July 3, 2025 • 51 mins
Nate and Maria take a quick break from the World Series of Poker to tape a live episode at the Aspen Ideas Festival. They give some updates on a scandal at the World Series, then discuss Zohran Mamdani’s recent win in New York City’s Democratic primary, and what it might mean for elections moving forward. They also discuss the language we use to convey probability, and why talking about it can be so difficult. Plus, they answer some audience questions.
Further Reading:
From Adam Kucharski’s newsletter, Understanding the unseen: Possibly a serious possibility
From Silver Bulletin: Zohran delivered the Democratic establishment the thrashing it deserved
For more from Nate and Maria, subscribe to their newsletters:
The Leap from Maria Konnikova
Silver Bulletin from Nate Silver
See omnystudio.com/listener for privacy information.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:15):
Pushkin, Hey, Risky Business listeners. This weekend, Nate and I
took a break from the World Series of Poker to
go to the Aspen Ideas Festival. Sunday night, we got
to tape a live episode of the Risky Business podcast
and we're so happy to share that with you today.
(00:38):
We hope you enjoy it. Welcome back to Risky Business,
a show about making better decisions. I'm Maria Kondakova.
Speaker 2 (00:47):
And I'm Nate Silver.
Speaker 1 (00:49):
So today on the show, we're going to be starting
with a little bit of poker. So Nate and I
are both here from lovely Las Vegas because it is
currently the middle of the World Series of Poker, but
we love Aspen and the Aspen Ideas Festival so much
that we're taking time off to be here.
Speaker 3 (01:05):
With only one straight days of poker, we can spare
one day for the Aspen Night Festivals.
Speaker 1 (01:10):
We're going to be talking about a recent controversy at
the World Series of Poker and what happened there. But
after that we're going to be getting into something much metior.
Speaker 2 (01:21):
Yeah, I think the election of z around.
Speaker 3 (01:23):
I'm Donnie in New York or not, excuse me, The
nomination he's still has to win. The general election is
one of the most interesting and seismic events in American politics,
at least since the election, you know, one of the
most successful opportunities for like a explicitly socialist left wing
candidate to Governess said, it's actually very pro financed. New
York is not left in the way that Portland is
(01:44):
or Espen might be, or things like us. We're going
to talk about both the strategy behind rank choice voting
and how that might have affected things, but also just
you know, a big political moment, how this might affect
the party's decisions going forward.
Speaker 1 (01:55):
And after that we will play a little game called
how likely is It where we will test our knowledge
and your knowledge of probabilistic thinking. So let's get into it, Nate. Yeah, So,
first of all, we have a controversy at the World
Series of Poker last week was one of the biggest
(02:17):
tournaments of the summer. It's called the millionaire Maker because
first place is always guaranteed to be at least a
million dollars. This was a record breaking millionaire Maker, so
second place was also over a million dollars. This was
complicated by the fact that there was also a promotion
being run by a rival brand, the World Poker Tour,
(02:40):
which one of the two players who ended up getting
heads up, which is one of the final two players,
was eligible for which meant that if he won the tournament,
and only if he won the bracelet, he would get
an extra million dollars. So think about for a second, right,
in the context of decision making, in the context of
incentives exactly, incentives matter. What that does they get heads up?
(03:05):
So two people left, only one.
Speaker 2 (03:07):
Time wines final feo.
Speaker 3 (03:10):
Happens to be the guy who can win this additional
million dollar bonus on top of the million dollars has
already won.
Speaker 1 (03:15):
Yes, Unfortunately, this guy has a chip deficit of nine
to one. So that means that the other player, right,
the one who is not eligible for the million dollars,
has him out chipped nine times. So what that means
is that usually nine times out of ten, that guy's
going to win the tournament. And what happens to the
million dollar bonus, It disappears incentives matter. So what ended
(03:42):
up happening was a very strange heads up match that
looked an awful lot. This is just allegations, you know,
nothing proven, an awful lot like collusion. There was a
lleged chip dumping where one of the players dumped chips
to the other players and made what was supposed to
be an incredibly competitive, televised by the way this was
all televised match into something that looked very strange into
(04:05):
people outside of poker. They were like, what in the
world was going on? The player who had the million
dollar incentive won the bracelet, won the tournament, and they
are now currently both under investigation.
Speaker 2 (04:20):
Yeah. No, I mean there are a couple of themes here.
Speaker 3 (04:21):
I mean one is kind of how so it's not
just that the tournament is televised, it's that in televised poker,
the audience gets to see the player's private cards.
Speaker 2 (04:31):
Right, So to think that you could have.
Speaker 3 (04:32):
This live streamed on TV and everybody can like see
the hands face up, basically accept the two opponents that's
taped to lay fifteen minutes. Right, If one player what's
his name, Jesse, Jesse, If Jesse had been way ahead.
Speaker 2 (04:45):
Then maybe, like you know what, maybe we're gonna be
a little loose.
Speaker 3 (04:48):
But instead, every single decision he plays as though he
has knowledge of what his opponent has.
Speaker 2 (04:55):
Right.
Speaker 3 (04:55):
Almost that exception to the point where the hosts are
commenting on the real time. If you go and look
at computers, computers now have solved poker at least heads
up pick a poke in particular to a high degree.
These are all plays that are done zero percent of
the time in op and we'll play that are done
almost your percent of the time by two very experienced players. Right,
things like folding a pair to a tiny bit, which
(05:17):
heads up poker.
Speaker 2 (05:18):
It's hard to make a hand in poker. You're never
supposed to do that. And so now and people are torn. Right.
Speaker 1 (05:24):
There are people who say, well, they didn't hurt anyone
because they were heads up, right, so it's not like
they took chips from a third player. Now, I'm writing
a book right now about cheating in games, and so
this is something that kind of I've thought about a lot.
And on the one hand, I am sympathetic a little
bit to that argument because a lot of the worst
cheaters and a lot of the big cheating things in games,
(05:45):
it hurts other people, right, it hurts other players. You're
taking away equity from other players. If we assume that
they were playing completely above board up until this point,
then no one else was hurt. However, However, there is
another consideration here. Right. So one of the things that
I am a huge proponent on, and we've talked about
(06:07):
this on the show, is sportsmen.
Speaker 2 (06:09):
Right.
Speaker 1 (06:10):
There are two concepts, gamesmanship and sportsmanship. Gamesmanship is you
know I'm going to win, and you know, I don't
care how I get there, right, Like, I will take
every single edge I can possibly take because I want
to get there. Sportsmanship is doing it in kind of
a the spirit of the game, right, the spirit of
the sport, in a to use an old school term,
(06:30):
in a gentlemanly fashion, right, that you actually respect the
game you're playing. When you're looking at a televised competition
that's representing the game and people are watching it and
expecting something to instead of competition, instead of an actual match,
to give people, you know, chip dumbing or whatever it is,
(06:54):
that goes against the spirit of the game, and that
is something.
Speaker 2 (06:57):
Also it also.
Speaker 3 (06:58):
Lates the rules, Like the first rule of poker is
that one player to a hand. It's an individual game,
not a team game. Right, So that fundamental precept of
poker is violated.
Speaker 1 (07:07):
It does, and you know, I was thinking about it
in kind of broader games. Like imagine if you were
watching a tennis match, right, that's also a heads up match,
a player one against the other, and it became clear
that someone was throwing the match, and that's happened, right.
Tennis is actually one of the sports where cheating is.
There's a lot of it going on, and if you
watch that, you feel cheated as a spectator and as
(07:30):
a lover of the game, you kind of feel like
something was taken away from you. So I can understand.
And by the way, I really like Jesse, like the
player who ended up winning. He's sweet and sweet, wonderful guy.
But you have to be careful, right, if you like someone,
it doesn't mean that what they did know in the rest.
Speaker 3 (07:46):
It's just kind of a theme that will tie this
into kind of larger themes at this conference. So I
not just straddle back and forth being poker and like
the real world, but like I am involved in like
lots of small, tight knit communities, right, I'm not an
effective out your wist, But I know a lot of
people who describe themselves that way, right, I know, like
the sports analytics nerds, I know people who work in
politics and politics analytics nerds right, and like over and
(08:08):
over again, people are very short sighted about the weird
by normal person standards, norms and their small communities and
don't think about what happens when this kind of translates
to the outside world that hey, actually there's such a
thing as like the state of Nevada has gaming regulations.
If there's no regularity, are actually obligated to report that?
Or the fact that, okay, why are we having this
(08:29):
world series poker? It's bigger every year, despite the tariffs
and despite various headwinds, writing their setting record fields again
this year.
Speaker 2 (08:36):
Well where do the players come from? Right?
Speaker 3 (08:37):
They come from like watching poker on TV or on
video and saying that would be extremely fun if one
day I were to make a final table and I've
done it, you know, I have one time finished second
place an event like this, right, you know, it's a
thrill of a lifetime. But like to undermine that and
to do it in this way that like, I don't know,
I think it a narrowness of like perspective.
Speaker 1 (08:56):
It does, it does, and I do think that. You know,
when you're even talking about game theory, there's short term
and there's a long term, and you need to be,
you know, no matter what, you need to have the
long term in mind and the long term health of
the game and of how it's perceived. And on that note, Nate,
do you want to switch gears and go a little
bit into the game theory of a different arena of politics.
(09:19):
So we are both New Yorkers and we just had
a Democratic primary that is national news. That is rare
for a primary, even in New York, but we had
a very unexpected winner of the primary and zar on
mom Donnie showing a lot of shifts in the Democratic Party,
(09:41):
the Democratic Party base, and the potential the game theory
for the Democratic Party going forward. This is one kind
of potential blueprint should they choose to accept it.
Speaker 3 (09:53):
So one amazing thing is that younger voters actually turned
out at a higher rate than older voters in a selection,
which basically never happens in elections anywhere. Right, So he
spoke very much the vernacular of vertical video and kind
of how young people think about in general. He's a
you know, charismatic guy that's kind of a New York
(10:15):
archetype of this kind of multi ethnic hustler type, but
friendly guy and obviously a smart ambitious guy. Right, It's
like a type we recognize, I think have some appreciation
for in New York. He's a problem member the Democratic
Socialist of America. During the campaign emphasized affordability, cost of living,
had tangible proposals on like free buses, rent freezes for
(10:37):
certain types of buildings, right, city owned grocery stores, thirty
dollars minimum wage. Right, So tangible focused on that, not
culture worse stuff. And he winds up beating former governor
and Dupomo, who in a terrible campaign but was very complacent.
And I think this is a kind of a generational moment.
Speaker 1 (10:55):
I think it is, and I think it's very interesting
to see that Momdani was actually able to get the
voters who turned to Trump during the presidential election, that
demographic to actually come out and vote for the Democrats.
And there are you know, videos from him campaigning where
he actually manages to talk to kind of that exact
(11:19):
demographic that you know, voted for not just a different
type of Democrat, but for Republicans in the presidential election.
Speaker 3 (11:27):
Yeah, I mean it's a little bit because you know,
so we had comparatively high turnout about a million, probably
one point oh five million, right.
Speaker 1 (11:33):
Yeah, this was our high start.
Speaker 2 (11:35):
But there are eight.
Speaker 3 (11:36):
Million people in New York City of whom three point
three to three point four million are registered Democrats, right,
so you're still only getting twenty five or thirty percent
of the electorate.
Speaker 2 (11:46):
With that said, very broad based.
Speaker 3 (11:48):
Right, He won precincts even in Staten Island, which is
kind of cuomo home turf. Not all of them, but
some of them.
Speaker 2 (11:54):
Right.
Speaker 3 (11:54):
You know, Cuomo wins the Central Parkies, but you go
even a couple of blocks into the Upper east Side,
one of the more conserve neighborhoods, he started some mom
don Aid precincts right there. So, you know, a very
impressive performance. And of course we will be accused as
the New Yorkers are being provincial. But New York is
so big and so diverse, right that not in the
same proportions, But we have like lots of Conservatives in
(12:16):
New York are out number by liberals. We have lots
of conservatives, right, We have every imaginable ethnic group and
slice of racial demographic right. There are lots of working
class people in New York. He mostly did well among
the kind of upper middle class, you know, kind of
white people. Basically, but there are those two, right, and
did well enough? This is important, did well enough among
(12:36):
the other groups, right, because sometimes can they say, Okay, well,
we're not going to win any you know Democrats, Right,
We're not going to win any working class white men,
so just write them off, treat them as a zero,
when actually, like getting thirty percent of working class non
college men as opposed to twenty percent makes a big deal. Right,
Trump in this past election got something like eighteen to
(12:57):
twenty percent of the black vote, which is a significant minority.
Speaker 2 (13:01):
Right.
Speaker 3 (13:01):
Mitt Romney got four percent against Barack Obama in twenty twelve. Right,
So going from four percent to twenty percent the population,
you can do that math, right, that's quite a big swing.
Speaker 1 (13:12):
Actually, yeah it is, mate. Do you actually think that
the election was at all affected by the fact that
this was the second primary where ranked choice voting was
actually in use, because that was something that people really were,
you know, emphasizing during the.
Speaker 3 (13:27):
Candidate You guys know what rank choice voting or run off?
Okay everyone.
Speaker 1 (13:33):
Festival, and we covered it for our listeners on the
pod last week. So I mean, okay, so ranked choice
voting means you have five choices, you rank your choices.
If your first choice candidate is not one of the
top two candidates, then your choice gets moved to your
(13:55):
next ranked candidate, and so on down the line.
Speaker 3 (13:59):
Yeah, so Zoran seemed to understand this and Cuomo did not,
yes one thing. He formed alliances with other candidates, right,
especially Brad Lander, the third place candidate. Now, from a
game theory standpoint, I don't think this is necessarily rational
for Brad Lander, because like, if you're in third place
and the other guy's in second place or maybe a
first place, right, you don't necessarily want to help him out, right,
(14:23):
But I think Brad Lander hates Andrew Cuomo's guts, has
a lot of people do in New York and so
and so there was that surround a very positive campaign
and a substantive campaign, which is a change from how
campaigns are often run.
Speaker 2 (14:38):
And I do think, like not uniquely the left in
the United States. I mean, look at Trump also.
Speaker 3 (14:44):
In NAGA, right, but like there often is a lot
of negativity, a lot of anxiety, right, and that wasn't
what he was doing, right. He was a smart, substantive guy,
you know, who literally walked the entire length of Manhattan,
like the last day before the campaign wearing a suit,
and so like did every podcast in the world.
Speaker 2 (15:02):
I think I've done. I've done like six podcasts in
the day before.
Speaker 3 (15:05):
I think Zorn probably beat that record, but he very
much earned it, and Cuomo was pure negative. We do
have a general election still where Cuomo is running again, right,
I don't know if that.
Speaker 1 (15:17):
And so is Sarah Adams maybe and Eric.
Speaker 3 (15:19):
Adams and come a mirror defective from your practic party
friendly with Trump. Right, you also have the proper Republican nominee,
Curtis Sliwa, who is a guy who founded The Guardian
Angels and owns like fifty six cats or something like that.
Speaker 1 (15:32):
So yeah, yeah, So I'm also interested, you know, from
from the point of view of like the game theory
of the Democratic Party. Right, we have this election which
seems like an anomaly but might not be, and a
lot of the Democratic establishment don't want to embrace Zora
Mom Donnie right there. They think that he is, you know,
(15:53):
too fringe, right, that he is too radical, that some
of his ideas are are too kind of too out there,
and that they want to go safer, They want to
go more middle of the road, which is what they
were saying during the presidential election that they lost.
Speaker 3 (16:09):
Yeah, it's kind of it's kind of hard to be
like an exciting centrist is part of the problem.
Speaker 2 (16:14):
You know, I don't know if Mayor Pete is exciting.
Speaker 3 (16:16):
I guess he's a well spoken person, for example. But like,
sometimes more the energy comes from the left. Again, like
to me, and look, I'm a University of Chicago economics major.
Speaker 2 (16:27):
I'm unapologetically kind of a neoliberal.
Speaker 3 (16:30):
Right, it does seem to me like, look, the left
has not had the economic left has not had a
lot of power in the United States recently, right, And
so I've become more sympathetics because I'm like, well, we
haven't made those mistakes. They will make mistakes, and it's
very hard to govern a state like New York. It's
particularly hard to govern New York City because New York
State controls the taxation policy, a lot of the budget
(16:52):
and things like that. They're always rivalries between Albany and
and city Hall, right that without being different.
Speaker 1 (17:00):
Yeah, absolutely, And I also wonder, you know, if mom
Donnie does get elected. Right, this is a big if.
Still right, we're we're i mean twenty five percent, but
seventy five percent, as we know, is not one hundred percent,
as we very well know. So he but let's assume
he gets elected. It's going to also be a very
(17:21):
interesting shift where kind of candidates like Mom Dannie have been,
you know, the underdog right, and it's been kind of
the the underdog story of someone who is kind of
young and kind of more radical and has those ideas
and wins despite the odds. Now, what happens when you
become the establishment right like that that underdog story shifts
(17:43):
your incentives. We were talking just now in poker about incentives.
Incentives matter in everything. Your incentives shift, right, the things
that you were able to promise suddenly you have to
make coalitions with other you know, with lobbyists, with other
ruling factions, with you know, you need to face the
realities of power. And so it's much easier to kind
(18:04):
of be the idealist before you get elected. And once
you're once you the establishment, that changes and you change.
And so I'm going to be very very curious to
see what happens and how that story kind of ends
up shifting, and then what happens to the supporters kind
of what all the downstream effects are going.
Speaker 2 (18:24):
To be Yeah, you're registered in Nevada. Now I am, Yeah,
I'm in New York.
Speaker 3 (18:27):
This is the rarer time when I have a general
election vote in New York that could plausibly matter. And
you know, people like me who might be kind of
on vaguely the center of the culturally center left and
economically centered something right, A lot of people are are
concerned about him, but like, to me, it's a bit
(18:48):
like if you're picking a founder for a startup, right,
you're kind of going more off like the rod intelligence
and talent and work ethic, maybe more than like the
particular program or platform, right, or at least it's kind
of like what I'm telling myself potentially, And the fact
that he's a lot of dexterity in talking about policy, right,
(19:10):
He went on, like the Odds odd Lots podcast, which
is Joe Wisenthal and Tracy Alloway, which is kind of
in the same family as Risky Business, right, and like
talking a lot of wankery about policy and things like that, Right,
And like I like politicians who who are elected officials
and are responsive to.
Speaker 2 (19:28):
Some degree to fulblic opinion.
Speaker 3 (19:30):
I think it's how democracy should should function, right, and
he can say here are my priors. I'll stay for
the working class. I don't like capitalism all that much. Right,
but he's not proposing anything too radical and like and
it's not angry. You know, Bernie Sanders understood that.
Speaker 2 (19:43):
Right.
Speaker 3 (19:45):
The one moment when the Sanders campaign got a little
bit angry was toward toward twenty twenty when they won
the first couple of primaries and they were instead of
bending the knee to the Timparty Party. Remember going to
a rally in Nevada, Bernie wound up winning basically three
states in a row. Iowa was disputed between him and
their pete, So we won't get into that, right, but
two and a half out of three, right, and he
(20:06):
gave species that were like, yeah, well screwed you Democrats establishment,
right now, you have to kiss my ring. And there
they still had leverage, right, they still had leverage. They
had the leverage to have Jim Clyburn and Amy club
Ashar Mayor Repete everybody else rally behind.
Speaker 2 (20:19):
Joe Biden successfully for one term.
Speaker 3 (20:22):
You know, whether that was a good decision of a
long run or not, we'll be I think debated, but like,
but yeah, you don't want to like rub it in
someone's face when they still have chips on the table,
so to speak, and so and so, you know, it
would behooves around to understand there's still a losible. We're
gona talk about what these probabilities mean. Twenty five percent
is a real possibility of losing, right, and so he
(20:42):
would be mindful to to keep up the strategy that
he had in the in the in the.
Speaker 1 (20:47):
Primary, and uh mindful to h if he gets selected
to try to uh keep up the same strategy if
you want.
Speaker 3 (20:57):
It's a really it's a really hard it's hard. It's
a really hard job.
Speaker 1 (21:00):
It is it's an incredibly hard job.
Speaker 3 (21:02):
You can probably do better than narrow dams, right, But
it's a it's a that's.
Speaker 1 (21:04):
A it's it is. It's it is an incredibly hard job.
And I think we do need to remember that. Nate,
Do you have any other kind of final thoughts on
the election or should we talk probabilities more generally?
Speaker 3 (21:16):
No, again, I kind of said at the top, I
do think that like the fact that Cuomo called in
all the cavalry right, he called him to Clinton to
endorse him. He called him like a Bloomberg called him
Jim Clyburn. Every black group, Jewish group, Italian group, got
all the ethnic groups in New York, right, lots and
lots and lots of unions, right, And that's how you
used to win in machine cities, machine states, that's how
(21:38):
you win elections.
Speaker 2 (21:39):
And like and like Cuomo, Cuomo.
Speaker 3 (21:41):
Kind of actually got the numbers that ordinarily would win
a New York mayoral race, right since two thousand and one,
he's the second highest total of votes. But like Mom, Donnie,
reached into new parts of the electorate, not totally new.
These are people who vote in presidential primaries and things
like that. But this is the case where it turnout
(22:02):
did matter quite a bit in a race where maybe
a third of Democrats turn out if you're lucky, maybe
twenty five percent. Then and getting people excited, being I mean,
being interesting. So many politicians are either psychopaths or boring, right,
like ninety four of one hundred US Saturday either psychopaths,
boring or both.
Speaker 1 (22:21):
Yeah, yeah, no, And a lot a lot can be
said for being nice and having energy and actually being
excited about the job you're going to do, even though
it's going to be a really really hard job, and
I think that's tough, right to show up every day
with that kind of energy. I mean, how many of
you can walk the entire length of Manhattan and tape
(22:42):
however many podcasts and I get.
Speaker 2 (22:45):
Not in a suit though I'm a sweater, not in
a suit.
Speaker 1 (22:50):
I can do it in high heels.
Speaker 4 (22:51):
Now, I kid, you're.
Speaker 2 (22:56):
Gonna hear a quick break and then we'll be back.
Speaker 1 (23:07):
We want to play a little game with you about probabilities.
We'll play it with each other first, but then we're
going to involve you. It's a game called how likely
is it? So how likely are certain probabilities? So let's
give you just a little bit of context behind this.
So back in nineteen fifty one March of nineteen fifty one,
(23:29):
there was a CIA analyst whose name was Sherman Kent,
and he filed a report on the probability of an
invasion by of Yugoslavia in the year nineteen fifty one.
We all know how that turned out. So how probable
is it that the USSR is going to invade? And
he concluded in his report that it was a quote
(23:51):
serious possibility. So what did he mean by serious possibility?
In retrospect. When he explained this, he thought it meant well,
first of all, just think in your heads what you
think it means, Nate, what do you think it mean?
Just you don't have to answer, Okay, So he thought
it meant sixty five percent or higher. So, right, more
(24:13):
than sixty five percent. Unfortunately, the person to whom he
conveyed his report and his findings, who was a chairman
of the policy Planning initiative, they had understood him to
mean that it was a lot lower than that. So
in their minds, serious possibility was like, oh, twenty percent
or maybe like a range from twenty to seventy eighty percent,
(24:37):
certainly not sixty five percent or higher. So there was
a huge miscommunication which resulted in massive policy missteps. Right,
just because how serious a serious possibility was was not Well.
Speaker 3 (24:53):
People are there were number match totobic right, you know
at former thirty eight, no silver bulletin. Right, we have
an election model where we give you know, a probability
is fundamentally defined, is a number between zero percent and
one hundred percent.
Speaker 2 (25:07):
Right, And a lot of times.
Speaker 3 (25:08):
People use weaseled They're like, well, Nicklint, you had Hillary
Clinton with a seventy one.
Speaker 2 (25:13):
Percent chance of winning the election. So you were wrong.
Speaker 3 (25:15):
We have the semantics of that, right, But like, but
you know, but you put a number there and people
think it's like, you know, understand that that represents it
bakes in the uncertainty in the model, the uncertainty in
the real world.
Speaker 1 (25:27):
Right.
Speaker 3 (25:27):
If I were to say, I think, by the way,
serious possibility to me implies like twenty percent. Right, if
I said that there's still a serious possibility Zaron could
lose a general election, right, because you're not saying probability,
You're saying, like, take this seriously, twenty.
Speaker 1 (25:41):
Twenty se Yeah, Well, when you put it in that context, right,
a serious possibility that Zar loses the election twenty five percent? Right, Now,
that sentence makes sense, which is why So when I
was a grad student and studying decision making, one of
the things that we talked about was how do you
communicate risk? Right? How do you communicate probabilities to people?
(26:02):
And it's really really hard, and it's hard in all
sorts of context. Right, how do you communicate probabilities when
it comes to things like global warming, right, or or
elections or something like that, And people just do not
understand probabilistic thinking. As we've talked about on the show
many many times, our brains just suck at probabilities and
(26:25):
at what they mean. Just by the way, why poker
is so good because it actually forces you to learn
what probability feels like viscerally, which is how the brain
learns the best. You know, I, for instance, you know
no bad beat stories on the podcast or in real life,
but I know how it feels to lose on day
four of the main event of the World Series as
(26:46):
a ninety eight point six percent favorite in a multi
millionship pot. It happens, right, It feels like it shouldn't
because ninety eight point six percent feels like it should
be one hundred percent. But it's not. Probabilities matter, and
we're so so bad at them. And yet something that
you just said, Nate, which is absolutely crucial, is that
we're number phobic. When you tell people, you know what,
(27:09):
the best way to communicate probability is, state the probability.
State the damn thing. Put a number on it. Actually
say you know it's I think the probability is between
ten percent and fifteen percent, and I am seventy five
percent sure In this estimate.
Speaker 3 (27:26):
Rights, be explicit about the language that you're using it.
I believe the IPCC the Global Climate reports. Right, they
will use language like very likely a lot. But in
the appendix you look it up and they say very
likely means whatever it is ninety five percent or higher?
Speaker 2 (27:41):
Right, nay?
Speaker 1 (27:42):
How many people reading the report then go to the appendix.
Speaker 3 (27:44):
To see see s report. My whole family once gave
each other the Iraq Study Group report for like Christmas
or something. It's that kind of that kind of family.
But no, but and then you know, look house this year,
but no, look uh, because the apsode is people use
this as weasel words. Right, They're intentionally ambiguous to say
(28:07):
later on, no, I was right, I was wrong, right,
which is lame.
Speaker 2 (28:10):
Right.
Speaker 3 (28:10):
People don't get any better unless they feel the pain of,
like of putting something which is in the public record
and is accountable to some degree.
Speaker 2 (28:18):
Obviously, you need like.
Speaker 3 (28:19):
A large sample of predictions to be able to evaluate,
you know, do do of your seventy percent probabilities? Do
seven out of ten come true in the long run? Right,
But you want to play a little bit of the
game here, how likely is it?
Speaker 1 (28:31):
Yeah, let's absolutely do it? So the way that this
game is going to work at first is I am
going to tell you a phrase, Nate, and then you
will tell me what percent probability you think that that
phrase represents, and then I'll think of my answer as well,
and if you guys want to play along, feel free
to think of yours. All right, So if I tell
(28:54):
you almost certainly, what are you thinking?
Speaker 2 (28:59):
Ninety five percent plus?
Speaker 1 (29:01):
Okay, so almost certainly ninety five percent plus. I was
actually going to go a little bit lower and say
ninety percent plus, just knowing that in this world basically
nothing is certain. And if we're at above ninety percent probability,
like holy shit. You know, as a gambler or as
an investor, if I told you that you had an
investment that had a ninety percent probability of succeeding, how
(29:23):
many of you would take that investment? And I hope,
I hope most of you. But and if I told
you that you could take a gamble with a ninety
percent probability of success.
Speaker 2 (29:33):
Yeah, people are there gambling, right.
Speaker 3 (29:35):
I mean, you'll learn in poke if you can get
like a fifty four percent edge, yeah, it's pretty good.
Speaker 1 (29:41):
It's amazing. But I'm not saying that that means almost certain,
but to me, like above ninety percent, given how much
uncertainty and ambiguity there are in the world, so those
are two different things, right. Uncertainty is we're not quite
sure what the probabilities are. Ambiguity is we're not even
quite sure kind of what the factors are. We're not
sure if our model is one hundred percent correct and
(30:02):
is accounting for everything. So given all of that, I
would actually say, like above ninety percent would be almost certainly.
Do you I don't know if that makes you rethink
your answer or not.
Speaker 3 (30:12):
You know, I watched en f NBA playoff games where
teams blue seventeen point leads and things like that in
the fourth quarter, So like, I'm feeling I want the
security of ninety five percent.
Speaker 1 (30:21):
All right, you want the security of.
Speaker 3 (30:23):
After playing poker for a few weeks. Yeah, We're nothing
is certain that I'm like, I want my almost certainly
s at ninety five Right.
Speaker 1 (30:28):
That makes that makes sense? So what would you would
you actually like what would you say for like a
ninety plus or an eight? Is there something that you
is there a phrase that you would think more accurately.
Speaker 2 (30:39):
Represents that very likely highly likely.
Speaker 1 (30:42):
Huh interesting because I would think that very likely would
be below ninety percent. See, this is this is how,
this is why this is ambiguous.
Speaker 2 (30:50):
All right?
Speaker 1 (30:51):
So I am going to give you another phrase. If
I said that something was unlikely to happen.
Speaker 3 (30:58):
Yeah, I'd say unlikely or for that matter of the counterpart.
Likely is one of the worst and most ambiguous terms
to use in that context, right, because literally it can
mean depending on the context. Anythink from like zero point
zero zero zero percent one percent zero zero zero one
to like forty nine percent.
Speaker 2 (31:15):
Right, it's very ambiguous.
Speaker 3 (31:16):
I would tend to think unlikely means twenty five or
thirty percent, somewhere in the middle of the below fifty
percent range.
Speaker 2 (31:22):
What about you, Yeah, I was.
Speaker 1 (31:24):
Going to be at around twenty five percent or below. Right,
Any of that is unlikely, and you know, we can
start we can start kind of playing around with it
a little bit with adjectives. But I totally agree with
you that likely. What about likely? By the way, would
would you say likely is above above what percentage is likely?
Is it above fifty?
Speaker 3 (31:44):
If feel like you're a little asymmetric like likely, I
think you have to be sixty or so.
Speaker 2 (31:49):
Right, Yeah, it is.
Speaker 3 (31:51):
Asymmetric, possible or probable. These ones are pretty bad, right,
You want to do one more?
Speaker 1 (31:57):
Yeah, let me let's do it all right? So, how
about if I actually add an adjective to unlikely and
say highly unlikely. Now, what are we talking now?
Speaker 3 (32:07):
Ten percent or below? I think it's kind of the
counterpart to I don't know why. I think it's in
percent of blowing. There was like ninety five percent.
Speaker 1 (32:13):
I was about to say, why they asymmetry, so you said,
you know, the just highly likely was ninety five I
have still.
Speaker 3 (32:18):
A large language model teasing out implicit contexts from the
way these phrases are used in the real world.
Speaker 2 (32:24):
I don't know what checchiput would say.
Speaker 1 (32:26):
So highly unlikely, I would say it is interesting because
I might actually be lower than you. I might say,
like below if it's highly unlikely, like below five percent,
Like it's just you're telling me that it's almost certainly
not going to happen to me. Right, that like highly
unlikely and almost certainly kind of go hand in hand.
(32:50):
But let's if you actually kind of go out in
context a little bit with that. Think about weather reports,
which is something where we experience kind of that's one
of these things where we do get probabilities, where we
do get percentages, and we experience those on a daily basis. Right, you,
(33:11):
what what is your threshold, Nate for bringing an umbrella?
Speaker 5 (33:14):
Like?
Speaker 1 (33:14):
What's your an umbrella?
Speaker 2 (33:16):
I find umbrella?
Speaker 1 (33:17):
Okay, that was about this is true?
Speaker 2 (33:20):
Why is umbrella technology not improved more?
Speaker 1 (33:23):
Nate and I have walked together in New York City
rainstorms where I'm like, do you want to share my umbrella?
He's like, I got my baseball cap. I'm good. But
but you know, for people who are not like you
and who actually care about rain, like, what's your threshold
for bringing an umbrella? Like for me, if it's like
fifty percent chance of rain, I'm probably not going to
(33:44):
bring it. You know, if it's like above sixty, I'll
probably probably bring an umbrella. You know, it just it
really just depends on what I'm doing. And so you
know that's but you think about those days when it
was ninety percent chance of rain and it didn't rain.
Speaker 2 (33:58):
Okay's great, let's get the audience.
Speaker 1 (34:01):
Let's do it all right, one last one. We're going
to do it with you guys, and I'm gonna So
I'm going to ask you to raise your hands.
Speaker 3 (34:07):
So if I say something is possible, that's a secret password, right, yeah, possible,
and you have to take one of the following ranges
zero twenty five percent, twenty about to fifty fifteen, seventy
five pcent five one hundred. Right, if I have something
is possible, raise your hand. If you interpret that as
zero to twenty five percent, okay, we have about a
quarter about z you're just twenty percent the hands up
(34:28):
in the audience, right, yeah, quite a few hands. I
will say twenty five to fifty percent a little bit more,
kind of solid.
Speaker 1 (34:36):
It's kind of similar, but probably a little more. Okay,
how about fifty to seventy five and.
Speaker 3 (34:42):
There are a handful of hands hands possible, that could
be And how about seventy five percent or more one day?
So the way to average is like thirty six or
something percent. We're like doing we're doing science here, yeah,
doing it on the fly. Yeah, but people think it
means anything from five percent to eighty percent, right if
you ask people to write down individual guesses so like,
(35:03):
so not very useful to have that, to have.
Speaker 1 (35:05):
That for you. No, No, it's really not because what
you know, what do you even mean probbable likely? Like
it is? You know, it's such a hedgeword. And what
we're trying to do is actually force you to be
more precise in your probabilistic judgments, because precision matters, right,
whether it's the precision of the USSR invading Yugoslavia or
(35:27):
a gamble that you're taking out the poker table right out.
Speaker 3 (35:32):
When it comes to like politics and things like that,
political questions, like, people are also just often interpreting stuff
in bad faith, right, Like I think that I think
that when you say there's a third chance of rain
and doesn't rain, people don't get as mad as when
there's a third chance of Donald Trump winning and he wins,
or things like that for example. But like, but you know,
(35:52):
politics makes people's brains misfire in various ways absolutely well.
Speaker 1 (35:58):
As soon as there's personal motivation there, right, as soon
as your identity is tied up in something like politics,
all of a sudden, your ability to parse these things.
You start thinking in absolutes, which is how are our
brains are programmed to think? Right? Ninety percent basically one
hundred seventy is basically one hundred sixty five basically one
hundred thirty basically zero.
Speaker 2 (36:18):
Right. We just let's at least.
Speaker 3 (36:20):
Get sixty five, right, is certainly either fifty fifty zero,
one hundred. Let's at least get those middle zones right
as a stepping stone to some more PI.
Speaker 1 (36:29):
Yeah, and I think I think that the bottom line
is that it's very difficult to communicate probabilities in plain language,
and you do need to get people accustomed to having
numbers associated with them, and one of the best ways
of doing that is to try to figure out, Okay,
what experience can I tie that to in their life
that makes them understand what this actually means?
Speaker 2 (36:51):
Right?
Speaker 1 (36:51):
That percent is not zero?
Speaker 2 (36:53):
I'm not way serious.
Speaker 1 (36:53):
Yeah, no, teacher, kids, poker. I've actually talked about this
many times, and I actually think that that is one
of the best ways that you can combat this.
Speaker 2 (37:04):
And we'll be right back after this break.
Speaker 1 (37:20):
Do you want to open it up to questions?
Speaker 3 (37:21):
Yeah, I say it's extraordinarily likely that we're going to
open it up to Q and A at this point.
Speaker 2 (37:27):
So there are mic runners. We can also point and shop,
but yeah.
Speaker 1 (37:30):
Okay, yeah, there are mic runners in the audience. So
raise your hand if you have a question. Yep, there's
one coming to you. Thanks.
Speaker 6 (37:38):
I studied statistics in graduate school and ended up in communications,
and I think one of the things that confounds this
problem is if somebody says to me, for example, climate
change isn't caused by us, I would say, not believing
myself that that's possible.
Speaker 4 (37:57):
That's my opinion.
Speaker 6 (37:57):
I know other people disagree, but in order to have
a conversation, I validate their opinion and move on. And
that's standard operating procedure when you're trying to actually change
minds of what you're saying is we're inaccurate and communicating.
Speaker 4 (38:12):
The real probabilities.
Speaker 6 (38:14):
But part of what's going on is that most of
the conversation is about trying to find some middle ground.
Speaker 1 (38:21):
So how do you separate those two uses?
Speaker 3 (38:24):
Yeah, it just and this kind of gets into the
conversation about Zoran earlier, right where he's going on podcasts
where the audience might not be favably inclined to him.
And I've done this too, Like marketing my book, I
talked to conserative audiences, liberal audiences, everything in between. Right,
And you're basically a politician, right, You're like you're trying
to code switch back and forth. You're trying to be
empathetic to your audience, You're trying to find points of
agreement in that disagreement. Maybe more politicians should take that lesson.
(38:47):
I mean, look, I generally think that when scientific communicators
try to like dumb things down too much, it's like
quite the right term. There's empathy, and there's there's empathy,
there's dumbing down, and there's like kind of like skipping
over the rough patches of the argument in a way.
(39:07):
They create like false certainty times, right, Like I generally
believe that like treat the audience as being reasonably smart
and sophisticated, right, I mean as poker players too, you know,
I think we are naturally suspicious, right, And I think
people can like people can tell I think when a
politician is being inauthentic or when they're not being kind
(39:32):
of communicated with fully forthrightly. Right, Like I thought this
was an issue at the beginning of the COVID pandemic.
We're changing advice about like masks and things like that, Right.
I think whenever people kind of like say, oh, the
science has settled on this question, well, on some questions,
it's settled on some questions that isn't right, and it's
like often used as a cudgel where there is genuine
(39:53):
uncertainty and so so yeah, I mean it's it's look,
we wrestle with this every day journalists too. But like,
I'm air more on the side of like, you know,
you can be empathetic in how you present something, and obviously,
if you're in a kind of question like not everything
you say in response, you're not going to correct any way.
Oh literally, you're wrong, you're wrong, but let me tell
you something else. Right, So I'm yeah, empathetic, but when
(40:15):
it official sign of a communication, I think should aim
more in the side of precision.
Speaker 1 (40:18):
I think that I think that we are also not
tolerant of ambiguity. Right that it's much easier to win elections.
It's much easier to win over a crowd if you
speak in absolutes, if you speak in certainties, and the
person who says, you know, I'm really not sure about this,
(40:42):
you know, they're here are the pros, here are the
cons And who gives the more nuanced response is not
the person who ends up getting ahead. And so there's
a fundamental mismatch between the need to communicate ambiguity and
uncertainty and the fact that you know some things we
just don't know, and that there are these kind of
confidence intervals there, and the need to tell a story
(41:07):
and tell a compelling story. And this is something that
you know, Nate, You and I have to struggle with
us storytellers too. I mean, we're communicators, we're journalists. We
make choices all the time when we write an article,
when we write a book, how do we tell the story?
What story do we tell? And you can't constantly. I
mean a book will be absolutely unreadable if every single
(41:28):
paragraph is a caveat where you know, well, you know,
you can also interpret it this way and this way
and I'm not quite sure about this, right, you can't.
You can't work that way, and so you make choices
all the time.
Speaker 3 (41:40):
Of course, sometimes ambiguity is strategic, right, Like let's say
Marie and I are on a double date with our
respective spouses and then a third couple that we don't know,
that a friend kind of set us with for a
friend's day, and they're super fucking annoying and we hate
their guts. Right, you know, if I say something like Marie,
what time did you say your flight was tomorrow morning?
Speaker 2 (41:57):
Right?
Speaker 3 (41:58):
Yeah, that's ambiguous. What it really means is that let's
gett's great.
Speaker 1 (42:02):
And Nate and I have known each other for long
enough that I would say, you know, it's at seven am,
we really really have to go. Yeah, so there are
strategic uses of it. Yeah, there are more questions back there.
Speaker 4 (42:13):
I am a longtime listener, first time caller.
Speaker 1 (42:16):
Wellco to the show.
Speaker 2 (42:17):
Yeah, yes.
Speaker 4 (42:18):
My question is how much do we do we think
Zauron's win is the inter syncracies in New York City
and him being a great candidate and Cuomo sucking, and
how much is the political climate has changed in some
way since the last election?
Speaker 1 (42:31):
That is, I mean, that is such a good question,
because the Cuomo sucking part of it is actually huge.
That sounds like that sounds like a silly statement, but
I actually think that that is an idiosyncrasy of this
election from a psychological standpoint, because never underestimate the power
(42:52):
of people to band together and coalitions to actually stick
together when there's one enemy, right, when there's a clear
someone who no one wants to see, When all of
a sudden, people who would never vote together, who would
never kind of partners partner up. And this is from
a psychological stamp.
Speaker 3 (43:10):
What you see that he both ran a bad campaign
and kind of, to us an informal term, kind of
like cock blocked all the other candidates in the field,
right where all the money from hedge funders and people
like that went to Cuomo. And you saw a quotes
when people were like big Cemo donors like I didn't
really care about that much, but it seemed like that's
what everyone was backing. I'm not going to back the
socialist right and so therefore and so yeah, you know,
(43:32):
if you'd had a fully fledged campaign between Zoran and
Brad Lander or something, or Adrian Adams, it might have
been closer.
Speaker 2 (43:39):
But he's a good can.
Speaker 3 (43:39):
I mean, look a lot of times political analysts like
me are left saying, yeah, the wins and losses are
what matter, but for analyzing trends and close counts, right
you know. So you know, look, if he had lost
seven point instead of won by seven points, I'd still
say that was pretty impressive.
Speaker 5 (43:55):
Right.
Speaker 2 (43:55):
It might be a sign of change here.
Speaker 3 (43:57):
It's a cleaner story, I think, But usually surprising outcomes
are overdetermined, right, you know, it has to do with
the changing of the guard generationally. It has to do
with like he kind of figured out the right formula
for more left wing ideas. It's not wilk culture stuff, right,
it's affordability, it's working class people, things like that.
Speaker 2 (44:16):
Right.
Speaker 3 (44:17):
He's a very well presenting guy, right, who's very New York.
I think in some ways his mom was a filmmaker,
and his visuals are all quite stunning and beautiful and cuomo.
Speaker 2 (44:28):
So it's like four things coming together.
Speaker 3 (44:31):
But he also won by enough margin where maybe only
three of those things or two, and to have it
to come together, we still have one probably.
Speaker 1 (44:36):
Yeah. And when things are over determined, by the way,
we can't answer your question right, When things are over determined,
you can't quite know what the crucial factors were. So
I think that the real answer to your question remains
to be seen. But it's a really interesting thing to
try to disambiguate and try to see kind of how
did we end up here? And I think that this
(44:58):
is an election that people will be looking back and
doing some commentary on for many years.
Speaker 7 (45:04):
So I want to ask political polls, so I think
you know something about it. So now I've heard the
lecture on words. And so if I see that one
candidate has a forty two percent chance of winning and
another candidate has a forty six percent chance, should I
(45:24):
interpret that to say they both have low probability? Or
they have or I mean I guess, or is it
so close? Really doesn't matter?
Speaker 3 (45:35):
Well, for one thing, people who work in polling or
who report on pulling need to be clear about a
probability versus a percent of the vote. Right, If it's
Trump forty six percent in say Texas, Harris forty two
percent undecided, third party is the remaining whatever eighteen percent?
Speaker 2 (45:52):
Right, like a four point lead. How often does that
translate into a win?
Speaker 3 (45:56):
That's an empirical question, right, The answer might be something
like seventy percent of the time.
Speaker 2 (46:01):
Russia, And in New York, what were the polls saying before?
In New York?
Speaker 3 (46:05):
No, the polls underestimated, I mean, had they had shown
the race tightening a lot. Some of the polls showed
Zoran pulling ahead after ranked choice voting. Almost none Maybee,
with one exception, had him winning the first round outright,
and none of them had him winning by like that
wide margin. Right, So this is what happens with polls
(46:25):
is like in a New York race, they assume turnouts
fairly low. They're surveying the people that like always turn
out in New York MARYORL races, who consideringly unlikely voters
are twenty percent of electorate.
Speaker 1 (46:36):
Right.
Speaker 3 (46:36):
Cuomo got his numbers among that twenty percent, but then
Zoran turned out people that never vote in mayoral elections
in e York. By the way, a lot of New
York's are transplants from around the country, all around.
Speaker 2 (46:46):
The world, right, so we don't have that like tie
to local politics. Right.
Speaker 3 (46:51):
I'm a person covers politics, listen to New York. I
don't know that much about like New York politics, right,
and it's very typical in some ways. But he he
broke through and became its cliche, but became viral in
a way that you know, I guess pollsters were too
conservative in their in their methods and missing and missing
these voters.
Speaker 1 (47:09):
We have time for one more question, hi.
Speaker 5 (47:11):
Things I was just curious. I know this is probably annoying,
like too long in the future kind of question, but
does Zorin's win at all change the probabilities that you
think about candidates in twenty twenty eight for Democratic primary
or I guess.
Speaker 1 (47:26):
The general election too.
Speaker 3 (47:28):
So with actually my former colleague at five thirty eight,
Galen Druke, we did a Democratic twenty twenty eight primary draft,
right or do it so it's like a draft, like
a fancy football draft or something. Galen got the first
pick and the first candidate on my list was AOC.
I thought he'd take Josh Shapiro or someone and said
he took AOC too, So it was mad about that.
(47:50):
But like we both thought, and this is before Zoran,
that she was let me put this carefully, from talking
about probabilities, right to say the most likely candidate might
mean a fifteen percent chance.
Speaker 2 (48:01):
Right, there's nobody in the field who is a clear
front runner.
Speaker 3 (48:04):
But we both thought that she was more luckily than
any other candidate to become the nominee in twenty twenty eight,
before before Mom Donnay came along, right, And again it's
probably because like look Democrats, of all these retreads, right,
the Clinton family, the Cuomo family, the Biden family. I
bet Jill will probably fantasize sometimes what if I become president? Right,
(48:26):
like House of Cards or something. Right, I'm I think
people are tired of all these families.
Speaker 2 (48:32):
Right.
Speaker 3 (48:32):
I remember seeing in twenty sixteen, I was in New
Hampshire covering the race for five thirty eight in ABC News, Right,
and like Hillary Clinton spoke to a group of like
then at college, right, Franklin Pierce College or something like that.
Speaker 2 (48:46):
Right, you know, the average age is twenty or something.
Speaker 3 (48:48):
She's talking about like the Cold War, and like the
students size are gleazing over they don't remember the Cold War, right,
And now that was you know, was eight nine years
ago now, right, And so like, look, I think I
think it's a good thing to see. I mean, Zaraan
was literally half of like Cuomo's age. Right, I think
it's a good thing. Mcrat parties about present and was
(49:10):
how can everyone's so freaking old? Right, I think it's
a good thing. Is is to you know, have cannates
that are good on social media, are substantive. I think
she's a pretty canny and smart politician and shows some
restraint at times.
Speaker 2 (49:23):
So yeah, it does change my views a little bit. Maria,
do you have a take now?
Speaker 1 (49:27):
I mean, this is one of the things that I
was talking about when I was talking about some of
the long term consequences of this election, right, And I
think a lot of it will depend on what ends
up happening once Zorn takes power, right, if he's elected,
how he actually handles himself in office, how popular he is.
I think that that will actually have a large bearing
(49:49):
on your question in terms of, you know, what does
the Democratic Party end up taking from this, because they
could take two very different lessons one AOC Two if
Zorn tanks for some reason right and becomes incredibly unpopular
and like the you know, we don't know, we can't
we don't have a crystal ball. But if something like
that were to happen, I think they'd be like, see,
(50:09):
we told you so right, we need to go back
to so I think you could see either thing working out,
so you can a lot rest on his shoulders.
Speaker 2 (50:18):
I guess.
Speaker 1 (50:19):
Yeah. That was our first Risky Business Live and we're
so happy you were here. That was our show from
the Aspen Ideas Festival. By the way, our segment on
probabilities was inspired by Adam Kucharski's newsletter Understanding the Unseen.
(50:40):
We'll have a link to that post in the show notes.
Thanks for listening. Let us know what you think of
the show. Reach out to us at Risky Business at
pushkin dot fm. And by the way, if you're a
Pushkin Plus subscriber, we have some bonus content for you
that's coming up right after the credits.
Speaker 3 (50:58):
And if you're not subscribing yet, consider signing up for
just six ninety nine a month. What a nice price
you get access to all that premium content and and
we're listening across Pushkin's entire network shows.
Speaker 1 (51:10):
Risky Business is hosted by me Maria Kanikova.
Speaker 2 (51:12):
And by me Nate Silver.
Speaker 3 (51:14):
The show is a co production of Pushkin Industries and iHeartMedia.
This episode was produced by Isabelle Carter. Our associate producer
is Sonia Gerwin. Sally Helm is our editor, and our
executive producer is Jacob Boldstein. Mixing by Sarah Bruguier.
Speaker 1 (51:29):
Thanks so much for tuning in.
Pushkin, Hey, Risky Business listeners. This weekend, Nate and I
took a break from the World Series of Poker to
go to the Aspen Ideas Festival. Sunday night, we got
to tape a live episode of the Risky Business podcast
and we're so happy to share that with you today.
(00:38):
We hope you enjoy it. Welcome back to Risky Business,
a show about making better decisions. I'm Maria Kondakova.
Speaker 2 (00:47):
And I'm Nate Silver.
Speaker 1 (00:49):
So today on the show, we're going to be starting
with a little bit of poker. So Nate and I
are both here from lovely Las Vegas because it is
currently the middle of the World Series of Poker, but
we love Aspen and the Aspen Ideas Festival so much
that we're taking time off to be here.
Speaker 3 (01:05):
With only one straight days of poker, we can spare
one day for the Aspen Night Festivals.
Speaker 1 (01:10):
We're going to be talking about a recent controversy at
the World Series of Poker and what happened there. But
after that we're going to be getting into something much metior.
Speaker 2 (01:21):
Yeah, I think the election of z around.
Speaker 3 (01:23):
I'm Donnie in New York or not, excuse me, The
nomination he's still has to win. The general election is
one of the most interesting and seismic events in American politics,
at least since the election, you know, one of the
most successful opportunities for like a explicitly socialist left wing
candidate to Governess said, it's actually very pro financed. New
York is not left in the way that Portland is
(01:44):
or Espen might be, or things like us. We're going
to talk about both the strategy behind rank choice voting
and how that might have affected things, but also just
you know, a big political moment, how this might affect
the party's decisions going forward.
Speaker 1 (01:55):
And after that we will play a little game called
how likely is It where we will test our knowledge
and your knowledge of probabilistic thinking. So let's get into it, Nate. Yeah, So,
first of all, we have a controversy at the World
Series of Poker last week was one of the biggest
(02:17):
tournaments of the summer. It's called the millionaire Maker because
first place is always guaranteed to be at least a
million dollars. This was a record breaking millionaire Maker, so
second place was also over a million dollars. This was
complicated by the fact that there was also a promotion
being run by a rival brand, the World Poker Tour,
(02:40):
which one of the two players who ended up getting
heads up, which is one of the final two players,
was eligible for which meant that if he won the tournament,
and only if he won the bracelet, he would get
an extra million dollars. So think about for a second, right,
in the context of decision making, in the context of
incentives exactly, incentives matter. What that does they get heads up?
(03:05):
So two people left, only one.
Speaker 2 (03:07):
Time wines final feo.
Speaker 3 (03:10):
Happens to be the guy who can win this additional
million dollar bonus on top of the million dollars has
already won.
Speaker 1 (03:15):
Yes, Unfortunately, this guy has a chip deficit of nine
to one. So that means that the other player, right,
the one who is not eligible for the million dollars,
has him out chipped nine times. So what that means
is that usually nine times out of ten, that guy's
going to win the tournament. And what happens to the
million dollar bonus, It disappears incentives matter. So what ended
(03:42):
up happening was a very strange heads up match that
looked an awful lot. This is just allegations, you know,
nothing proven, an awful lot like collusion. There was a
lleged chip dumping where one of the players dumped chips
to the other players and made what was supposed to
be an incredibly competitive, televised by the way this was
all televised match into something that looked very strange into
(04:05):
people outside of poker. They were like, what in the
world was going on? The player who had the million
dollar incentive won the bracelet, won the tournament, and they
are now currently both under investigation.
Speaker 2 (04:20):
Yeah. No, I mean there are a couple of themes here.
Speaker 3 (04:21):
I mean one is kind of how so it's not
just that the tournament is televised, it's that in televised poker,
the audience gets to see the player's private cards.
Speaker 2 (04:31):
Right, So to think that you could have.
Speaker 3 (04:32):
This live streamed on TV and everybody can like see
the hands face up, basically accept the two opponents that's
taped to lay fifteen minutes. Right, If one player what's
his name, Jesse, Jesse, If Jesse had been way ahead.
Speaker 2 (04:45):
Then maybe, like you know what, maybe we're gonna be
a little loose.
Speaker 3 (04:48):
But instead, every single decision he plays as though he
has knowledge of what his opponent has.
Speaker 2 (04:55):
Right.
Speaker 3 (04:55):
Almost that exception to the point where the hosts are
commenting on the real time. If you go and look
at computers, computers now have solved poker at least heads
up pick a poke in particular to a high degree.
These are all plays that are done zero percent of
the time in op and we'll play that are done
almost your percent of the time by two very experienced players. Right,
things like folding a pair to a tiny bit, which
(05:17):
heads up poker.
Speaker 2 (05:18):
It's hard to make a hand in poker. You're never
supposed to do that. And so now and people are torn. Right.
Speaker 1 (05:24):
There are people who say, well, they didn't hurt anyone
because they were heads up, right, so it's not like
they took chips from a third player. Now, I'm writing
a book right now about cheating in games, and so
this is something that kind of I've thought about a lot.
And on the one hand, I am sympathetic a little
bit to that argument because a lot of the worst
cheaters and a lot of the big cheating things in games,
(05:45):
it hurts other people, right, it hurts other players. You're
taking away equity from other players. If we assume that
they were playing completely above board up until this point,
then no one else was hurt. However, However, there is
another consideration here. Right. So one of the things that
I am a huge proponent on, and we've talked about
(06:07):
this on the show, is sportsmen.
Speaker 2 (06:09):
Right.
Speaker 1 (06:10):
There are two concepts, gamesmanship and sportsmanship. Gamesmanship is you
know I'm going to win, and you know, I don't
care how I get there, right, Like, I will take
every single edge I can possibly take because I want
to get there. Sportsmanship is doing it in kind of
a the spirit of the game, right, the spirit of
the sport, in a to use an old school term,
(06:30):
in a gentlemanly fashion, right, that you actually respect the
game you're playing. When you're looking at a televised competition
that's representing the game and people are watching it and
expecting something to instead of competition, instead of an actual match,
to give people, you know, chip dumbing or whatever it is,
(06:54):
that goes against the spirit of the game, and that
is something.
Speaker 2 (06:57):
Also it also.
Speaker 3 (06:58):
Lates the rules, Like the first rule of poker is
that one player to a hand. It's an individual game,
not a team game. Right, So that fundamental precept of
poker is violated.
Speaker 1 (07:07):
It does, and you know, I was thinking about it
in kind of broader games. Like imagine if you were
watching a tennis match, right, that's also a heads up match,
a player one against the other, and it became clear
that someone was throwing the match, and that's happened, right.
Tennis is actually one of the sports where cheating is.
There's a lot of it going on, and if you
watch that, you feel cheated as a spectator and as
(07:30):
a lover of the game, you kind of feel like
something was taken away from you. So I can understand.
And by the way, I really like Jesse, like the
player who ended up winning. He's sweet and sweet, wonderful guy.
But you have to be careful, right, if you like someone,
it doesn't mean that what they did know in the rest.
Speaker 3 (07:46):
It's just kind of a theme that will tie this
into kind of larger themes at this conference. So I
not just straddle back and forth being poker and like
the real world, but like I am involved in like
lots of small, tight knit communities, right, I'm not an
effective out your wist, But I know a lot of
people who describe themselves that way, right, I know, like
the sports analytics nerds, I know people who work in
politics and politics analytics nerds right, and like over and
(08:08):
over again, people are very short sighted about the weird
by normal person standards, norms and their small communities and
don't think about what happens when this kind of translates
to the outside world that hey, actually there's such a
thing as like the state of Nevada has gaming regulations.
If there's no regularity, are actually obligated to report that?
Or the fact that, okay, why are we having this
(08:29):
world series poker? It's bigger every year, despite the tariffs
and despite various headwinds, writing their setting record fields again
this year.
Speaker 2 (08:36):
Well where do the players come from? Right?
Speaker 3 (08:37):
They come from like watching poker on TV or on
video and saying that would be extremely fun if one
day I were to make a final table and I've
done it, you know, I have one time finished second
place an event like this, right, you know, it's a
thrill of a lifetime. But like to undermine that and
to do it in this way that like, I don't know,
I think it a narrowness of like perspective.
Speaker 1 (08:56):
It does, it does, and I do think that. You know,
when you're even talking about game theory, there's short term
and there's a long term, and you need to be,
you know, no matter what, you need to have the
long term in mind and the long term health of
the game and of how it's perceived. And on that note, Nate,
do you want to switch gears and go a little
bit into the game theory of a different arena of politics.
(09:19):
So we are both New Yorkers and we just had
a Democratic primary that is national news. That is rare
for a primary, even in New York, but we had
a very unexpected winner of the primary and zar on
mom Donnie showing a lot of shifts in the Democratic Party,
(09:41):
the Democratic Party base, and the potential the game theory
for the Democratic Party going forward. This is one kind
of potential blueprint should they choose to accept it.
Speaker 3 (09:53):
So one amazing thing is that younger voters actually turned
out at a higher rate than older voters in a selection,
which basically never happens in elections anywhere. Right, So he
spoke very much the vernacular of vertical video and kind
of how young people think about in general. He's a
you know, charismatic guy that's kind of a New York
(10:15):
archetype of this kind of multi ethnic hustler type, but
friendly guy and obviously a smart ambitious guy. Right, It's
like a type we recognize, I think have some appreciation
for in New York. He's a problem member the Democratic
Socialist of America. During the campaign emphasized affordability, cost of living,
had tangible proposals on like free buses, rent freezes for
(10:37):
certain types of buildings, right, city owned grocery stores, thirty
dollars minimum wage. Right, So tangible focused on that, not
culture worse stuff. And he winds up beating former governor
and Dupomo, who in a terrible campaign but was very complacent.
And I think this is a kind of a generational moment.
Speaker 1 (10:55):
I think it is, and I think it's very interesting
to see that Momdani was actually able to get the
voters who turned to Trump during the presidential election, that
demographic to actually come out and vote for the Democrats.
And there are you know, videos from him campaigning where
he actually manages to talk to kind of that exact
(11:19):
demographic that you know, voted for not just a different
type of Democrat, but for Republicans in the presidential election.
Speaker 3 (11:27):
Yeah, I mean it's a little bit because you know,
so we had comparatively high turnout about a million, probably
one point oh five million, right.
Speaker 1 (11:33):
Yeah, this was our high start.
Speaker 2 (11:35):
But there are eight.
Speaker 3 (11:36):
Million people in New York City of whom three point
three to three point four million are registered Democrats, right,
so you're still only getting twenty five or thirty percent
of the electorate.
Speaker 2 (11:46):
With that said, very broad based.
Speaker 3 (11:48):
Right, He won precincts even in Staten Island, which is
kind of cuomo home turf. Not all of them, but
some of them.
Speaker 2 (11:54):
Right.
Speaker 3 (11:54):
You know, Cuomo wins the Central Parkies, but you go
even a couple of blocks into the Upper east Side,
one of the more conserve neighborhoods, he started some mom
don Aid precincts right there. So, you know, a very
impressive performance. And of course we will be accused as
the New Yorkers are being provincial. But New York is
so big and so diverse, right that not in the
same proportions, But we have like lots of Conservatives in
(12:16):
New York are out number by liberals. We have lots
of conservatives, right, We have every imaginable ethnic group and
slice of racial demographic right. There are lots of working
class people in New York. He mostly did well among
the kind of upper middle class, you know, kind of
white people. Basically, but there are those two, right, and
did well enough? This is important, did well enough among
(12:36):
the other groups, right, because sometimes can they say, Okay, well,
we're not going to win any you know Democrats, Right,
We're not going to win any working class white men,
so just write them off, treat them as a zero,
when actually, like getting thirty percent of working class non
college men as opposed to twenty percent makes a big deal. Right,
Trump in this past election got something like eighteen to
(12:57):
twenty percent of the black vote, which is a significant minority.
Speaker 2 (13:01):
Right.
Speaker 3 (13:01):
Mitt Romney got four percent against Barack Obama in twenty twelve. Right,
So going from four percent to twenty percent the population,
you can do that math, right, that's quite a big swing.
Speaker 1 (13:12):
Actually, yeah it is, mate. Do you actually think that
the election was at all affected by the fact that
this was the second primary where ranked choice voting was
actually in use, because that was something that people really were,
you know, emphasizing during the.
Speaker 3 (13:27):
Candidate You guys know what rank choice voting or run off?
Okay everyone.
Speaker 1 (13:33):
Festival, and we covered it for our listeners on the
pod last week. So I mean, okay, so ranked choice
voting means you have five choices, you rank your choices.
If your first choice candidate is not one of the
top two candidates, then your choice gets moved to your
(13:55):
next ranked candidate, and so on down the line.
Speaker 3 (13:59):
Yeah, so Zoran seemed to understand this and Cuomo did not,
yes one thing. He formed alliances with other candidates, right,
especially Brad Lander, the third place candidate. Now, from a
game theory standpoint, I don't think this is necessarily rational
for Brad Lander, because like, if you're in third place
and the other guy's in second place or maybe a
first place, right, you don't necessarily want to help him out, right,
(14:23):
But I think Brad Lander hates Andrew Cuomo's guts, has
a lot of people do in New York and so
and so there was that surround a very positive campaign
and a substantive campaign, which is a change from how
campaigns are often run.
Speaker 2 (14:38):
And I do think, like not uniquely the left in
the United States. I mean, look at Trump also.
Speaker 3 (14:44):
In NAGA, right, but like there often is a lot
of negativity, a lot of anxiety, right, and that wasn't
what he was doing, right. He was a smart, substantive guy,
you know, who literally walked the entire length of Manhattan,
like the last day before the campaign wearing a suit,
and so like did every podcast in the world.
Speaker 2 (15:02):
I think I've done. I've done like six podcasts in
the day before.
Speaker 3 (15:05):
I think Zorn probably beat that record, but he very
much earned it, and Cuomo was pure negative. We do
have a general election still where Cuomo is running again, right,
I don't know if that.
Speaker 1 (15:17):
And so is Sarah Adams maybe and Eric.
Speaker 3 (15:19):
Adams and come a mirror defective from your practic party
friendly with Trump. Right, you also have the proper Republican nominee,
Curtis Sliwa, who is a guy who founded The Guardian
Angels and owns like fifty six cats or something like that.
Speaker 1 (15:32):
So yeah, yeah, So I'm also interested, you know, from
from the point of view of like the game theory
of the Democratic Party. Right, we have this election which
seems like an anomaly but might not be, and a
lot of the Democratic establishment don't want to embrace Zora
Mom Donnie right there. They think that he is, you know,
(15:53):
too fringe, right, that he is too radical, that some
of his ideas are are too kind of too out there,
and that they want to go safer, They want to
go more middle of the road, which is what they
were saying during the presidential election that they lost.
Speaker 3 (16:09):
Yeah, it's kind of it's kind of hard to be
like an exciting centrist is part of the problem.
Speaker 2 (16:14):
You know, I don't know if Mayor Pete is exciting.
Speaker 3 (16:16):
I guess he's a well spoken person, for example. But like,
sometimes more the energy comes from the left. Again, like
to me, and look, I'm a University of Chicago economics major.
Speaker 2 (16:27):
I'm unapologetically kind of a neoliberal.
Speaker 3 (16:30):
Right, it does seem to me like, look, the left
has not had the economic left has not had a
lot of power in the United States recently, right, And
so I've become more sympathetics because I'm like, well, we
haven't made those mistakes. They will make mistakes, and it's
very hard to govern a state like New York. It's
particularly hard to govern New York City because New York
State controls the taxation policy, a lot of the budget
(16:52):
and things like that. They're always rivalries between Albany and
and city Hall, right that without being different.
Speaker 1 (17:00):
Yeah, absolutely, And I also wonder, you know, if mom
Donnie does get elected. Right, this is a big if.
Still right, we're we're i mean twenty five percent, but
seventy five percent, as we know, is not one hundred percent,
as we very well know. So he but let's assume
he gets elected. It's going to also be a very
(17:21):
interesting shift where kind of candidates like Mom Dannie have been,
you know, the underdog right, and it's been kind of
the the underdog story of someone who is kind of
young and kind of more radical and has those ideas
and wins despite the odds. Now, what happens when you
become the establishment right like that that underdog story shifts
(17:43):
your incentives. We were talking just now in poker about incentives.
Incentives matter in everything. Your incentives shift, right, the things
that you were able to promise suddenly you have to
make coalitions with other you know, with lobbyists, with other
ruling factions, with you know, you need to face the
realities of power. And so it's much easier to kind
(18:04):
of be the idealist before you get elected. And once
you're once you the establishment, that changes and you change.
And so I'm going to be very very curious to
see what happens and how that story kind of ends
up shifting, and then what happens to the supporters kind
of what all the downstream effects are going.
Speaker 2 (18:24):
To be Yeah, you're registered in Nevada. Now I am, Yeah,
I'm in New York.
Speaker 3 (18:27):
This is the rarer time when I have a general
election vote in New York that could plausibly matter. And
you know, people like me who might be kind of
on vaguely the center of the culturally center left and
economically centered something right, A lot of people are are
concerned about him, but like, to me, it's a bit
(18:48):
like if you're picking a founder for a startup, right,
you're kind of going more off like the rod intelligence
and talent and work ethic, maybe more than like the
particular program or platform, right, or at least it's kind
of like what I'm telling myself potentially, And the fact
that he's a lot of dexterity in talking about policy, right,
(19:10):
He went on, like the Odds odd Lots podcast, which
is Joe Wisenthal and Tracy Alloway, which is kind of
in the same family as Risky Business, right, and like
talking a lot of wankery about policy and things like that, Right,
And like I like politicians who who are elected officials
and are responsive to.
Speaker 2 (19:28):
Some degree to fulblic opinion.
Speaker 3 (19:30):
I think it's how democracy should should function, right, and
he can say here are my priors. I'll stay for
the working class. I don't like capitalism all that much. Right,
but he's not proposing anything too radical and like and
it's not angry. You know, Bernie Sanders understood that.
Speaker 2 (19:43):
Right.
Speaker 3 (19:45):
The one moment when the Sanders campaign got a little
bit angry was toward toward twenty twenty when they won
the first couple of primaries and they were instead of
bending the knee to the Timparty Party. Remember going to
a rally in Nevada, Bernie wound up winning basically three
states in a row. Iowa was disputed between him and
their pete, So we won't get into that, right, but
two and a half out of three, right, and he
(20:06):
gave species that were like, yeah, well screwed you Democrats establishment,
right now, you have to kiss my ring. And there
they still had leverage, right, they still had leverage. They
had the leverage to have Jim Clyburn and Amy club
Ashar Mayor Repete everybody else rally behind.
Speaker 2 (20:19):
Joe Biden successfully for one term.
Speaker 3 (20:22):
You know, whether that was a good decision of a
long run or not, we'll be I think debated, but like,
but yeah, you don't want to like rub it in
someone's face when they still have chips on the table,
so to speak, and so and so, you know, it
would behooves around to understand there's still a losible. We're
gona talk about what these probabilities mean. Twenty five percent
is a real possibility of losing, right, and so he
(20:42):
would be mindful to to keep up the strategy that
he had in the in the in the.
Speaker 1 (20:47):
Primary, and uh mindful to h if he gets selected
to try to uh keep up the same strategy if
you want.
Speaker 3 (20:57):
It's a really it's a really hard it's hard. It's
a really hard job.
Speaker 1 (21:00):
It is it's an incredibly hard job.
Speaker 3 (21:02):
You can probably do better than narrow dams, right, But
it's a it's a that's.
Speaker 1 (21:04):
A it's it is. It's it is an incredibly hard job.
And I think we do need to remember that. Nate,
Do you have any other kind of final thoughts on
the election or should we talk probabilities more generally?
Speaker 3 (21:16):
No, again, I kind of said at the top, I
do think that like the fact that Cuomo called in
all the cavalry right, he called him to Clinton to
endorse him. He called him like a Bloomberg called him
Jim Clyburn. Every black group, Jewish group, Italian group, got
all the ethnic groups in New York, right, lots and
lots and lots of unions, right, And that's how you
used to win in machine cities, machine states, that's how
(21:38):
you win elections.
Speaker 2 (21:39):
And like and like Cuomo, Cuomo.
Speaker 3 (21:41):
Kind of actually got the numbers that ordinarily would win
a New York mayoral race, right since two thousand and one,
he's the second highest total of votes. But like Mom, Donnie,
reached into new parts of the electorate, not totally new.
These are people who vote in presidential primaries and things
like that. But this is the case where it turnout
(22:02):
did matter quite a bit in a race where maybe
a third of Democrats turn out if you're lucky, maybe
twenty five percent. Then and getting people excited, being I mean,
being interesting. So many politicians are either psychopaths or boring, right,
like ninety four of one hundred US Saturday either psychopaths,
boring or both.
Speaker 1 (22:21):
Yeah, yeah, no, And a lot a lot can be
said for being nice and having energy and actually being
excited about the job you're going to do, even though
it's going to be a really really hard job, and
I think that's tough, right to show up every day
with that kind of energy. I mean, how many of
you can walk the entire length of Manhattan and tape
(22:42):
however many podcasts and I get.
Speaker 2 (22:45):
Not in a suit though I'm a sweater, not in
a suit.
Speaker 1 (22:50):
I can do it in high heels.
Speaker 4 (22:51):
Now, I kid, you're.
Speaker 2 (22:56):
Gonna hear a quick break and then we'll be back.
Speaker 1 (23:07):
We want to play a little game with you about probabilities.
We'll play it with each other first, but then we're
going to involve you. It's a game called how likely
is it? So how likely are certain probabilities? So let's
give you just a little bit of context behind this.
So back in nineteen fifty one March of nineteen fifty one,
(23:29):
there was a CIA analyst whose name was Sherman Kent,
and he filed a report on the probability of an
invasion by of Yugoslavia in the year nineteen fifty one.
We all know how that turned out. So how probable
is it that the USSR is going to invade? And
he concluded in his report that it was a quote
(23:51):
serious possibility. So what did he mean by serious possibility?
In retrospect. When he explained this, he thought it meant well,
first of all, just think in your heads what you
think it means, Nate, what do you think it mean?
Just you don't have to answer, Okay, So he thought
it meant sixty five percent or higher. So, right, more
(24:13):
than sixty five percent. Unfortunately, the person to whom he
conveyed his report and his findings, who was a chairman
of the policy Planning initiative, they had understood him to
mean that it was a lot lower than that. So
in their minds, serious possibility was like, oh, twenty percent
or maybe like a range from twenty to seventy eighty percent,
(24:37):
certainly not sixty five percent or higher. So there was
a huge miscommunication which resulted in massive policy missteps. Right,
just because how serious a serious possibility was was not Well.
Speaker 3 (24:53):
People are there were number match totobic right, you know
at former thirty eight, no silver bulletin. Right, we have
an election model where we give you know, a probability
is fundamentally defined, is a number between zero percent and
one hundred percent.
Speaker 2 (25:07):
Right, And a lot of times.
Speaker 3 (25:08):
People use weaseled They're like, well, Nicklint, you had Hillary
Clinton with a seventy one.
Speaker 2 (25:13):
Percent chance of winning the election. So you were wrong.
Speaker 3 (25:15):
We have the semantics of that, right, But like, but
you know, but you put a number there and people
think it's like, you know, understand that that represents it
bakes in the uncertainty in the model, the uncertainty in
the real world.
Speaker 1 (25:27):
Right.
Speaker 3 (25:27):
If I were to say, I think, by the way,
serious possibility to me implies like twenty percent. Right, if
I said that there's still a serious possibility Zaron could
lose a general election, right, because you're not saying probability,
You're saying, like, take this seriously, twenty.
Speaker 1 (25:41):
Twenty se Yeah, Well, when you put it in that context, right,
a serious possibility that Zar loses the election twenty five percent? Right, Now,
that sentence makes sense, which is why So when I
was a grad student and studying decision making, one of
the things that we talked about was how do you
communicate risk? Right? How do you communicate probabilities to people?
(26:02):
And it's really really hard, and it's hard in all
sorts of context. Right, how do you communicate probabilities when
it comes to things like global warming, right, or or
elections or something like that, And people just do not
understand probabilistic thinking. As we've talked about on the show
many many times, our brains just suck at probabilities and
(26:25):
at what they mean. Just by the way, why poker
is so good because it actually forces you to learn
what probability feels like viscerally, which is how the brain
learns the best. You know, I, for instance, you know
no bad beat stories on the podcast or in real life,
but I know how it feels to lose on day
four of the main event of the World Series as
(26:46):
a ninety eight point six percent favorite in a multi
millionship pot. It happens, right, It feels like it shouldn't
because ninety eight point six percent feels like it should
be one hundred percent. But it's not. Probabilities matter, and
we're so so bad at them. And yet something that
you just said, Nate, which is absolutely crucial, is that
we're number phobic. When you tell people, you know what,
(27:09):
the best way to communicate probability is, state the probability.
State the damn thing. Put a number on it. Actually
say you know it's I think the probability is between
ten percent and fifteen percent, and I am seventy five
percent sure In this estimate.
Speaker 3 (27:26):
Rights, be explicit about the language that you're using it.
I believe the IPCC the Global Climate reports. Right, they
will use language like very likely a lot. But in
the appendix you look it up and they say very
likely means whatever it is ninety five percent or higher?
Speaker 2 (27:41):
Right, nay?
Speaker 1 (27:42):
How many people reading the report then go to the appendix.
Speaker 3 (27:44):
To see see s report. My whole family once gave
each other the Iraq Study Group report for like Christmas
or something. It's that kind of that kind of family.
But no, but and then you know, look house this year,
but no, look uh, because the apsode is people use
this as weasel words. Right, They're intentionally ambiguous to say
(28:07):
later on, no, I was right, I was wrong, right,
which is lame.
Speaker 2 (28:10):
Right.
Speaker 3 (28:10):
People don't get any better unless they feel the pain of,
like of putting something which is in the public record
and is accountable to some degree.
Speaker 2 (28:18):
Obviously, you need like.
Speaker 3 (28:19):
A large sample of predictions to be able to evaluate,
you know, do do of your seventy percent probabilities? Do
seven out of ten come true in the long run? Right,
But you want to play a little bit of the
game here, how likely is it?
Speaker 1 (28:31):
Yeah, let's absolutely do it? So the way that this
game is going to work at first is I am
going to tell you a phrase, Nate, and then you
will tell me what percent probability you think that that
phrase represents, and then I'll think of my answer as well,
and if you guys want to play along, feel free
to think of yours. All right, So if I tell
(28:54):
you almost certainly, what are you thinking?
Speaker 2 (28:59):
Ninety five percent plus?
Speaker 1 (29:01):
Okay, so almost certainly ninety five percent plus. I was
actually going to go a little bit lower and say
ninety percent plus, just knowing that in this world basically
nothing is certain. And if we're at above ninety percent probability,
like holy shit. You know, as a gambler or as
an investor, if I told you that you had an
investment that had a ninety percent probability of succeeding, how
(29:23):
many of you would take that investment? And I hope,
I hope most of you. But and if I told
you that you could take a gamble with a ninety
percent probability of success.
Speaker 2 (29:33):
Yeah, people are there gambling, right.
Speaker 3 (29:35):
I mean, you'll learn in poke if you can get
like a fifty four percent edge, yeah, it's pretty good.
Speaker 1 (29:41):
It's amazing. But I'm not saying that that means almost certain,
but to me, like above ninety percent, given how much
uncertainty and ambiguity there are in the world, so those
are two different things, right. Uncertainty is we're not quite
sure what the probabilities are. Ambiguity is we're not even
quite sure kind of what the factors are. We're not
sure if our model is one hundred percent correct and
(30:02):
is accounting for everything. So given all of that, I
would actually say, like above ninety percent would be almost certainly.
Do you I don't know if that makes you rethink
your answer or not.
Speaker 3 (30:12):
You know, I watched en f NBA playoff games where
teams blue seventeen point leads and things like that in
the fourth quarter, So like, I'm feeling I want the
security of ninety five percent.
Speaker 1 (30:21):
All right, you want the security of.
Speaker 3 (30:23):
After playing poker for a few weeks. Yeah, We're nothing
is certain that I'm like, I want my almost certainly
s at ninety five Right.
Speaker 1 (30:28):
That makes that makes sense? So what would you would
you actually like what would you say for like a
ninety plus or an eight? Is there something that you
is there a phrase that you would think more accurately.
Speaker 2 (30:39):
Represents that very likely highly likely.
Speaker 1 (30:42):
Huh interesting because I would think that very likely would
be below ninety percent. See, this is this is how,
this is why this is ambiguous.
Speaker 2 (30:50):
All right?
Speaker 1 (30:51):
So I am going to give you another phrase. If
I said that something was unlikely to happen.
Speaker 3 (30:58):
Yeah, I'd say unlikely or for that matter of the counterpart.
Likely is one of the worst and most ambiguous terms
to use in that context, right, because literally it can
mean depending on the context. Anythink from like zero point
zero zero zero percent one percent zero zero zero one
to like forty nine percent.
Speaker 2 (31:15):
Right, it's very ambiguous.
Speaker 3 (31:16):
I would tend to think unlikely means twenty five or
thirty percent, somewhere in the middle of the below fifty
percent range.
Speaker 2 (31:22):
What about you, Yeah, I was.
Speaker 1 (31:24):
Going to be at around twenty five percent or below. Right,
Any of that is unlikely, and you know, we can
start we can start kind of playing around with it
a little bit with adjectives. But I totally agree with
you that likely. What about likely? By the way, would
would you say likely is above above what percentage is likely?
Is it above fifty?
Speaker 3 (31:44):
If feel like you're a little asymmetric like likely, I
think you have to be sixty or so.
Speaker 2 (31:49):
Right, Yeah, it is.
Speaker 3 (31:51):
Asymmetric, possible or probable. These ones are pretty bad, right,
You want to do one more?
Speaker 1 (31:57):
Yeah, let me let's do it all right? So, how
about if I actually add an adjective to unlikely and
say highly unlikely. Now, what are we talking now?
Speaker 3 (32:07):
Ten percent or below? I think it's kind of the
counterpart to I don't know why. I think it's in
percent of blowing. There was like ninety five percent.
Speaker 1 (32:13):
I was about to say, why they asymmetry, so you said,
you know, the just highly likely was ninety five I
have still.
Speaker 3 (32:18):
A large language model teasing out implicit contexts from the
way these phrases are used in the real world.
Speaker 2 (32:24):
I don't know what checchiput would say.
Speaker 1 (32:26):
So highly unlikely, I would say it is interesting because
I might actually be lower than you. I might say,
like below if it's highly unlikely, like below five percent,
Like it's just you're telling me that it's almost certainly
not going to happen to me. Right, that like highly
unlikely and almost certainly kind of go hand in hand.
(32:50):
But let's if you actually kind of go out in
context a little bit with that. Think about weather reports,
which is something where we experience kind of that's one
of these things where we do get probabilities, where we
do get percentages, and we experience those on a daily basis. Right, you,
(33:11):
what what is your threshold, Nate for bringing an umbrella?
Speaker 5 (33:14):
Like?
Speaker 1 (33:14):
What's your an umbrella?
Speaker 2 (33:16):
I find umbrella?
Speaker 1 (33:17):
Okay, that was about this is true?
Speaker 2 (33:20):
Why is umbrella technology not improved more?
Speaker 1 (33:23):
Nate and I have walked together in New York City
rainstorms where I'm like, do you want to share my umbrella?
He's like, I got my baseball cap. I'm good. But
but you know, for people who are not like you
and who actually care about rain, like, what's your threshold
for bringing an umbrella? Like for me, if it's like
fifty percent chance of rain, I'm probably not going to
(33:44):
bring it. You know, if it's like above sixty, I'll
probably probably bring an umbrella. You know, it just it
really just depends on what I'm doing. And so you
know that's but you think about those days when it
was ninety percent chance of rain and it didn't rain.
Speaker 2 (33:58):
Okay's great, let's get the audience.
Speaker 1 (34:01):
Let's do it all right, one last one. We're going
to do it with you guys, and I'm gonna So
I'm going to ask you to raise your hands.
Speaker 3 (34:07):
So if I say something is possible, that's a secret password, right, yeah, possible,
and you have to take one of the following ranges
zero twenty five percent, twenty about to fifty fifteen, seventy
five pcent five one hundred. Right, if I have something
is possible, raise your hand. If you interpret that as
zero to twenty five percent, okay, we have about a
quarter about z you're just twenty percent the hands up
(34:28):
in the audience, right, yeah, quite a few hands. I
will say twenty five to fifty percent a little bit more,
kind of solid.
Speaker 1 (34:36):
It's kind of similar, but probably a little more. Okay,
how about fifty to seventy five and.
Speaker 3 (34:42):
There are a handful of hands hands possible, that could
be And how about seventy five percent or more one day?
So the way to average is like thirty six or
something percent. We're like doing we're doing science here, yeah,
doing it on the fly. Yeah, but people think it
means anything from five percent to eighty percent, right if
you ask people to write down individual guesses so like,
(35:03):
so not very useful to have that, to have.
Speaker 1 (35:05):
That for you. No, No, it's really not because what
you know, what do you even mean probbable likely? Like
it is? You know, it's such a hedgeword. And what
we're trying to do is actually force you to be
more precise in your probabilistic judgments, because precision matters, right,
whether it's the precision of the USSR invading Yugoslavia or
(35:27):
a gamble that you're taking out the poker table right out.
Speaker 3 (35:32):
When it comes to like politics and things like that,
political questions, like, people are also just often interpreting stuff
in bad faith, right, Like I think that I think
that when you say there's a third chance of rain
and doesn't rain, people don't get as mad as when
there's a third chance of Donald Trump winning and he wins,
or things like that for example. But like, but you know,
(35:52):
politics makes people's brains misfire in various ways absolutely well.
Speaker 1 (35:58):
As soon as there's personal motivation there, right, as soon
as your identity is tied up in something like politics,
all of a sudden, your ability to parse these things.
You start thinking in absolutes, which is how are our
brains are programmed to think? Right? Ninety percent basically one
hundred seventy is basically one hundred sixty five basically one
hundred thirty basically zero.
Speaker 2 (36:18):
Right. We just let's at least.
Speaker 3 (36:20):
Get sixty five, right, is certainly either fifty fifty zero,
one hundred. Let's at least get those middle zones right
as a stepping stone to some more PI.
Speaker 1 (36:29):
Yeah, and I think I think that the bottom line
is that it's very difficult to communicate probabilities in plain language,
and you do need to get people accustomed to having
numbers associated with them, and one of the best ways
of doing that is to try to figure out, Okay,
what experience can I tie that to in their life
that makes them understand what this actually means?
Speaker 2 (36:51):
Right?
Speaker 1 (36:51):
That percent is not zero?
Speaker 2 (36:53):
I'm not way serious.
Speaker 1 (36:53):
Yeah, no, teacher, kids, poker. I've actually talked about this
many times, and I actually think that that is one
of the best ways that you can combat this.
Speaker 2 (37:04):
And we'll be right back after this break.
Speaker 1 (37:20):
Do you want to open it up to questions?
Speaker 3 (37:21):
Yeah, I say it's extraordinarily likely that we're going to
open it up to Q and A at this point.
Speaker 2 (37:27):
So there are mic runners. We can also point and shop,
but yeah.
Speaker 1 (37:30):
Okay, yeah, there are mic runners in the audience. So
raise your hand if you have a question. Yep, there's
one coming to you. Thanks.
Speaker 6 (37:38):
I studied statistics in graduate school and ended up in communications,
and I think one of the things that confounds this
problem is if somebody says to me, for example, climate
change isn't caused by us, I would say, not believing
myself that that's possible.
Speaker 4 (37:57):
That's my opinion.
Speaker 6 (37:57):
I know other people disagree, but in order to have
a conversation, I validate their opinion and move on. And
that's standard operating procedure when you're trying to actually change
minds of what you're saying is we're inaccurate and communicating.
Speaker 4 (38:12):
The real probabilities.
Speaker 6 (38:14):
But part of what's going on is that most of
the conversation is about trying to find some middle ground.
Speaker 1 (38:21):
So how do you separate those two uses?
Speaker 3 (38:24):
Yeah, it just and this kind of gets into the
conversation about Zoran earlier, right where he's going on podcasts
where the audience might not be favably inclined to him.
And I've done this too, Like marketing my book, I
talked to conserative audiences, liberal audiences, everything in between. Right,
And you're basically a politician, right, You're like you're trying
to code switch back and forth. You're trying to be
empathetic to your audience, You're trying to find points of
agreement in that disagreement. Maybe more politicians should take that lesson.
(38:47):
I mean, look, I generally think that when scientific communicators
try to like dumb things down too much, it's like
quite the right term. There's empathy, and there's there's empathy,
there's dumbing down, and there's like kind of like skipping
over the rough patches of the argument in a way.
(39:07):
They create like false certainty times, right, Like I generally
believe that like treat the audience as being reasonably smart
and sophisticated, right, I mean as poker players too, you know,
I think we are naturally suspicious, right, And I think
people can like people can tell I think when a
politician is being inauthentic or when they're not being kind
(39:32):
of communicated with fully forthrightly. Right, Like I thought this
was an issue at the beginning of the COVID pandemic.
We're changing advice about like masks and things like that, Right.
I think whenever people kind of like say, oh, the
science has settled on this question, well, on some questions,
it's settled on some questions that isn't right, and it's
like often used as a cudgel where there is genuine
(39:53):
uncertainty and so so yeah, I mean it's it's look,
we wrestle with this every day journalists too. But like,
I'm air more on the side of like, you know,
you can be empathetic in how you present something, and obviously,
if you're in a kind of question like not everything
you say in response, you're not going to correct any way.
Oh literally, you're wrong, you're wrong, but let me tell
you something else. Right, So I'm yeah, empathetic, but when
(40:15):
it official sign of a communication, I think should aim
more in the side of precision.
Speaker 1 (40:18):
I think that I think that we are also not
tolerant of ambiguity. Right that it's much easier to win elections.
It's much easier to win over a crowd if you
speak in absolutes, if you speak in certainties, and the
person who says, you know, I'm really not sure about this,
(40:42):
you know, they're here are the pros, here are the
cons And who gives the more nuanced response is not
the person who ends up getting ahead. And so there's
a fundamental mismatch between the need to communicate ambiguity and
uncertainty and the fact that you know some things we
just don't know, and that there are these kind of
confidence intervals there, and the need to tell a story
(41:07):
and tell a compelling story. And this is something that
you know, Nate, You and I have to struggle with
us storytellers too. I mean, we're communicators, we're journalists. We
make choices all the time when we write an article,
when we write a book, how do we tell the story?
What story do we tell? And you can't constantly. I
mean a book will be absolutely unreadable if every single
(41:28):
paragraph is a caveat where you know, well, you know,
you can also interpret it this way and this way
and I'm not quite sure about this, right, you can't.
You can't work that way, and so you make choices
all the time.
Speaker 3 (41:40):
Of course, sometimes ambiguity is strategic, right, Like let's say
Marie and I are on a double date with our
respective spouses and then a third couple that we don't know,
that a friend kind of set us with for a
friend's day, and they're super fucking annoying and we hate
their guts. Right, you know, if I say something like Marie,
what time did you say your flight was tomorrow morning?
Speaker 2 (41:57):
Right?
Speaker 3 (41:58):
Yeah, that's ambiguous. What it really means is that let's
gett's great.
Speaker 1 (42:02):
And Nate and I have known each other for long
enough that I would say, you know, it's at seven am,
we really really have to go. Yeah, so there are
strategic uses of it. Yeah, there are more questions back there.
Speaker 4 (42:13):
I am a longtime listener, first time caller.
Speaker 1 (42:16):
Wellco to the show.
Speaker 2 (42:17):
Yeah, yes.
Speaker 4 (42:18):
My question is how much do we do we think
Zauron's win is the inter syncracies in New York City
and him being a great candidate and Cuomo sucking, and
how much is the political climate has changed in some
way since the last election?
Speaker 1 (42:31):
That is, I mean, that is such a good question,
because the Cuomo sucking part of it is actually huge.
That sounds like that sounds like a silly statement, but
I actually think that that is an idiosyncrasy of this
election from a psychological standpoint, because never underestimate the power
(42:52):
of people to band together and coalitions to actually stick
together when there's one enemy, right, when there's a clear
someone who no one wants to see, When all of
a sudden, people who would never vote together, who would
never kind of partners partner up. And this is from
a psychological stamp.
Speaker 3 (43:10):
What you see that he both ran a bad campaign
and kind of, to us an informal term, kind of
like cock blocked all the other candidates in the field,
right where all the money from hedge funders and people
like that went to Cuomo. And you saw a quotes
when people were like big Cemo donors like I didn't
really care about that much, but it seemed like that's
what everyone was backing. I'm not going to back the
socialist right and so therefore and so yeah, you know,
(43:32):
if you'd had a fully fledged campaign between Zoran and
Brad Lander or something, or Adrian Adams, it might have
been closer.
Speaker 2 (43:39):
But he's a good can.
Speaker 3 (43:39):
I mean, look a lot of times political analysts like
me are left saying, yeah, the wins and losses are
what matter, but for analyzing trends and close counts, right
you know. So you know, look, if he had lost
seven point instead of won by seven points, I'd still
say that was pretty impressive.
Speaker 5 (43:55):
Right.
Speaker 2 (43:55):
It might be a sign of change here.
Speaker 3 (43:57):
It's a cleaner story, I think, But usually surprising outcomes
are overdetermined, right, you know, it has to do with
the changing of the guard generationally. It has to do
with like he kind of figured out the right formula
for more left wing ideas. It's not wilk culture stuff, right,
it's affordability, it's working class people, things like that.
Speaker 2 (44:16):
Right.
Speaker 3 (44:17):
He's a very well presenting guy, right, who's very New York.
I think in some ways his mom was a filmmaker,
and his visuals are all quite stunning and beautiful and cuomo.
Speaker 2 (44:28):
So it's like four things coming together.
Speaker 3 (44:31):
But he also won by enough margin where maybe only
three of those things or two, and to have it
to come together, we still have one probably.
Speaker 1 (44:36):
Yeah. And when things are over determined, by the way,
we can't answer your question right, When things are over determined,
you can't quite know what the crucial factors were. So
I think that the real answer to your question remains
to be seen. But it's a really interesting thing to
try to disambiguate and try to see kind of how
did we end up here? And I think that this
(44:58):
is an election that people will be looking back and
doing some commentary on for many years.
Speaker 7 (45:04):
So I want to ask political polls, so I think
you know something about it. So now I've heard the
lecture on words. And so if I see that one
candidate has a forty two percent chance of winning and
another candidate has a forty six percent chance, should I
(45:24):
interpret that to say they both have low probability? Or
they have or I mean I guess, or is it
so close? Really doesn't matter?
Speaker 3 (45:35):
Well, for one thing, people who work in polling or
who report on pulling need to be clear about a
probability versus a percent of the vote. Right, If it's
Trump forty six percent in say Texas, Harris forty two
percent undecided, third party is the remaining whatever eighteen percent?
Speaker 2 (45:52):
Right, like a four point lead. How often does that
translate into a win?
Speaker 3 (45:56):
That's an empirical question, right, The answer might be something
like seventy percent of the time.
Speaker 2 (46:01):
Russia, And in New York, what were the polls saying before?
In New York?
Speaker 3 (46:05):
No, the polls underestimated, I mean, had they had shown
the race tightening a lot. Some of the polls showed
Zoran pulling ahead after ranked choice voting. Almost none Maybee,
with one exception, had him winning the first round outright,
and none of them had him winning by like that
wide margin. Right, So this is what happens with polls
(46:25):
is like in a New York race, they assume turnouts
fairly low. They're surveying the people that like always turn
out in New York MARYORL races, who consideringly unlikely voters
are twenty percent of electorate.
Speaker 1 (46:36):
Right.
Speaker 3 (46:36):
Cuomo got his numbers among that twenty percent, but then
Zoran turned out people that never vote in mayoral elections
in e York. By the way, a lot of New
York's are transplants from around the country, all around.
Speaker 2 (46:46):
The world, right, so we don't have that like tie
to local politics. Right.
Speaker 3 (46:51):
I'm a person covers politics, listen to New York. I
don't know that much about like New York politics, right,
and it's very typical in some ways. But he he
broke through and became its cliche, but became viral in
a way that you know, I guess pollsters were too
conservative in their in their methods and missing and missing
these voters.
Speaker 1 (47:09):
We have time for one more question, hi.
Speaker 5 (47:11):
Things I was just curious. I know this is probably annoying,
like too long in the future kind of question, but
does Zorin's win at all change the probabilities that you
think about candidates in twenty twenty eight for Democratic primary
or I guess.
Speaker 1 (47:26):
The general election too.
Speaker 3 (47:28):
So with actually my former colleague at five thirty eight,
Galen Druke, we did a Democratic twenty twenty eight primary draft,
right or do it so it's like a draft, like
a fancy football draft or something. Galen got the first
pick and the first candidate on my list was AOC.
I thought he'd take Josh Shapiro or someone and said
he took AOC too, So it was mad about that.
(47:50):
But like we both thought, and this is before Zoran,
that she was let me put this carefully, from talking
about probabilities, right to say the most likely candidate might
mean a fifteen percent chance.
Speaker 2 (48:01):
Right, there's nobody in the field who is a clear
front runner.
Speaker 3 (48:04):
But we both thought that she was more luckily than
any other candidate to become the nominee in twenty twenty eight,
before before Mom Donnay came along, right, And again it's
probably because like look Democrats, of all these retreads, right,
the Clinton family, the Cuomo family, the Biden family. I
bet Jill will probably fantasize sometimes what if I become president? Right,
(48:26):
like House of Cards or something. Right, I'm I think
people are tired of all these families.
Speaker 2 (48:32):
Right.
Speaker 3 (48:32):
I remember seeing in twenty sixteen, I was in New
Hampshire covering the race for five thirty eight in ABC News, Right,
and like Hillary Clinton spoke to a group of like
then at college, right, Franklin Pierce College or something like that.
Speaker 2 (48:46):
Right, you know, the average age is twenty or something.
Speaker 3 (48:48):
She's talking about like the Cold War, and like the
students size are gleazing over they don't remember the Cold War, right,
And now that was you know, was eight nine years
ago now, right, And so like, look, I think I
think it's a good thing to see. I mean, Zaraan
was literally half of like Cuomo's age. Right, I think
it's a good thing. Mcrat parties about present and was
(49:10):
how can everyone's so freaking old? Right, I think it's
a good thing. Is is to you know, have cannates
that are good on social media, are substantive. I think
she's a pretty canny and smart politician and shows some
restraint at times.
Speaker 2 (49:23):
So yeah, it does change my views a little bit. Maria,
do you have a take now?
Speaker 1 (49:27):
I mean, this is one of the things that I
was talking about when I was talking about some of
the long term consequences of this election, right, And I
think a lot of it will depend on what ends
up happening once Zorn takes power, right, if he's elected,
how he actually handles himself in office, how popular he is.
I think that that will actually have a large bearing
(49:49):
on your question in terms of, you know, what does
the Democratic Party end up taking from this, because they
could take two very different lessons one AOC Two if
Zorn tanks for some reason right and becomes incredibly unpopular
and like the you know, we don't know, we can't
we don't have a crystal ball. But if something like
that were to happen, I think they'd be like, see,
(50:09):
we told you so right, we need to go back
to so I think you could see either thing working out,
so you can a lot rest on his shoulders.
Speaker 2 (50:18):
I guess.
Speaker 1 (50:19):
Yeah. That was our first Risky Business Live and we're
so happy you were here. That was our show from
the Aspen Ideas Festival. By the way, our segment on
probabilities was inspired by Adam Kucharski's newsletter Understanding the Unseen.
(50:40):
We'll have a link to that post in the show notes.
Thanks for listening. Let us know what you think of
the show. Reach out to us at Risky Business at
pushkin dot fm. And by the way, if you're a
Pushkin Plus subscriber, we have some bonus content for you
that's coming up right after the credits.
Speaker 3 (50:58):
And if you're not subscribing yet, consider signing up for
just six ninety nine a month. What a nice price
you get access to all that premium content and and
we're listening across Pushkin's entire network shows.
Speaker 1 (51:10):
Risky Business is hosted by me Maria Kanikova.
Speaker 2 (51:12):
And by me Nate Silver.
Speaker 3 (51:14):
The show is a co production of Pushkin Industries and iHeartMedia.
This episode was produced by Isabelle Carter. Our associate producer
is Sonia Gerwin. Sally Helm is our editor, and our
executive producer is Jacob Boldstein. Mixing by Sarah Bruguier.
Speaker 1 (51:29):
Thanks so much for tuning in.
Hosts And Creators
Maria Konnikova
Nate Silver
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