1
00:00:15,604 --> 00:00:26,604
Speaker 1: Pushkin, Hey, Risky Business listeners. This weekend, Nate and I

2
00:00:26,644 --> 00:00:28,604
Speaker 1: took a break from the World Series of Poker to

3
00:00:28,684 --> 00:00:32,124
Speaker 1: go to the Aspen Ideas Festival. Sunday night, we got

4
00:00:32,124 --> 00:00:35,244
Speaker 1: to tape a live episode of the Risky Business podcast

5
00:00:35,564 --> 00:00:38,204
Speaker 1: and we're so happy to share that with you today.

6
00:00:38,484 --> 00:00:44,044
Speaker 1: We hope you enjoy it. Welcome back to Risky Business,

7
00:00:44,084 --> 00:00:47,884
Speaker 1: a show about making better decisions. I'm Maria Kondakova.

8
00:00:47,564 --> 00:00:48,524
Speaker 2: And I'm Nate Silver.

9
00:00:49,244 --> 00:00:51,844
Speaker 1: So today on the show, we're going to be starting

10
00:00:52,404 --> 00:00:54,284
Speaker 1: with a little bit of poker. So Nate and I

11
00:00:54,324 --> 00:00:57,364
Speaker 1: are both here from lovely Las Vegas because it is

12
00:00:57,404 --> 00:01:00,004
Speaker 1: currently the middle of the World Series of Poker, but

13
00:01:00,124 --> 00:01:02,884
Speaker 1: we love Aspen and the Aspen Ideas Festival so much

14
00:01:03,204 --> 00:01:05,084
Speaker 1: that we're taking time off to be here.

15
00:01:05,284 --> 00:01:08,204
Speaker 3: With only one straight days of poker, we can spare

16
00:01:08,284 --> 00:01:10,164
Speaker 3: one day for the Aspen Night Festivals.

17
00:01:10,484 --> 00:01:14,284
Speaker 1: We're going to be talking about a recent controversy at

18
00:01:14,444 --> 00:01:17,124
Speaker 1: the World Series of Poker and what happened there. But

19
00:01:17,924 --> 00:01:21,044
Speaker 1: after that we're going to be getting into something much metior.

20
00:01:21,444 --> 00:01:23,524
Speaker 2: Yeah, I think the election of z around.

21
00:01:23,604 --> 00:01:26,284
Speaker 3: I'm Donnie in New York or not, excuse me, The

22
00:01:26,364 --> 00:01:29,004
Speaker 3: nomination he's still has to win. The general election is

23
00:01:29,164 --> 00:01:32,084
Speaker 3: one of the most interesting and seismic events in American politics,

24
00:01:32,444 --> 00:01:34,444
Speaker 3: at least since the election, you know, one of the

25
00:01:34,484 --> 00:01:38,484
Speaker 3: most successful opportunities for like a explicitly socialist left wing

26
00:01:38,484 --> 00:01:41,444
Speaker 3: candidate to Governess said, it's actually very pro financed. New

27
00:01:41,484 --> 00:01:44,404
Speaker 3: York is not left in the way that Portland is

28
00:01:44,524 --> 00:01:46,244
Speaker 3: or Espen might be, or things like us. We're going

29
00:01:46,284 --> 00:01:48,804
Speaker 3: to talk about both the strategy behind rank choice voting

30
00:01:48,804 --> 00:01:50,364
Speaker 3: and how that might have affected things, but also just

31
00:01:50,764 --> 00:01:53,364
Speaker 3: you know, a big political moment, how this might affect

32
00:01:53,364 --> 00:01:54,924
Speaker 3: the party's decisions going forward.

33
00:01:55,284 --> 00:01:58,364
Speaker 1: And after that we will play a little game called

34
00:01:58,524 --> 00:02:02,484
Speaker 1: how likely is It where we will test our knowledge

35
00:02:02,524 --> 00:02:08,284
Speaker 1: and your knowledge of probabilistic thinking. So let's get into it, Nate. Yeah, So,

36
00:02:08,444 --> 00:02:14,124
Speaker 1: first of all, we have a controversy at the World

37
00:02:14,164 --> 00:02:17,284
Speaker 1: Series of Poker last week was one of the biggest

38
00:02:17,364 --> 00:02:20,364
Speaker 1: tournaments of the summer. It's called the millionaire Maker because

39
00:02:20,404 --> 00:02:22,924
Speaker 1: first place is always guaranteed to be at least a

40
00:02:22,924 --> 00:02:26,844
Speaker 1: million dollars. This was a record breaking millionaire Maker, so

41
00:02:27,004 --> 00:02:30,884
Speaker 1: second place was also over a million dollars. This was

42
00:02:31,204 --> 00:02:35,804
Speaker 1: complicated by the fact that there was also a promotion

43
00:02:36,364 --> 00:02:39,804
Speaker 1: being run by a rival brand, the World Poker Tour,

44
00:02:40,204 --> 00:02:42,964
Speaker 1: which one of the two players who ended up getting

45
00:02:43,004 --> 00:02:44,924
Speaker 1: heads up, which is one of the final two players,

46
00:02:45,004 --> 00:02:48,404
Speaker 1: was eligible for which meant that if he won the tournament,

47
00:02:48,484 --> 00:02:51,484
Speaker 1: and only if he won the bracelet, he would get

48
00:02:51,484 --> 00:02:56,284
Speaker 1: an extra million dollars. So think about for a second, right,

49
00:02:56,324 --> 00:02:59,284
Speaker 1: in the context of decision making, in the context of

50
00:02:59,884 --> 00:03:04,884
Speaker 1: incentives exactly, incentives matter. What that does they get heads up?

51
00:03:05,204 --> 00:03:07,244
Speaker 1: So two people left, only one.

52
00:03:07,084 --> 00:03:09,924
Speaker 2: Time wines final feo.

53
00:03:10,004 --> 00:03:12,644
Speaker 3: Happens to be the guy who can win this additional

54
00:03:12,684 --> 00:03:15,204
Speaker 3: million dollar bonus on top of the million dollars has

55
00:03:15,204 --> 00:03:15,644
Speaker 3: already won.

56
00:03:15,844 --> 00:03:20,124
Speaker 1: Yes, Unfortunately, this guy has a chip deficit of nine

57
00:03:20,284 --> 00:03:23,284
Speaker 1: to one. So that means that the other player, right,

58
00:03:23,324 --> 00:03:26,124
Speaker 1: the one who is not eligible for the million dollars,

59
00:03:26,364 --> 00:03:30,524
Speaker 1: has him out chipped nine times. So what that means

60
00:03:30,604 --> 00:03:33,124
Speaker 1: is that usually nine times out of ten, that guy's

61
00:03:33,164 --> 00:03:35,604
Speaker 1: going to win the tournament. And what happens to the

62
00:03:35,604 --> 00:03:42,404
Speaker 1: million dollar bonus, It disappears incentives matter. So what ended

63
00:03:42,484 --> 00:03:46,764
Speaker 1: up happening was a very strange heads up match that

64
00:03:46,844 --> 00:03:49,764
Speaker 1: looked an awful lot. This is just allegations, you know,

65
00:03:49,844 --> 00:03:53,604
Speaker 1: nothing proven, an awful lot like collusion. There was a

66
00:03:53,724 --> 00:03:56,604
Speaker 1: lleged chip dumping where one of the players dumped chips

67
00:03:56,644 --> 00:03:59,284
Speaker 1: to the other players and made what was supposed to

68
00:03:59,324 --> 00:04:02,004
Speaker 1: be an incredibly competitive, televised by the way this was

69
00:04:02,044 --> 00:04:05,604
Speaker 1: all televised match into something that looked very strange into

70
00:04:05,644 --> 00:04:07,684
Speaker 1: people outside of poker. They were like, what in the

71
00:04:07,684 --> 00:04:12,044
Speaker 1: world was going on? The player who had the million

72
00:04:12,084 --> 00:04:16,164
Speaker 1: dollar incentive won the bracelet, won the tournament, and they

73
00:04:16,164 --> 00:04:18,244
Speaker 1: are now currently both under investigation.

74
00:04:20,204 --> 00:04:21,884
Speaker 2: Yeah. No, I mean there are a couple of themes here.

75
00:04:21,924 --> 00:04:23,764
Speaker 3: I mean one is kind of how so it's not

76
00:04:23,844 --> 00:04:27,524
Speaker 3: just that the tournament is televised, it's that in televised poker,

77
00:04:27,964 --> 00:04:30,924
Speaker 3: the audience gets to see the player's private cards.

78
00:04:31,204 --> 00:04:32,804
Speaker 2: Right, So to think that you could have.

79
00:04:32,844 --> 00:04:35,844
Speaker 3: This live streamed on TV and everybody can like see

80
00:04:35,844 --> 00:04:37,884
Speaker 3: the hands face up, basically accept the two opponents that's

81
00:04:37,884 --> 00:04:40,964
Speaker 3: taped to lay fifteen minutes. Right, If one player what's

82
00:04:40,964 --> 00:04:45,884
Speaker 3: his name, Jesse, Jesse, If Jesse had been way ahead.

83
00:04:45,644 --> 00:04:47,684
Speaker 2: Then maybe, like you know what, maybe we're gonna be

84
00:04:47,724 --> 00:04:48,204
Speaker 2: a little loose.

85
00:04:48,244 --> 00:04:52,404
Speaker 3: But instead, every single decision he plays as though he

86
00:04:52,444 --> 00:04:55,164
Speaker 3: has knowledge of what his opponent has.

87
00:04:55,284 --> 00:04:55,484
Speaker 2: Right.

88
00:04:55,524 --> 00:04:57,124
Speaker 3: Almost that exception to the point where the hosts are

89
00:04:57,124 --> 00:04:59,484
Speaker 3: commenting on the real time. If you go and look

90
00:04:59,524 --> 00:05:02,964
Speaker 3: at computers, computers now have solved poker at least heads

91
00:05:03,044 --> 00:05:05,044
Speaker 3: up pick a poke in particular to a high degree.

92
00:05:05,204 --> 00:05:07,924
Speaker 3: These are all plays that are done zero percent of

93
00:05:08,004 --> 00:05:10,724
Speaker 3: the time in op and we'll play that are done

94
00:05:10,764 --> 00:05:14,564
Speaker 3: almost your percent of the time by two very experienced players. Right,

95
00:05:14,884 --> 00:05:17,604
Speaker 3: things like folding a pair to a tiny bit, which

96
00:05:17,684 --> 00:05:18,204
Speaker 3: heads up poker.

97
00:05:18,204 --> 00:05:19,924
Speaker 2: It's hard to make a hand in poker. You're never

98
00:05:19,964 --> 00:05:24,164
Speaker 2: supposed to do that. And so now and people are torn. Right.

99
00:05:24,164 --> 00:05:26,684
Speaker 1: There are people who say, well, they didn't hurt anyone

100
00:05:26,724 --> 00:05:29,124
Speaker 1: because they were heads up, right, so it's not like

101
00:05:29,164 --> 00:05:31,764
Speaker 1: they took chips from a third player. Now, I'm writing

102
00:05:31,764 --> 00:05:34,724
Speaker 1: a book right now about cheating in games, and so

103
00:05:34,844 --> 00:05:37,244
Speaker 1: this is something that kind of I've thought about a lot.

104
00:05:37,444 --> 00:05:40,044
Speaker 1: And on the one hand, I am sympathetic a little

105
00:05:40,044 --> 00:05:42,444
Speaker 1: bit to that argument because a lot of the worst

106
00:05:42,724 --> 00:05:45,364
Speaker 1: cheaters and a lot of the big cheating things in games,

107
00:05:45,484 --> 00:05:48,484
Speaker 1: it hurts other people, right, it hurts other players. You're

108
00:05:48,524 --> 00:05:52,564
Speaker 1: taking away equity from other players. If we assume that

109
00:05:52,644 --> 00:05:56,684
Speaker 1: they were playing completely above board up until this point,

110
00:05:56,884 --> 00:06:00,764
Speaker 1: then no one else was hurt. However, However, there is

111
00:06:00,804 --> 00:06:03,644
Speaker 1: another consideration here. Right. So one of the things that

112
00:06:03,804 --> 00:06:07,444
Speaker 1: I am a huge proponent on, and we've talked about

113
00:06:07,444 --> 00:06:09,324
Speaker 1: this on the show, is sportsmen.

114
00:06:09,884 --> 00:06:10,004
Speaker 2: Right.

115
00:06:10,044 --> 00:06:14,044
Speaker 1: There are two concepts, gamesmanship and sportsmanship. Gamesmanship is you

116
00:06:14,124 --> 00:06:16,484
Speaker 1: know I'm going to win, and you know, I don't

117
00:06:16,484 --> 00:06:18,604
Speaker 1: care how I get there, right, Like, I will take

118
00:06:18,684 --> 00:06:22,204
Speaker 1: every single edge I can possibly take because I want

119
00:06:22,284 --> 00:06:25,164
Speaker 1: to get there. Sportsmanship is doing it in kind of

120
00:06:25,164 --> 00:06:28,124
Speaker 1: a the spirit of the game, right, the spirit of

121
00:06:28,164 --> 00:06:30,924
Speaker 1: the sport, in a to use an old school term,

122
00:06:30,924 --> 00:06:35,084
Speaker 1: in a gentlemanly fashion, right, that you actually respect the

123
00:06:35,084 --> 00:06:38,924
Speaker 1: game you're playing. When you're looking at a televised competition

124
00:06:39,204 --> 00:06:42,244
Speaker 1: that's representing the game and people are watching it and

125
00:06:42,324 --> 00:06:47,884
Speaker 1: expecting something to instead of competition, instead of an actual match,

126
00:06:48,244 --> 00:06:53,724
Speaker 1: to give people, you know, chip dumbing or whatever it is,

127
00:06:54,244 --> 00:06:56,644
Speaker 1: that goes against the spirit of the game, and that

128
00:06:56,764 --> 00:06:57,084
Speaker 1: is something.

129
00:06:57,204 --> 00:06:58,124
Speaker 2: Also it also.

130
00:06:58,124 --> 00:07:00,364
Speaker 3: Lates the rules, Like the first rule of poker is

131
00:07:00,364 --> 00:07:03,204
Speaker 3: that one player to a hand. It's an individual game,

132
00:07:03,444 --> 00:07:06,084
Speaker 3: not a team game. Right, So that fundamental precept of

133
00:07:06,084 --> 00:07:07,004
Speaker 3: poker is violated.

134
00:07:07,164 --> 00:07:09,124
Speaker 1: It does, and you know, I was thinking about it

135
00:07:09,164 --> 00:07:12,124
Speaker 1: in kind of broader games. Like imagine if you were

136
00:07:12,164 --> 00:07:14,964
Speaker 1: watching a tennis match, right, that's also a heads up match,

137
00:07:15,004 --> 00:07:17,764
Speaker 1: a player one against the other, and it became clear

138
00:07:18,204 --> 00:07:20,964
Speaker 1: that someone was throwing the match, and that's happened, right.

139
00:07:21,044 --> 00:07:23,604
Speaker 1: Tennis is actually one of the sports where cheating is.

140
00:07:24,404 --> 00:07:27,084
Speaker 1: There's a lot of it going on, and if you

141
00:07:27,164 --> 00:07:30,124
Speaker 1: watch that, you feel cheated as a spectator and as

142
00:07:30,124 --> 00:07:32,164
Speaker 1: a lover of the game, you kind of feel like

143
00:07:32,244 --> 00:07:35,204
Speaker 1: something was taken away from you. So I can understand.

144
00:07:35,404 --> 00:07:38,244
Speaker 1: And by the way, I really like Jesse, like the

145
00:07:38,644 --> 00:07:42,084
Speaker 1: player who ended up winning. He's sweet and sweet, wonderful guy.

146
00:07:42,404 --> 00:07:44,804
Speaker 1: But you have to be careful, right, if you like someone,

147
00:07:44,884 --> 00:07:46,644
Speaker 1: it doesn't mean that what they did know in the rest.

148
00:07:46,644 --> 00:07:47,964
Speaker 3: It's just kind of a theme that will tie this

149
00:07:48,044 --> 00:07:50,564
Speaker 3: into kind of larger themes at this conference. So I

150
00:07:50,684 --> 00:07:52,684
Speaker 3: not just straddle back and forth being poker and like

151
00:07:53,044 --> 00:07:54,884
Speaker 3: the real world, but like I am involved in like

152
00:07:55,524 --> 00:07:58,644
Speaker 3: lots of small, tight knit communities, right, I'm not an

153
00:07:58,684 --> 00:08:00,004
Speaker 3: effective out your wist, But I know a lot of

154
00:08:00,004 --> 00:08:02,524
Speaker 3: people who describe themselves that way, right, I know, like

155
00:08:02,564 --> 00:08:05,244
Speaker 3: the sports analytics nerds, I know people who work in

156
00:08:05,244 --> 00:08:08,044
Speaker 3: politics and politics analytics nerds right, and like over and

157
00:08:08,084 --> 00:08:11,284
Speaker 3: over again, people are very short sighted about the weird

158
00:08:11,764 --> 00:08:14,764
Speaker 3: by normal person standards, norms and their small communities and

159
00:08:15,564 --> 00:08:18,284
Speaker 3: don't think about what happens when this kind of translates

160
00:08:18,564 --> 00:08:20,684
Speaker 3: to the outside world that hey, actually there's such a

161
00:08:20,684 --> 00:08:23,364
Speaker 3: thing as like the state of Nevada has gaming regulations.

162
00:08:23,524 --> 00:08:26,724
Speaker 3: If there's no regularity, are actually obligated to report that?

163
00:08:26,924 --> 00:08:29,044
Speaker 3: Or the fact that, okay, why are we having this

164
00:08:29,044 --> 00:08:32,204
Speaker 3: world series poker? It's bigger every year, despite the tariffs

165
00:08:32,204 --> 00:08:35,764
Speaker 3: and despite various headwinds, writing their setting record fields again

166
00:08:35,844 --> 00:08:36,204
Speaker 3: this year.

167
00:08:36,244 --> 00:08:37,764
Speaker 2: Well where do the players come from? Right?

168
00:08:37,804 --> 00:08:41,004
Speaker 3: They come from like watching poker on TV or on

169
00:08:41,084 --> 00:08:43,004
Speaker 3: video and saying that would be extremely fun if one

170
00:08:43,044 --> 00:08:44,684
Speaker 3: day I were to make a final table and I've

171
00:08:44,684 --> 00:08:46,964
Speaker 3: done it, you know, I have one time finished second

172
00:08:47,004 --> 00:08:49,244
Speaker 3: place an event like this, right, you know, it's a

173
00:08:49,284 --> 00:08:51,604
Speaker 3: thrill of a lifetime. But like to undermine that and

174
00:08:51,644 --> 00:08:53,764
Speaker 3: to do it in this way that like, I don't know,

175
00:08:53,804 --> 00:08:56,724
Speaker 3: I think it a narrowness of like perspective.

176
00:08:56,884 --> 00:08:59,204
Speaker 1: It does, it does, and I do think that. You know,

177
00:08:59,244 --> 00:09:01,964
Speaker 1: when you're even talking about game theory, there's short term

178
00:09:01,964 --> 00:09:03,924
Speaker 1: and there's a long term, and you need to be,

179
00:09:04,604 --> 00:09:06,084
Speaker 1: you know, no matter what, you need to have the

180
00:09:06,124 --> 00:09:07,924
Speaker 1: long term in mind and the long term health of

181
00:09:07,964 --> 00:09:12,284
Speaker 1: the game and of how it's perceived. And on that note, Nate,

182
00:09:12,364 --> 00:09:15,724
Speaker 1: do you want to switch gears and go a little

183
00:09:15,764 --> 00:09:19,444
Speaker 1: bit into the game theory of a different arena of politics.

184
00:09:19,884 --> 00:09:24,724
Speaker 1: So we are both New Yorkers and we just had

185
00:09:25,324 --> 00:09:29,844
Speaker 1: a Democratic primary that is national news. That is rare

186
00:09:30,244 --> 00:09:33,964
Speaker 1: for a primary, even in New York, but we had

187
00:09:34,004 --> 00:09:36,644
Speaker 1: a very unexpected winner of the primary and zar on

188
00:09:36,684 --> 00:09:41,844
Speaker 1: mom Donnie showing a lot of shifts in the Democratic Party,

189
00:09:41,964 --> 00:09:45,804
Speaker 1: the Democratic Party base, and the potential the game theory

190
00:09:45,804 --> 00:09:49,324
Speaker 1: for the Democratic Party going forward. This is one kind

191
00:09:49,364 --> 00:09:52,964
Speaker 1: of potential blueprint should they choose to accept it.

192
00:09:53,364 --> 00:09:57,324
Speaker 3: So one amazing thing is that younger voters actually turned

193
00:09:57,324 --> 00:10:00,484
Speaker 3: out at a higher rate than older voters in a selection,

194
00:10:00,604 --> 00:10:06,444
Speaker 3: which basically never happens in elections anywhere. Right, So he

195
00:10:06,524 --> 00:10:09,884
Speaker 3: spoke very much the vernacular of vertical video and kind

196
00:10:09,884 --> 00:10:12,084
Speaker 3: of how young people think about in general. He's a

197
00:10:12,164 --> 00:10:14,604
Speaker 3: you know, charismatic guy that's kind of a New York

198
00:10:15,124 --> 00:10:18,284
Speaker 3: archetype of this kind of multi ethnic hustler type, but

199
00:10:18,364 --> 00:10:21,004
Speaker 3: friendly guy and obviously a smart ambitious guy. Right, It's

200
00:10:21,044 --> 00:10:23,724
Speaker 3: like a type we recognize, I think have some appreciation

201
00:10:23,844 --> 00:10:26,964
Speaker 3: for in New York. He's a problem member the Democratic

202
00:10:27,044 --> 00:10:32,444
Speaker 3: Socialist of America. During the campaign emphasized affordability, cost of living,

203
00:10:32,884 --> 00:10:37,764
Speaker 3: had tangible proposals on like free buses, rent freezes for

204
00:10:37,844 --> 00:10:42,844
Speaker 3: certain types of buildings, right, city owned grocery stores, thirty

205
00:10:42,844 --> 00:10:45,804
Speaker 3: dollars minimum wage. Right, So tangible focused on that, not

206
00:10:45,804 --> 00:10:48,604
Speaker 3: culture worse stuff. And he winds up beating former governor

207
00:10:48,644 --> 00:10:51,564
Speaker 3: and Dupomo, who in a terrible campaign but was very complacent.

208
00:10:51,604 --> 00:10:55,284
Speaker 3: And I think this is a kind of a generational moment.

209
00:10:55,804 --> 00:10:58,524
Speaker 1: I think it is, and I think it's very interesting

210
00:10:58,604 --> 00:11:03,204
Speaker 1: to see that Momdani was actually able to get the

211
00:11:03,284 --> 00:11:08,364
Speaker 1: voters who turned to Trump during the presidential election, that

212
00:11:08,524 --> 00:11:12,124
Speaker 1: demographic to actually come out and vote for the Democrats.

213
00:11:12,164 --> 00:11:15,724
Speaker 1: And there are you know, videos from him campaigning where

214
00:11:15,764 --> 00:11:19,404
Speaker 1: he actually manages to talk to kind of that exact

215
00:11:19,564 --> 00:11:23,884
Speaker 1: demographic that you know, voted for not just a different

216
00:11:23,924 --> 00:11:27,364
Speaker 1: type of Democrat, but for Republicans in the presidential election.

217
00:11:27,484 --> 00:11:29,004
Speaker 3: Yeah, I mean it's a little bit because you know,

218
00:11:29,364 --> 00:11:32,244
Speaker 3: so we had comparatively high turnout about a million, probably

219
00:11:32,284 --> 00:11:33,804
Speaker 3: one point oh five million, right.

220
00:11:33,724 --> 00:11:35,244
Speaker 1: Yeah, this was our high start.

221
00:11:35,924 --> 00:11:36,484
Speaker 2: But there are eight.

222
00:11:36,444 --> 00:11:39,004
Speaker 3: Million people in New York City of whom three point

223
00:11:39,044 --> 00:11:41,284
Speaker 3: three to three point four million are registered Democrats, right,

224
00:11:41,324 --> 00:11:44,204
Speaker 3: so you're still only getting twenty five or thirty percent

225
00:11:44,684 --> 00:11:45,444
Speaker 3: of the electorate.

226
00:11:46,164 --> 00:11:48,284
Speaker 2: With that said, very broad based.

227
00:11:48,084 --> 00:11:51,684
Speaker 3: Right, He won precincts even in Staten Island, which is

228
00:11:51,724 --> 00:11:53,804
Speaker 3: kind of cuomo home turf. Not all of them, but

229
00:11:53,844 --> 00:11:54,244
Speaker 3: some of them.

230
00:11:54,284 --> 00:11:54,484
Speaker 2: Right.

231
00:11:54,844 --> 00:11:57,404
Speaker 3: You know, Cuomo wins the Central Parkies, but you go

232
00:11:57,444 --> 00:11:59,084
Speaker 3: even a couple of blocks into the Upper east Side,

233
00:11:59,084 --> 00:12:01,244
Speaker 3: one of the more conserve neighborhoods, he started some mom

234
00:12:01,284 --> 00:12:04,764
Speaker 3: don Aid precincts right there. So, you know, a very

235
00:12:04,764 --> 00:12:07,404
Speaker 3: impressive performance. And of course we will be accused as

236
00:12:07,444 --> 00:12:09,924
Speaker 3: the New Yorkers are being provincial. But New York is

237
00:12:10,004 --> 00:12:13,364
Speaker 3: so big and so diverse, right that not in the

238
00:12:13,364 --> 00:12:16,204
Speaker 3: same proportions, But we have like lots of Conservatives in

239
00:12:16,204 --> 00:12:17,804
Speaker 3: New York are out number by liberals. We have lots

240
00:12:17,844 --> 00:12:21,564
Speaker 3: of conservatives, right, We have every imaginable ethnic group and

241
00:12:21,844 --> 00:12:24,164
Speaker 3: slice of racial demographic right. There are lots of working

242
00:12:24,164 --> 00:12:27,684
Speaker 3: class people in New York. He mostly did well among

243
00:12:27,724 --> 00:12:30,924
Speaker 3: the kind of upper middle class, you know, kind of

244
00:12:31,004 --> 00:12:33,804
Speaker 3: white people. Basically, but there are those two, right, and

245
00:12:33,844 --> 00:12:36,684
Speaker 3: did well enough? This is important, did well enough among

246
00:12:36,684 --> 00:12:39,124
Speaker 3: the other groups, right, because sometimes can they say, Okay, well,

247
00:12:39,324 --> 00:12:41,924
Speaker 3: we're not going to win any you know Democrats, Right,

248
00:12:41,964 --> 00:12:44,084
Speaker 3: We're not going to win any working class white men,

249
00:12:44,164 --> 00:12:46,204
Speaker 3: so just write them off, treat them as a zero,

250
00:12:46,364 --> 00:12:49,884
Speaker 3: when actually, like getting thirty percent of working class non

251
00:12:49,964 --> 00:12:54,324
Speaker 3: college men as opposed to twenty percent makes a big deal. Right,

252
00:12:54,444 --> 00:12:57,644
Speaker 3: Trump in this past election got something like eighteen to

253
00:12:57,644 --> 00:13:01,164
Speaker 3: twenty percent of the black vote, which is a significant minority.

254
00:13:01,284 --> 00:13:01,484
Speaker 2: Right.

255
00:13:01,684 --> 00:13:06,484
Speaker 3: Mitt Romney got four percent against Barack Obama in twenty twelve. Right,

256
00:13:06,564 --> 00:13:09,964
Speaker 3: So going from four percent to twenty percent the population,

257
00:13:10,004 --> 00:13:12,124
Speaker 3: you can do that math, right, that's quite a big swing.

258
00:13:12,244 --> 00:13:15,084
Speaker 1: Actually, yeah it is, mate. Do you actually think that

259
00:13:15,484 --> 00:13:18,324
Speaker 1: the election was at all affected by the fact that

260
00:13:18,364 --> 00:13:21,924
Speaker 1: this was the second primary where ranked choice voting was

261
00:13:21,964 --> 00:13:26,124
Speaker 1: actually in use, because that was something that people really were,

262
00:13:26,484 --> 00:13:27,964
Speaker 1: you know, emphasizing during the.

263
00:13:27,884 --> 00:13:30,884
Speaker 3: Candidate You guys know what rank choice voting or run off?

264
00:13:30,964 --> 00:13:32,524
Speaker 3: Okay everyone.

265
00:13:33,964 --> 00:13:37,924
Speaker 1: Festival, and we covered it for our listeners on the

266
00:13:37,924 --> 00:13:43,964
Speaker 1: pod last week. So I mean, okay, so ranked choice

267
00:13:44,004 --> 00:13:48,364
Speaker 1: voting means you have five choices, you rank your choices.

268
00:13:48,764 --> 00:13:53,004
Speaker 1: If your first choice candidate is not one of the

269
00:13:53,044 --> 00:13:55,884
Speaker 1: top two candidates, then your choice gets moved to your

270
00:13:55,924 --> 00:13:59,164
Speaker 1: next ranked candidate, and so on down the line.

271
00:13:59,684 --> 00:14:02,764
Speaker 3: Yeah, so Zoran seemed to understand this and Cuomo did not,

272
00:14:03,404 --> 00:14:07,804
Speaker 3: yes one thing. He formed alliances with other candidates, right,

273
00:14:08,004 --> 00:14:11,644
Speaker 3: especially Brad Lander, the third place candidate. Now, from a

274
00:14:11,644 --> 00:14:15,084
Speaker 3: game theory standpoint, I don't think this is necessarily rational

275
00:14:15,124 --> 00:14:18,084
Speaker 3: for Brad Lander, because like, if you're in third place

276
00:14:18,124 --> 00:14:19,684
Speaker 3: and the other guy's in second place or maybe a

277
00:14:19,684 --> 00:14:23,124
Speaker 3: first place, right, you don't necessarily want to help him out, right,

278
00:14:23,364 --> 00:14:25,764
Speaker 3: But I think Brad Lander hates Andrew Cuomo's guts, has

279
00:14:25,764 --> 00:14:27,244
Speaker 3: a lot of people do in New York and so

280
00:14:27,724 --> 00:14:32,844
Speaker 3: and so there was that surround a very positive campaign

281
00:14:32,884 --> 00:14:37,284
Speaker 3: and a substantive campaign, which is a change from how

282
00:14:37,324 --> 00:14:38,804
Speaker 3: campaigns are often run.

283
00:14:38,844 --> 00:14:41,684
Speaker 2: And I do think, like not uniquely the left in

284
00:14:41,724 --> 00:14:44,244
Speaker 2: the United States. I mean, look at Trump also.

285
00:14:44,044 --> 00:14:46,084
Speaker 3: In NAGA, right, but like there often is a lot

286
00:14:46,084 --> 00:14:49,804
Speaker 3: of negativity, a lot of anxiety, right, and that wasn't

287
00:14:49,804 --> 00:14:52,804
Speaker 3: what he was doing, right. He was a smart, substantive guy,

288
00:14:53,324 --> 00:14:57,284
Speaker 3: you know, who literally walked the entire length of Manhattan,

289
00:14:57,364 --> 00:15:00,004
Speaker 3: like the last day before the campaign wearing a suit,

290
00:15:00,044 --> 00:15:02,764
Speaker 3: and so like did every podcast in the world.

291
00:15:02,804 --> 00:15:04,484
Speaker 2: I think I've done. I've done like six podcasts in

292
00:15:04,484 --> 00:15:04,964
Speaker 2: the day before.

293
00:15:05,004 --> 00:15:08,324
Speaker 3: I think Zorn probably beat that record, but he very

294
00:15:08,404 --> 00:15:12,444
Speaker 3: much earned it, and Cuomo was pure negative. We do

295
00:15:12,444 --> 00:15:16,164
Speaker 3: have a general election still where Cuomo is running again, right,

296
00:15:16,524 --> 00:15:17,164
Speaker 3: I don't know if that.

297
00:15:17,284 --> 00:15:19,444
Speaker 1: And so is Sarah Adams maybe and Eric.

298
00:15:19,284 --> 00:15:22,404
Speaker 3: Adams and come a mirror defective from your practic party

299
00:15:23,164 --> 00:15:26,204
Speaker 3: friendly with Trump. Right, you also have the proper Republican nominee,

300
00:15:26,244 --> 00:15:29,164
Speaker 3: Curtis Sliwa, who is a guy who founded The Guardian

301
00:15:29,204 --> 00:15:31,844
Speaker 3: Angels and owns like fifty six cats or something like that.

302
00:15:32,244 --> 00:15:36,204
Speaker 1: So yeah, yeah, So I'm also interested, you know, from

303
00:15:36,444 --> 00:15:38,724
Speaker 1: from the point of view of like the game theory

304
00:15:38,764 --> 00:15:43,524
Speaker 1: of the Democratic Party. Right, we have this election which

305
00:15:44,004 --> 00:15:47,204
Speaker 1: seems like an anomaly but might not be, and a

306
00:15:47,204 --> 00:15:50,684
Speaker 1: lot of the Democratic establishment don't want to embrace Zora

307
00:15:50,804 --> 00:15:53,564
Speaker 1: Mom Donnie right there. They think that he is, you know,

308
00:15:53,644 --> 00:15:57,604
Speaker 1: too fringe, right, that he is too radical, that some

309
00:15:57,644 --> 00:16:00,844
Speaker 1: of his ideas are are too kind of too out there,

310
00:16:00,964 --> 00:16:03,964
Speaker 1: and that they want to go safer, They want to

311
00:16:03,964 --> 00:16:06,044
Speaker 1: go more middle of the road, which is what they

312
00:16:06,564 --> 00:16:09,644
Speaker 1: were saying during the presidential election that they lost.

313
00:16:09,724 --> 00:16:11,364
Speaker 3: Yeah, it's kind of it's kind of hard to be

314
00:16:11,444 --> 00:16:14,284
Speaker 3: like an exciting centrist is part of the problem.

315
00:16:14,324 --> 00:16:16,844
Speaker 2: You know, I don't know if Mayor Pete is exciting.

316
00:16:16,884 --> 00:16:19,964
Speaker 3: I guess he's a well spoken person, for example. But like,

317
00:16:20,044 --> 00:16:22,844
Speaker 3: sometimes more the energy comes from the left. Again, like

318
00:16:23,084 --> 00:16:27,364
Speaker 3: to me, and look, I'm a University of Chicago economics major.

319
00:16:27,404 --> 00:16:30,084
Speaker 2: I'm unapologetically kind of a neoliberal.

320
00:16:30,164 --> 00:16:33,124
Speaker 3: Right, it does seem to me like, look, the left

321
00:16:33,124 --> 00:16:35,244
Speaker 3: has not had the economic left has not had a

322
00:16:35,284 --> 00:16:38,924
Speaker 3: lot of power in the United States recently, right, And

323
00:16:38,964 --> 00:16:40,884
Speaker 3: so I've become more sympathetics because I'm like, well, we

324
00:16:40,884 --> 00:16:42,964
Speaker 3: haven't made those mistakes. They will make mistakes, and it's

325
00:16:43,004 --> 00:16:45,964
Speaker 3: very hard to govern a state like New York. It's

326
00:16:46,004 --> 00:16:48,724
Speaker 3: particularly hard to govern New York City because New York

327
00:16:48,764 --> 00:16:52,124
Speaker 3: State controls the taxation policy, a lot of the budget

328
00:16:52,364 --> 00:16:56,444
Speaker 3: and things like that. They're always rivalries between Albany and

329
00:16:56,444 --> 00:16:59,564
Speaker 3: and city Hall, right that without being different.

330
00:17:00,124 --> 00:17:02,884
Speaker 1: Yeah, absolutely, And I also wonder, you know, if mom

331
00:17:02,924 --> 00:17:05,524
Speaker 1: Donnie does get elected. Right, this is a big if.

332
00:17:05,604 --> 00:17:10,004
Speaker 1: Still right, we're we're i mean twenty five percent, but

333
00:17:10,044 --> 00:17:13,844
Speaker 1: seventy five percent, as we know, is not one hundred percent,

334
00:17:14,564 --> 00:17:17,764
Speaker 1: as we very well know. So he but let's assume

335
00:17:17,804 --> 00:17:21,764
Speaker 1: he gets elected. It's going to also be a very

336
00:17:21,764 --> 00:17:25,684
Speaker 1: interesting shift where kind of candidates like Mom Dannie have been,

337
00:17:26,004 --> 00:17:28,044
Speaker 1: you know, the underdog right, and it's been kind of

338
00:17:28,084 --> 00:17:31,204
Speaker 1: the the underdog story of someone who is kind of

339
00:17:31,724 --> 00:17:35,164
Speaker 1: young and kind of more radical and has those ideas

340
00:17:35,484 --> 00:17:38,524
Speaker 1: and wins despite the odds. Now, what happens when you

341
00:17:38,604 --> 00:17:43,244
Speaker 1: become the establishment right like that that underdog story shifts

342
00:17:43,444 --> 00:17:47,164
Speaker 1: your incentives. We were talking just now in poker about incentives.

343
00:17:47,204 --> 00:17:51,684
Speaker 1: Incentives matter in everything. Your incentives shift, right, the things

344
00:17:51,724 --> 00:17:55,124
Speaker 1: that you were able to promise suddenly you have to

345
00:17:55,164 --> 00:17:58,404
Speaker 1: make coalitions with other you know, with lobbyists, with other

346
00:17:58,484 --> 00:18:01,644
Speaker 1: ruling factions, with you know, you need to face the

347
00:18:01,644 --> 00:18:04,764
Speaker 1: realities of power. And so it's much easier to kind

348
00:18:04,804 --> 00:18:08,564
Speaker 1: of be the idealist before you get elected. And once

349
00:18:08,644 --> 00:18:13,484
Speaker 1: you're once you the establishment, that changes and you change.

350
00:18:13,604 --> 00:18:16,604
Speaker 1: And so I'm going to be very very curious to

351
00:18:16,644 --> 00:18:20,164
Speaker 1: see what happens and how that story kind of ends

352
00:18:20,244 --> 00:18:22,964
Speaker 1: up shifting, and then what happens to the supporters kind

353
00:18:23,004 --> 00:18:25,044
Speaker 1: of what all the downstream effects are going.

354
00:18:24,844 --> 00:18:27,164
Speaker 2: To be Yeah, you're registered in Nevada. Now I am, Yeah,

355
00:18:27,164 --> 00:18:27,644
Speaker 2: I'm in New York.

356
00:18:27,724 --> 00:18:30,484
Speaker 3: This is the rarer time when I have a general

357
00:18:30,524 --> 00:18:34,444
Speaker 3: election vote in New York that could plausibly matter. And

358
00:18:34,884 --> 00:18:37,324
Speaker 3: you know, people like me who might be kind of

359
00:18:37,364 --> 00:18:40,204
Speaker 3: on vaguely the center of the culturally center left and

360
00:18:40,284 --> 00:18:44,644
Speaker 3: economically centered something right, A lot of people are are

361
00:18:45,644 --> 00:18:48,364
Speaker 3: concerned about him, but like, to me, it's a bit

362
00:18:48,444 --> 00:18:52,124
Speaker 3: like if you're picking a founder for a startup, right,

363
00:18:52,124 --> 00:18:57,444
Speaker 3: you're kind of going more off like the rod intelligence

364
00:18:57,484 --> 00:19:00,804
Speaker 3: and talent and work ethic, maybe more than like the

365
00:19:00,804 --> 00:19:04,204
Speaker 3: particular program or platform, right, or at least it's kind

366
00:19:04,204 --> 00:19:06,924
Speaker 3: of like what I'm telling myself potentially, And the fact

367
00:19:06,924 --> 00:19:10,364
Speaker 3: that he's a lot of dexterity in talking about policy, right,

368
00:19:10,404 --> 00:19:12,484
Speaker 3: He went on, like the Odds odd Lots podcast, which

369
00:19:12,484 --> 00:19:15,404
Speaker 3: is Joe Wisenthal and Tracy Alloway, which is kind of

370
00:19:15,404 --> 00:19:17,724
Speaker 3: in the same family as Risky Business, right, and like

371
00:19:18,244 --> 00:19:22,404
Speaker 3: talking a lot of wankery about policy and things like that, Right,

372
00:19:22,444 --> 00:19:26,804
Speaker 3: And like I like politicians who who are elected officials

373
00:19:27,124 --> 00:19:28,644
Speaker 3: and are responsive to.

374
00:19:28,644 --> 00:19:30,244
Speaker 2: Some degree to fulblic opinion.

375
00:19:30,244 --> 00:19:33,204
Speaker 3: I think it's how democracy should should function, right, and

376
00:19:33,244 --> 00:19:35,204
Speaker 3: he can say here are my priors. I'll stay for

377
00:19:35,244 --> 00:19:37,924
Speaker 3: the working class. I don't like capitalism all that much. Right,

378
00:19:37,964 --> 00:19:40,324
Speaker 3: but he's not proposing anything too radical and like and

379
00:19:40,364 --> 00:19:43,604
Speaker 3: it's not angry. You know, Bernie Sanders understood that.

380
00:19:43,844 --> 00:19:44,044
Speaker 2: Right.

381
00:19:45,084 --> 00:19:47,604
Speaker 3: The one moment when the Sanders campaign got a little

382
00:19:47,604 --> 00:19:50,764
Speaker 3: bit angry was toward toward twenty twenty when they won

383
00:19:50,804 --> 00:19:53,164
Speaker 3: the first couple of primaries and they were instead of

384
00:19:53,644 --> 00:19:55,604
Speaker 3: bending the knee to the Timparty Party. Remember going to

385
00:19:55,604 --> 00:19:58,964
Speaker 3: a rally in Nevada, Bernie wound up winning basically three

386
00:19:58,964 --> 00:20:01,444
Speaker 3: states in a row. Iowa was disputed between him and

387
00:20:01,524 --> 00:20:03,644
Speaker 3: their pete, So we won't get into that, right, but

388
00:20:03,684 --> 00:20:06,524
Speaker 3: two and a half out of three, right, and he

389
00:20:06,564 --> 00:20:10,044
Speaker 3: gave species that were like, yeah, well screwed you Democrats establishment,

390
00:20:10,124 --> 00:20:12,684
Speaker 3: right now, you have to kiss my ring. And there

391
00:20:12,724 --> 00:20:14,444
Speaker 3: they still had leverage, right, they still had leverage. They

392
00:20:14,484 --> 00:20:16,804
Speaker 3: had the leverage to have Jim Clyburn and Amy club

393
00:20:16,884 --> 00:20:19,884
Speaker 3: Ashar Mayor Repete everybody else rally behind.

394
00:20:19,724 --> 00:20:22,284
Speaker 2: Joe Biden successfully for one term.

395
00:20:22,364 --> 00:20:23,644
Speaker 3: You know, whether that was a good decision of a

396
00:20:23,644 --> 00:20:25,884
Speaker 3: long run or not, we'll be I think debated, but like,

397
00:20:26,124 --> 00:20:27,564
Speaker 3: but yeah, you don't want to like rub it in

398
00:20:27,604 --> 00:20:30,764
Speaker 3: someone's face when they still have chips on the table,

399
00:20:30,804 --> 00:20:32,924
Speaker 3: so to speak, and so and so, you know, it

400
00:20:32,924 --> 00:20:36,724
Speaker 3: would behooves around to understand there's still a losible. We're

401
00:20:36,724 --> 00:20:39,164
Speaker 3: gona talk about what these probabilities mean. Twenty five percent

402
00:20:39,324 --> 00:20:42,564
Speaker 3: is a real possibility of losing, right, and so he

403
00:20:42,604 --> 00:20:45,964
Speaker 3: would be mindful to to keep up the strategy that

404
00:20:46,004 --> 00:20:47,524
Speaker 3: he had in the in the in the.

405
00:20:47,444 --> 00:20:52,044
Speaker 1: Primary, and uh mindful to h if he gets selected

406
00:20:52,604 --> 00:20:57,044
Speaker 1: to try to uh keep up the same strategy if

407
00:20:57,044 --> 00:20:57,284
Speaker 1: you want.

408
00:20:57,324 --> 00:20:59,724
Speaker 3: It's a really it's a really hard it's hard. It's

409
00:20:59,764 --> 00:21:00,564
Speaker 3: a really hard job.

410
00:21:00,684 --> 00:21:01,964
Speaker 1: It is it's an incredibly hard job.

411
00:21:02,004 --> 00:21:03,724
Speaker 3: You can probably do better than narrow dams, right, But

412
00:21:03,764 --> 00:21:05,004
Speaker 3: it's a it's a that's.

413
00:21:04,804 --> 00:21:08,204
Speaker 1: A it's it is. It's it is an incredibly hard job.

414
00:21:08,204 --> 00:21:11,484
Speaker 1: And I think we do need to remember that. Nate,

415
00:21:11,484 --> 00:21:13,644
Speaker 1: Do you have any other kind of final thoughts on

416
00:21:13,644 --> 00:21:16,324
Speaker 1: the election or should we talk probabilities more generally?

417
00:21:16,484 --> 00:21:18,124
Speaker 3: No, again, I kind of said at the top, I

418
00:21:18,204 --> 00:21:20,764
Speaker 3: do think that like the fact that Cuomo called in

419
00:21:20,924 --> 00:21:23,644
Speaker 3: all the cavalry right, he called him to Clinton to

420
00:21:23,724 --> 00:21:25,484
Speaker 3: endorse him. He called him like a Bloomberg called him

421
00:21:25,524 --> 00:21:29,804
Speaker 3: Jim Clyburn. Every black group, Jewish group, Italian group, got

422
00:21:29,844 --> 00:21:33,524
Speaker 3: all the ethnic groups in New York, right, lots and

423
00:21:33,564 --> 00:21:35,444
Speaker 3: lots and lots of unions, right, And that's how you

424
00:21:35,524 --> 00:21:38,084
Speaker 3: used to win in machine cities, machine states, that's how

425
00:21:38,084 --> 00:21:39,004
Speaker 3: you win elections.

426
00:21:39,044 --> 00:21:41,324
Speaker 2: And like and like Cuomo, Cuomo.

427
00:21:41,084 --> 00:21:44,364
Speaker 3: Kind of actually got the numbers that ordinarily would win

428
00:21:44,404 --> 00:21:47,684
Speaker 3: a New York mayoral race, right since two thousand and one,

429
00:21:48,044 --> 00:21:51,724
Speaker 3: he's the second highest total of votes. But like Mom, Donnie,

430
00:21:51,924 --> 00:21:56,164
Speaker 3: reached into new parts of the electorate, not totally new.

431
00:21:56,204 --> 00:21:59,484
Speaker 3: These are people who vote in presidential primaries and things

432
00:21:59,524 --> 00:22:02,044
Speaker 3: like that. But this is the case where it turnout

433
00:22:02,044 --> 00:22:05,844
Speaker 3: did matter quite a bit in a race where maybe

434
00:22:05,924 --> 00:22:07,684
Speaker 3: a third of Democrats turn out if you're lucky, maybe

435
00:22:07,684 --> 00:22:11,804
Speaker 3: twenty five percent. Then and getting people excited, being I mean,

436
00:22:11,884 --> 00:22:16,364
Speaker 3: being interesting. So many politicians are either psychopaths or boring, right,

437
00:22:16,764 --> 00:22:19,524
Speaker 3: like ninety four of one hundred US Saturday either psychopaths,

438
00:22:19,764 --> 00:22:20,804
Speaker 3: boring or both.

439
00:22:21,124 --> 00:22:23,924
Speaker 1: Yeah, yeah, no, And a lot a lot can be

440
00:22:23,924 --> 00:22:29,084
Speaker 1: said for being nice and having energy and actually being

441
00:22:29,124 --> 00:22:31,244
Speaker 1: excited about the job you're going to do, even though

442
00:22:31,244 --> 00:22:33,804
Speaker 1: it's going to be a really really hard job, and

443
00:22:33,884 --> 00:22:35,924
Speaker 1: I think that's tough, right to show up every day

444
00:22:35,964 --> 00:22:38,724
Speaker 1: with that kind of energy. I mean, how many of

445
00:22:38,764 --> 00:22:42,844
Speaker 1: you can walk the entire length of Manhattan and tape

446
00:22:42,844 --> 00:22:45,364
Speaker 1: however many podcasts and I get.

447
00:22:45,924 --> 00:22:48,364
Speaker 2: Not in a suit though I'm a sweater, not in

448
00:22:48,404 --> 00:22:49,124
Speaker 2: a suit.

449
00:22:50,604 --> 00:22:51,684
Speaker 1: I can do it in high heels.

450
00:22:51,684 --> 00:22:56,644
Speaker 4: Now, I kid, you're.

451
00:22:56,524 --> 00:22:58,444
Speaker 2: Gonna hear a quick break and then we'll be back.

452
00:23:07,244 --> 00:23:10,924
Speaker 1: We want to play a little game with you about probabilities.

453
00:23:10,924 --> 00:23:13,804
Speaker 1: We'll play it with each other first, but then we're

454
00:23:13,844 --> 00:23:17,084
Speaker 1: going to involve you. It's a game called how likely

455
00:23:17,164 --> 00:23:21,924
Speaker 1: is it? So how likely are certain probabilities? So let's

456
00:23:21,924 --> 00:23:24,364
Speaker 1: give you just a little bit of context behind this.

457
00:23:25,564 --> 00:23:29,164
Speaker 1: So back in nineteen fifty one March of nineteen fifty one,

458
00:23:29,844 --> 00:23:32,444
Speaker 1: there was a CIA analyst whose name was Sherman Kent,

459
00:23:33,124 --> 00:23:36,244
Speaker 1: and he filed a report on the probability of an

460
00:23:36,284 --> 00:23:40,444
Speaker 1: invasion by of Yugoslavia in the year nineteen fifty one.

461
00:23:40,564 --> 00:23:44,364
Speaker 1: We all know how that turned out. So how probable

462
00:23:44,444 --> 00:23:47,724
Speaker 1: is it that the USSR is going to invade? And

463
00:23:48,084 --> 00:23:51,044
Speaker 1: he concluded in his report that it was a quote

464
00:23:51,564 --> 00:23:57,964
Speaker 1: serious possibility. So what did he mean by serious possibility?

465
00:23:58,164 --> 00:24:01,684
Speaker 1: In retrospect. When he explained this, he thought it meant well,

466
00:24:01,724 --> 00:24:03,404
Speaker 1: first of all, just think in your heads what you

467
00:24:03,444 --> 00:24:05,724
Speaker 1: think it means, Nate, what do you think it mean?

468
00:24:05,924 --> 00:24:08,924
Speaker 1: Just you don't have to answer, Okay, So he thought

469
00:24:08,964 --> 00:24:13,924
Speaker 1: it meant sixty five percent or higher. So, right, more

470
00:24:13,964 --> 00:24:18,164
Speaker 1: than sixty five percent. Unfortunately, the person to whom he

471
00:24:18,244 --> 00:24:21,204
Speaker 1: conveyed his report and his findings, who was a chairman

472
00:24:21,244 --> 00:24:26,324
Speaker 1: of the policy Planning initiative, they had understood him to

473
00:24:26,444 --> 00:24:29,724
Speaker 1: mean that it was a lot lower than that. So

474
00:24:29,844 --> 00:24:33,124
Speaker 1: in their minds, serious possibility was like, oh, twenty percent

475
00:24:33,484 --> 00:24:37,524
Speaker 1: or maybe like a range from twenty to seventy eighty percent,

476
00:24:37,604 --> 00:24:40,724
Speaker 1: certainly not sixty five percent or higher. So there was

477
00:24:40,804 --> 00:24:47,964
Speaker 1: a huge miscommunication which resulted in massive policy missteps. Right,

478
00:24:48,444 --> 00:24:53,324
Speaker 1: just because how serious a serious possibility was was not Well.

479
00:24:53,244 --> 00:24:56,044
Speaker 3: People are there were number match totobic right, you know

480
00:24:56,204 --> 00:24:58,524
Speaker 3: at former thirty eight, no silver bulletin. Right, we have

481
00:24:58,524 --> 00:25:02,204
Speaker 3: an election model where we give you know, a probability

482
00:25:02,244 --> 00:25:06,204
Speaker 3: is fundamentally defined, is a number between zero percent and

483
00:25:06,244 --> 00:25:07,084
Speaker 3: one hundred percent.

484
00:25:07,204 --> 00:25:09,124
Speaker 2: Right, And a lot of times.

485
00:25:08,924 --> 00:25:12,444
Speaker 3: People use weaseled They're like, well, Nicklint, you had Hillary

486
00:25:12,484 --> 00:25:13,564
Speaker 3: Clinton with a seventy one.

487
00:25:13,404 --> 00:25:15,484
Speaker 2: Percent chance of winning the election. So you were wrong.

488
00:25:15,764 --> 00:25:18,204
Speaker 3: We have the semantics of that, right, But like, but

489
00:25:18,404 --> 00:25:19,964
Speaker 3: you know, but you put a number there and people

490
00:25:19,964 --> 00:25:22,804
Speaker 3: think it's like, you know, understand that that represents it

491
00:25:22,804 --> 00:25:26,964
Speaker 3: bakes in the uncertainty in the model, the uncertainty in

492
00:25:27,004 --> 00:25:27,604
Speaker 3: the real world.

493
00:25:27,684 --> 00:25:27,764
Speaker 1: Right.

494
00:25:27,844 --> 00:25:29,204
Speaker 3: If I were to say, I think, by the way,

495
00:25:29,484 --> 00:25:32,844
Speaker 3: serious possibility to me implies like twenty percent. Right, if

496
00:25:32,884 --> 00:25:35,324
Speaker 3: I said that there's still a serious possibility Zaron could

497
00:25:35,364 --> 00:25:38,924
Speaker 3: lose a general election, right, because you're not saying probability,

498
00:25:39,324 --> 00:25:41,524
Speaker 3: You're saying, like, take this seriously, twenty.

499
00:25:41,444 --> 00:25:44,164
Speaker 1: Twenty se Yeah, Well, when you put it in that context, right,

500
00:25:44,204 --> 00:25:48,684
Speaker 1: a serious possibility that Zar loses the election twenty five percent? Right, Now,

501
00:25:48,884 --> 00:25:53,044
Speaker 1: that sentence makes sense, which is why So when I

502
00:25:53,164 --> 00:25:57,044
Speaker 1: was a grad student and studying decision making, one of

503
00:25:57,044 --> 00:25:58,684
Speaker 1: the things that we talked about was how do you

504
00:25:58,724 --> 00:26:02,444
Speaker 1: communicate risk? Right? How do you communicate probabilities to people?

505
00:26:02,964 --> 00:26:07,004
Speaker 1: And it's really really hard, and it's hard in all

506
00:26:07,044 --> 00:26:10,324
Speaker 1: sorts of context. Right, how do you communicate probabilities when

507
00:26:10,324 --> 00:26:13,364
Speaker 1: it comes to things like global warming, right, or or

508
00:26:13,404 --> 00:26:16,924
Speaker 1: elections or something like that, And people just do not

509
00:26:17,284 --> 00:26:21,084
Speaker 1: understand probabilistic thinking. As we've talked about on the show

510
00:26:21,124 --> 00:26:25,284
Speaker 1: many many times, our brains just suck at probabilities and

511
00:26:25,284 --> 00:26:27,364
Speaker 1: at what they mean. Just by the way, why poker

512
00:26:27,924 --> 00:26:30,564
Speaker 1: is so good because it actually forces you to learn

513
00:26:30,604 --> 00:26:34,764
Speaker 1: what probability feels like viscerally, which is how the brain

514
00:26:34,964 --> 00:26:38,444
Speaker 1: learns the best. You know, I, for instance, you know

515
00:26:38,444 --> 00:26:41,084
Speaker 1: no bad beat stories on the podcast or in real life,

516
00:26:41,324 --> 00:26:44,564
Speaker 1: but I know how it feels to lose on day

517
00:26:44,604 --> 00:26:46,564
Speaker 1: four of the main event of the World Series as

518
00:26:46,564 --> 00:26:49,324
Speaker 1: a ninety eight point six percent favorite in a multi

519
00:26:49,364 --> 00:26:52,964
Speaker 1: millionship pot. It happens, right, It feels like it shouldn't

520
00:26:52,964 --> 00:26:54,964
Speaker 1: because ninety eight point six percent feels like it should

521
00:26:54,964 --> 00:26:59,204
Speaker 1: be one hundred percent. But it's not. Probabilities matter, and

522
00:26:59,284 --> 00:27:02,604
Speaker 1: we're so so bad at them. And yet something that

523
00:27:02,644 --> 00:27:06,164
Speaker 1: you just said, Nate, which is absolutely crucial, is that

524
00:27:06,204 --> 00:27:09,004
Speaker 1: we're number phobic. When you tell people, you know what,

525
00:27:09,044 --> 00:27:13,484
Speaker 1: the best way to communicate probability is, state the probability.

526
00:27:13,924 --> 00:27:16,804
Speaker 1: State the damn thing. Put a number on it. Actually

527
00:27:16,924 --> 00:27:20,204
Speaker 1: say you know it's I think the probability is between

528
00:27:20,684 --> 00:27:23,924
Speaker 1: ten percent and fifteen percent, and I am seventy five

529
00:27:23,964 --> 00:27:26,404
Speaker 1: percent sure In this estimate.

530
00:27:26,484 --> 00:27:30,244
Speaker 3: Rights, be explicit about the language that you're using it.

531
00:27:30,364 --> 00:27:33,644
Speaker 3: I believe the IPCC the Global Climate reports. Right, they

532
00:27:33,684 --> 00:27:36,604
Speaker 3: will use language like very likely a lot. But in

533
00:27:36,644 --> 00:27:38,764
Speaker 3: the appendix you look it up and they say very

534
00:27:38,844 --> 00:27:41,244
Speaker 3: likely means whatever it is ninety five percent or higher?

535
00:27:41,324 --> 00:27:41,884
Speaker 2: Right, nay?

536
00:27:42,004 --> 00:27:45,164
Speaker 1: How many people reading the report then go to the appendix.

537
00:27:44,684 --> 00:27:49,124
Speaker 3: To see see s report. My whole family once gave

538
00:27:49,164 --> 00:27:51,364
Speaker 3: each other the Iraq Study Group report for like Christmas

539
00:27:51,484 --> 00:27:53,524
Speaker 3: or something. It's that kind of that kind of family.

540
00:27:54,884 --> 00:27:58,444
Speaker 3: But no, but and then you know, look house this year,

541
00:28:00,244 --> 00:28:03,164
Speaker 3: but no, look uh, because the apsode is people use

542
00:28:03,164 --> 00:28:07,044
Speaker 3: this as weasel words. Right, They're intentionally ambiguous to say

543
00:28:07,124 --> 00:28:09,324
Speaker 3: later on, no, I was right, I was wrong, right,

544
00:28:09,764 --> 00:28:10,404
Speaker 3: which is lame.

545
00:28:10,484 --> 00:28:10,604
Speaker 2: Right.

546
00:28:10,604 --> 00:28:13,324
Speaker 3: People don't get any better unless they feel the pain of,

547
00:28:13,404 --> 00:28:16,724
Speaker 3: like of putting something which is in the public record

548
00:28:16,764 --> 00:28:18,284
Speaker 3: and is accountable to some degree.

549
00:28:18,324 --> 00:28:19,084
Speaker 2: Obviously, you need like.

550
00:28:19,124 --> 00:28:21,324
Speaker 3: A large sample of predictions to be able to evaluate,

551
00:28:21,564 --> 00:28:24,764
Speaker 3: you know, do do of your seventy percent probabilities? Do

552
00:28:24,804 --> 00:28:27,284
Speaker 3: seven out of ten come true in the long run? Right,

553
00:28:28,124 --> 00:28:29,724
Speaker 3: But you want to play a little bit of the

554
00:28:29,764 --> 00:28:31,084
Speaker 3: game here, how likely is it?

555
00:28:31,324 --> 00:28:34,764
Speaker 1: Yeah, let's absolutely do it? So the way that this

556
00:28:34,844 --> 00:28:37,364
Speaker 1: game is going to work at first is I am

557
00:28:37,444 --> 00:28:41,044
Speaker 1: going to tell you a phrase, Nate, and then you

558
00:28:41,084 --> 00:28:44,964
Speaker 1: will tell me what percent probability you think that that

559
00:28:45,004 --> 00:28:48,124
Speaker 1: phrase represents, and then I'll think of my answer as well,

560
00:28:48,364 --> 00:28:51,164
Speaker 1: and if you guys want to play along, feel free

561
00:28:51,164 --> 00:28:54,884
Speaker 1: to think of yours. All right, So if I tell

562
00:28:54,924 --> 00:28:58,684
Speaker 1: you almost certainly, what are you thinking?

563
00:28:59,684 --> 00:29:01,564
Speaker 2: Ninety five percent plus?

564
00:29:01,884 --> 00:29:04,764
Speaker 1: Okay, so almost certainly ninety five percent plus. I was

565
00:29:04,804 --> 00:29:07,284
Speaker 1: actually going to go a little bit lower and say

566
00:29:07,404 --> 00:29:11,284
Speaker 1: ninety percent plus, just knowing that in this world basically

567
00:29:11,324 --> 00:29:14,964
Speaker 1: nothing is certain. And if we're at above ninety percent probability,

568
00:29:15,084 --> 00:29:17,804
Speaker 1: like holy shit. You know, as a gambler or as

569
00:29:17,804 --> 00:29:19,524
Speaker 1: an investor, if I told you that you had an

570
00:29:19,564 --> 00:29:23,444
Speaker 1: investment that had a ninety percent probability of succeeding, how

571
00:29:23,444 --> 00:29:25,964
Speaker 1: many of you would take that investment? And I hope,

572
00:29:26,244 --> 00:29:29,284
Speaker 1: I hope most of you. But and if I told

573
00:29:29,364 --> 00:29:31,124
Speaker 1: you that you could take a gamble with a ninety

574
00:29:31,124 --> 00:29:33,724
Speaker 1: percent probability of success.

575
00:29:33,644 --> 00:29:35,364
Speaker 2: Yeah, people are there gambling, right.

576
00:29:35,564 --> 00:29:36,924
Speaker 3: I mean, you'll learn in poke if you can get

577
00:29:36,964 --> 00:29:41,204
Speaker 3: like a fifty four percent edge, yeah, it's pretty good.

578
00:29:41,044 --> 00:29:44,564
Speaker 1: It's amazing. But I'm not saying that that means almost certain,

579
00:29:44,804 --> 00:29:48,564
Speaker 1: but to me, like above ninety percent, given how much

580
00:29:48,644 --> 00:29:51,924
Speaker 1: uncertainty and ambiguity there are in the world, so those

581
00:29:51,924 --> 00:29:54,924
Speaker 1: are two different things, right. Uncertainty is we're not quite

582
00:29:54,924 --> 00:29:57,684
Speaker 1: sure what the probabilities are. Ambiguity is we're not even

583
00:29:57,724 --> 00:29:59,764
Speaker 1: quite sure kind of what the factors are. We're not

584
00:29:59,804 --> 00:30:02,524
Speaker 1: sure if our model is one hundred percent correct and

585
00:30:02,644 --> 00:30:05,204
Speaker 1: is accounting for everything. So given all of that, I

586
00:30:05,204 --> 00:30:09,404
Speaker 1: would actually say, like above ninety percent would be almost certainly.

587
00:30:09,524 --> 00:30:11,924
Speaker 1: Do you I don't know if that makes you rethink

588
00:30:11,964 --> 00:30:12,684
Speaker 1: your answer or not.

589
00:30:12,804 --> 00:30:15,164
Speaker 3: You know, I watched en f NBA playoff games where

590
00:30:15,204 --> 00:30:17,844
Speaker 3: teams blue seventeen point leads and things like that in

591
00:30:17,884 --> 00:30:20,084
Speaker 3: the fourth quarter, So like, I'm feeling I want the

592
00:30:20,084 --> 00:30:21,324
Speaker 3: security of ninety five percent.

593
00:30:21,404 --> 00:30:23,044
Speaker 1: All right, you want the security of.

594
00:30:23,044 --> 00:30:25,044
Speaker 3: After playing poker for a few weeks. Yeah, We're nothing

595
00:30:25,044 --> 00:30:26,844
Speaker 3: is certain that I'm like, I want my almost certainly

596
00:30:26,884 --> 00:30:28,124
Speaker 3: s at ninety five Right.

597
00:30:28,124 --> 00:30:30,524
Speaker 1: That makes that makes sense? So what would you would

598
00:30:30,564 --> 00:30:33,404
Speaker 1: you actually like what would you say for like a

599
00:30:33,524 --> 00:30:36,044
Speaker 1: ninety plus or an eight? Is there something that you

600
00:30:36,564 --> 00:30:40,444
Speaker 1: is there a phrase that you would think more accurately.

601
00:30:39,884 --> 00:30:42,124
Speaker 2: Represents that very likely highly likely.

602
00:30:42,764 --> 00:30:45,124
Speaker 1: Huh interesting because I would think that very likely would

603
00:30:45,124 --> 00:30:48,204
Speaker 1: be below ninety percent. See, this is this is how,

604
00:30:48,324 --> 00:30:50,164
Speaker 1: this is why this is ambiguous.

605
00:30:50,404 --> 00:30:50,764
Speaker 2: All right?

606
00:30:51,204 --> 00:30:54,004
Speaker 1: So I am going to give you another phrase. If

607
00:30:54,044 --> 00:30:58,284
Speaker 1: I said that something was unlikely to happen.

608
00:30:58,204 --> 00:31:01,524
Speaker 3: Yeah, I'd say unlikely or for that matter of the counterpart.

609
00:31:02,284 --> 00:31:05,204
Speaker 3: Likely is one of the worst and most ambiguous terms

610
00:31:05,204 --> 00:31:07,844
Speaker 3: to use in that context, right, because literally it can

611
00:31:07,924 --> 00:31:10,124
Speaker 3: mean depending on the context. Anythink from like zero point

612
00:31:10,204 --> 00:31:13,684
Speaker 3: zero zero zero percent one percent zero zero zero one

613
00:31:13,724 --> 00:31:15,404
Speaker 3: to like forty nine percent.

614
00:31:15,524 --> 00:31:16,924
Speaker 2: Right, it's very ambiguous.

615
00:31:16,964 --> 00:31:19,644
Speaker 3: I would tend to think unlikely means twenty five or

616
00:31:19,644 --> 00:31:22,044
Speaker 3: thirty percent, somewhere in the middle of the below fifty

617
00:31:22,044 --> 00:31:22,604
Speaker 3: percent range.

618
00:31:22,604 --> 00:31:24,244
Speaker 2: What about you, Yeah, I was.

619
00:31:24,164 --> 00:31:27,604
Speaker 1: Going to be at around twenty five percent or below. Right,

620
00:31:27,684 --> 00:31:30,004
Speaker 1: Any of that is unlikely, and you know, we can

621
00:31:30,404 --> 00:31:33,484
Speaker 1: start we can start kind of playing around with it

622
00:31:33,524 --> 00:31:36,124
Speaker 1: a little bit with adjectives. But I totally agree with

623
00:31:36,164 --> 00:31:39,044
Speaker 1: you that likely. What about likely? By the way, would

624
00:31:39,164 --> 00:31:43,764
Speaker 1: would you say likely is above above what percentage is likely?

625
00:31:44,124 --> 00:31:44,924
Speaker 1: Is it above fifty?

626
00:31:44,964 --> 00:31:47,164
Speaker 3: If feel like you're a little asymmetric like likely, I

627
00:31:47,164 --> 00:31:49,524
Speaker 3: think you have to be sixty or so.

628
00:31:49,724 --> 00:31:51,964
Speaker 2: Right, Yeah, it is.

629
00:31:51,924 --> 00:31:55,404
Speaker 3: Asymmetric, possible or probable. These ones are pretty bad, right,

630
00:31:56,644 --> 00:31:57,244
Speaker 3: You want to do one more?

631
00:31:57,724 --> 00:32:00,724
Speaker 1: Yeah, let me let's do it all right? So, how

632
00:32:00,724 --> 00:32:03,564
Speaker 1: about if I actually add an adjective to unlikely and

633
00:32:03,604 --> 00:32:07,724
Speaker 1: say highly unlikely. Now, what are we talking now?

634
00:32:07,884 --> 00:32:09,924
Speaker 3: Ten percent or below? I think it's kind of the

635
00:32:09,924 --> 00:32:11,644
Speaker 3: counterpart to I don't know why. I think it's in

636
00:32:11,724 --> 00:32:13,284
Speaker 3: percent of blowing. There was like ninety five percent.

637
00:32:13,524 --> 00:32:15,684
Speaker 1: I was about to say, why they asymmetry, so you said,

638
00:32:15,804 --> 00:32:18,644
Speaker 1: you know, the just highly likely was ninety five I

639
00:32:18,644 --> 00:32:19,164
Speaker 1: have still.

640
00:32:18,964 --> 00:32:21,484
Speaker 3: A large language model teasing out implicit contexts from the

641
00:32:21,524 --> 00:32:23,724
Speaker 3: way these phrases are used in the real world.

642
00:32:24,164 --> 00:32:25,764
Speaker 2: I don't know what checchiput would say.

643
00:32:26,564 --> 00:32:32,524
Speaker 1: So highly unlikely, I would say it is interesting because

644
00:32:32,564 --> 00:32:34,564
Speaker 1: I might actually be lower than you. I might say,

645
00:32:34,644 --> 00:32:37,764
Speaker 1: like below if it's highly unlikely, like below five percent,

646
00:32:37,924 --> 00:32:41,844
Speaker 1: Like it's just you're telling me that it's almost certainly

647
00:32:42,004 --> 00:32:45,684
Speaker 1: not going to happen to me. Right, that like highly

648
00:32:45,764 --> 00:32:49,244
Speaker 1: unlikely and almost certainly kind of go hand in hand.

649
00:32:50,364 --> 00:32:53,604
Speaker 1: But let's if you actually kind of go out in

650
00:32:53,764 --> 00:32:59,044
Speaker 1: context a little bit with that. Think about weather reports,

651
00:32:59,084 --> 00:33:02,644
Speaker 1: which is something where we experience kind of that's one

652
00:33:02,684 --> 00:33:05,044
Speaker 1: of these things where we do get probabilities, where we

653
00:33:05,124 --> 00:33:10,724
Speaker 1: do get percentages, and we experience those on a daily basis. Right, you,

654
00:33:11,244 --> 00:33:13,844
Speaker 1: what what is your threshold, Nate for bringing an umbrella?

655
00:33:14,324 --> 00:33:14,364
Speaker 5: Like?

656
00:33:14,524 --> 00:33:16,524
Speaker 1: What's your an umbrella?

657
00:33:16,564 --> 00:33:17,364
Speaker 2: I find umbrella?

658
00:33:17,884 --> 00:33:20,684
Speaker 1: Okay, that was about this is true?

659
00:33:20,724 --> 00:33:22,604
Speaker 2: Why is umbrella technology not improved more?

660
00:33:23,644 --> 00:33:26,204
Speaker 1: Nate and I have walked together in New York City

661
00:33:26,604 --> 00:33:29,724
Speaker 1: rainstorms where I'm like, do you want to share my umbrella?

662
00:33:29,764 --> 00:33:33,444
Speaker 1: He's like, I got my baseball cap. I'm good. But

663
00:33:34,044 --> 00:33:36,804
Speaker 1: but you know, for people who are not like you

664
00:33:36,924 --> 00:33:39,684
Speaker 1: and who actually care about rain, like, what's your threshold

665
00:33:39,764 --> 00:33:42,524
Speaker 1: for bringing an umbrella? Like for me, if it's like

666
00:33:42,644 --> 00:33:44,564
Speaker 1: fifty percent chance of rain, I'm probably not going to

667
00:33:44,644 --> 00:33:47,044
Speaker 1: bring it. You know, if it's like above sixty, I'll

668
00:33:47,044 --> 00:33:50,164
Speaker 1: probably probably bring an umbrella. You know, it just it

669
00:33:50,324 --> 00:33:52,484
Speaker 1: really just depends on what I'm doing. And so you

670
00:33:53,044 --> 00:33:55,844
Speaker 1: know that's but you think about those days when it

671
00:33:55,964 --> 00:33:58,124
Speaker 1: was ninety percent chance of rain and it didn't rain.

672
00:33:58,324 --> 00:33:59,764
Speaker 2: Okay's great, let's get the audience.

673
00:34:01,844 --> 00:34:04,284
Speaker 1: Let's do it all right, one last one. We're going

674
00:34:04,364 --> 00:34:05,844
Speaker 1: to do it with you guys, and I'm gonna So

675
00:34:05,924 --> 00:34:07,484
Speaker 1: I'm going to ask you to raise your hands.

676
00:34:07,764 --> 00:34:13,084
Speaker 3: So if I say something is possible, that's a secret password, right, yeah, possible,

677
00:34:13,644 --> 00:34:15,844
Speaker 3: and you have to take one of the following ranges

678
00:34:16,524 --> 00:34:18,404
Speaker 3: zero twenty five percent, twenty about to fifty fifteen, seventy

679
00:34:18,404 --> 00:34:20,364
Speaker 3: five pcent five one hundred. Right, if I have something

680
00:34:20,484 --> 00:34:22,604
Speaker 3: is possible, raise your hand. If you interpret that as

681
00:34:22,684 --> 00:34:26,724
Speaker 3: zero to twenty five percent, okay, we have about a

682
00:34:26,804 --> 00:34:28,844
Speaker 3: quarter about z you're just twenty percent the hands up

683
00:34:28,844 --> 00:34:31,404
Speaker 3: in the audience, right, yeah, quite a few hands. I

684
00:34:31,444 --> 00:34:35,684
Speaker 3: will say twenty five to fifty percent a little bit more,

685
00:34:35,844 --> 00:34:36,724
Speaker 3: kind of solid.

686
00:34:36,484 --> 00:34:39,084
Speaker 1: It's kind of similar, but probably a little more. Okay,

687
00:34:39,164 --> 00:34:42,124
Speaker 1: how about fifty to seventy five and.

688
00:34:42,244 --> 00:34:44,604
Speaker 3: There are a handful of hands hands possible, that could

689
00:34:44,644 --> 00:34:48,004
Speaker 3: be And how about seventy five percent or more one day?

690
00:34:48,684 --> 00:34:50,844
Speaker 3: So the way to average is like thirty six or

691
00:34:50,884 --> 00:34:54,004
Speaker 3: something percent. We're like doing we're doing science here, yeah,

692
00:34:54,284 --> 00:34:57,884
Speaker 3: doing it on the fly. Yeah, but people think it

693
00:34:57,924 --> 00:35:01,604
Speaker 3: means anything from five percent to eighty percent, right if

694
00:35:01,644 --> 00:35:03,324
Speaker 3: you ask people to write down individual guesses so like,

695
00:35:03,524 --> 00:35:05,164
Speaker 3: so not very useful to have that, to have.

696
00:35:05,244 --> 00:35:07,764
Speaker 1: That for you. No, No, it's really not because what

697
00:35:07,964 --> 00:35:10,484
Speaker 1: you know, what do you even mean probbable likely? Like

698
00:35:10,964 --> 00:35:13,804
Speaker 1: it is? You know, it's such a hedgeword. And what

699
00:35:14,004 --> 00:35:16,364
Speaker 1: we're trying to do is actually force you to be

700
00:35:16,564 --> 00:35:20,964
Speaker 1: more precise in your probabilistic judgments, because precision matters, right,

701
00:35:21,124 --> 00:35:27,004
Speaker 1: whether it's the precision of the USSR invading Yugoslavia or

702
00:35:27,604 --> 00:35:31,204
Speaker 1: a gamble that you're taking out the poker table right out.

703
00:35:32,004 --> 00:35:34,444
Speaker 3: When it comes to like politics and things like that,

704
00:35:34,604 --> 00:35:38,244
Speaker 3: political questions, like, people are also just often interpreting stuff

705
00:35:38,284 --> 00:35:41,404
Speaker 3: in bad faith, right, Like I think that I think

706
00:35:41,484 --> 00:35:43,764
Speaker 3: that when you say there's a third chance of rain

707
00:35:44,284 --> 00:35:47,124
Speaker 3: and doesn't rain, people don't get as mad as when

708
00:35:47,164 --> 00:35:49,404
Speaker 3: there's a third chance of Donald Trump winning and he wins,

709
00:35:49,764 --> 00:35:52,084
Speaker 3: or things like that for example. But like, but you know,

710
00:35:52,684 --> 00:35:58,124
Speaker 3: politics makes people's brains misfire in various ways absolutely well.

711
00:35:58,204 --> 00:36:01,484
Speaker 1: As soon as there's personal motivation there, right, as soon

712
00:36:01,524 --> 00:36:03,844
Speaker 1: as your identity is tied up in something like politics,

713
00:36:04,324 --> 00:36:06,964
Speaker 1: all of a sudden, your ability to parse these things.

714
00:36:07,044 --> 00:36:09,524
Speaker 1: You start thinking in absolutes, which is how are our

715
00:36:09,564 --> 00:36:13,364
Speaker 1: brains are programmed to think? Right? Ninety percent basically one

716
00:36:13,444 --> 00:36:16,484
Speaker 1: hundred seventy is basically one hundred sixty five basically one

717
00:36:16,524 --> 00:36:17,884
Speaker 1: hundred thirty basically zero.

718
00:36:18,484 --> 00:36:20,484
Speaker 2: Right. We just let's at least.

719
00:36:20,364 --> 00:36:23,844
Speaker 3: Get sixty five, right, is certainly either fifty fifty zero,

720
00:36:23,884 --> 00:36:26,084
Speaker 3: one hundred. Let's at least get those middle zones right

721
00:36:26,164 --> 00:36:28,964
Speaker 3: as a stepping stone to some more PI.

722
00:36:29,204 --> 00:36:31,164
Speaker 1: Yeah, and I think I think that the bottom line

723
00:36:31,364 --> 00:36:35,284
Speaker 1: is that it's very difficult to communicate probabilities in plain language,

724
00:36:35,604 --> 00:36:39,564
Speaker 1: and you do need to get people accustomed to having

725
00:36:40,044 --> 00:36:43,044
Speaker 1: numbers associated with them, and one of the best ways

726
00:36:43,044 --> 00:36:44,844
Speaker 1: of doing that is to try to figure out, Okay,

727
00:36:44,964 --> 00:36:48,044
Speaker 1: what experience can I tie that to in their life

728
00:36:48,124 --> 00:36:50,884
Speaker 1: that makes them understand what this actually means?

729
00:36:51,044 --> 00:36:51,164
Speaker 2: Right?

730
00:36:51,404 --> 00:36:53,004
Speaker 1: That percent is not zero?

731
00:36:53,084 --> 00:36:53,844
Speaker 2: I'm not way serious.

732
00:36:53,964 --> 00:36:56,404
Speaker 1: Yeah, no, teacher, kids, poker. I've actually talked about this

733
00:36:56,484 --> 00:36:59,124
Speaker 1: many times, and I actually think that that is one

734
00:36:59,164 --> 00:37:01,844
Speaker 1: of the best ways that you can combat this.

735
00:37:04,684 --> 00:37:06,524
Speaker 2: And we'll be right back after this break.

736
00:37:20,124 --> 00:37:21,364
Speaker 1: Do you want to open it up to questions?

737
00:37:21,404 --> 00:37:24,404
Speaker 3: Yeah, I say it's extraordinarily likely that we're going to

738
00:37:24,444 --> 00:37:26,564
Speaker 3: open it up to Q and A at this point.

739
00:37:27,644 --> 00:37:30,444
Speaker 2: So there are mic runners. We can also point and shop,

740
00:37:30,484 --> 00:37:31,044
Speaker 2: but yeah.

741
00:37:30,964 --> 00:37:33,324
Speaker 1: Okay, yeah, there are mic runners in the audience. So

742
00:37:33,484 --> 00:37:35,204
Speaker 1: raise your hand if you have a question. Yep, there's

743
00:37:35,284 --> 00:37:37,284
Speaker 1: one coming to you. Thanks.

744
00:37:38,484 --> 00:37:43,164
Speaker 6: I studied statistics in graduate school and ended up in communications,

745
00:37:43,164 --> 00:37:45,004
Speaker 6: and I think one of the things that confounds this

746
00:37:45,204 --> 00:37:49,324
Speaker 6: problem is if somebody says to me, for example, climate

747
00:37:49,844 --> 00:37:54,364
Speaker 6: change isn't caused by us, I would say, not believing

748
00:37:54,484 --> 00:37:56,684
Speaker 6: myself that that's possible.

749
00:37:57,124 --> 00:37:57,844
Speaker 4: That's my opinion.

750
00:37:57,924 --> 00:38:00,964
Speaker 6: I know other people disagree, but in order to have

751
00:38:01,124 --> 00:38:04,604
Speaker 6: a conversation, I validate their opinion and move on. And

752
00:38:04,684 --> 00:38:08,164
Speaker 6: that's standard operating procedure when you're trying to actually change

753
00:38:08,244 --> 00:38:13,244
Speaker 6: minds of what you're saying is we're inaccurate and communicating.

754
00:38:12,724 --> 00:38:13,844
Speaker 4: The real probabilities.

755
00:38:14,444 --> 00:38:16,284
Speaker 6: But part of what's going on is that most of

756
00:38:16,364 --> 00:38:19,364
Speaker 6: the conversation is about trying to find some middle ground.

757
00:38:21,044 --> 00:38:24,444
Speaker 1: So how do you separate those two uses?

758
00:38:24,844 --> 00:38:26,284
Speaker 3: Yeah, it just and this kind of gets into the

759
00:38:26,324 --> 00:38:29,684
Speaker 3: conversation about Zoran earlier, right where he's going on podcasts

760
00:38:29,724 --> 00:38:31,444
Speaker 3: where the audience might not be favably inclined to him.

761
00:38:31,444 --> 00:38:33,284
Speaker 3: And I've done this too, Like marketing my book, I

762
00:38:33,324 --> 00:38:36,084
Speaker 3: talked to conserative audiences, liberal audiences, everything in between. Right,

763
00:38:36,084 --> 00:38:38,404
Speaker 3: And you're basically a politician, right, You're like you're trying

764
00:38:38,444 --> 00:38:40,604
Speaker 3: to code switch back and forth. You're trying to be

765
00:38:40,684 --> 00:38:43,244
Speaker 3: empathetic to your audience, You're trying to find points of

766
00:38:43,284 --> 00:38:46,924
Speaker 3: agreement in that disagreement. Maybe more politicians should take that lesson.

767
00:38:47,044 --> 00:38:52,844
Speaker 3: I mean, look, I generally think that when scientific communicators

768
00:38:54,404 --> 00:38:58,204
Speaker 3: try to like dumb things down too much, it's like

769
00:38:58,244 --> 00:39:01,164
Speaker 3: quite the right term. There's empathy, and there's there's empathy,

770
00:39:01,644 --> 00:39:04,324
Speaker 3: there's dumbing down, and there's like kind of like skipping

771
00:39:04,404 --> 00:39:07,724
Speaker 3: over the rough patches of the argument in a way.

772
00:39:07,764 --> 00:39:11,004
Speaker 3: They create like false certainty times, right, Like I generally

773
00:39:11,044 --> 00:39:16,124
Speaker 3: believe that like treat the audience as being reasonably smart

774
00:39:16,644 --> 00:39:19,364
Speaker 3: and sophisticated, right, I mean as poker players too, you know,

775
00:39:20,364 --> 00:39:23,764
Speaker 3: I think we are naturally suspicious, right, And I think

776
00:39:23,764 --> 00:39:27,564
Speaker 3: people can like people can tell I think when a

777
00:39:27,724 --> 00:39:32,044
Speaker 3: politician is being inauthentic or when they're not being kind

778
00:39:32,044 --> 00:39:34,844
Speaker 3: of communicated with fully forthrightly. Right, Like I thought this

779
00:39:34,924 --> 00:39:37,804
Speaker 3: was an issue at the beginning of the COVID pandemic.

780
00:39:37,884 --> 00:39:41,604
Speaker 3: We're changing advice about like masks and things like that, Right.

781
00:39:42,764 --> 00:39:46,284
Speaker 3: I think whenever people kind of like say, oh, the

782
00:39:46,324 --> 00:39:48,444
Speaker 3: science has settled on this question, well, on some questions,

783
00:39:48,444 --> 00:39:50,324
Speaker 3: it's settled on some questions that isn't right, and it's

784
00:39:50,364 --> 00:39:53,004
Speaker 3: like often used as a cudgel where there is genuine

785
00:39:53,444 --> 00:39:57,044
Speaker 3: uncertainty and so so yeah, I mean it's it's look,

786
00:39:57,204 --> 00:39:59,204
Speaker 3: we wrestle with this every day journalists too. But like,

787
00:39:59,284 --> 00:40:02,364
Speaker 3: I'm air more on the side of like, you know,

788
00:40:02,604 --> 00:40:05,484
Speaker 3: you can be empathetic in how you present something, and obviously,

789
00:40:05,484 --> 00:40:07,124
Speaker 3: if you're in a kind of question like not everything

790
00:40:07,164 --> 00:40:09,364
Speaker 3: you say in response, you're not going to correct any way.

791
00:40:09,724 --> 00:40:11,844
Speaker 3: Oh literally, you're wrong, you're wrong, but let me tell

792
00:40:11,844 --> 00:40:14,964
Speaker 3: you something else. Right, So I'm yeah, empathetic, but when

793
00:40:15,004 --> 00:40:17,404
Speaker 3: it official sign of a communication, I think should aim

794
00:40:17,444 --> 00:40:18,564
Speaker 3: more in the side of precision.

795
00:40:18,764 --> 00:40:22,004
Speaker 1: I think that I think that we are also not

796
00:40:23,324 --> 00:40:30,484
Speaker 1: tolerant of ambiguity. Right that it's much easier to win elections.

797
00:40:30,644 --> 00:40:34,044
Speaker 1: It's much easier to win over a crowd if you

798
00:40:34,244 --> 00:40:38,164
Speaker 1: speak in absolutes, if you speak in certainties, and the

799
00:40:38,284 --> 00:40:41,644
Speaker 1: person who says, you know, I'm really not sure about this,

800
00:40:42,004 --> 00:40:43,884
Speaker 1: you know, they're here are the pros, here are the

801
00:40:44,004 --> 00:40:47,284
Speaker 1: cons And who gives the more nuanced response is not

802
00:40:47,524 --> 00:40:50,644
Speaker 1: the person who ends up getting ahead. And so there's

803
00:40:50,964 --> 00:40:56,684
Speaker 1: a fundamental mismatch between the need to communicate ambiguity and

804
00:40:56,924 --> 00:40:59,124
Speaker 1: uncertainty and the fact that you know some things we

805
00:40:59,324 --> 00:41:01,724
Speaker 1: just don't know, and that there are these kind of

806
00:41:01,804 --> 00:41:06,284
Speaker 1: confidence intervals there, and the need to tell a story

807
00:41:07,084 --> 00:41:09,124
Speaker 1: and tell a compelling story. And this is something that

808
00:41:09,524 --> 00:41:11,404
Speaker 1: you know, Nate, You and I have to struggle with

809
00:41:11,524 --> 00:41:15,204
Speaker 1: us storytellers too. I mean, we're communicators, we're journalists. We

810
00:41:15,324 --> 00:41:18,884
Speaker 1: make choices all the time when we write an article,

811
00:41:19,004 --> 00:41:21,444
Speaker 1: when we write a book, how do we tell the story?

812
00:41:21,604 --> 00:41:24,564
Speaker 1: What story do we tell? And you can't constantly. I

813
00:41:24,644 --> 00:41:28,724
Speaker 1: mean a book will be absolutely unreadable if every single

814
00:41:28,884 --> 00:41:32,364
Speaker 1: paragraph is a caveat where you know, well, you know,

815
00:41:32,564 --> 00:41:34,684
Speaker 1: you can also interpret it this way and this way

816
00:41:34,684 --> 00:41:36,924
Speaker 1: and I'm not quite sure about this, right, you can't.

817
00:41:37,084 --> 00:41:39,604
Speaker 1: You can't work that way, and so you make choices

818
00:41:39,684 --> 00:41:40,164
Speaker 1: all the time.

819
00:41:40,364 --> 00:41:43,004
Speaker 3: Of course, sometimes ambiguity is strategic, right, Like let's say

820
00:41:43,004 --> 00:41:46,084
Speaker 3: Marie and I are on a double date with our

821
00:41:46,124 --> 00:41:49,284
Speaker 3: respective spouses and then a third couple that we don't know,

822
00:41:49,644 --> 00:41:50,884
Speaker 3: that a friend kind of set us with for a

823
00:41:50,884 --> 00:41:53,284
Speaker 3: friend's day, and they're super fucking annoying and we hate

824
00:41:53,284 --> 00:41:56,044
Speaker 3: their guts. Right, you know, if I say something like Marie,

825
00:41:56,084 --> 00:41:57,884
Speaker 3: what time did you say your flight was tomorrow morning?

826
00:41:57,964 --> 00:41:58,044
Speaker 2: Right?

827
00:41:58,124 --> 00:42:00,164
Speaker 3: Yeah, that's ambiguous. What it really means is that let's

828
00:42:00,164 --> 00:42:01,684
Speaker 3: gett's great.

829
00:42:02,324 --> 00:42:03,964
Speaker 1: And Nate and I have known each other for long

830
00:42:04,044 --> 00:42:05,644
Speaker 1: enough that I would say, you know, it's at seven am,

831
00:42:05,724 --> 00:42:10,284
Speaker 1: we really really have to go. Yeah, so there are

832
00:42:10,284 --> 00:42:12,724
Speaker 1: strategic uses of it. Yeah, there are more questions back there.

833
00:42:13,204 --> 00:42:15,404
Speaker 4: I am a longtime listener, first time caller.

834
00:42:16,844 --> 00:42:17,724
Speaker 1: Wellco to the show.

835
00:42:17,844 --> 00:42:18,404
Speaker 2: Yeah, yes.

836
00:42:18,844 --> 00:42:21,644
Speaker 4: My question is how much do we do we think

837
00:42:21,724 --> 00:42:24,564
Speaker 4: Zauron's win is the inter syncracies in New York City

838
00:42:24,684 --> 00:42:27,004
Speaker 4: and him being a great candidate and Cuomo sucking, and

839
00:42:27,124 --> 00:42:29,404
Speaker 4: how much is the political climate has changed in some

840
00:42:29,564 --> 00:42:31,164
Speaker 4: way since the last election?

841
00:42:31,964 --> 00:42:34,004
Speaker 1: That is, I mean, that is such a good question,

842
00:42:34,204 --> 00:42:37,124
Speaker 1: because the Cuomo sucking part of it is actually huge.

843
00:42:37,924 --> 00:42:41,324
Speaker 1: That sounds like that sounds like a silly statement, but

844
00:42:41,844 --> 00:42:45,084
Speaker 1: I actually think that that is an idiosyncrasy of this

845
00:42:46,044 --> 00:42:52,084
Speaker 1: election from a psychological standpoint, because never underestimate the power

846
00:42:52,324 --> 00:42:55,884
Speaker 1: of people to band together and coalitions to actually stick

847
00:42:55,964 --> 00:42:59,324
Speaker 1: together when there's one enemy, right, when there's a clear

848
00:42:59,644 --> 00:43:02,164
Speaker 1: someone who no one wants to see, When all of

849
00:43:02,204 --> 00:43:05,644
Speaker 1: a sudden, people who would never vote together, who would

850
00:43:05,764 --> 00:43:09,564
Speaker 1: never kind of partners partner up. And this is from

851
00:43:09,604 --> 00:43:10,524
Speaker 1: a psychological stamp.

852
00:43:10,524 --> 00:43:12,964
Speaker 3: What you see that he both ran a bad campaign

853
00:43:13,004 --> 00:43:15,524
Speaker 3: and kind of, to us an informal term, kind of

854
00:43:15,564 --> 00:43:18,804
Speaker 3: like cock blocked all the other candidates in the field,

855
00:43:18,964 --> 00:43:21,044
Speaker 3: right where all the money from hedge funders and people

856
00:43:21,164 --> 00:43:23,764
Speaker 3: like that went to Cuomo. And you saw a quotes

857
00:43:23,884 --> 00:43:25,724
Speaker 3: when people were like big Cemo donors like I didn't

858
00:43:25,764 --> 00:43:27,844
Speaker 3: really care about that much, but it seemed like that's

859
00:43:27,884 --> 00:43:29,644
Speaker 3: what everyone was backing. I'm not going to back the

860
00:43:29,764 --> 00:43:32,564
Speaker 3: socialist right and so therefore and so yeah, you know,

861
00:43:32,964 --> 00:43:36,084
Speaker 3: if you'd had a fully fledged campaign between Zoran and

862
00:43:36,204 --> 00:43:38,684
Speaker 3: Brad Lander or something, or Adrian Adams, it might have

863
00:43:38,804 --> 00:43:39,244
Speaker 3: been closer.

864
00:43:39,284 --> 00:43:39,884
Speaker 2: But he's a good can.

865
00:43:39,924 --> 00:43:42,404
Speaker 3: I mean, look a lot of times political analysts like

866
00:43:42,524 --> 00:43:44,764
Speaker 3: me are left saying, yeah, the wins and losses are

867
00:43:44,804 --> 00:43:48,404
Speaker 3: what matter, but for analyzing trends and close counts, right

868
00:43:48,844 --> 00:43:51,044
Speaker 3: you know. So you know, look, if he had lost

869
00:43:51,564 --> 00:43:54,204
Speaker 3: seven point instead of won by seven points, I'd still

870
00:43:54,204 --> 00:43:55,324
Speaker 3: say that was pretty impressive.

871
00:43:55,404 --> 00:43:55,484
Speaker 5: Right.

872
00:43:55,564 --> 00:43:57,084
Speaker 2: It might be a sign of change here.

873
00:43:57,164 --> 00:44:01,524
Speaker 3: It's a cleaner story, I think, But usually surprising outcomes

874
00:44:01,724 --> 00:44:04,164
Speaker 3: are overdetermined, right, you know, it has to do with

875
00:44:04,244 --> 00:44:07,284
Speaker 3: the changing of the guard generationally. It has to do

876
00:44:07,444 --> 00:44:10,004
Speaker 3: with like he kind of figured out the right formula

877
00:44:10,244 --> 00:44:13,564
Speaker 3: for more left wing ideas. It's not wilk culture stuff, right,

878
00:44:13,604 --> 00:44:16,204
Speaker 3: it's affordability, it's working class people, things like that.

879
00:44:16,484 --> 00:44:16,604
Speaker 2: Right.

880
00:44:17,124 --> 00:44:21,164
Speaker 3: He's a very well presenting guy, right, who's very New York.

881
00:44:21,244 --> 00:44:24,724
Speaker 3: I think in some ways his mom was a filmmaker,

882
00:44:24,764 --> 00:44:28,564
Speaker 3: and his visuals are all quite stunning and beautiful and cuomo.

883
00:44:28,724 --> 00:44:30,084
Speaker 2: So it's like four things coming together.

884
00:44:31,604 --> 00:44:33,564
Speaker 3: But he also won by enough margin where maybe only

885
00:44:33,604 --> 00:44:34,724
Speaker 3: three of those things or two, and to have it

886
00:44:34,764 --> 00:44:36,524
Speaker 3: to come together, we still have one probably.

887
00:44:36,924 --> 00:44:39,204
Speaker 1: Yeah. And when things are over determined, by the way,

888
00:44:39,244 --> 00:44:42,564
Speaker 1: we can't answer your question right, When things are over determined,

889
00:44:42,604 --> 00:44:46,684
Speaker 1: you can't quite know what the crucial factors were. So

890
00:44:46,804 --> 00:44:49,124
Speaker 1: I think that the real answer to your question remains

891
00:44:49,164 --> 00:44:52,644
Speaker 1: to be seen. But it's a really interesting thing to

892
00:44:52,724 --> 00:44:56,084
Speaker 1: try to disambiguate and try to see kind of how

893
00:44:56,124 --> 00:44:58,164
Speaker 1: did we end up here? And I think that this

894
00:44:58,284 --> 00:45:01,164
Speaker 1: is an election that people will be looking back and

895
00:45:01,324 --> 00:45:03,124
Speaker 1: doing some commentary on for many years.

896
00:45:04,324 --> 00:45:07,884
Speaker 7: So I want to ask political polls, so I think

897
00:45:07,924 --> 00:45:11,604
Speaker 7: you know something about it. So now I've heard the

898
00:45:11,804 --> 00:45:17,404
Speaker 7: lecture on words. And so if I see that one

899
00:45:17,524 --> 00:45:21,204
Speaker 7: candidate has a forty two percent chance of winning and

900
00:45:21,284 --> 00:45:24,764
Speaker 7: another candidate has a forty six percent chance, should I

901
00:45:24,884 --> 00:45:29,004
Speaker 7: interpret that to say they both have low probability? Or

902
00:45:29,124 --> 00:45:32,164
Speaker 7: they have or I mean I guess, or is it

903
00:45:32,284 --> 00:45:34,124
Speaker 7: so close? Really doesn't matter?

904
00:45:35,124 --> 00:45:38,244
Speaker 3: Well, for one thing, people who work in polling or

905
00:45:38,244 --> 00:45:39,764
Speaker 3: who report on pulling need to be clear about a

906
00:45:39,804 --> 00:45:43,284
Speaker 3: probability versus a percent of the vote. Right, If it's

907
00:45:43,604 --> 00:45:48,644
Speaker 3: Trump forty six percent in say Texas, Harris forty two

908
00:45:48,684 --> 00:45:52,204
Speaker 3: percent undecided, third party is the remaining whatever eighteen percent?

909
00:45:52,324 --> 00:45:54,924
Speaker 2: Right, like a four point lead. How often does that

910
00:45:55,004 --> 00:45:56,004
Speaker 2: translate into a win?

911
00:45:56,524 --> 00:45:59,164
Speaker 3: That's an empirical question, right, The answer might be something

912
00:45:59,244 --> 00:46:00,724
Speaker 3: like seventy percent of the time.

913
00:46:01,164 --> 00:46:03,964
Speaker 2: Russia, And in New York, what were the polls saying before?

914
00:46:04,284 --> 00:46:04,844
Speaker 2: In New York?

915
00:46:05,084 --> 00:46:08,004
Speaker 3: No, the polls underestimated, I mean, had they had shown

916
00:46:08,044 --> 00:46:11,564
Speaker 3: the race tightening a lot. Some of the polls showed

917
00:46:11,644 --> 00:46:15,844
Speaker 3: Zoran pulling ahead after ranked choice voting. Almost none Maybee,

918
00:46:15,964 --> 00:46:19,644
Speaker 3: with one exception, had him winning the first round outright,

919
00:46:20,004 --> 00:46:21,884
Speaker 3: and none of them had him winning by like that

920
00:46:22,124 --> 00:46:25,244
Speaker 3: wide margin. Right, So this is what happens with polls

921
00:46:25,364 --> 00:46:27,524
Speaker 3: is like in a New York race, they assume turnouts

922
00:46:27,524 --> 00:46:31,564
Speaker 3: fairly low. They're surveying the people that like always turn

923
00:46:31,644 --> 00:46:34,764
Speaker 3: out in New York MARYORL races, who consideringly unlikely voters

924
00:46:34,764 --> 00:46:35,924
Speaker 3: are twenty percent of electorate.

925
00:46:36,044 --> 00:46:36,124
Speaker 1: Right.

926
00:46:36,564 --> 00:46:39,844
Speaker 3: Cuomo got his numbers among that twenty percent, but then

927
00:46:39,924 --> 00:46:42,604
Speaker 3: Zoran turned out people that never vote in mayoral elections

928
00:46:42,764 --> 00:46:43,684
Speaker 3: in e York. By the way, a lot of New

929
00:46:43,764 --> 00:46:46,404
Speaker 3: York's are transplants from around the country, all around.

930
00:46:46,084 --> 00:46:49,004
Speaker 2: The world, right, so we don't have that like tie

931
00:46:49,124 --> 00:46:51,084
Speaker 2: to local politics. Right.

932
00:46:51,364 --> 00:46:53,684
Speaker 3: I'm a person covers politics, listen to New York. I

933
00:46:53,724 --> 00:46:56,124
Speaker 3: don't know that much about like New York politics, right,

934
00:46:56,164 --> 00:46:58,284
Speaker 3: and it's very typical in some ways. But he he

935
00:46:58,444 --> 00:47:02,004
Speaker 3: broke through and became its cliche, but became viral in

936
00:47:02,084 --> 00:47:04,644
Speaker 3: a way that you know, I guess pollsters were too

937
00:47:04,684 --> 00:47:08,004
Speaker 3: conservative in their in their methods and missing and missing

938
00:47:08,044 --> 00:47:08,564
Speaker 3: these voters.

939
00:47:09,404 --> 00:47:11,284
Speaker 1: We have time for one more question, hi.

940
00:47:11,364 --> 00:47:15,764
Speaker 5: Things I was just curious. I know this is probably annoying,

941
00:47:15,884 --> 00:47:17,804
Speaker 5: like too long in the future kind of question, but

942
00:47:18,284 --> 00:47:22,804
Speaker 5: does Zorin's win at all change the probabilities that you

943
00:47:22,884 --> 00:47:26,284
Speaker 5: think about candidates in twenty twenty eight for Democratic primary

944
00:47:26,364 --> 00:47:26,844
Speaker 5: or I guess.

945
00:47:26,724 --> 00:47:27,764
Speaker 1: The general election too.

946
00:47:28,404 --> 00:47:31,084
Speaker 3: So with actually my former colleague at five thirty eight,

947
00:47:31,524 --> 00:47:35,484
Speaker 3: Galen Druke, we did a Democratic twenty twenty eight primary draft,

948
00:47:36,004 --> 00:47:37,484
Speaker 3: right or do it so it's like a draft, like

949
00:47:37,524 --> 00:47:42,204
Speaker 3: a fancy football draft or something. Galen got the first

950
00:47:42,244 --> 00:47:45,164
Speaker 3: pick and the first candidate on my list was AOC.

951
00:47:45,884 --> 00:47:47,924
Speaker 3: I thought he'd take Josh Shapiro or someone and said

952
00:47:47,924 --> 00:47:50,604
Speaker 3: he took AOC too, So it was mad about that.

953
00:47:50,724 --> 00:47:52,764
Speaker 3: But like we both thought, and this is before Zoran,

954
00:47:53,524 --> 00:47:57,444
Speaker 3: that she was let me put this carefully, from talking

955
00:47:57,444 --> 00:47:59,884
Speaker 3: about probabilities, right to say the most likely candidate might

956
00:47:59,924 --> 00:48:01,404
Speaker 3: mean a fifteen percent chance.

957
00:48:01,884 --> 00:48:03,884
Speaker 2: Right, there's nobody in the field who is a clear

958
00:48:03,964 --> 00:48:04,484
Speaker 2: front runner.

959
00:48:04,684 --> 00:48:06,284
Speaker 3: But we both thought that she was more luckily than

960
00:48:06,284 --> 00:48:09,644
Speaker 3: any other candidate to become the nominee in twenty twenty eight,

961
00:48:10,084 --> 00:48:14,924
Speaker 3: before before Mom Donnay came along, right, And again it's

962
00:48:14,964 --> 00:48:18,324
Speaker 3: probably because like look Democrats, of all these retreads, right,

963
00:48:18,364 --> 00:48:22,244
Speaker 3: the Clinton family, the Cuomo family, the Biden family. I

964
00:48:22,324 --> 00:48:25,444
Speaker 3: bet Jill will probably fantasize sometimes what if I become president? Right,

965
00:48:26,404 --> 00:48:29,484
Speaker 3: like House of Cards or something. Right, I'm I think

966
00:48:29,524 --> 00:48:31,964
Speaker 3: people are tired of all these families.

967
00:48:32,084 --> 00:48:32,204
Speaker 2: Right.

968
00:48:32,324 --> 00:48:35,684
Speaker 3: I remember seeing in twenty sixteen, I was in New

969
00:48:35,724 --> 00:48:38,964
Speaker 3: Hampshire covering the race for five thirty eight in ABC News, Right,

970
00:48:39,124 --> 00:48:43,164
Speaker 3: and like Hillary Clinton spoke to a group of like

971
00:48:43,364 --> 00:48:46,404
Speaker 3: then at college, right, Franklin Pierce College or something like that.

972
00:48:46,564 --> 00:48:48,684
Speaker 2: Right, you know, the average age is twenty or something.

973
00:48:48,764 --> 00:48:51,364
Speaker 3: She's talking about like the Cold War, and like the

974
00:48:51,404 --> 00:48:55,084
Speaker 3: students size are gleazing over they don't remember the Cold War, right,

975
00:48:55,364 --> 00:48:58,764
Speaker 3: And now that was you know, was eight nine years

976
00:48:58,804 --> 00:49:02,964
Speaker 3: ago now, right, And so like, look, I think I

977
00:49:03,004 --> 00:49:04,924
Speaker 3: think it's a good thing to see. I mean, Zaraan

978
00:49:05,044 --> 00:49:08,524
Speaker 3: was literally half of like Cuomo's age. Right, I think

979
00:49:08,604 --> 00:49:10,564
Speaker 3: it's a good thing. Mcrat parties about present and was

980
00:49:10,564 --> 00:49:12,444
Speaker 3: how can everyone's so freaking old? Right, I think it's

981
00:49:12,484 --> 00:49:15,244
Speaker 3: a good thing. Is is to you know, have cannates

982
00:49:15,244 --> 00:49:18,124
Speaker 3: that are good on social media, are substantive. I think

983
00:49:18,164 --> 00:49:21,804
Speaker 3: she's a pretty canny and smart politician and shows some

984
00:49:21,964 --> 00:49:23,444
Speaker 3: restraint at times.

985
00:49:23,804 --> 00:49:26,004
Speaker 2: So yeah, it does change my views a little bit. Maria,

986
00:49:26,084 --> 00:49:27,404
Speaker 2: do you have a take now?

987
00:49:27,484 --> 00:49:28,964
Speaker 1: I mean, this is one of the things that I

988
00:49:29,124 --> 00:49:31,084
Speaker 1: was talking about when I was talking about some of

989
00:49:31,164 --> 00:49:34,884
Speaker 1: the long term consequences of this election, right, And I

990
00:49:34,964 --> 00:49:37,724
Speaker 1: think a lot of it will depend on what ends

991
00:49:37,804 --> 00:49:41,444
Speaker 1: up happening once Zorn takes power, right, if he's elected,

992
00:49:41,844 --> 00:49:45,764
Speaker 1: how he actually handles himself in office, how popular he is.

993
00:49:46,164 --> 00:49:49,444
Speaker 1: I think that that will actually have a large bearing

994
00:49:49,524 --> 00:49:52,324
Speaker 1: on your question in terms of, you know, what does

995
00:49:52,364 --> 00:49:55,044
Speaker 1: the Democratic Party end up taking from this, because they

996
00:49:55,084 --> 00:49:59,004
Speaker 1: could take two very different lessons one AOC Two if

997
00:49:59,124 --> 00:50:02,604
Speaker 1: Zorn tanks for some reason right and becomes incredibly unpopular

998
00:50:02,724 --> 00:50:05,684
Speaker 1: and like the you know, we don't know, we can't

999
00:50:05,844 --> 00:50:07,684
Speaker 1: we don't have a crystal ball. But if something like

1000
00:50:07,764 --> 00:50:09,804
Speaker 1: that were to happen, I think they'd be like, see,

1001
00:50:09,884 --> 00:50:12,084
Speaker 1: we told you so right, we need to go back

1002
00:50:12,164 --> 00:50:15,844
Speaker 1: to so I think you could see either thing working out,

1003
00:50:16,084 --> 00:50:18,364
Speaker 1: so you can a lot rest on his shoulders.

1004
00:50:18,684 --> 00:50:18,924
Speaker 2: I guess.

1005
00:50:19,884 --> 00:50:23,084
Speaker 1: Yeah. That was our first Risky Business Live and we're

1006
00:50:23,324 --> 00:50:30,964
Speaker 1: so happy you were here. That was our show from

1007
00:50:31,004 --> 00:50:34,364
Speaker 1: the Aspen Ideas Festival. By the way, our segment on

1008
00:50:34,484 --> 00:50:40,244
Speaker 1: probabilities was inspired by Adam Kucharski's newsletter Understanding the Unseen.

1009
00:50:40,724 --> 00:50:42,884
Speaker 1: We'll have a link to that post in the show notes.

1010
00:50:43,084 --> 00:50:46,964
Speaker 1: Thanks for listening. Let us know what you think of

1011
00:50:47,044 --> 00:50:49,804
Speaker 1: the show. Reach out to us at Risky Business at

1012
00:50:49,884 --> 00:50:53,204
Speaker 1: pushkin dot fm. And by the way, if you're a

1013
00:50:53,204 --> 00:50:55,804
Speaker 1: Pushkin Plus subscriber, we have some bonus content for you

1014
00:50:56,324 --> 00:50:58,084
Speaker 1: that's coming up right after the credits.

1015
00:50:58,484 --> 00:51:01,724
Speaker 3: And if you're not subscribing yet, consider signing up for

1016
00:51:01,924 --> 00:51:04,084
Speaker 3: just six ninety nine a month. What a nice price

1017
00:51:04,444 --> 00:51:07,084
Speaker 3: you get access to all that premium content and and

1018
00:51:07,284 --> 00:51:09,844
Speaker 3: we're listening across Pushkin's entire network shows.

1019
00:51:10,124 --> 00:51:13,164
Speaker 1: Risky Business is hosted by me Maria Kanikova.

1020
00:51:12,924 --> 00:51:14,244
Speaker 2: And by me Nate Silver.

1021
00:51:14,644 --> 00:51:17,724
Speaker 3: The show is a co production of Pushkin Industries and iHeartMedia.

1022
00:51:18,404 --> 00:51:21,764
Speaker 3: This episode was produced by Isabelle Carter. Our associate producer

1023
00:51:21,844 --> 00:51:24,804
Speaker 3: is Sonia Gerwin. Sally Helm is our editor, and our

1024
00:51:24,804 --> 00:51:28,364
Speaker 3: executive producer is Jacob Boldstein. Mixing by Sarah Bruguier.

1025
00:51:29,044 --> 00:51:30,204
Speaker 1: Thanks so much for tuning in.