,
some of this sounds very familiar, Marie, I know if
I'm talking to you, the notion of like a good
business gone bad. I mean, even FTX was a pretty
(19:28):
good business, right, It was like the leading brand for
crypto trading. They made legitimate profits, et cetera. But like
you know, it turns sour or I think you know,
Sam bacon Free couldn't resist the temptation to take all
this money staying on the sideline. He couldn't like resist
the temptation to go and gamble with it. But yeah,
the lack of advanced planning coupled with the kind of
(19:50):
miscalculating consequences. You know, if you're very charming, which I
think Sam Israel is more so than SBF, it's a
different story. You can kind of weasele your way out of.
Speaker 3 (20:00):
Things, right.
Speaker 4 (20:01):
You can think you can like dance your way out
of anything, and you can up the con a level
or two or three, and then you may on some level, no,
it's not going to work.
Speaker 3 (20:10):
But I don't know. I mean, at some point there's
a point of no return, right.
Speaker 2 (20:15):
There is a point of no return. Yeah, I think
I think that's absolutely right, Nate. I think one of
the this is a characteristic that you have both uh,
both with raverians and non reveriance and and Tim. I'm
sure you've come across this in other cautionary tales, but
I think a lot of it is this over confidence
in hubris, right, that comes with a certain level of
(20:36):
success and people. And I think to be an entrepreneur
and to be a risk taker, you need to be
over confident to a certain extent. You know, as as
we all know, if you actually know your odds of success,
you're not gonna You're not gonna start the damn company
you're not gonna You're not gonna try it because it's
the risk of failure and the chances of failure are
(20:58):
so high, So it's a it's this fine balance, and
I think over confidence so turns into delusion and turns
into this thinking that actually, you know, I can keep
doing this forever. And because you've gotten away with it
for so long, it seems like probabilistically speaking, you know,
(21:19):
your base rates change, I've gotten you know, okay, you
know one year, two years, three years, four years, everything's good,
This is all going good.
Speaker 4 (21:27):
Yeah, if the coin comes up heads five times in
a row, I mean you see it.
Speaker 3 (21:32):
In poker all the time, right, Yeah.
Speaker 4 (21:35):
You know, winner's tilt is something which is maybe underdiscussed
loser tilt we all have experienced, maybe Maria, but Winter's
tilt where you're on a hot streak and you're like a,
maybe I have some gift from God to play poker
really well or something is also a big deal.
Speaker 2 (21:52):
It absolutely is. One of My favorite psych studies is
from Ellen Langer, and I think the name of the
paper is something like heads, I win tails, It's chance
something like that. Yeah, And she had people bet not bet,
but guess the results of a coin toss, and it
(22:13):
was actually not a fair coin. It was rigged, and
there were different Basically, it came up heads and tails
the exact same number of times in all of the
different conditions, but in some of them it was pretty random.
In others it was clustered near the end, and in
the most important condition, the correct guesses were clustered near
(22:34):
the beginning, right, So basically you would say, you know, heads,
you'd guess, and then they'd make sure it landed on heads.
It was a rigged toss, so that you were right
it was yeah, And the people who were correct clustered
at the beginning would then and these were Harvard students,
by the way. Then they got all sorts of questions
like I'm good at predicting the outcomes of coin tosses,
(22:58):
and they would rate themselves as actually quite good at it.
They would say, if I had more time to practice
and to guess, I'd get even better. So things that
made it very clear that they thought that this was
a skill and not actually completely random. And it was
so easy to get people to believe that they were
skilled at something where it was just complete randomness when
(23:18):
they had those those things happened at the beginning. So Tim,
I think this goes back to the beginning of your question.
This is how you get into Ponzi schemes. Think about
Bernie Madeoff right. He was successful for far longer than
Sam Israel, and Sam Israel, by the way, was the
single biggest Ponzi scheme before Bernie made Off.
Speaker 1 (23:34):
Now I am I'm curious. We've been talking about people
who were have an appetite for risk and who it
all came apart for Maria, I know you've been doing
a little bit of research into one of the most
important gamblers in economic history.
Speaker 2 (23:53):
Yeah, John Law. He was someone who I wrote about
for The Confidence Game and I've come back to so
my next book is about cheating. So I've kind of
been thinking about him. But one of the reasons I
am interested in John Law. So when we're talking about
someone like Sam Israel, right, it's pretty clear con artist,
(24:14):
right Ponzi scheme. When you're talking about someone like John Law,
it becomes much less clear because he's someone who was
a huge gambler and we know that sometimes he was successful,
but he also ran his father's business into the ground.
If I remember correctly through gambling. But I guess he
got better with time and killed.
Speaker 4 (24:36):
Man and likely killed a man literal gambling or like
literal gambling.
Speaker 2 (24:41):
So yeah, so he was someone who came from money.
Who's you know whose parents had a financial business.
Speaker 1 (24:48):
We should say it was seventeen hundreds, just just a situation, right, Yes,
for those small number of listeners who don't know who
John Law is or everybody should.
Speaker 2 (24:57):
We're in the seventeen hundreds and he's going to be
making friends with the Duke of Orleans or the Duke
of Orleans who was then Regent of France, and he's
going to be basically setting up France's banking system. So
the reason why I was fascinated by him is that
it's actually unclear if he was a con artist or not,
(25:18):
like did he believe that? Because it was the kind
of the end of his time at the height of
finance was with the establishment of this thing called the
Mississippi Company, which was a huge bubble and basically bankrupted
a ton of people. And the question is, you know,
(25:39):
did he know what he was doing and get unlucky
or did he like basically did he do this as
a kind of Ponzi scheme as a kind of con
or not.
Speaker 1 (25:47):
And the fact that we still don't really agree on that,
I think is fascinating. I mean, we should say so.
He he was originally Scott, a Scott. He he killed
a guy and a duel, was sentenced to death for murder.
Escape from prison, traveled Europe, wound up in Paris, made
a few friends with some influential nobles, made a huge
(26:09):
amount of money gambling because he would set himself up
as the house and he understood the probability enough that
he knew he had an edge. So he's gambling with
all these nobles. He's making a huge amount of money.
And then he sets up his own bank and he
starts issuing paper money. This is not the first paper
(26:32):
money in the history of the world, it's not even
the first paper money in the history of France, but
it is. It's pretty new and people are still trying
to figure out kind of how it works. And of
course this is revolutionary. He's ahead of his time, like
paper money is how we do things right. It's kind
of amazing. And then the whole thing just gets wrapped
up with French government debt and gets wrapped up with
(26:53):
the Mississippi bubble, and the Mississippi bubble was it was
a stock market bubble. One stock was involved, the stock
of the Mississippi Company, and John Law controlled the Mississippi Company.
But it was clear that nobody really understood what was
going on except that go up, and if numb, but
go up, everyone everyone gets very excited.
Speaker 4 (27:12):
Yeah, it's very intoxicating when the number goes up. Right,
I did wonder too, there is some survivorship bias in
which kind of scams and schemes we discover, you know,
the best frauds in history. Probably nobody knows about it. Yeah,
good point. Sbl was convinced that he could somehow navigate
his way through bankruptcy, or not through bankruptcy, now, his
(27:35):
way through this downfall and bitcoin and come out on
either side of it.
Speaker 3 (27:38):
And maybe people wouldn't really notice.
Speaker 4 (27:40):
Right, Maybe it's like a page a sixteen story, not
in a one story. If he like, if there's a
spontaneous rise in bitcoin prices and they recover these losses
that they have, although they were ten million and ten
billion in a hole, which is pretty hard to overcome.
Speaker 2 (27:53):
It's funny, Nate. I think it's that's a really important
point that the best con artists are never caught. When
people when we talk about connartists and people ask me,
you know, why aren't there as many female con artists,
I say a few things, but one of the it's
kind of a joke but kind of not, which is
that they're just better at it. So we don't know
(28:15):
them because they haven't been caught. They don't have as
much ego, and they know when to disappear and how
to disappear much better than the sam Israel's of the world.
Speaker 4 (28:25):
Or like cheating in poker, a lot of these famous
cheating scandals, like online cheating scandals, people are are very
greedy where they win at like, you know, thirteen centered
deviations above some random rate, whereas if we won at
two center deviations above random, it would be almost impossible
to detect and you'd have a great life. Although we
don't find those people though, right, we don't find the
(28:45):
people that are that are actually good at cheating a.
Speaker 3 (28:47):
Lot of time.
Speaker 2 (28:49):
Yeah, but so so as we you know, wrap up
the story of John law I do think that it's
interesting that, I mean, economists don't agree, historians don't agree
whether whether or not he was, you know, greedy cheat.
He was obviously greedy. I think everyone agrees on that,
but whether he thought that this could actually all worked out.
I found a rhyme that I would love to share
(29:12):
if you guys are in poetry mode, that come from
the time about what happened with the Mississippi bubble. And
it goes like this. My shares, which on Monday I bought,
were worth millions. On Tuesday, I thought so. On Wednesday,
I chose my abode in my carriage. On Thursday I
rode to the ballroom. On Friday I went to the workhouse.
(29:34):
Next day I was sent.
Speaker 3 (29:36):
First poetry reading on the Risky Business podcast.
Speaker 2 (29:39):
I believe it is.
Speaker 1 (29:40):
It is I think that should stop tradition. That's very good.
Speaker 2 (29:45):
And one nobleman of the time said, thus sends the
system of paper money, which has enriched a thousand beggars
and impoverished one hundred thousand men. And obviously that's not true,
which is why we You know, that was not the
end of the system of paper money. It was just
it just happened to be the end of John Law.
He had to escape France, by the way, because he
(30:05):
was convicted and was going to be sent to prison there.
So he dressed up as a beggar, ran away to
Italy and died in Venice, totally impoverished. And I guess
the cautionary tales.
Speaker 1 (30:17):
It is a cautionary tale. And I guess the lesson,
or maybe the lesson is that the economics lesson is,
if you're going to have paper money, if you're going
to have somebody who has the right to just create
money with the printing press, you've got to make sure
you have the right controls over that person or over
that institution. It can't just be some guy who killed
a guy in a duel and came over one a
(30:39):
lot of money and gambling and then he's the guy
who can do it.
Speaker 3 (30:42):
It's you.
Speaker 1 (30:43):
You need this institutional scaffolding, which you know, when we
have it, it seems to work just fine.
Speaker 3 (30:50):
We'll be back right after this.
Speaker 4 (31:06):
I mean, are there like two or three on big takeaways,
like common patterns and when you know something is becoming
a cautionary tale or a can.
Speaker 1 (31:18):
At the risk of quoting that classic opening line of
Ana Karenina that all happy families are alike and every
unhappy family is unhappy in its own way, I think
one of the striking things about cautionary tales is that
there are a lot of different ways for things to
go wrong. The organizational problems, informational problems, engineering problems, hubris
(31:47):
and arrogance, short sightedness, lots and lots of self delusion,
lots of wishful thinking. I mean, it's a miracle that
human civilization survives, actually, given how many different ways there
are to go wrong. But I mean that is part
of the slightly perverse joy of researching and writing these
(32:08):
cautionary tales. There is always a new disaster, and always
a new way for disaster to happen.
Speaker 2 (32:16):
You make that sound almost gleeful.
Speaker 1 (32:18):
Yeah, I mean sometimes I have to remind myself that, like,
I'm not supposed to be enjoying this, because some of
them are very, very sad. Some of them are straightforwardly
hilarious and no great harm is done, but a lot
of them are pretty painful.
Speaker 4 (32:33):
Yeah, Maria, I remember you telling me that, like, cons
are most likely to occur when you're in an upcycle
or a down cycle, right, not in the steady state,
but when there's something new and novel and people are panicking.
Speaker 2 (32:44):
Yeah, moments of transition. So whether those are societal transitions
or whether they're personal transitions, is when you're most vulnerable
to get cons So it's not a personality trait. It's
not intelligence, it's not it's not anything like that. It
is this kind of moment of either up or down
euphoria or you know, despondency. But when things are uncertain
(33:10):
and your worldview gets challenged, gets shattered, gets displaced, you
look for certainty and that's when con artists swoop in
and give that certainty to you.
Speaker 1 (33:21):
So as long as nothing ever changes, we will say
from Collins, we're good.
Speaker 4 (33:26):
You know my uh my great grandfather faked his death
and got a.
Speaker 2 (33:31):
Wait what okay, Nate, can we just can we we
need this story. I'm sorry we're pausing everything, Nate, please.
Speaker 3 (33:38):
I mean his name was Ferdinand Thrunn, which is a
great name.
Speaker 2 (33:42):
It's an amazing name.
Speaker 4 (33:42):
He was written up in the Chicago Tribune and the
New York Times and places like that. Yeah, he was
like an insurance frauds ster. We should do this as
a separate segment sometime, yeah, But basically his technique was
to commit crimes so devious that there was no law
to charge them with. Because I hadn't figured out like
this particular type of fraud. But we should do proper
research and do an episode on this.
Speaker 1 (34:02):
Maria, Yeah, absolutely so, so Maria Knight. I now we've
discussed some as well. We discussed John Law. I actually
had a couple of questions, given that you guys are
absolutely experts on this sort of thing. I had a
couple of questions for you that I hope you won't
mind me asking, and that The first one is, I
(34:23):
have you your two most recent books in front of me.
I have Nates on the Edge, I have Maria's The
Biggest Bluff Stone Cold Classic Amazing. I looked in the index.
The word experiments does not appear in the index of
either of your books. Expected value, of course does appear,
(34:44):
but experiments does not. And I just wondered whether you
to brilliant risk takers, analysts, poker players. But I thought
a poker player can't really experiment, Like if you want to,
if you want to find out, you need to, you
need to make the bet. You know, you need to
put down the money. There's no cheap way to find
(35:05):
out what the other person's cards are. And maybe that
is a blind spot in poker playing relative to decision
making advice in everyday life, because what I've what I've
always been saying to people is Okay, if you're facing
an uncertain situation, you know, you don't know what the
right thing to do is. Maybe there's an experiment, maybe
(35:25):
that you can run a little pilot, Maybe you can
run a little you know, a b test. Maybe there's
a cheap way to find out without betting all your
chips metaphorically speaking. So I just wanted to ask why
why did neither of you talk about experiments? And is
this in fact a blind spot in the poker player's
view of the world.
Speaker 4 (35:45):
It's a great point to I have a home game
I play maybe every third week. That's a one dollar
two dollar game, which for me is you know, on
the lower side of the stakes I play, and I
probably am doing some experimenting in that game, right.
Speaker 3 (36:00):
You know?
Speaker 4 (36:00):
Last night I made I had a nut flushtra which
some of our artists will know what that means. I
had the Asi flustra on a boarder that was King
Queen x X. I made like a three x overbent
shove on the turn. I'm just getting an experiment. I
bet probably there's some frequency which you're supposed to do
this in game theory. But like, but if I lose
this pot, then you know, I'll win sometimes to catch
(36:21):
my flush and like it'll be a fun hand to
show down and whatever. But I did feel I think
we do probably experiment a little bit, and that kind
of like naughty feeling you have of like having an
experiment and getting away with it, like you're kind of
taking the piss to use. Is that the British term. Yeah,
you're taking the piss. You kind of get away with it.
Like that's a very satisfying feeling, and I think encourages
kind artistry sometimes.
Speaker 2 (36:42):
Yeah, yeah, I think that there are so two things. One, yes,
I think that you can experiment this way, and to me,
I do it when I move down in stakes as well,
right when the money is not not as meaningful and
you get to test certain theories out Right, So if
I'm studying and I'm kind of figuring out different possibilities
(37:04):
for playing similar spots, I might test those out and
feel comfortable testing them out when I don't care as
much about the stakes, when it's not kind of as important.
Now that said, we can't experiment as in the traditional
So I'm you know, I'm a trained psychologist, right, So
when I was doing studies for my PhD, you have
to have a very strict experimental design where you have
(37:25):
your control group, and you have your test groups, and
you know, you have all of these things where you're
trying to subtly change the conditions and see if the
outcome changes. That obviously you can't do because in some ways,
you know, my whole book was an experiment. So experiments
not in the index, but the biggest bluff, all of
it was was experiment. And I saw poker as kind
(37:47):
of a psychology laboratory of testing out a lot of
the psychological theories that I had kind of known in
theory and putting them into practice at the table and
being able to see, oh, you know, this is how
this plays out, this is how that plays out. And
I do think that poker is great for that. But
of course you can't when you're playing in a tournament,
(38:08):
when you're playing in a game, you can't have the
exact same conditions where you say, Okay, on this exact
same board, I'm going to do this, let's see what happens.
Speaker 1 (38:18):
All right.
Speaker 2 (38:19):
Pretend I didn't do that. Let's go back. Now, I'm
going to do something else and we'll see what happens there.
Because even if Nate and I were thinking, oh, okay,
let's see what it feels like to overbt three times
the pot in this particular spot, and Nay says, okay,
I'm going to do this, and then Maria you do
why people that's not in poker, that experiment is actually
(38:41):
not a valid control group because Nate and I are
so different. People respond to us differently, and all of
a sudden, you can't control the environment because it's a
different environment. The moment you switch out the players, right,
all of a sudden, the experimental conditions change, even if
you've changed literally nothing except who's sitting in that chair.
And I think that's actually fascinating and a really that's
(39:03):
how life works. That's why sometimes psych studies from the
laboratory don't generalize well to the real world, because the
real world does get messier and it's much more difficult
to control. No. Look, I think of your variables.
Speaker 4 (39:15):
As someone who's self reflectively kind of seen his social
status rise and fall different times. If you're charming and
privileged and are seen as being on a winning streak,
you can get away.
Speaker 3 (39:27):
With a lot. Yeah. People really are afraid to call
you on your bullshit.
Speaker 1 (39:32):
Yeah, okay, yes, second quick question. Second quick question, because
I have to take advantage of the opportunity to tap
into your wisdom. Okay, So you I think I think
it's fair to say that both of you would advocate
you're putting a probability on something. If you're going to
make a risky decision, you have to have an idea.
(39:52):
Is this like a five to one? Is is it
a three to one? Is there twenty percent chances is
going to happen? Is there are seventy percent chances is
going to happen? And you know, and there's a difference
between say a fifty three percent chance and a forty
eight percent chance, even though they're both close to fifty
to fifty. So it's important to quantify as much as
you can, even though you don't always have the data. Okay,
(40:15):
So two very little stories to get you to reflect
on the case in favor of quantification. Apparently, when the
US government was pondering the Bay of Pigs invasion, the
Joint chiefs of Staff thought that the chance of success
was thirty percent, and a report was prepared for President
(40:36):
Kennedy and Kennedy and thirty percent was presumably they thought,
are the president working to understand percentages? So he was
told there is a fair chance of success, and by
fair chance of success they meant well, thirty percent. Now
we don't know what Kennedy understood by a fair chance
of success, but he seems to have thought it was
a good chance of success, so and he approved this
(40:59):
total fiasco. So it might seem more user friendly to
express things as well, this is common or uncommon, or
likely or un likely, But actually none of those words
really mean the same thing to the person who's uttering
the word as to the person who's receiving it. So
you should always put probabilities on things. Here's the counterexample. Counterexample.
(41:22):
Think back to the financial crisis two thousand and seven,
two thousand and eight. You had quants putting probabilities on things.
This is the probability that such and such a thing
will default based on what we know about history, based
on what we know about other things that are correlated
with it. But actually all of those probabilities were spuriously precise.
(41:44):
People had too much confidence in the probabilities, and it's
fine to say, oh, we think there's like a zero
point five percent chance that this will default. That's fine.
Then the problem is you feed the zero point five
percent into a model, which gets fed into another model,
which gets fed into another model, and in the end
you'd be like, oh, well, we've repackaged this thing, and
now there's like only a one in a trillion chance
that this will default. And it turns out that that's
(42:06):
all dependent on the quality of your original sumption, and
you shouldn't be betting the existence of Western civilization on
that calculation. And people got it wrong. So the case
against quantification is once you have a number, then you
are tempted to rely on that number too much and
to analyze or to manipulate or to remodel or to
(42:27):
reanalyze that number too much, and to forget that actually
the number was always basically just an educated guess.
Speaker 2 (42:36):
Well, I think that when you're talking about quantification and
when you're talking about probabilities, it's the exact same logic
that you have to apply to algorithms and to kind
of building algorithms, which is something that Nate and I
have talked about on the pod with AI, which is
garbage in garbage out right. If your assumptions are garbage,
(42:57):
then your probabilistic assessment is going to be garbage. So
I actually think that both of these things they're not
counter examples. The thirty percent chance of the Bay of pigs.
I just think that these were people who had a
lot of qualifications, had done the research, had done regulus
rigorous analysis, and that was not garbage. And right there
(43:20):
they had assumptions that were there for a good reason.
They had good historical data. I have no idea how
they came upon the thirty percent. I'm just making yeah,
hindsight by us exactly, And so you get thirty percent
and by the way, you should absolutely have told Kennedy
thirty percent and not fair chance. There are so many
(43:41):
psych studies about this that trying to put words with
percentages backfires because people do not understand. It's like if
you have a weather man and says a fair chance
of rain, Right, let's talk about not a fair chance
that the Bay of pigs is a success fair chance
of rain? Do you bring an umbrella? You want to
(44:02):
know what the percentage chances. You want to know that
actual number because otherwise a quantification gets all out of whack.
Financial cis when you have those numbers in the models.
Those were people whose incentives were not aligned with giving
you a correct probabilistic assessment. Their incentives were to make money.
(44:22):
That's also a question that you have to make. You
always have to ask, and this is something that Nate
and I talk about as well. When you're making these assumptions,
do the incentives align, Where are the assumptions coming from,
and do you have an incentive to be correct? Right?
And in this particular case, their incentive was to make
(44:44):
money for them today and to make their company think
that this was going to be a great bet and okay,
that it was going to work out. And so those
percentages are not something that you want to rely on. Now,
if my incentive is if my percentage is wrong, I'm
getting fired. Right. If my percentage is wrong, then I'm
making zero dollars. Then all of a sudden, I come
(45:08):
up with different percentages, I use different inputs. My model
looks very very different. But Wall Street didn't work that way,
still doesn't work that way. That's not how you're incentivized.
Speaker 4 (45:17):
Yeah, look, I think there's a risk of laundering subjective
opinions through probabilities and forgetting their subjective right. If I'm
running link the airport, there's traffic on the van Wick
or whatever, right, I might say to myself it's a
five percent chance is going to miss my flight. Right,
It's not coming out of any regression analysis or anything.
You know, I've probably used the phrase in this show,
(45:38):
like quoting Vice President Harris. A model does not fall
out of a coconut tree. It exists in the context
of that which became before it, or whatever else you're
trying to get at the truth with the model. And
I think mediocre modelers in particular will publish a number
and then forget how many assumptions are driven into that.
Speaker 3 (45:58):
Right. Look, I still think it's worth quantifying things.
Speaker 4 (46:01):
I mean, at the end of the day, probability is
defined as a number between point zero and one, and.
Speaker 3 (46:09):
You have to make decisions even in conditions of uncertainty.
Speaker 4 (46:12):
But to Tim's point, yeah, I think there are cases
where people don't forget how provisional a guess is when
you put a number on it.
Speaker 2 (46:20):
Yeah, And I think it is always important to not
have a false sense of certainty. And there's also a
lot of data that shows that when you have numbers,
and when you have a lot of these things, it
does give you a false sense of certainty, right that
you often do become a little bit over confident when
you're like, well, I have this model in this model,
so it must be and there you have the bias
(46:42):
that we've talked about a lot, where it goes from
being probabilistic to seeming much more certain like this will
not default, This will not happen because you forget that
it ain't zero.
Speaker 1 (46:57):
Thank you so much, guys, fantastic Tim.
Speaker 2 (46:59):
Thank you so much for coming on the pod today.
It's been such a pleasure having you.
Speaker 1 (47:03):
Oh it's been really really fun. Thank you for sharing
your wisdom. And if people want to hear more about
Sound Israel or any other stories of things going disastrously
wrong and me trying to investigate the social science behind
why they went wrong cause New Tales with Tim Harford
is one of Risky Business's sister podcasts on pushkin.
Speaker 2 (47:23):
It is and there are lots of tales of risk
taking assessments that do not turn out quite the way
the risk taker thought they would. Risky Business is hosted
(47:49):
by me Maria Kunakova and me Mate Silver. The show
is a co production of Pushkin Industries and iHeartMedia. This
episode was produced by Isabel Carter. Our associate producer is
Gabriel Hunter Chang. Our executive producer is Jacob Goldstein.
Speaker 3 (48:04):
And if you want to listen to and add free version,
sign up for Pushkin Plus. For six seventy nine a
month you can access to ad free listening. Thanks for
tuning in
Speaker 1 (48:28):
H
Pushkin. Over the years, Cautionary Tales has warned you about
Ponzi schemes, dodgy Christmas savings clubs, and promotions that are
too good to be true. So it may come as
a surprise when I urge you to get into Risky Business.
Speaker 2 (00:33):
Don't worry.
Speaker 1 (00:34):
I'm not trying to pull a fast one. I just
want you to try out a podcast I think you'll enjoy.
Risky Business is a weekly show about making better decisions.
The hosts, Maria Konakova and Nate Silver, are both writers
and high stakes poker players. Maria and Nate cover everything
from politics to poker to personal decisions, so when they
(00:55):
asked me to join them for an episode, I was
eager to try. I even got the chance to talk
to Maria about one of the fraudsters featured in Cautionary Tales.
She has met him and he assured her yes, he
was a liar. You can listen to Risky Business wherever
you get your podcasts, But for now, here's the episode
featuring me. I hope you like it. There are duels,
(01:17):
prison breaks, banking bubbles, poetry, and Nate reveals he has
a relative who faked his own death.
Speaker 2 (01:30):
Hi, everyone, Welcome back to Risky Business, our show about
making better decisions. I'm Maria Kanikova.
Speaker 3 (01:36):
And I'm Nate Silver.
Speaker 2 (01:38):
So today we have a slightly different and fun show
for you. We're going to be bringing on a very
special guest, Tim Harford, who hosts another Pushkin podcast, Cautionary Tales,
and we'll be talking about the intersection of risk and
cautionary tales from history. Tim, welcome to the show to
(02:03):
be on the show. Thank you so for listeners of Pushkin,
you're probably familiar with Tim as the host of Cautionary Tales.
I've been lucky enough to be on the show and
to have been a listener of the show. I think
it's wonderful. My episodes are obviously the best, but it's
all pretty good. Tim is an economist, a journalist. He
(02:24):
has a column in the Financial Times, He's written multiple
amazing books. You know, longtime friend of the two of us. Nate,
I don't know if you want to add anything else,
but we're so happy to be here and to do
kind of an episode where Cautionary Tales and Risky Business intersect,
where we talk about cautionary tales that are about risky business.
(02:45):
That are about risk, about taking risks, about how risk
taking can go wrong, and how sometimes you know, the
lines between legitimate risks and cons and deceptions might get
blurred a little bit and cross over into territory that
goes from legitimate to illegitimate very quickly.
Speaker 3 (03:04):
Do you mean to say that campbling doesn't always work out, Maria?
Speaker 2 (03:06):
It's weird, it's so weird.
Speaker 1 (03:08):
The chance of loss is in fact one hundred percent,
which I guess we'll get we'll get to that, but yes, that.
Speaker 2 (03:13):
Is absolutely true. So when we were kind of thinking
about ways to make this episode work, Tim, you thought
about one particular story where you and I have actually
intersected on this because we've both thought about this person
and he's someone who I actually had on my previous podcast,
The Grift, and he is a well, let's let's have
(03:36):
you lay him out. Let us meet Sam Israel, the
first kind of our first subject for today.
Speaker 1 (03:42):
Sam Israel, the third I think is his full name. Third,
absolutely remarkable gentleman if gentlemen is the right term, and
it probably isn't. So we did a Cautionary Tales episode
live on stage about pyramid schemes and Ponzi schemes and
white people fall for them, but also white people set
(04:05):
them up. And this kind of strange snowball of disaster
where the Ponzi scheme becomes increasingly difficult to cover. And
the most amazing example I've ever come across is by
You Capital, which was set up by Sam Israel. I
saw one writer described Sam Israel and by You Capital.
(04:26):
It's like somebody took the Bernie Madoff story but was
told to write a Hollywood script and to punch it
up a bit, make it sing a bit more. And
everything that made made Off's Ponzi scheme notorious applies to
Sam Israel, but it just all gets crazier. So Sam
(04:48):
came from a wealthy family, I think of commodity traders
in Louisiana, but he wanted to show he could make
it himself, and he got into Wall Street at an
early age, absorbed that Wall Street culture, you know, all
that kind of broish culture of Wall Street in the
nineteen eighties. And so he takes all this in, he
(05:11):
keeps his mouth shut. He watches various dubious activities, and
not just the kind of the sex work and the excess,
but also illegality, financial illegality, observes people kind of insider trading,
for example, and then he sets up his own firm,
by You Capital, which is a hedge fund, and very quickly,
(05:32):
by You Capital turns from being a hedge fund into
being a ponzi scheme. And just to remind people what
a ponzi scheme is, it's very simple. Investors give you money,
and then you announce you've made massive profits, and then
more investors give you money, and you announce you made
even more massive profits, and then more investors give you money,
and you keep saying you've made massive profits. And if
(05:53):
anybody ever says, that's great, I'd like my money back, well,
that's easy. You can give them the money back with
the profits because more people keep giving you, keep giving
you their money. And the insight that Sam Israel had
was with a hedge fund, it's kind of open ended.
The money keeps growing, and why would anybody ever want
their money back if you keep telling them they made
(06:14):
another twenty percent this year, they made another twenty five
percent this year, Like no one ever asks for their
money back. They just leave the money with you. And
so the fraud went on for a very long time,
and then things started to unravel. But Maria, you met
Sam so so, and you met Sam in prison, so
a spoiler. So tell us what did you make for
him as a person? How did he get into this?
(06:35):
Why did he get into this?
Speaker 2 (06:36):
Well, it's funny because my interview with him was from
a while back, you know, twenty seventeen something like that.
I honestly don't remember.
Speaker 1 (06:47):
We should say he was arrested, I think in about
two thousand and seven, two thousand and eight something like that.
Speaker 2 (06:53):
Wasn't yeah, exactly exactly, but so I was trying to
refresh my memory, and you know, just looked at some
of the transcripts and then also looked at an interview
that he did with Andrew Ross Sorkin, and he told
us the exact same thing at the beginning, which is like,
don't believe me, I'm a liar. And it's so funny
(07:13):
because I think that he thinks that that absolves him, right,
if he puts that disclaimer up top, then he can
sort of charm his way out and say, but actually,
I'm a good guy, right, I'm not like that bad
guy made off.
Speaker 1 (07:29):
So I should say there's one amazing scene. Gee Lawson
wrote this book The Octopus, which is like the quintessential
account of Sammy's wail. But there's a scene in that
book where his wife walks in and catches him bent
over his desk snorting cocaine through a fifty dollar bill
and says, why are you taking cocaine? And he goes,
(07:49):
how dare you accuse me of taking drugs? So yeah, sorry,
I interrupted, but.
Speaker 2 (07:54):
No, he is. It is the kind of guy he is.
And you know, he was incredibly charismatic, and he said,
I was doing really really well on Wall Street. Right,
he kind of got in. He didn't want to compete
with his siblings, wanted to do it on his own,
so he didn't want to go into the family business. Instead,
he had this opportunity to go into Wall Street, worked
(08:16):
at a very successful hedge fund, and was actually making money.
By the way, this is all according to sam Israel, Right.
I haven't actually looked at his returns. I did not
look at his balance sheets. I don't know how he
did as a trader. He assures me that he was
making millions for people and for himself in his prior
Wall Street days. So let's just we'll take that on faith.
(08:38):
But what I've learned working with con artists is you
can't take anything on faith, so asterisk. But he was
very successful on Wall Street, and I assume he must
have been to a certain degree because he started his
own hedge fund right and he was able to raise
I think about three hundred million to begin with of
outside money, which back then this was nineteen ninety six,
I want to say something around somewhere around there in
(08:59):
ninety so that was a lot of money. And he
went in with a partner who was a close friend
of his, who was a disgraced fund manager whose fund
had just gone under. But Sam believed in him and
thought that, you know, that he was a good guy
and that this would work. So the way Sam told
it to me was that when they started by you
(09:20):
in nineteen ninety six, he kind of relied on this guy,
you know, to be an equal partner, and that this
guy was started losing a lot of money, and Sam said, well,
I'm a good trader, I'm good at this. I'll be
able to kind of work my way out of the hole.
But he couldn't, and the hole kept getting bigger, and
so at some point he realized, you know, shit, we've
(09:42):
lost twelve percent in our first year. You know, it's
even worse in our second year. This is looking bad
and our ability to raise money is going down because
our returns are shit. They're absolutely horrible. And so that's
when it became a Ponzi scheme.
Speaker 1 (09:56):
And his accountant, who was a guy called Dan Marino. Hell,
there is footnote for body. Well if anybody so think
about it, this is nineteen ninety six. If anybody googles
as pre google, right, if anybody who tries to search
on the Internet for Dan Marino, they get the football player.
So he's working with this accountant who is completely invisible
(10:19):
to Internet searches. And the accountants are smart. Yeah, it's
really smart. The accountant's completely crooked and basically sets up
his own fake Uh.
Speaker 4 (10:29):
Sounds like a cricket I've read a stereotype based on
last but Deno sounds like a cricket account accountant or
an NFL quarterback.
Speaker 1 (10:36):
So he sets up his own fake auditing firm. So
he's basically auditing his own accounts. And if anybody sort
of were to really go and check the go the
guy who says that Dan Marino's accounts are genuine is
an uditor called Dan Marino, and they're the same guy,
so that that was kind of an important part of
this fraud. But yeah, Dan Marinos told the author Gey
(10:58):
Lawson that one of the problems was, there's this idea, Oh,
we're going to have a really good year, We're going
to make a lot of money for real. And when
we make a lot of money for real, then it
will no longer be a palmzy scheme. You know, we'll
have you know, it's all genuine, it all come out
good in the end. Dan Marino said. The problem is
sometimes they did have good years, but whenever they had
(11:20):
a good year, they would claim it was an even
better year, and whenever they had a bad year, they
would never admit that they had a bad year. So
there was a you know, whatever it was, vanity, fear
of the consequences, whatever it was. He just made it
completely impossible for him ever to catch up with his
own life.
Speaker 2 (11:37):
And I think that that's very typical of con artists,
right where they say I'll fix it, I'll make it better.
This isn't this is just temporary, but it never is.
But the most incredible thing about Sam Israel is that
once the scheme kind of comes undone, right, which happens
at some point, just like with SBF. Note right, at
(11:58):
some point people are going to ask for their money
and people are going to get spooked. And when they
get spooked, like there's going to be a day of reckoning.
And he had a moment where he said, oh shit,
you know I'm going to jail. And he thought he
would get seven or eight years, which was pretty typical
for white collar criminals. And then they switched judges and
(12:20):
the judge gave him two hundred and forty months, so
twenty years right instead. And he was like, oh shit,
you know I can't do twenty years. I'm going to
be an old man. This is this is not cool.
I was ready for seven I can't do twenty. And
so instead of you know, figuring out how do I
(12:42):
deal with this, he decides to fake his own death.
Speaker 1 (12:44):
Yeah, which he's obviously going to work out really well.
Speaker 2 (12:47):
Oh it's going to work out great, We'll be back
in a minute. He only has a few months to plan, right,
It's not like he has been thinking, oh, I'm going
to fake my own death. This is my exit strategy.
(13:08):
Because a lot of connor is they don't think that
far ahead, right, They don't think of the exit strategy.
They think it's always going to work out. So he says,
I'm gonna I'm gonna fake my own death. I've watched
this really cool movie it's called r V, and I'm
going to buy an RV and I'm going to, you know,
just go around the country and maybe make my way
to go by the way. One of the things he
(13:28):
told me was that as after his sentencing, as he
was walking out, an FBI agent, one of the ones
he'd gotten friendly with, looked at him and said, I
have two words for you, Costa Rica. I find it
very difficult to believe that that actually has.
Speaker 1 (13:44):
Yes, I also doubt.
Speaker 3 (13:48):
Marino Dan Marino two woods to you, Costa Rica. I
don't know what.
Speaker 2 (13:54):
I think.
Speaker 1 (13:54):
You've got a career this so but I'm curious. So, Marie,
you said that this is very this is short term thinking.
He didn't. He wasn't really thinking to the consequences of
his actions, and that that's true. Any Ponzi scheme inevitably
become completely unsustainable. You cannot possibly keep it going. It
will come to an end. So what is the way out?
(14:17):
And then the faking the suicide again like of course
he's gonna get caught. Of course that's not going to work.
Speaker 2 (14:21):
So yeah, he decided he was going to jump off
a bridge.
Speaker 1 (14:24):
Well not just he decided he was going to pretend
that he had jumped off.
Speaker 3 (14:27):
A bridge, right, he actually jumped off a.
Speaker 1 (14:29):
Bridge because he because he then he did actually actually claim.
Speaker 2 (14:35):
Actually he actually jumped off a bridge. He did. So
this is the research he was doing. When you're trying
to fake your own death, and I interviewed this woman,
Elizabeth Greenwood, who wrote about faking your own death, you
have to think very far ahead. You have to figure
out money. You know, how am I going to be
off the grid right these days? Like how am I
going to survive? How am I going to get out
of the country, and you know where where's my cash
(14:58):
going to come from? All of these things. Instead, what
he spends his time thinking is researching all of the
bridges in New York to try to figure out which
one he could conceivably jump off of an die. So
he finds a bridge that's under construction, so there are
nets underneath, and he's like, oh, perfect, Like I'm gonna
(15:19):
jump and I'm going to land in the net and
then I'll use the net to scramble up and get out.
So he does this, not realizing that those nets are
pretty damn hard to climb out of, so he manages
to make the net. By the way, thinking about risk, right,
risk reward if you miss the net, the you know
(15:41):
the risk reward equation there is not great.
Speaker 1 (15:45):
The designed to catch people or just like a span
of that somebody drops.
Speaker 2 (15:49):
I mean that's the right, No, it's I think it
was gonna I think it was designed to catch bricks
and you know, falling debris from construction. So when a
person goes into it, it just like you know, it
goes all the way down. So then he's stuck in it.
And at this point he's like, I think I'm going
to die anyway, except it's going to be much worse
because I'm going to have spent my last minute trying
to scramble up this net. But he actually does manage
(16:12):
to get out, and he has a driver waiting for
him to take him to his RV and he thinks
he's going to drive off into the sunset. Oh, by
the way, another really really important thing, if you're trying
to fake your own death, do not tell your mother,
your girlfriend, your son, and the driver that you're going
(16:34):
to be faking your own death. Don't worry, mom, I'm
not actually going calling uber.
Speaker 3 (16:41):
Do it in style.
Speaker 2 (16:43):
But that's this is what happened. So you know, he's
fucked from the beginning because he has not thought any
of this through. But he does manage to make it
out of the net. He's met by a driver, makes
it to his RV, and for the first few weeks
it actually seems like everything is kind of okay because
even though he's living in an RV, living in RV parks,
(17:06):
you know, he's kind of getting away with it. And
then he walks into a bar one day and he
sees himself on TV on America's Most Wanted, and he
goes and reads about himself on the Internet, which is
a big, big no no if you're faking your own
death to start googling yourself, but he does that, and
he sees that his girlfriend has been arrested as an
(17:28):
accomplice and that they're looking to arrest his mother. He
doesn't realize that this is a trap, that the police
do this kind of thing to try to get people
kind of out of hiding. He thinks this is real,
and so he gets on a motorcycle, goes to the
police department to turn himself in, walks in. He says,
you know, hey, I'm here to turn myself in, and
(17:48):
the police officers like what you know? In for what?
You need to use the bathroom, like it's over there anyway,
there's all of this miscommunication. He says, no, you know,
I turning myself in. I'm wanted and I just don't
want any press here. And at this point the police
officer actually looks at him, realizes who he is, and
that is when he gets caught and gets an additional
(18:12):
two years added on to his sentence for faking his
own death and running away.
Speaker 1 (18:16):
It's astonishing. I'm not one thing you said, Maria. You
said that the craziest thing about him, or the most
amazing thing about him. I'm not even sure that is
the craziest thing about him. But you know, we haven't
got all day, so that there are other stories you
could tell about Sam. But I wanted to ask Nate.
Given that, Nate, you've been thinking about the habits of
(18:37):
risk taking individuals, these people you call Riverians. Is short
termism part of the or kind of a side effect
or a glitch in the Riverian thinking system. So on
the one hand, you need that ability to think probabilistically,
you need that ability to take calculated risks. But I mean,
(18:59):
Sam as Weel just seems to have never been able
to see past the It had no problem taking risks,
but just couldn't see past the end of his nose.
Speaker 4 (19:07):
Yeah. No, look, I think the better investors and gamblers
have a longer time horizon. That's kind of one of
one of Silicon Valley's secrets, despite their mini flaws, that
they do kind of think ten years ahead. But yeah,
some of this sounds very familiar, Marie, I know if
I'm talking to you, the notion of like a good
business gone bad. I mean, even FTX was a pretty
(19:28):
good business, right, It was like the leading brand for
crypto trading. They made legitimate profits, et cetera. But like
you know, it turns sour or I think you know,
Sam bacon Free couldn't resist the temptation to take all
this money staying on the sideline. He couldn't like resist
the temptation to go and gamble with it. But yeah,
the lack of advanced planning coupled with the kind of
(19:50):
miscalculating consequences. You know, if you're very charming, which I
think Sam Israel is more so than SBF, it's a
different story. You can kind of weasele your way out of.
Speaker 3 (20:00):
Things, right.
Speaker 4 (20:01):
You can think you can like dance your way out
of anything, and you can up the con a level
or two or three, and then you may on some level, no,
it's not going to work.
Speaker 3 (20:10):
But I don't know. I mean, at some point there's
a point of no return, right.
Speaker 2 (20:15):
There is a point of no return. Yeah, I think
I think that's absolutely right, Nate. I think one of
the this is a characteristic that you have both uh,
both with raverians and non reveriance and and Tim. I'm
sure you've come across this in other cautionary tales, but
I think a lot of it is this over confidence
in hubris, right, that comes with a certain level of
(20:36):
success and people. And I think to be an entrepreneur
and to be a risk taker, you need to be
over confident to a certain extent. You know, as as
we all know, if you actually know your odds of success,
you're not gonna You're not gonna start the damn company
you're not gonna You're not gonna try it because it's
the risk of failure and the chances of failure are
(20:58):
so high, So it's a it's this fine balance, and
I think over confidence so turns into delusion and turns
into this thinking that actually, you know, I can keep
doing this forever. And because you've gotten away with it
for so long, it seems like probabilistically speaking, you know,
(21:19):
your base rates change, I've gotten you know, okay, you
know one year, two years, three years, four years, everything's good,
This is all going good.
Speaker 4 (21:27):
Yeah, if the coin comes up heads five times in
a row, I mean you see it.
Speaker 3 (21:32):
In poker all the time, right, Yeah.
Speaker 4 (21:35):
You know, winner's tilt is something which is maybe underdiscussed
loser tilt we all have experienced, maybe Maria, but Winter's
tilt where you're on a hot streak and you're like a,
maybe I have some gift from God to play poker
really well or something is also a big deal.
Speaker 2 (21:52):
It absolutely is. One of My favorite psych studies is
from Ellen Langer, and I think the name of the
paper is something like heads, I win tails, It's chance
something like that. Yeah, And she had people bet not bet,
but guess the results of a coin toss, and it
(22:13):
was actually not a fair coin. It was rigged, and
there were different Basically, it came up heads and tails
the exact same number of times in all of the
different conditions, but in some of them it was pretty random.
In others it was clustered near the end, and in
the most important condition, the correct guesses were clustered near
(22:34):
the beginning, right, So basically you would say, you know, heads,
you'd guess, and then they'd make sure it landed on heads.
It was a rigged toss, so that you were right
it was yeah, And the people who were correct clustered
at the beginning would then and these were Harvard students,
by the way. Then they got all sorts of questions
like I'm good at predicting the outcomes of coin tosses,
(22:58):
and they would rate themselves as actually quite good at it.
They would say, if I had more time to practice
and to guess, I'd get even better. So things that
made it very clear that they thought that this was
a skill and not actually completely random. And it was
so easy to get people to believe that they were
skilled at something where it was just complete randomness when
(23:18):
they had those those things happened at the beginning. So Tim,
I think this goes back to the beginning of your question.
This is how you get into Ponzi schemes. Think about
Bernie Madeoff right. He was successful for far longer than
Sam Israel, and Sam Israel, by the way, was the
single biggest Ponzi scheme before Bernie made Off.
Speaker 1 (23:34):
Now I am I'm curious. We've been talking about people
who were have an appetite for risk and who it
all came apart for Maria, I know you've been doing
a little bit of research into one of the most
important gamblers in economic history.
Speaker 2 (23:53):
Yeah, John Law. He was someone who I wrote about
for The Confidence Game and I've come back to so
my next book is about cheating. So I've kind of
been thinking about him. But one of the reasons I
am interested in John Law. So when we're talking about
someone like Sam Israel, right, it's pretty clear con artist,
(24:14):
right Ponzi scheme. When you're talking about someone like John Law,
it becomes much less clear because he's someone who was
a huge gambler and we know that sometimes he was successful,
but he also ran his father's business into the ground.
If I remember correctly through gambling. But I guess he
got better with time and killed.
Speaker 4 (24:36):
Man and likely killed a man literal gambling or like
literal gambling.
Speaker 2 (24:41):
So yeah, so he was someone who came from money.
Who's you know whose parents had a financial business.
Speaker 1 (24:48):
We should say it was seventeen hundreds, just just a situation, right, Yes,
for those small number of listeners who don't know who
John Law is or everybody should.
Speaker 2 (24:57):
We're in the seventeen hundreds and he's going to be
making friends with the Duke of Orleans or the Duke
of Orleans who was then Regent of France, and he's
going to be basically setting up France's banking system. So
the reason why I was fascinated by him is that
it's actually unclear if he was a con artist or not,
(25:18):
like did he believe that? Because it was the kind
of the end of his time at the height of
finance was with the establishment of this thing called the
Mississippi Company, which was a huge bubble and basically bankrupted
a ton of people. And the question is, you know,
(25:39):
did he know what he was doing and get unlucky
or did he like basically did he do this as
a kind of Ponzi scheme as a kind of con
or not.
Speaker 1 (25:47):
And the fact that we still don't really agree on that,
I think is fascinating. I mean, we should say so.
He he was originally Scott, a Scott. He he killed
a guy and a duel, was sentenced to death for murder.
Escape from prison, traveled Europe, wound up in Paris, made
a few friends with some influential nobles, made a huge
(26:09):
amount of money gambling because he would set himself up
as the house and he understood the probability enough that
he knew he had an edge. So he's gambling with
all these nobles. He's making a huge amount of money.
And then he sets up his own bank and he
starts issuing paper money. This is not the first paper
(26:32):
money in the history of the world, it's not even
the first paper money in the history of France, but
it is. It's pretty new and people are still trying
to figure out kind of how it works. And of
course this is revolutionary. He's ahead of his time, like
paper money is how we do things right. It's kind
of amazing. And then the whole thing just gets wrapped
up with French government debt and gets wrapped up with
(26:53):
the Mississippi bubble, and the Mississippi bubble was it was
a stock market bubble. One stock was involved, the stock
of the Mississippi Company, and John Law controlled the Mississippi Company.
But it was clear that nobody really understood what was
going on except that go up, and if numb, but
go up, everyone everyone gets very excited.
Speaker 4 (27:12):
Yeah, it's very intoxicating when the number goes up. Right,
I did wonder too, there is some survivorship bias in
which kind of scams and schemes we discover, you know,
the best frauds in history. Probably nobody knows about it. Yeah,
good point. Sbl was convinced that he could somehow navigate
his way through bankruptcy, or not through bankruptcy, now, his
(27:35):
way through this downfall and bitcoin and come out on
either side of it.
Speaker 3 (27:38):
And maybe people wouldn't really notice.
Speaker 4 (27:40):
Right, Maybe it's like a page a sixteen story, not
in a one story. If he like, if there's a
spontaneous rise in bitcoin prices and they recover these losses
that they have, although they were ten million and ten
billion in a hole, which is pretty hard to overcome.
Speaker 2 (27:53):
It's funny, Nate. I think it's that's a really important
point that the best con artists are never caught. When
people when we talk about connartists and people ask me,
you know, why aren't there as many female con artists,
I say a few things, but one of the it's
kind of a joke but kind of not, which is
that they're just better at it. So we don't know
(28:15):
them because they haven't been caught. They don't have as
much ego, and they know when to disappear and how
to disappear much better than the sam Israel's of the world.
Speaker 4 (28:25):
Or like cheating in poker, a lot of these famous
cheating scandals, like online cheating scandals, people are are very
greedy where they win at like, you know, thirteen centered
deviations above some random rate, whereas if we won at
two center deviations above random, it would be almost impossible
to detect and you'd have a great life. Although we
don't find those people though, right, we don't find the
(28:45):
people that are that are actually good at cheating a.
Speaker 3 (28:47):
Lot of time.
Speaker 2 (28:49):
Yeah, but so so as we you know, wrap up
the story of John law I do think that it's
interesting that, I mean, economists don't agree, historians don't agree
whether whether or not he was, you know, greedy cheat.
He was obviously greedy. I think everyone agrees on that,
but whether he thought that this could actually all worked out.
I found a rhyme that I would love to share
(29:12):
if you guys are in poetry mode, that come from
the time about what happened with the Mississippi bubble. And
it goes like this. My shares, which on Monday I bought,
were worth millions. On Tuesday, I thought so. On Wednesday,
I chose my abode in my carriage. On Thursday I
rode to the ballroom. On Friday I went to the workhouse.
(29:34):
Next day I was sent.
Speaker 3 (29:36):
First poetry reading on the Risky Business podcast.
Speaker 2 (29:39):
I believe it is.
Speaker 1 (29:40):
It is I think that should stop tradition. That's very good.
Speaker 2 (29:45):
And one nobleman of the time said, thus sends the
system of paper money, which has enriched a thousand beggars
and impoverished one hundred thousand men. And obviously that's not true,
which is why we You know, that was not the
end of the system of paper money. It was just
it just happened to be the end of John Law.
He had to escape France, by the way, because he
(30:05):
was convicted and was going to be sent to prison there.
So he dressed up as a beggar, ran away to
Italy and died in Venice, totally impoverished. And I guess
the cautionary tales.
Speaker 1 (30:17):
It is a cautionary tale. And I guess the lesson,
or maybe the lesson is that the economics lesson is,
if you're going to have paper money, if you're going
to have somebody who has the right to just create
money with the printing press, you've got to make sure
you have the right controls over that person or over
that institution. It can't just be some guy who killed
a guy in a duel and came over one a
(30:39):
lot of money and gambling and then he's the guy
who can do it.
Speaker 3 (30:42):
It's you.
Speaker 1 (30:43):
You need this institutional scaffolding, which you know, when we
have it, it seems to work just fine.
Speaker 3 (30:50):
We'll be back right after this.
Speaker 4 (31:06):
I mean, are there like two or three on big takeaways,
like common patterns and when you know something is becoming
a cautionary tale or a can.
Speaker 1 (31:18):
At the risk of quoting that classic opening line of
Ana Karenina that all happy families are alike and every
unhappy family is unhappy in its own way, I think
one of the striking things about cautionary tales is that
there are a lot of different ways for things to
go wrong. The organizational problems, informational problems, engineering problems, hubris
(31:47):
and arrogance, short sightedness, lots and lots of self delusion,
lots of wishful thinking. I mean, it's a miracle that
human civilization survives, actually, given how many different ways there
are to go wrong. But I mean that is part
of the slightly perverse joy of researching and writing these
(32:08):
cautionary tales. There is always a new disaster, and always
a new way for disaster to happen.
Speaker 2 (32:16):
You make that sound almost gleeful.
Speaker 1 (32:18):
Yeah, I mean sometimes I have to remind myself that, like,
I'm not supposed to be enjoying this, because some of
them are very, very sad. Some of them are straightforwardly
hilarious and no great harm is done, but a lot
of them are pretty painful.
Speaker 4 (32:33):
Yeah, Maria, I remember you telling me that, like, cons
are most likely to occur when you're in an upcycle
or a down cycle, right, not in the steady state,
but when there's something new and novel and people are panicking.
Speaker 2 (32:44):
Yeah, moments of transition. So whether those are societal transitions
or whether they're personal transitions, is when you're most vulnerable
to get cons So it's not a personality trait. It's
not intelligence, it's not it's not anything like that. It
is this kind of moment of either up or down
euphoria or you know, despondency. But when things are uncertain
(33:10):
and your worldview gets challenged, gets shattered, gets displaced, you
look for certainty and that's when con artists swoop in
and give that certainty to you.
Speaker 1 (33:21):
So as long as nothing ever changes, we will say
from Collins, we're good.
Speaker 4 (33:26):
You know my uh my great grandfather faked his death
and got a.
Speaker 2 (33:31):
Wait what okay, Nate, can we just can we we
need this story. I'm sorry we're pausing everything, Nate, please.
Speaker 3 (33:38):
I mean his name was Ferdinand Thrunn, which is a
great name.
Speaker 2 (33:42):
It's an amazing name.
Speaker 4 (33:42):
He was written up in the Chicago Tribune and the
New York Times and places like that. Yeah, he was
like an insurance frauds ster. We should do this as
a separate segment sometime, yeah, But basically his technique was
to commit crimes so devious that there was no law
to charge them with. Because I hadn't figured out like
this particular type of fraud. But we should do proper
research and do an episode on this.
Speaker 1 (34:02):
Maria, Yeah, absolutely so, so Maria Knight. I now we've
discussed some as well. We discussed John Law. I actually
had a couple of questions, given that you guys are
absolutely experts on this sort of thing. I had a
couple of questions for you that I hope you won't
mind me asking, and that The first one is, I
(34:23):
have you your two most recent books in front of me.
I have Nates on the Edge, I have Maria's The
Biggest Bluff Stone Cold Classic Amazing. I looked in the index.
The word experiments does not appear in the index of
either of your books. Expected value, of course does appear,
(34:44):
but experiments does not. And I just wondered whether you
to brilliant risk takers, analysts, poker players. But I thought
a poker player can't really experiment, Like if you want to,
if you want to find out, you need to, you
need to make the bet. You know, you need to
put down the money. There's no cheap way to find
(35:05):
out what the other person's cards are. And maybe that
is a blind spot in poker playing relative to decision
making advice in everyday life, because what I've what I've
always been saying to people is Okay, if you're facing
an uncertain situation, you know, you don't know what the
right thing to do is. Maybe there's an experiment, maybe
(35:25):
that you can run a little pilot, Maybe you can
run a little you know, a b test. Maybe there's
a cheap way to find out without betting all your
chips metaphorically speaking. So I just wanted to ask why
why did neither of you talk about experiments? And is
this in fact a blind spot in the poker player's
view of the world.
Speaker 4 (35:45):
It's a great point to I have a home game
I play maybe every third week. That's a one dollar
two dollar game, which for me is you know, on
the lower side of the stakes I play, and I
probably am doing some experimenting in that game, right.
Speaker 3 (36:00):
You know?
Speaker 4 (36:00):
Last night I made I had a nut flushtra which
some of our artists will know what that means. I
had the Asi flustra on a boarder that was King
Queen x X. I made like a three x overbent
shove on the turn. I'm just getting an experiment. I
bet probably there's some frequency which you're supposed to do
this in game theory. But like, but if I lose
this pot, then you know, I'll win sometimes to catch
(36:21):
my flush and like it'll be a fun hand to
show down and whatever. But I did feel I think
we do probably experiment a little bit, and that kind
of like naughty feeling you have of like having an
experiment and getting away with it, like you're kind of
taking the piss to use. Is that the British term. Yeah,
you're taking the piss. You kind of get away with it.
Like that's a very satisfying feeling, and I think encourages
kind artistry sometimes.
Speaker 2 (36:42):
Yeah, yeah, I think that there are so two things. One, yes,
I think that you can experiment this way, and to me,
I do it when I move down in stakes as well,
right when the money is not not as meaningful and
you get to test certain theories out Right, So if
I'm studying and I'm kind of figuring out different possibilities
(37:04):
for playing similar spots, I might test those out and
feel comfortable testing them out when I don't care as
much about the stakes, when it's not kind of as important.
Now that said, we can't experiment as in the traditional
So I'm you know, I'm a trained psychologist, right, So
when I was doing studies for my PhD, you have
to have a very strict experimental design where you have
(37:25):
your control group, and you have your test groups, and
you know, you have all of these things where you're
trying to subtly change the conditions and see if the
outcome changes. That obviously you can't do because in some ways,
you know, my whole book was an experiment. So experiments
not in the index, but the biggest bluff, all of
it was was experiment. And I saw poker as kind
(37:47):
of a psychology laboratory of testing out a lot of
the psychological theories that I had kind of known in
theory and putting them into practice at the table and
being able to see, oh, you know, this is how
this plays out, this is how that plays out. And
I do think that poker is great for that. But
of course you can't when you're playing in a tournament,
(38:08):
when you're playing in a game, you can't have the
exact same conditions where you say, Okay, on this exact
same board, I'm going to do this, let's see what happens.
Speaker 1 (38:18):
All right.
Speaker 2 (38:19):
Pretend I didn't do that. Let's go back. Now, I'm
going to do something else and we'll see what happens there.
Because even if Nate and I were thinking, oh, okay,
let's see what it feels like to overbt three times
the pot in this particular spot, and Nay says, okay,
I'm going to do this, and then Maria you do
why people that's not in poker, that experiment is actually
(38:41):
not a valid control group because Nate and I are
so different. People respond to us differently, and all of
a sudden, you can't control the environment because it's a
different environment. The moment you switch out the players, right,
all of a sudden, the experimental conditions change, even if
you've changed literally nothing except who's sitting in that chair.
And I think that's actually fascinating and a really that's
(39:03):
how life works. That's why sometimes psych studies from the
laboratory don't generalize well to the real world, because the
real world does get messier and it's much more difficult
to control. No. Look, I think of your variables.
Speaker 4 (39:15):
As someone who's self reflectively kind of seen his social
status rise and fall different times. If you're charming and
privileged and are seen as being on a winning streak,
you can get away.
Speaker 3 (39:27):
With a lot. Yeah. People really are afraid to call
you on your bullshit.
Speaker 1 (39:32):
Yeah, okay, yes, second quick question. Second quick question, because
I have to take advantage of the opportunity to tap
into your wisdom. Okay, So you I think I think
it's fair to say that both of you would advocate
you're putting a probability on something. If you're going to
make a risky decision, you have to have an idea.
(39:52):
Is this like a five to one? Is is it
a three to one? Is there twenty percent chances is
going to happen? Is there are seventy percent chances is
going to happen? And you know, and there's a difference
between say a fifty three percent chance and a forty
eight percent chance, even though they're both close to fifty
to fifty. So it's important to quantify as much as
you can, even though you don't always have the data. Okay,
(40:15):
So two very little stories to get you to reflect
on the case in favor of quantification. Apparently, when the
US government was pondering the Bay of Pigs invasion, the
Joint chiefs of Staff thought that the chance of success
was thirty percent, and a report was prepared for President
(40:36):
Kennedy and Kennedy and thirty percent was presumably they thought,
are the president working to understand percentages? So he was
told there is a fair chance of success, and by
fair chance of success they meant well, thirty percent. Now
we don't know what Kennedy understood by a fair chance
of success, but he seems to have thought it was
a good chance of success, so and he approved this
(40:59):
total fiasco. So it might seem more user friendly to
express things as well, this is common or uncommon, or
likely or un likely, But actually none of those words
really mean the same thing to the person who's uttering
the word as to the person who's receiving it. So
you should always put probabilities on things. Here's the counterexample. Counterexample.
(41:22):
Think back to the financial crisis two thousand and seven,
two thousand and eight. You had quants putting probabilities on things.
This is the probability that such and such a thing
will default based on what we know about history, based
on what we know about other things that are correlated
with it. But actually all of those probabilities were spuriously precise.
(41:44):
People had too much confidence in the probabilities, and it's
fine to say, oh, we think there's like a zero
point five percent chance that this will default. That's fine.
Then the problem is you feed the zero point five
percent into a model, which gets fed into another model,
which gets fed into another model, and in the end
you'd be like, oh, well, we've repackaged this thing, and
now there's like only a one in a trillion chance
that this will default. And it turns out that that's
(42:06):
all dependent on the quality of your original sumption, and
you shouldn't be betting the existence of Western civilization on
that calculation. And people got it wrong. So the case
against quantification is once you have a number, then you
are tempted to rely on that number too much and
to analyze or to manipulate or to remodel or to
(42:27):
reanalyze that number too much, and to forget that actually
the number was always basically just an educated guess.
Speaker 2 (42:36):
Well, I think that when you're talking about quantification and
when you're talking about probabilities, it's the exact same logic
that you have to apply to algorithms and to kind
of building algorithms, which is something that Nate and I
have talked about on the pod with AI, which is
garbage in garbage out right. If your assumptions are garbage,
(42:57):
then your probabilistic assessment is going to be garbage. So
I actually think that both of these things they're not
counter examples. The thirty percent chance of the Bay of pigs.
I just think that these were people who had a
lot of qualifications, had done the research, had done regulus
rigorous analysis, and that was not garbage. And right there
(43:20):
they had assumptions that were there for a good reason.
They had good historical data. I have no idea how
they came upon the thirty percent. I'm just making yeah,
hindsight by us exactly, And so you get thirty percent
and by the way, you should absolutely have told Kennedy
thirty percent and not fair chance. There are so many
(43:41):
psych studies about this that trying to put words with
percentages backfires because people do not understand. It's like if
you have a weather man and says a fair chance
of rain, Right, let's talk about not a fair chance
that the Bay of pigs is a success fair chance
of rain? Do you bring an umbrella? You want to
(44:02):
know what the percentage chances. You want to know that
actual number because otherwise a quantification gets all out of whack.
Financial cis when you have those numbers in the models.
Those were people whose incentives were not aligned with giving
you a correct probabilistic assessment. Their incentives were to make money.
(44:22):
That's also a question that you have to make. You
always have to ask, and this is something that Nate
and I talk about as well. When you're making these assumptions,
do the incentives align, Where are the assumptions coming from,
and do you have an incentive to be correct? Right?
And in this particular case, their incentive was to make
(44:44):
money for them today and to make their company think
that this was going to be a great bet and okay,
that it was going to work out. And so those
percentages are not something that you want to rely on. Now,
if my incentive is if my percentage is wrong, I'm
getting fired. Right. If my percentage is wrong, then I'm
making zero dollars. Then all of a sudden, I come
(45:08):
up with different percentages, I use different inputs. My model
looks very very different. But Wall Street didn't work that way,
still doesn't work that way. That's not how you're incentivized.
Speaker 4 (45:17):
Yeah, look, I think there's a risk of laundering subjective
opinions through probabilities and forgetting their subjective right. If I'm
running link the airport, there's traffic on the van Wick
or whatever, right, I might say to myself it's a
five percent chance is going to miss my flight. Right,
It's not coming out of any regression analysis or anything.
You know, I've probably used the phrase in this show,
(45:38):
like quoting Vice President Harris. A model does not fall
out of a coconut tree. It exists in the context
of that which became before it, or whatever else you're
trying to get at the truth with the model. And
I think mediocre modelers in particular will publish a number
and then forget how many assumptions are driven into that.
Speaker 3 (45:58):
Right. Look, I still think it's worth quantifying things.
Speaker 4 (46:01):
I mean, at the end of the day, probability is
defined as a number between point zero and one, and.
Speaker 3 (46:09):
You have to make decisions even in conditions of uncertainty.
Speaker 4 (46:12):
But to Tim's point, yeah, I think there are cases
where people don't forget how provisional a guess is when
you put a number on it.
Speaker 2 (46:20):
Yeah, And I think it is always important to not
have a false sense of certainty. And there's also a
lot of data that shows that when you have numbers,
and when you have a lot of these things, it
does give you a false sense of certainty, right that
you often do become a little bit over confident when
you're like, well, I have this model in this model,
so it must be and there you have the bias
(46:42):
that we've talked about a lot, where it goes from
being probabilistic to seeming much more certain like this will
not default, This will not happen because you forget that
it ain't zero.
Speaker 1 (46:57):
Thank you so much, guys, fantastic Tim.
Speaker 2 (46:59):
Thank you so much for coming on the pod today.
It's been such a pleasure having you.
Speaker 1 (47:03):
Oh it's been really really fun. Thank you for sharing
your wisdom. And if people want to hear more about
Sound Israel or any other stories of things going disastrously
wrong and me trying to investigate the social science behind
why they went wrong cause New Tales with Tim Harford
is one of Risky Business's sister podcasts on pushkin.
Speaker 2 (47:23):
It is and there are lots of tales of risk
taking assessments that do not turn out quite the way
the risk taker thought they would. Risky Business is hosted
(47:49):
by me Maria Kunakova and me Mate Silver. The show
is a co production of Pushkin Industries and iHeartMedia. This
episode was produced by Isabel Carter. Our associate producer is
Gabriel Hunter Chang. Our executive producer is Jacob Goldstein.
Speaker 3 (48:04):
And if you want to listen to and add free version,
sign up for Pushkin Plus. For six seventy nine a
month you can access to ad free listening. Thanks for
tuning in
Speaker 1 (48:28):
H
Host
Tim Harford
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