1
00:00:00,520 --> 00:00:05,240
Speaker 1: The right plays on fear identifies villains more quickly and

2
00:00:05,280 --> 00:00:07,920
Speaker 1: more effectively than the left. But if you go to

3
00:00:07,960 --> 00:00:10,879
Speaker 1: Bernie and to Tucker Carlson, they will give you a

4
00:00:10,920 --> 00:00:14,720
Speaker 1: similar diagnosis. Up front, we need better models of masculinity.

5
00:00:14,760 --> 00:00:16,480
Speaker 1: And where I think the left has sort of failed

6
00:00:16,560 --> 00:00:20,200
Speaker 1: is the narrative of toxic masculinity is bad as a

7
00:00:20,239 --> 00:00:22,960
Speaker 1: primary message. I think it pushes people away.

8
00:00:24,520 --> 00:00:26,400
Speaker 2: This is Gavin Newsom.

9
00:00:26,960 --> 00:00:28,200
Speaker 1: And this is David Pacman.

10
00:00:31,640 --> 00:00:32,080
Speaker 2: We got it.

11
00:00:32,080 --> 00:00:36,760
Speaker 3: Just start right there, mister Argentina, yes, born, yeah, in Argentina.

12
00:00:36,920 --> 00:00:39,680
Speaker 2: Yeah, I mean, have you recovered? You good? Is he

13
00:00:39,760 --> 00:00:40,120
Speaker 2: all right?

14
00:00:40,280 --> 00:00:43,680
Speaker 1: You know? Second place is pretty good? No, but you

15
00:00:43,720 --> 00:00:44,720
Speaker 1: always want to be first.

16
00:00:44,800 --> 00:00:45,879
Speaker 2: Oh it is.

17
00:00:46,120 --> 00:00:50,240
Speaker 1: It is completely devastating when they lose. That's and honestly

18
00:00:50,320 --> 00:00:52,479
Speaker 1: it's been it's been really tough with there's been this

19
00:00:52,560 --> 00:00:56,320
Speaker 1: three week campaign of there's no worse country than Argentina.

20
00:00:56,360 --> 00:01:00,520
Speaker 1: Now Argentina is the most racist. Argentina is both Nazi

21
00:01:00,840 --> 00:01:03,960
Speaker 1: and in bed with BBS like anything that can be

22
00:01:04,000 --> 00:01:06,480
Speaker 1: thrown at it. And that part is really a bummer

23
00:01:06,680 --> 00:01:11,440
Speaker 1: because Argentina does not get attention for anything globally usually,

24
00:01:11,840 --> 00:01:16,440
Speaker 1: and it's like Milas friends with Trump and Argentinians are

25
00:01:16,440 --> 00:01:19,560
Speaker 1: horrible people. So you had a horrible week. Was you

26
00:01:19,600 --> 00:01:21,000
Speaker 1: had to suffer through all of that?

27
00:01:21,240 --> 00:01:25,679
Speaker 3: Yeah, yeah, and sit there and watch MESSI as he's

28
00:01:25,720 --> 00:01:28,560
Speaker 3: just absorbing and sobbing.

29
00:01:29,160 --> 00:01:30,680
Speaker 1: At least we didn't lose to England.

30
00:01:30,840 --> 00:01:32,000
Speaker 2: Is the takeaway is.

31
00:01:31,920 --> 00:01:34,720
Speaker 1: That it well historically because that's a big matchup in rivalry.

32
00:01:34,800 --> 00:01:37,800
Speaker 3: But you're still agree with them putting out those you know,

33
00:01:37,800 --> 00:01:40,240
Speaker 3: I mean just the flags and everything.

34
00:01:40,800 --> 00:01:45,240
Speaker 1: I am not into how politicized it was, and I

35
00:01:45,280 --> 00:01:47,920
Speaker 1: think it was also a little hypocritical. Like, as an example,

36
00:01:48,520 --> 00:01:53,720
Speaker 1: just to point out one hypocrisy, we're against colonizers, and

37
00:01:53,760 --> 00:01:56,880
Speaker 1: we're against colonizers, and we're rooting for Spain against Argentina,

38
00:01:57,040 --> 00:01:59,720
Speaker 1: the colonizer of Argentina. Like that doesn't make a.

39
00:01:59,680 --> 00:02:01,600
Speaker 3: Lot of sen Wow, So you really are you know

40
00:02:01,720 --> 00:02:05,160
Speaker 3: you this is nature nurture. Yeah, you're defending your home

41
00:02:05,200 --> 00:02:06,280
Speaker 3: country back in the day.

42
00:02:06,680 --> 00:02:08,679
Speaker 1: I respect that man, but also I defended that the

43
00:02:08,800 --> 00:02:11,400
Speaker 1: United States would have been much better off winning without

44
00:02:11,720 --> 00:02:14,440
Speaker 1: Trump's intervention if they could have done it and just

45
00:02:14,480 --> 00:02:15,200
Speaker 1: devalues it.

46
00:02:15,360 --> 00:02:17,280
Speaker 3: But you thought it was I mean, you liked seeing

47
00:02:17,280 --> 00:02:19,720
Speaker 3: Trump there at the celebration, right when it's nice to

48
00:02:19,760 --> 00:02:21,760
Speaker 3: see that our president didn't make you proud.

49
00:02:21,919 --> 00:02:24,519
Speaker 1: I liked that. Here's the what I loved about the

50
00:02:24,520 --> 00:02:29,679
Speaker 1: Spanish players is they didn't give whatever about Trump being there,

51
00:02:29,840 --> 00:02:31,919
Speaker 1: and they were doing their celebration and they were looking

52
00:02:31,960 --> 00:02:33,679
Speaker 1: at him like, who's this guy, what's he doing here?

53
00:02:33,720 --> 00:02:36,400
Speaker 1: And then they cropped him out of the celebration of pictures,

54
00:02:36,400 --> 00:02:37,160
Speaker 1: which is beautiful.

55
00:02:37,200 --> 00:02:40,520
Speaker 3: I mean even FIFA cropped him out, which is Jesus.

56
00:02:40,560 --> 00:02:41,919
Speaker 2: I mean that was I mean.

57
00:02:42,040 --> 00:02:46,200
Speaker 3: And the Spain actually like literally didn't even crop them out.

58
00:02:46,440 --> 00:02:49,960
Speaker 1: They literally ai eliminated. Yeah, yeah, yeah photo. How could

59
00:02:49,960 --> 00:02:51,880
Speaker 1: you do that to the winner of the FIFA Peace Prize.

60
00:02:51,919 --> 00:02:55,480
Speaker 3: You know, I appreciate your sensitivity, so you're always looking

61
00:02:55,480 --> 00:02:57,880
Speaker 3: in the world from a different set of eyes. I respect,

62
00:02:57,880 --> 00:03:00,360
Speaker 3: but so just you know, by the way, I just

63
00:03:00,639 --> 00:03:04,200
Speaker 3: to rub it in a little bit further, my son

64
00:03:04,520 --> 00:03:05,119
Speaker 3: was sitting there.

65
00:03:05,240 --> 00:03:06,040
Speaker 2: He's ten years old.

66
00:03:06,120 --> 00:03:08,639
Speaker 3: It's the sweetest I can only if he felt this way,

67
00:03:08,639 --> 00:03:11,680
Speaker 3: I can't even imagine how are the ar design fans felt.

68
00:03:11,680 --> 00:03:15,320
Speaker 3: But I mean, he started sobbing after they lost, and

69
00:03:15,800 --> 00:03:18,400
Speaker 3: his sisters were making fun of her, and then everyone

70
00:03:18,440 --> 00:03:21,200
Speaker 3: realized how serious it was. It was like twenty minutes

71
00:03:21,680 --> 00:03:24,560
Speaker 3: of just intense, emotional you know.

72
00:03:24,560 --> 00:03:27,240
Speaker 2: Just release. Yeah, so you know it is a big

73
00:03:27,480 --> 00:03:28,000
Speaker 2: it's a big thing.

74
00:03:28,040 --> 00:03:30,480
Speaker 1: And what's interesting about that is my oldest daughter is four,

75
00:03:30,800 --> 00:03:33,080
Speaker 1: and she was asking when can we get back to

76
00:03:33,080 --> 00:03:36,280
Speaker 1: paw Patrol? But we watched with some slightly older kids

77
00:03:36,320 --> 00:03:38,600
Speaker 1: who were crying, and it was it was tough. It

78
00:03:38,640 --> 00:03:39,440
Speaker 1: was tough to see that.

79
00:03:39,840 --> 00:03:41,920
Speaker 3: So when did you know that you could make a

80
00:03:42,000 --> 00:03:45,400
Speaker 3: career out of, you know, using your voice.

81
00:03:45,440 --> 00:03:48,040
Speaker 1: It's an interesting question. I mean, the first five years

82
00:03:48,040 --> 00:03:50,440
Speaker 1: of this show it made zero. And I don't mean

83
00:03:50,520 --> 00:03:52,640
Speaker 1: like it didn't make a lot of money. It made

84
00:03:52,760 --> 00:03:55,760
Speaker 1: z There was just no revenue. And so I think like,

85
00:03:56,000 --> 00:03:59,040
Speaker 1: in some sense, getting from zero dollars to one dollar

86
00:03:59,400 --> 00:04:02,080
Speaker 1: is the spot where it's like, okay, it can make

87
00:04:02,120 --> 00:04:05,480
Speaker 1: a dollar. Can this be something? And so I think

88
00:04:05,520 --> 00:04:07,840
Speaker 1: that was that was a big deal. And then when

89
00:04:07,840 --> 00:04:10,920
Speaker 1: I hired my first real employee and was able to say, Okay,

90
00:04:10,920 --> 00:04:13,760
Speaker 1: now this is now a business, I think that was

91
00:04:13,880 --> 00:04:16,040
Speaker 1: that was probably the beginning of thinking there might be

92
00:04:16,040 --> 00:04:17,840
Speaker 1: something to this. And I was in grad school at

93
00:04:17,839 --> 00:04:20,960
Speaker 1: the time doing an MBA, and my friends were becoming

94
00:04:21,000 --> 00:04:25,400
Speaker 1: financial advisors and bankers and going into private equity, which

95
00:04:25,520 --> 00:04:28,880
Speaker 1: seemed very cushy and lucrative in the immediate but the

96
00:04:28,960 --> 00:04:31,120
Speaker 1: long term of that just didn't appeal to me. So

97
00:04:31,160 --> 00:04:33,120
Speaker 1: I said, I'll give myself a year to really see

98
00:04:33,120 --> 00:04:33,760
Speaker 1: if this can become.

99
00:04:33,960 --> 00:04:35,880
Speaker 3: And was it always I mean, was it a political

100
00:04:35,960 --> 00:04:39,080
Speaker 3: show from the outset? Yes, And it was commenting about

101
00:04:39,200 --> 00:04:44,640
Speaker 3: local city council. It was always commission, always national interesting,

102
00:04:44,720 --> 00:04:46,120
Speaker 3: pake the picture twenty one years ago?

103
00:04:46,160 --> 00:04:46,960
Speaker 2: What were the big issues?

104
00:04:47,000 --> 00:04:50,400
Speaker 1: You remember, well, twenty one years ago. It was in

105
00:04:50,440 --> 00:04:55,080
Speaker 1: the immediate pre Obama era, so it was the Iraq War.

106
00:04:56,560 --> 00:04:58,920
Speaker 1: It was what is it going to look like when

107
00:04:58,920 --> 00:05:01,800
Speaker 1: George W. Bush has done the second term? What is

108
00:05:01,839 --> 00:05:04,120
Speaker 1: the direction Republicans are going to go? This was pre

109
00:05:04,240 --> 00:05:06,760
Speaker 1: Tea Party. I mean, this is it's like almost ancient

110
00:05:06,839 --> 00:05:09,159
Speaker 1: history to people who are now twenty five and voted

111
00:05:09,200 --> 00:05:10,039
Speaker 1: for the first same time.

112
00:05:10,040 --> 00:05:12,000
Speaker 3: It has a lot of echoes of today right on

113
00:05:12,080 --> 00:05:14,440
Speaker 3: the other side, not the Tea Party but DSA for

114
00:05:14,480 --> 00:05:15,160
Speaker 3: the Democrats.

115
00:05:15,200 --> 00:05:17,520
Speaker 1: Democrats in the wilderness. What happens of the second term?

116
00:05:17,680 --> 00:05:19,760
Speaker 2: Oh boy, we're going into it.

117
00:05:19,800 --> 00:05:23,159
Speaker 1: I did a commentary that's on my show today which

118
00:05:23,400 --> 00:05:26,000
Speaker 1: is making this exact analogy, which is there was a

119
00:05:26,040 --> 00:05:28,840
Speaker 1: time before Trump, in the Tea Party era, where the

120
00:05:28,960 --> 00:05:32,200
Speaker 1: establishment Republican Party kind of said, these people are never

121
00:05:32,240 --> 00:05:34,240
Speaker 1: going to influence the party, they're never going to guide

122
00:05:34,279 --> 00:05:37,320
Speaker 1: the direction. And the Tea Party really led to MAGA

123
00:05:37,360 --> 00:05:40,640
Speaker 1: and to trump Ism, and I you know, I've been

124
00:05:40,680 --> 00:05:43,880
Speaker 1: critical of the kind of what I call do nothing centrism,

125
00:05:43,960 --> 00:05:45,719
Speaker 1: which is like, let's find a couple things on the

126
00:05:45,720 --> 00:05:48,320
Speaker 1: fringes to say we will do and end up doing nothing.

127
00:05:48,360 --> 00:05:50,640
Speaker 1: I don't think that's good for the Democratic Party. But

128
00:05:50,800 --> 00:05:53,080
Speaker 1: also what I'm seeing I was just looking at the

129
00:05:53,120 --> 00:05:58,720
Speaker 1: DSA platform, which it has moral motivations that I respect,

130
00:05:59,320 --> 00:06:02,400
Speaker 1: but a lot of completely unrealistic stuff that if it

131
00:06:02,440 --> 00:06:05,920
Speaker 1: becomes litmus test worthy, is going to be a real

132
00:06:05,960 --> 00:06:09,440
Speaker 1: problem for Democrats. And so I don't know when the

133
00:06:09,520 --> 00:06:11,680
Speaker 1: right time is to have that conversation. I tend to

134
00:06:11,680 --> 00:06:14,120
Speaker 1: think it's as soon as you realize something's up, it's

135
00:06:14,160 --> 00:06:16,000
Speaker 1: a good time to do it. Without saying, well, if

136
00:06:16,040 --> 00:06:18,159
Speaker 1: we talk about it now, how will it affect the midterms?

137
00:06:18,160 --> 00:06:19,919
Speaker 1: I think now is when it has to be talked about.

138
00:06:21,000 --> 00:06:23,560
Speaker 1: I think social democracy is the path forward, which is

139
00:06:23,560 --> 00:06:25,159
Speaker 1: a sort of Northern European.

140
00:06:24,760 --> 00:06:29,080
Speaker 2: Model, so we can go I'm going to get back

141
00:06:29,120 --> 00:06:29,640
Speaker 2: to the DSA.

142
00:06:29,640 --> 00:06:31,360
Speaker 3: It's interesting and we could talk some of those lipman

143
00:06:31,440 --> 00:06:33,640
Speaker 3: test issues because I think they're important to illuminate because

144
00:06:33,640 --> 00:06:36,800
Speaker 3: not everybody is familiar right with some of those platform

145
00:06:36,920 --> 00:06:38,919
Speaker 3: issues as it relates to private prisons. A number of

146
00:06:38,920 --> 00:06:41,719
Speaker 3: issues that do deserve a little bit more attention beyond

147
00:06:41,720 --> 00:06:45,000
Speaker 3: the tonality of sort of this anti establishment and this

148
00:06:45,120 --> 00:06:49,479
Speaker 3: desire to see more aggressive and clear leadership, etc. But

149
00:06:50,120 --> 00:06:52,359
Speaker 3: let's jump into your book because what you've been writing

150
00:06:52,400 --> 00:06:54,320
Speaker 3: books for some time now. You've been at this and

151
00:06:54,320 --> 00:06:55,840
Speaker 3: I think is I wanted to paint a picture you've

152
00:06:55,839 --> 00:06:58,599
Speaker 3: been also at this art form of sorts for twenty

153
00:06:58,640 --> 00:07:00,960
Speaker 3: one years. Because so you don't come to this issue

154
00:07:01,080 --> 00:07:03,760
Speaker 3: that you bring in highlight in the book from a

155
00:07:03,839 --> 00:07:06,400
Speaker 3: perspective as an outsider. I mean you've lived and breathed

156
00:07:06,440 --> 00:07:09,960
Speaker 3: this in a pretty profound, bottom up way. You've been

157
00:07:10,000 --> 00:07:12,640
Speaker 3: at this as well writing books for some time. You

158
00:07:12,680 --> 00:07:14,520
Speaker 3: wrote a book in twenty twenty five about the right

159
00:07:14,600 --> 00:07:17,320
Speaker 3: wing and the echo chambers. You've written a lot of

160
00:07:17,360 --> 00:07:22,640
Speaker 3: children's books, which is interesting. You mentioned your child's pap

161
00:07:22,640 --> 00:07:26,560
Speaker 3: patrol affinity which I respect. But you've also written a

162
00:07:26,600 --> 00:07:30,000
Speaker 3: number of children's book but this one pay attention how

163
00:07:30,000 --> 00:07:33,560
Speaker 3: the algorithms and the media wars are suppressing truth and

164
00:07:33,920 --> 00:07:38,120
Speaker 3: re wiring our brain. Is Your latest work is available

165
00:07:38,320 --> 00:07:40,760
Speaker 3: in September. So I love that we had a chance

166
00:07:41,240 --> 00:07:43,480
Speaker 3: to talk about the book before it's even out there,

167
00:07:43,840 --> 00:07:48,000
Speaker 3: and full disclosure, read it, love it, and I really

168
00:07:48,040 --> 00:07:50,800
Speaker 3: want to dive deep into it because we've talked so much.

169
00:07:50,920 --> 00:07:54,760
Speaker 3: All of us say we collectively talk about this issue,

170
00:07:54,800 --> 00:07:57,920
Speaker 3: and around this issue, we understand aspects of it, tenants

171
00:07:57,920 --> 00:08:00,680
Speaker 3: of it, trend lines of it, but not I think

172
00:08:00,960 --> 00:08:07,640
Speaker 3: how pervasive and profound the issue is around algorithms, around

173
00:08:07,720 --> 00:08:10,760
Speaker 3: what media is all about. And so let's talk a

174
00:08:10,800 --> 00:08:14,080
Speaker 3: little bit about this book and start with the obvious,

175
00:08:14,120 --> 00:08:15,920
Speaker 3: and that is you start in the prologue about this

176
00:08:16,080 --> 00:08:21,680
Speaker 3: arms race, and you're the first to acknowledge you're participating

177
00:08:22,080 --> 00:08:26,160
Speaker 3: in this arms race, right, And so you, sir David,

178
00:08:26,760 --> 00:08:28,080
Speaker 3: are you not the problem?

179
00:08:28,480 --> 00:08:31,920
Speaker 1: Well, listen, I think everybody is in a sense contributing

180
00:08:31,960 --> 00:08:34,400
Speaker 1: to this. And also I think the best thing we

181
00:08:34,440 --> 00:08:37,199
Speaker 1: can do is identify the systems that are at play

182
00:08:37,600 --> 00:08:39,680
Speaker 1: and then figure out what are our choices one choice

183
00:08:39,760 --> 00:08:42,080
Speaker 1: is we just kind of abandon it. If we abandon it,

184
00:08:42,160 --> 00:08:46,840
Speaker 1: we seed ground to those with terrible ideas to completely dominate.

185
00:08:46,920 --> 00:08:49,600
Speaker 1: I don't think that's a good idea. The second option

186
00:08:49,760 --> 00:08:52,120
Speaker 1: is we figure out how to play the game while

187
00:08:52,200 --> 00:08:57,439
Speaker 1: not kind of losing our soul to deception, lies, and misinformation.

188
00:08:58,120 --> 00:09:00,360
Speaker 1: That's where I kind of tend to land, which is

189
00:09:00,520 --> 00:09:04,480
Speaker 1: we could ignore these platforms and algorithms, but then the

190
00:09:04,520 --> 00:09:08,000
Speaker 1: worst people just take them over, right, And I don't

191
00:09:08,000 --> 00:09:10,800
Speaker 1: think that that makes sense if we understand that these

192
00:09:10,840 --> 00:09:14,400
Speaker 1: algorithms are determining elections to a great degree. The elections

193
00:09:14,440 --> 00:09:18,080
Speaker 1: determine who gets power. Who has power determines policy. So

194
00:09:18,120 --> 00:09:19,800
Speaker 1: when I talk to people who go, yeah, I spend

195
00:09:19,840 --> 00:09:21,480
Speaker 1: a lot of time on social media, but I'm not

196
00:09:21,559 --> 00:09:24,760
Speaker 1: into politics. I don't vote. I talk to them about

197
00:09:24,800 --> 00:09:27,800
Speaker 1: what do you care about? Almost always they will list

198
00:09:27,920 --> 00:09:31,560
Speaker 1: issues things affecting them that relate to who is in power,

199
00:09:32,120 --> 00:09:34,720
Speaker 1: and then we can explain, well, you know, you should

200
00:09:34,760 --> 00:09:37,120
Speaker 1: be engaged in that because the fact that you don't

201
00:09:37,120 --> 00:09:39,560
Speaker 1: care about politics, you're just struggling to make a living.

202
00:09:39,920 --> 00:09:43,960
Speaker 1: That's housing, affordability, groceries, energy prices, and jobs. All of

203
00:09:43,960 --> 00:09:47,160
Speaker 1: that stuff is determined by municipal, state, and federal elections

204
00:09:47,200 --> 00:09:49,160
Speaker 1: and who you vote for, and then it sort of

205
00:09:49,200 --> 00:09:52,559
Speaker 1: starts to click once we get there. It's okay, why

206
00:09:52,600 --> 00:09:55,160
Speaker 1: are you hearing about what you're hearing about and someone

207
00:09:55,160 --> 00:09:58,240
Speaker 1: else is hearing about something totally different. It's these algorithms,

208
00:09:58,240 --> 00:10:01,560
Speaker 1: it's these platforms, and so the the big why why now?

209
00:10:01,600 --> 00:10:02,280
Speaker 2: Why this book?

210
00:10:02,280 --> 00:10:04,160
Speaker 3: I mean, I mean it's I mean, in some ways

211
00:10:04,559 --> 00:10:08,560
Speaker 3: what you just stated is a partial response. But why

212
00:10:08,640 --> 00:10:11,880
Speaker 3: the big call out? I mean, pay attention, you know,

213
00:10:11,920 --> 00:10:13,960
Speaker 3: it's an expressive frame.

214
00:10:15,160 --> 00:10:17,360
Speaker 2: Wake up? Yeah, maybe another.

215
00:10:17,960 --> 00:10:21,079
Speaker 1: It's two things. It's one. At this point, the elections

216
00:10:21,160 --> 00:10:24,040
Speaker 1: more than ever being affected by these platforms, and twenty

217
00:10:24,080 --> 00:10:27,440
Speaker 1: twenty eight probably more than any before that is going

218
00:10:27,480 --> 00:10:30,479
Speaker 1: to be highly determined by the narratives that these algorithms

219
00:10:31,080 --> 00:10:33,480
Speaker 1: determine are the most emotionally salient and put in front

220
00:10:33,480 --> 00:10:35,880
Speaker 1: of people. That's number one, and number two because of

221
00:10:35,720 --> 00:10:38,240
Speaker 1: the AI aspect of it. The whole last part of

222
00:10:38,280 --> 00:10:40,480
Speaker 1: the book is about how AI will change this. The

223
00:10:40,559 --> 00:10:46,960
Speaker 1: technology is essentially there to create synthetic influencers. I have

224
00:10:47,040 --> 00:10:48,560
Speaker 1: to sit in front of a camera and if I

225
00:10:48,559 --> 00:10:50,600
Speaker 1: want to do an hour of content. I've got to

226
00:10:50,640 --> 00:10:54,720
Speaker 1: record an hour of video. With technology, you can dial

227
00:10:54,800 --> 00:10:57,320
Speaker 1: up a thousand of me. Some might be male, some

228
00:10:57,440 --> 00:11:01,360
Speaker 1: might be female, different identities, whatever will appeal most directly

229
00:11:01,400 --> 00:11:04,280
Speaker 1: to people and spin them up with nothing other than

230
00:11:04,320 --> 00:11:08,439
Speaker 1: compute power and the thousand X what I'm doing tailored

231
00:11:08,520 --> 00:11:11,839
Speaker 1: to the algorithms of people. It's sixty seventy percent of

232
00:11:11,880 --> 00:11:15,080
Speaker 1: the way there. As we're recording this very very dangerous

233
00:11:15,360 --> 00:11:16,959
Speaker 1: and you've run your own experience.

234
00:11:17,000 --> 00:11:18,320
Speaker 3: We'll get to that and you write about it in

235
00:11:18,360 --> 00:11:22,280
Speaker 3: the book, but you start the introduction begins with AI

236
00:11:22,440 --> 00:11:25,480
Speaker 3: in some respects, and it's that sort of iconic image

237
00:11:25,480 --> 00:11:28,280
Speaker 3: of Donald Trump with the walker, and you make the

238
00:11:28,320 --> 00:11:30,480
Speaker 3: point that he did this right after he went after

239
00:11:30,520 --> 00:11:33,880
Speaker 3: states like California. California being the first state in the

240
00:11:33,920 --> 00:11:36,600
Speaker 3: country to go after large language model, frontier models and

241
00:11:36,679 --> 00:11:40,880
Speaker 3: do transparency language legislation as it relates to regulating AI.

242
00:11:41,240 --> 00:11:44,280
Speaker 3: He didn't like that. David Sachs's ais are didn't like that.

243
00:11:44,559 --> 00:11:47,120
Speaker 3: They tried to preempt the state of California and stop

244
00:11:47,200 --> 00:11:51,040
Speaker 3: other states. All the while we saw a viral video

245
00:11:51,160 --> 00:11:52,840
Speaker 3: of Donald Trump in a walker.

246
00:11:53,320 --> 00:11:55,360
Speaker 1: That's right, and the point I make in the book

247
00:11:55,600 --> 00:11:58,600
Speaker 1: is that by the time it was determined that this

248
00:11:58,679 --> 00:12:01,559
Speaker 1: image of Trump with the Walker isn't real, it kind

249
00:12:01,559 --> 00:12:05,640
Speaker 1: of didn't matter because it accomplished a bunch of different

250
00:12:05,679 --> 00:12:08,679
Speaker 1: things for different people. It's not all positive for not

251
00:12:08,960 --> 00:12:11,840
Speaker 1: all positive or negative for Donald Trump. But the point was,

252
00:12:11,920 --> 00:12:14,200
Speaker 1: and it kind of returns at the end of the

253
00:12:14,200 --> 00:12:17,160
Speaker 1: book when we talk about the coming AI flood. What's

254
00:12:17,200 --> 00:12:19,920
Speaker 1: going to matter is the emotional reaction that this stuff

255
00:12:19,960 --> 00:12:23,160
Speaker 1: triggers in people. The truth of it is almost irrelevant.

256
00:12:23,440 --> 00:12:26,520
Speaker 1: And I even talk about talking with creators who have

257
00:12:26,640 --> 00:12:30,920
Speaker 1: published accidentally as far as I know AI stuff, and

258
00:12:30,960 --> 00:12:33,840
Speaker 1: I've said to them, listen, you know that that actually

259
00:12:33,880 --> 00:12:35,600
Speaker 1: wasn't real, Like I know, it was an honest mistake.

260
00:12:35,640 --> 00:12:38,320
Speaker 1: That wasn't real, and they go, yeah, but it worked.

261
00:12:38,440 --> 00:12:40,880
Speaker 1: It got clicks, it got views, And whether I agree

262
00:12:40,880 --> 00:12:42,640
Speaker 1: with the message or not, I think that is dangerous.

263
00:12:43,160 --> 00:12:44,960
Speaker 3: And that goes to the beginning of the book. I mean,

264
00:12:45,000 --> 00:12:48,160
Speaker 3: you open a chapter one. It's about attention. I mean, period,

265
00:12:48,200 --> 00:12:48,760
Speaker 3: full stop.

266
00:12:48,920 --> 00:12:51,440
Speaker 1: Yeah, there's the idea I think a lot of people

267
00:12:51,559 --> 00:12:54,840
Speaker 1: have that the likes and how much time you spend

268
00:12:54,880 --> 00:12:58,520
Speaker 1: on stuff on these platforms will naturally surface. What's true

269
00:12:58,520 --> 00:13:00,719
Speaker 1: and what's right, and that is not the way these

270
00:13:00,720 --> 00:13:03,800
Speaker 1: platforms are designed. And sometimes I think when we attribute

271
00:13:03,800 --> 00:13:06,360
Speaker 1: political bias to like people want to talk about, what

272
00:13:06,400 --> 00:13:11,240
Speaker 1: are Mark Zuckerberg's personal politics, for example, interesting question, that's

273
00:13:11,280 --> 00:13:13,800
Speaker 1: not really what determines what does well on Facebook. What

274
00:13:13,920 --> 00:13:17,360
Speaker 1: does well on Facebook is what starts to spread quickly.

275
00:13:17,720 --> 00:13:20,000
Speaker 1: And you can think about I mean, forget about truth

276
00:13:20,040 --> 00:13:23,120
Speaker 1: for a second. Just to think about vaccines, the COVID vaccine,

277
00:13:23,160 --> 00:13:26,600
Speaker 1: for example, if there's two competing claims. One is these

278
00:13:26,679 --> 00:13:30,600
Speaker 1: vaccines are killing millions of people and the government has

279
00:13:30,640 --> 00:13:34,120
Speaker 1: covered it up. That's claim number one. Claim number two is, hey,

280
00:13:34,120 --> 00:13:37,160
Speaker 1: these vaccines are really safe. Not as effective at preventing

281
00:13:37,160 --> 00:13:39,360
Speaker 1: the spread of COVID as we had hoped, pretty good

282
00:13:39,360 --> 00:13:41,800
Speaker 1: at keeping you out of the hospital, or which one

283
00:13:41,880 --> 00:13:44,120
Speaker 1: forget about what's true? Which one is going to get

284
00:13:44,120 --> 00:13:47,240
Speaker 1: grandma and a college student and whoever else to like it,

285
00:13:47,280 --> 00:13:50,880
Speaker 1: comment and share it. Of course, it's the emotionally salient one.

286
00:13:51,080 --> 00:13:53,079
Speaker 1: That's what these platforms are optimized for.

287
00:13:53,679 --> 00:13:54,880
Speaker 2: So that goes to.

288
00:13:54,760 --> 00:13:58,400
Speaker 3: This, you know, and then as the book goes on,

289
00:13:58,480 --> 00:14:00,360
Speaker 3: in the next chapter, you talk about you we used

290
00:14:00,360 --> 00:14:02,240
Speaker 3: to have editors, We used to be able to actually,

291
00:14:03,200 --> 00:14:05,800
Speaker 3: we'd fix that by making sure we fix to some

292
00:14:05,960 --> 00:14:08,880
Speaker 3: north star of truth so we can build trust.

293
00:14:09,200 --> 00:14:13,440
Speaker 1: Now no longer that's the case right there. There are

294
00:14:13,480 --> 00:14:16,600
Speaker 1: a lot of really interesting books I read in writing this, including,

295
00:14:16,640 --> 00:14:19,920
Speaker 1: for example, about the New York Times investigation into Harvey

296
00:14:19,920 --> 00:14:23,320
Speaker 1: Weinstein and one of the things that comes up, or

297
00:14:23,480 --> 00:14:25,920
Speaker 1: Ronan Pharaoh's book about the same topic. A lot of

298
00:14:25,960 --> 00:14:29,080
Speaker 1: these investigative journals and books, and they all tell stories

299
00:14:29,240 --> 00:14:33,400
Speaker 1: of editors and executives and all of these layers that

300
00:14:33,600 --> 00:14:37,000
Speaker 1: have different incentives to slow down a lot of these investigations,

301
00:14:37,040 --> 00:14:39,320
Speaker 1: and then you find out there's personal stuff at play,

302
00:14:39,360 --> 00:14:42,080
Speaker 1: and there's financial incentives, all these different things. That's a

303
00:14:42,200 --> 00:14:45,880
Speaker 1: problem with that legacy system. One of the great things

304
00:14:45,880 --> 00:14:48,760
Speaker 1: about the digital platforms is you kind of get around that,

305
00:14:48,880 --> 00:14:52,280
Speaker 1: or you eliminate that. The other problem with it is

306
00:14:52,320 --> 00:14:55,760
Speaker 1: that with no fact checking and with no layers of

307
00:14:55,840 --> 00:14:59,080
Speaker 1: let's make sure we feel good about this, stuff will

308
00:14:59,080 --> 00:15:03,480
Speaker 1: go ultra viral simply because it's emotionally salient. So I

309
00:15:03,520 --> 00:15:07,040
Speaker 1: don't tell this the book is not about bad legacy media.

310
00:15:07,960 --> 00:15:11,200
Speaker 1: There's pros and cons to these systems. The democratization of

311
00:15:11,320 --> 00:15:14,560
Speaker 1: the news and politics space has been phenomenal. On the

312
00:15:14,640 --> 00:15:17,280
Speaker 1: other hand, we also have this problem of truth versus

313
00:15:17,360 --> 00:15:19,480
Speaker 1: virality to contend with in you till.

314
00:15:19,360 --> 00:15:21,440
Speaker 3: I mean, it's interesting you frame, and I think it's

315
00:15:21,480 --> 00:15:24,880
Speaker 3: important we talk about censorship. It's been talked about obviously,

316
00:15:24,960 --> 00:15:28,080
Speaker 3: Trump talked and nauseum about censorship. But your issue is,

317
00:15:28,120 --> 00:15:30,840
Speaker 3: and I think you just hit on it, is abundance.

318
00:15:31,200 --> 00:15:32,400
Speaker 1: This is overwhelming.

319
00:15:33,520 --> 00:15:36,360
Speaker 3: I mean, just the narratives coming from every single direction.

320
00:15:36,840 --> 00:15:39,320
Speaker 3: How you sess out that truth from trust that's right?

321
00:15:39,360 --> 00:15:41,720
Speaker 1: And not only that, not everybody is given all of

322
00:15:41,760 --> 00:15:44,480
Speaker 1: the same material from which they can then say, here's

323
00:15:44,520 --> 00:15:47,400
Speaker 1: the side I come down on. Based on your interests

324
00:15:47,440 --> 00:15:51,600
Speaker 1: and online behavior, you and I and everybody else can

325
00:15:51,640 --> 00:15:54,320
Speaker 1: have a completely different sense of what's going.

326
00:15:54,080 --> 00:15:55,320
Speaker 2: On out in the world.

327
00:15:55,640 --> 00:15:59,400
Speaker 1: A great example is with the Trump medical stuff that

328
00:15:59,480 --> 00:16:01,600
Speaker 1: was you know, when he went for his third physical

329
00:16:01,600 --> 00:16:06,120
Speaker 1: in thirteen months. There were two completely competing narratives. There

330
00:16:06,200 --> 00:16:08,960
Speaker 1: was one side of the space that was saying, the

331
00:16:09,000 --> 00:16:14,000
Speaker 1: disclosures have never been fulsome and complete. There are inconsistencies here.

332
00:16:14,120 --> 00:16:16,600
Speaker 1: We don't believe the height and weight that's on these documents.

333
00:16:16,640 --> 00:16:19,120
Speaker 1: There's stuff missing. He talked about an MRI for two months.

334
00:16:19,120 --> 00:16:21,480
Speaker 1: It turns out it was a cat scan. That's one side.

335
00:16:21,880 --> 00:16:24,120
Speaker 1: There are millions of people who vote who were not

336
00:16:24,160 --> 00:16:26,920
Speaker 1: even exposed to that. It wasn't that they said, oh

337
00:16:27,000 --> 00:16:29,000
Speaker 1: I don't believe that, or I don't like that. Their

338
00:16:29,040 --> 00:16:31,560
Speaker 1: algorithms don't even show them that content. They don't even

339
00:16:31,600 --> 00:16:33,960
Speaker 1: get the opportunity to say, do I want to examine

340
00:16:34,000 --> 00:16:37,360
Speaker 1: this critically? How do you fix that? That's a major problem.

341
00:16:37,400 --> 00:16:39,760
Speaker 3: And you make that point in the book that the

342
00:16:39,800 --> 00:16:42,960
Speaker 3: algorithm then becomes the boss. That's right, and I mean

343
00:16:43,040 --> 00:16:46,520
Speaker 3: it's and I mean to me, there's nothing. It explains

344
00:16:46,560 --> 00:16:49,520
Speaker 3: so many things in so many ways of our interactions

345
00:16:49,560 --> 00:16:51,160
Speaker 3: we have when you know, fill in the blank with

346
00:16:51,240 --> 00:16:53,960
Speaker 3: you know, uncle Joe or something at the Thanksgiving dinner

347
00:16:53,960 --> 00:16:56,600
Speaker 3: table and you're like, what the hell's happened uncle Joe? Yep,

348
00:16:56,800 --> 00:16:58,840
Speaker 3: And in many respects, it's completely understandable.

349
00:16:58,880 --> 00:16:59,600
Speaker 2: What's happened to him?

350
00:16:59,680 --> 00:17:04,159
Speaker 3: Yeah, he's sincere about his beliefs because he doesn't see Yeah,

351
00:17:04,240 --> 00:17:07,359
Speaker 3: the other side and by the way, uh, maybe we don't.

352
00:17:07,880 --> 00:17:08,720
Speaker 2: You don't either.

353
00:17:09,200 --> 00:17:13,639
Speaker 1: No, I advise my audience, if you want to still

354
00:17:13,640 --> 00:17:16,560
Speaker 1: be informed and still sort of participate in the space

355
00:17:16,600 --> 00:17:18,480
Speaker 1: of online news and politics. But you want to kind

356
00:17:18,480 --> 00:17:21,439
Speaker 1: of take control back a little bit. One of the

357
00:17:21,440 --> 00:17:25,399
Speaker 1: things you can do is seek out audio podcasts, or

358
00:17:25,440 --> 00:17:27,960
Speaker 1: they might be video as well, but long form podcasts

359
00:17:28,400 --> 00:17:31,119
Speaker 1: that you have identified as these are good faith people

360
00:17:31,200 --> 00:17:34,720
Speaker 1: trying to explore what is really true. Podcasts are not

361
00:17:34,960 --> 00:17:39,280
Speaker 1: really in this algorithmic space. Yet people mostly find podcasts

362
00:17:39,320 --> 00:17:41,360
Speaker 1: not because of swipeing and how long and where they're

363
00:17:41,359 --> 00:17:43,680
Speaker 1: looking and that sort of thing. They're finding them through

364
00:17:43,760 --> 00:17:47,800
Speaker 1: interpersonal recommendations, hearing about them on other podcasts, et cetera.

365
00:17:47,920 --> 00:17:50,439
Speaker 1: So I still think long form podcasts are one of

366
00:17:50,440 --> 00:17:52,520
Speaker 1: the best spots to kind of exits.

367
00:17:52,680 --> 00:17:56,320
Speaker 2: I mean, most of the podcasts you find through viral clips.

368
00:17:55,920 --> 00:18:00,280
Speaker 3: Clips, podcasts that are built it's in this very frame

369
00:18:00,320 --> 00:18:01,000
Speaker 3: that we're talking about.

370
00:18:01,040 --> 00:18:03,879
Speaker 1: That's absolutely it's absolutely true. The other thing that I

371
00:18:03,920 --> 00:18:07,199
Speaker 1: think is good is after you've come to identify some

372
00:18:07,320 --> 00:18:10,280
Speaker 1: of these mechanisms, you can have a sort of self

373
00:18:10,400 --> 00:18:13,760
Speaker 1: check thing where you say, Okay, I'm seeing a lot

374
00:18:13,800 --> 00:18:17,000
Speaker 1: of content that is telling me x is that really

375
00:18:17,040 --> 00:18:19,320
Speaker 1: all there is to this? So being aware of the

376
00:18:19,359 --> 00:18:21,560
Speaker 1: fact that this is taking place can be a really

377
00:18:21,600 --> 00:18:24,840
Speaker 1: good kind of inoculation against it, and then you can

378
00:18:24,880 --> 00:18:27,440
Speaker 1: go and say, hey, let's look at some other ideas

379
00:18:27,520 --> 00:18:29,800
Speaker 1: about this. There was a point to go back to

380
00:18:29,800 --> 00:18:33,160
Speaker 1: the COVID vaccine stuff, where your algorithm would basically take

381
00:18:33,240 --> 00:18:37,119
Speaker 1: you to anti Fauci stuff, he's a criminal. Then it

382
00:18:37,160 --> 00:18:40,640
Speaker 1: takes you to some long form podcasters who would invite

383
00:18:41,040 --> 00:18:44,480
Speaker 1: Sometimes they were medical doctors, sometimes they had PhDs, but

384
00:18:44,520 --> 00:18:46,480
Speaker 1: they were sort of presented as if they were experts

385
00:18:46,480 --> 00:18:49,840
Speaker 1: in medicine, and you would go down this very dark path.

386
00:18:50,400 --> 00:18:52,600
Speaker 1: At some point you could have said, if you had

387
00:18:52,640 --> 00:18:55,280
Speaker 1: been armed with the knowledge that you're being taken down

388
00:18:55,320 --> 00:18:58,400
Speaker 1: this garden path, I'm going to now go back and say,

389
00:18:58,520 --> 00:19:00,960
Speaker 1: let's look at some randomized controlled try let's look at

390
00:19:01,000 --> 00:19:04,040
Speaker 1: what the people at actual medical institutions are saying. So

391
00:19:04,119 --> 00:19:06,960
Speaker 1: the point is knowing that you are pushed, push, pushed

392
00:19:06,960 --> 00:19:09,560
Speaker 1: further and further is a really good starting point to

393
00:19:09,560 --> 00:19:11,359
Speaker 1: say I'm going to go and seek out something else.

394
00:19:11,480 --> 00:19:13,560
Speaker 1: A lot of times this is really innocent. I tell

395
00:19:13,600 --> 00:19:16,280
Speaker 1: the story in the Book of For example, it could

396
00:19:16,320 --> 00:19:20,120
Speaker 1: be people looking for workout content or parenting advice. These

397
00:19:20,119 --> 00:19:23,199
Speaker 1: are like two you'd think parenting advice workout content, These

398
00:19:23,200 --> 00:19:27,320
Speaker 1: are radioactive spaces mom groups on Facebook where you go

399
00:19:27,440 --> 00:19:32,280
Speaker 1: and say, hey, I'm looking for some toys that are whatever,

400
00:19:32,760 --> 00:19:35,119
Speaker 1: And next thing you know, you're being fed stuff about

401
00:19:35,520 --> 00:19:38,119
Speaker 1: alternative parenting techniques. Do you know what they're teaching your

402
00:19:38,200 --> 00:19:40,119
Speaker 1: kids in school? By the way, did you know public

403
00:19:40,119 --> 00:19:43,200
Speaker 1: schools require vaccinations? It takes you through a dark path.

404
00:19:43,240 --> 00:19:45,600
Speaker 1: You just want a toy recommendation. So this is this

405
00:19:45,640 --> 00:19:47,160
Speaker 1: can happen within weeks to people.

406
00:19:47,680 --> 00:19:49,639
Speaker 2: I mean happen. I mean I happened.

407
00:19:49,800 --> 00:19:52,280
Speaker 3: This is the origin story of this podcast in so

408
00:19:52,320 --> 00:19:55,439
Speaker 3: many respects. I mean during COVID suns on is he

409
00:19:55,600 --> 00:19:58,520
Speaker 3: wasn't on any devices that I was aware of. Outside

410
00:19:59,680 --> 00:20:03,760
Speaker 3: is advice that came from school which allowed him to

411
00:20:03,760 --> 00:20:07,480
Speaker 3: access YouTube, And he's checking on fitness, and he's checking

412
00:20:07,520 --> 00:20:09,359
Speaker 3: on you know, some of the things that you know

413
00:20:09,400 --> 00:20:10,920
Speaker 3: a lot of these young boys are into it. And

414
00:20:10,960 --> 00:20:13,200
Speaker 3: all of a sudden, he's talking to me about Andrew Tait. Right,

415
00:20:13,400 --> 00:20:15,680
Speaker 3: Rogan was a passing phase of sorts. It was more

416
00:20:15,760 --> 00:20:19,440
Speaker 3: Charlie Kirk and then different conversations to your point, and

417
00:20:19,680 --> 00:20:21,800
Speaker 3: within it was his entire friend group.

418
00:20:21,920 --> 00:20:23,960
Speaker 2: I mean, and I don't care. There was an experiment

419
00:20:23,960 --> 00:20:24,680
Speaker 2: I read the other.

420
00:20:24,640 --> 00:20:29,600
Speaker 3: Day where they provided tablets for boys around the globe,

421
00:20:29,960 --> 00:20:33,600
Speaker 3: and it was I think within twenty two minutes they

422
00:20:33,640 --> 00:20:36,520
Speaker 3: all had formulated the same construct in terms of the

423
00:20:36,520 --> 00:20:39,760
Speaker 3: algorithms that found them, that sought them out. You're not

424
00:20:40,400 --> 00:20:45,560
Speaker 3: searching for information, they're seeking you out and targeting you

425
00:20:45,600 --> 00:20:47,720
Speaker 3: at a level. So that's I mean, how And this

426
00:20:47,800 --> 00:20:50,480
Speaker 3: is the challenge. And you write about you know, you're

427
00:20:50,480 --> 00:20:53,360
Speaker 3: had a confessional chapter in there about the machine being

428
00:20:53,600 --> 00:20:55,919
Speaker 3: inside the machine, so sort of work us through that.

429
00:20:56,040 --> 00:20:58,720
Speaker 3: What was your own confession in this context? Well, then

430
00:20:58,720 --> 00:21:00,400
Speaker 3: how do we start to work ourselves out out of this?

431
00:21:00,480 --> 00:21:03,760
Speaker 1: I mean, there's no way. Listen, anybody who makes content

432
00:21:04,240 --> 00:21:05,880
Speaker 1: is not doing it for it to be seen by

433
00:21:05,880 --> 00:21:07,040
Speaker 1: as few people as possible.

434
00:21:07,080 --> 00:21:07,840
Speaker 2: That's the challenge.

435
00:21:07,880 --> 00:21:12,240
Speaker 1: You're making it full. Those are the incentive structures. And

436
00:21:12,320 --> 00:21:14,840
Speaker 1: so what I try to be aware of is I'm

437
00:21:14,880 --> 00:21:17,480
Speaker 1: not going to deliberately choose stuff that will bomb and

438
00:21:17,520 --> 00:21:20,600
Speaker 1: that nobody's interested in that. I mean that it seems counterproductive.

439
00:21:21,119 --> 00:21:23,120
Speaker 1: But the way I kind of see it is I'm

440
00:21:23,119 --> 00:21:26,520
Speaker 1: going to package the content as best as my brain

441
00:21:26,600 --> 00:21:30,159
Speaker 1: will let me figure out how to maximize eyeballs while

442
00:21:30,240 --> 00:21:34,080
Speaker 1: being honest so that then I can also give people

443
00:21:34,480 --> 00:21:37,640
Speaker 1: the conversation with the PhD nutritionist I had on last

444
00:21:37,640 --> 00:21:40,720
Speaker 1: week who explains the truth about the Maha stuff and

445
00:21:40,760 --> 00:21:43,119
Speaker 1: the food dies and GMO, And so I'm sort of

446
00:21:43,440 --> 00:21:48,439
Speaker 1: using the techniques to buy myself the bandwidth for the

447
00:21:48,520 --> 00:21:52,160
Speaker 1: audience to then also accept the stuff that's less likely

448
00:21:52,240 --> 00:21:55,440
Speaker 1: to go gigaviral but is valuable and I think it's important.

449
00:21:55,480 --> 00:21:58,040
Speaker 1: So it's sort of a it's a negotiation with yourself

450
00:21:58,040 --> 00:22:00,760
Speaker 1: in a sense that you're having backage the stuff in

451
00:22:00,800 --> 00:22:03,280
Speaker 1: the most boring way possible and never build an audience.

452
00:22:03,480 --> 00:22:06,439
Speaker 1: Might it feel good maybe on some level, but then

453
00:22:06,480 --> 00:22:09,679
Speaker 1: I've built no capital that I can then spend on

454
00:22:09,800 --> 00:22:11,639
Speaker 1: important ideas that I want to put in front of

455
00:22:11,680 --> 00:22:13,320
Speaker 1: my audience, if that makes sense. So I think it's

456
00:22:13,320 --> 00:22:16,040
Speaker 1: a negotiation every creator has. And I talk in the

457
00:22:16,040 --> 00:22:18,239
Speaker 1: book about some who go too far, and they've got

458
00:22:18,320 --> 00:22:20,760
Speaker 1: titles like Trump taken out on a stretcher, and then

459
00:22:20,800 --> 00:22:22,439
Speaker 1: you watch the video and it's like Trump was not

460
00:22:22,440 --> 00:22:25,920
Speaker 1: taken out on a stretcher. That's very far beyond the pale.

461
00:22:26,200 --> 00:22:29,879
Speaker 1: But editorializing about what I see as Caroline Lovett's failings

462
00:22:29,880 --> 00:22:32,880
Speaker 1: as a press secretary and making that as engaging as possible.

463
00:22:33,119 --> 00:22:36,320
Speaker 1: I think you have to play that game. And again

464
00:22:36,760 --> 00:22:39,520
Speaker 1: in the audio podcast, there's none of that stuff. It's

465
00:22:39,560 --> 00:22:42,800
Speaker 1: seventy minutes of me talking. There's none of this editorialized

466
00:22:42,840 --> 00:22:45,520
Speaker 1: titles or anything because you don't need it, and you.

467
00:22:45,400 --> 00:22:47,600
Speaker 3: Talk about colors as well. It was interesting just I mean,

468
00:22:48,040 --> 00:22:50,199
Speaker 3: I never looked at the shades in the context of

469
00:22:50,480 --> 00:22:51,080
Speaker 3: how that's.

470
00:22:50,920 --> 00:22:52,240
Speaker 2: Able to move the needle as well.

471
00:22:52,400 --> 00:22:57,199
Speaker 1: Yeah, it's intuitively the specifics change over time. But what

472
00:22:57,280 --> 00:22:59,760
Speaker 1: we figured out intuitively, and most of these algorithms are

473
00:22:59,760 --> 00:23:03,560
Speaker 1: black boxes, so you never get hard data about it. Intuitively,

474
00:23:03,960 --> 00:23:07,520
Speaker 1: more sort of saturated colors and bright colors colors about

475
00:23:07,560 --> 00:23:11,800
Speaker 1: alarm and attention do better than muted colors. This it's

476
00:23:11,840 --> 00:23:15,399
Speaker 1: such a funny thing because of Donald Trump's orangeeness.

477
00:23:15,600 --> 00:23:17,000
Speaker 2: The orange you right about it, It.

478
00:23:17,000 --> 00:23:21,159
Speaker 1: Naturally lends itself to YouTube thumbnails that do well. I mean,

479
00:23:21,200 --> 00:23:23,800
Speaker 1: it's a crazy thing. There are creators who will dial

480
00:23:23,880 --> 00:23:26,920
Speaker 1: up the saturation on Trump's orange. I don't do that.

481
00:23:27,400 --> 00:23:30,280
Speaker 1: It's an interesting technique though, because it just naturally lends

482
00:23:30,320 --> 00:23:31,920
Speaker 1: itself to attracting the eye.

483
00:23:32,800 --> 00:23:37,199
Speaker 3: In the attracting the eye sort of begs as in

484
00:23:37,240 --> 00:23:40,520
Speaker 3: the book. You know, you write in another chapter about

485
00:23:40,720 --> 00:23:42,800
Speaker 3: how it also changes you. We're being watched twenty four

486
00:23:42,800 --> 00:23:46,840
Speaker 3: to seven. We're all become performers. I mean particularly these streamers. Yes,

487
00:23:46,960 --> 00:23:49,439
Speaker 3: so that are quite literally twenty four to seven. Their

488
00:23:49,560 --> 00:23:54,119
Speaker 3: entire life is online. But you make the point politicians,

489
00:23:54,200 --> 00:23:59,480
Speaker 3: you know right now, I mean we're performing. It's changing us. Yeah,

490
00:23:59,720 --> 00:24:03,280
Speaker 3: in every way, shape or form. Our physiological changes. Not

491
00:24:03,400 --> 00:24:05,000
Speaker 3: just what we say, it's how we say it, Yeah,

492
00:24:05,000 --> 00:24:05,719
Speaker 3: where we say it.

493
00:24:05,840 --> 00:24:08,719
Speaker 1: I hear from a lot of congressional and Senate staffers

494
00:24:09,280 --> 00:24:15,240
Speaker 1: who want to figure out how do I make my principles, content, speeches,

495
00:24:15,240 --> 00:24:18,800
Speaker 1: et cetera more interesting for them to get covered. And

496
00:24:18,920 --> 00:24:20,879
Speaker 1: you know there's one hundred senators and four hundred and

497
00:24:20,920 --> 00:24:22,920
Speaker 1: thirty five in the House. They're all competing for attention.

498
00:24:23,200 --> 00:24:24,600
Speaker 1: They all kind of want to be in that top

499
00:24:24,640 --> 00:24:27,679
Speaker 1: five percent of who is brought on shows to comment

500
00:24:27,720 --> 00:24:31,040
Speaker 1: on stuff. And I don't necessarily have the answers for them.

501
00:24:31,080 --> 00:24:33,959
Speaker 1: It's not my area of expertise. But they understand that

502
00:24:34,040 --> 00:24:37,600
Speaker 1: there's more than just what they are saying. It's the packaging,

503
00:24:37,720 --> 00:24:41,120
Speaker 1: it's the appearance, it's the emotionality and the tone. So

504
00:24:41,160 --> 00:24:43,840
Speaker 1: this goes way beyond content creators and streamers and what

505
00:24:43,880 --> 00:24:45,399
Speaker 1: I mean, what's your you know, what do you make

506
00:24:45,440 --> 00:24:45,639
Speaker 1: of that?

507
00:24:45,680 --> 00:24:47,520
Speaker 3: I mean, obviously you know we you know, I get

508
00:24:47,560 --> 00:24:52,120
Speaker 3: some a bunch of Kennedy memorabilia up here, my favorite

509
00:24:52,119 --> 00:24:55,439
Speaker 3: with his hand on at the desk like exacerbated. But

510
00:24:55,560 --> 00:24:58,080
Speaker 3: you know, the modern era television as it relates to

511
00:24:58,280 --> 00:25:01,880
Speaker 3: you know, how debates were one and how people began

512
00:25:01,960 --> 00:25:04,160
Speaker 3: to perform a little bit. And we've seen the performance

513
00:25:04,359 --> 00:25:06,959
Speaker 3: changes as it relates to even city council meetings, yes,

514
00:25:07,119 --> 00:25:09,679
Speaker 3: when they're televised and when they're not. H and how

515
00:25:09,680 --> 00:25:12,480
Speaker 3: it quite literally changes people. It changes the tone and

516
00:25:12,520 --> 00:25:14,960
Speaker 3: tenor it changes out what people say, how they again,

517
00:25:15,000 --> 00:25:16,600
Speaker 3: how they say it, and how long they say it,

518
00:25:16,720 --> 00:25:17,919
Speaker 3: whether or not they look engaged.

519
00:25:17,920 --> 00:25:20,560
Speaker 2: You're not engaged. You know what do you make of that?

520
00:25:20,640 --> 00:25:22,840
Speaker 3: In the context of what this is doing to all

521
00:25:22,880 --> 00:25:25,680
Speaker 3: of us, to me, to you, to all of us listening.

522
00:25:25,960 --> 00:25:29,159
Speaker 1: Everybody who is on these platforms is affected by this.

523
00:25:29,359 --> 00:25:31,080
Speaker 1: Even if you say I'm not a creator, I'm not

524
00:25:31,119 --> 00:25:33,760
Speaker 1: a streamer, I'm not an elected official. If you are

525
00:25:33,960 --> 00:25:38,239
Speaker 1: participating in comment threads, if you're posting vacation pictures, if

526
00:25:38,280 --> 00:25:40,000
Speaker 1: you're doing the thing at the restaurant where you take

527
00:25:40,040 --> 00:25:42,679
Speaker 1: pictures of your food, and then everybody is sort of

528
00:25:42,840 --> 00:25:46,879
Speaker 1: staging some version of their life and then gauging the

529
00:25:46,920 --> 00:25:49,520
Speaker 1: reaction that it gets. So it's affecting everybody. And there

530
00:25:49,520 --> 00:25:52,600
Speaker 1: are people who aren't professional content creators who just get

531
00:25:52,640 --> 00:25:54,879
Speaker 1: bummed out when the you know, teenagers who post stuff

532
00:25:54,880 --> 00:25:57,480
Speaker 1: and their friends don't like it, or they get attacked

533
00:25:57,560 --> 00:25:59,600
Speaker 1: or all of the stuff. So everybody's in this space

534
00:25:59,600 --> 00:26:00,439
Speaker 1: if you're on the platform.

535
00:26:00,520 --> 00:26:03,160
Speaker 2: Yeah, but so what happened. But aren't we all celebrating

536
00:26:03,240 --> 00:26:05,800
Speaker 2: the authentic? Isn't that what we're all after?

537
00:26:06,320 --> 00:26:09,360
Speaker 1: So that's a really that's a really interesting word because

538
00:26:09,600 --> 00:26:12,520
Speaker 1: you kind of if you're in this twenty four to seven,

539
00:26:12,560 --> 00:26:15,080
Speaker 1: like a lot of people are, you start to lose

540
00:26:15,160 --> 00:26:19,560
Speaker 1: touch with what is the authentic self, right, And at

541
00:26:19,560 --> 00:26:24,159
Speaker 1: this point you may be evaluating the prior performance and

542
00:26:24,240 --> 00:26:26,879
Speaker 1: tweaking that, And I don't know what that does to

543
00:26:26,920 --> 00:26:30,200
Speaker 1: interpersonal relationships. I mean, I think one of the things

544
00:26:30,359 --> 00:26:34,280
Speaker 1: that is definitely true is ninety eight percent of my

545
00:26:34,640 --> 00:26:40,040
Speaker 1: interactions online with people are very negative, and ninety eight

546
00:26:40,080 --> 00:26:42,919
Speaker 1: percent and one hundred percent of my in person interactions

547
00:26:42,960 --> 00:26:46,959
Speaker 1: with people are positive or neutral, and so the disinhibiting

548
00:26:47,320 --> 00:26:50,919
Speaker 1: nature of these interpersonal means where you see people you

549
00:26:51,000 --> 00:26:53,040
Speaker 1: kind of think you know them, you're willing to say.

550
00:26:53,160 --> 00:26:56,600
Speaker 1: Sometimes I'll get emails from people who say horrible, horrible

551
00:26:56,600 --> 00:26:58,800
Speaker 1: things to me, and I rarely write back, but sometimes

552
00:26:58,880 --> 00:27:01,120
Speaker 1: I I'll just as a test, go do you think

553
00:27:01,160 --> 00:27:03,320
Speaker 1: you would say this to me if we met in person?

554
00:27:03,800 --> 00:27:08,360
Speaker 1: And oftentimes it completely deflates the anger and people go

555
00:27:08,680 --> 00:27:11,320
Speaker 1: after a day, I was really upset with what you said.

556
00:27:11,760 --> 00:27:13,840
Speaker 1: The truth is, I know you're just saying what you believe.

557
00:27:13,920 --> 00:27:16,440
Speaker 1: I disagree with it. We'd probably have a good conversation

558
00:27:16,520 --> 00:27:18,479
Speaker 1: in person, which is a really interesting switch.

559
00:27:20,119 --> 00:27:23,240
Speaker 3: Just looking back, I'm curious, is you said, do you

560
00:27:23,240 --> 00:27:26,879
Speaker 3: remember the first thing that just blew up first? I

561
00:27:26,920 --> 00:27:29,320
Speaker 3: mean something that you said or did or how you

562
00:27:29,359 --> 00:27:31,520
Speaker 3: said it, how you did it, how you thumb it,

563
00:27:31,600 --> 00:27:35,440
Speaker 3: whatever it might have been that we're like, whoa this thing?

564
00:27:35,760 --> 00:27:38,240
Speaker 2: Like? Do you remember what was it? I do.

565
00:27:38,480 --> 00:27:41,119
Speaker 1: There was a story where a woman did a test.

566
00:27:41,480 --> 00:27:44,679
Speaker 1: A black woman was not getting job interviews, and she

567
00:27:44,760 --> 00:27:49,040
Speaker 1: did a test where she started submitting her resume with

568
00:27:49,080 --> 00:27:52,159
Speaker 1: what you would call a white sounding name instead of

569
00:27:52,240 --> 00:27:55,320
Speaker 1: what would be considered a black sounding name, same exact resume,

570
00:27:55,800 --> 00:27:58,280
Speaker 1: and she suddenly got a ton of callbacks, and I

571
00:27:58,280 --> 00:28:00,639
Speaker 1: thought it was interesting. I didn't think that that story

572
00:28:00,720 --> 00:28:04,360
Speaker 1: would perform well, but I thought that it was fascinating

573
00:28:04,440 --> 00:28:07,479
Speaker 1: as a social commentary, and so I talked about it

574
00:28:07,960 --> 00:28:11,119
Speaker 1: and it just went absolutely crazy, and it did a

575
00:28:11,119 --> 00:28:13,080
Speaker 1: couple things. Number One, it showed me the power of

576
00:28:13,080 --> 00:28:16,000
Speaker 1: some of these platforms as they grew, that in overnight

577
00:28:16,040 --> 00:28:18,400
Speaker 1: they could generate tens of millions of views, which is crazy.

578
00:28:18,920 --> 00:28:22,120
Speaker 1: But number two, it also showed me there was something

579
00:28:22,600 --> 00:28:27,359
Speaker 1: very emotionally salient about that individual's experience, the story of

580
00:28:27,440 --> 00:28:30,160
Speaker 1: one particular woman rather than a large group of people.

581
00:28:30,200 --> 00:28:33,480
Speaker 1: That particular woman's story really resonated with people and maybe

582
00:28:33,520 --> 00:28:36,159
Speaker 1: got them thinking about their own experiences. And it kind

583
00:28:36,160 --> 00:28:37,400
Speaker 1: of surprised me how well it did.

584
00:28:38,200 --> 00:28:40,320
Speaker 3: And on the flip side of that, things that just

585
00:28:40,520 --> 00:28:43,560
Speaker 3: don't work. I mean, you talked about the complexity nuance

586
00:28:44,040 --> 00:28:49,160
Speaker 3: seeing both sides storytelling policy versus emotion. I mean, what

587
00:28:50,200 --> 00:28:52,040
Speaker 3: are the things that continue to use hit your head?

588
00:28:52,080 --> 00:28:55,280
Speaker 3: And just I do not understand why this is not

589
00:28:55,440 --> 00:28:56,000
Speaker 3: breaking through.

590
00:28:56,280 --> 00:28:59,960
Speaker 1: Well, maybe not understand is interesting when I do long

591
00:29:00,120 --> 00:29:03,240
Speaker 1: form discussions with economists. For example, I'm doing one next

592
00:29:03,240 --> 00:29:06,240
Speaker 1: week on wealth taxes, and we'll talk about the proposal

593
00:29:06,280 --> 00:29:08,920
Speaker 1: here and then the federal one that you've talked about,

594
00:29:08,920 --> 00:29:11,200
Speaker 1: what Europe has done, where it's worked, where it hasn't.

595
00:29:11,520 --> 00:29:14,400
Speaker 1: If we really want to be serious about collecting more

596
00:29:14,480 --> 00:29:17,600
Speaker 1: money from the wealthiest, this is like the most important

597
00:29:17,600 --> 00:29:20,160
Speaker 1: conversation that we could be having you. It's not going

598
00:29:20,240 --> 00:29:23,600
Speaker 1: to do that well on YouTube. The clips on TikTok

599
00:29:23,600 --> 00:29:25,480
Speaker 1: are probably not going to do that.

600
00:29:25,240 --> 00:29:26,920
Speaker 2: I've even done it, you know, But.

601
00:29:26,800 --> 00:29:29,320
Speaker 1: My long form audience will like it. So this is

602
00:29:29,320 --> 00:29:31,320
Speaker 1: the sort of thing where people will take the time

603
00:29:31,360 --> 00:29:33,520
Speaker 1: to email me and say, that was a really great discussion.

604
00:29:33,560 --> 00:29:36,720
Speaker 1: Now I understand why wealth taxes will or won't work,

605
00:29:36,800 --> 00:29:39,400
Speaker 1: or how they need to be structured. It doesn't have

606
00:29:39,760 --> 00:29:45,440
Speaker 1: the it hits you emotional salience of Donald Trump being

607
00:29:45,520 --> 00:29:48,960
Speaker 1: cropped out of the World Cup picture right. It doesn't

608
00:29:48,960 --> 00:29:51,880
Speaker 1: have that. It's thirty forty minutes with an economist on

609
00:29:51,960 --> 00:29:55,440
Speaker 1: dense stuff. I wish that that did better. I wish

610
00:29:55,440 --> 00:29:57,680
Speaker 1: it did better. It's extraordinarily important.

611
00:29:59,280 --> 00:30:03,640
Speaker 3: The right wing tends to do better in this medium.

612
00:30:03,800 --> 00:30:06,240
Speaker 3: You write about Rush Limbaugh. I had my second guests

613
00:30:06,920 --> 00:30:10,480
Speaker 3: on this podcast when I launched it was Michael Savage,

614
00:30:10,600 --> 00:30:13,800
Speaker 3: who you know, was competing with Limbaugh.

615
00:30:12,960 --> 00:30:13,480
Speaker 2: Back in the day.

616
00:30:13,520 --> 00:30:16,680
Speaker 3: He was the guy who created the frame language, borders

617
00:30:16,680 --> 00:30:22,040
Speaker 3: and culture. Was unbelievably effective in that frame and built

618
00:30:22,160 --> 00:30:26,040
Speaker 3: a huge audience and it still has a career that

619
00:30:26,200 --> 00:30:32,280
Speaker 3: continues to this day. They're more naturally successful in this space.

620
00:30:32,640 --> 00:30:35,800
Speaker 3: You write that, you write about that, why two.

621
00:30:35,640 --> 00:30:41,360
Speaker 1: Parts to it. One the right plays on fear identifies

622
00:30:41,480 --> 00:30:46,760
Speaker 1: villains more quickly and more effectively than the left. That's

623
00:30:46,840 --> 00:30:47,240
Speaker 1: number one.

624
00:30:47,240 --> 00:30:48,000
Speaker 2: Why though, why?

625
00:30:48,600 --> 00:30:51,600
Speaker 1: Well, I mean this this gets into deeper stuff. There

626
00:30:51,640 --> 00:30:56,000
Speaker 1: are some studies that show that the sort of brain

627
00:30:56,200 --> 00:31:00,080
Speaker 1: realities of the right are more reactive to fear and

628
00:31:00,120 --> 00:31:02,480
Speaker 1: discussed than the left. It gets into deeper stuff. But

629
00:31:02,720 --> 00:31:05,760
Speaker 1: one thing is they identify scapegoats and villains really quickly.

630
00:31:06,240 --> 00:31:09,240
Speaker 1: Some of their arguments are just better in these platforms.

631
00:31:09,280 --> 00:31:11,480
Speaker 1: Like to go to some other examples that I talk

632
00:31:11,520 --> 00:31:14,760
Speaker 1: about in the book. If I just go listen, it's

633
00:31:14,800 --> 00:31:20,000
Speaker 1: your money, taxes are theft and we need tax relief.

634
00:31:20,600 --> 00:31:23,640
Speaker 1: That's a really tidy and efficient argument, right. And if

635
00:31:23,640 --> 00:31:25,120
Speaker 1: I come in as the guy on the left, I

636
00:31:25,160 --> 00:31:28,080
Speaker 1: don't go, no, taxes are awesome, and raise them as

637
00:31:28,120 --> 00:31:30,760
Speaker 1: high as possible. I have to go listen. If you

638
00:31:30,800 --> 00:31:34,240
Speaker 1: want to live in a society with basic infrastructure, the

639
00:31:34,320 --> 00:31:36,760
Speaker 1: only way to do it is through the collection of

640
00:31:36,760 --> 00:31:39,240
Speaker 1: taxes by the government. Is it sort of coercive, well

641
00:31:39,280 --> 00:31:41,880
Speaker 1: in a sense, but it's which one of those is

642
00:31:41,920 --> 00:31:45,120
Speaker 1: going to do better? Of course, it's they're stealing your money.

643
00:31:45,200 --> 00:31:48,560
Speaker 1: It's yours. You should get to keep it. That's structural

644
00:31:48,640 --> 00:31:53,320
Speaker 1: to their argument on abortion. There's a similar analogy. Murdering

645
00:31:53,360 --> 00:31:55,400
Speaker 1: babies is bad. Abortion's murder.

646
00:31:55,720 --> 00:31:56,040
Speaker 2: That's it.

647
00:31:56,240 --> 00:31:58,840
Speaker 1: We're not doing it, and we on the left, at least,

648
00:31:58,840 --> 00:32:01,480
Speaker 1: I've never met anyone who goes abortions awesome. Let's look

649
00:32:01,480 --> 00:32:03,400
Speaker 1: to increase the number of abortions. We say, there's a

650
00:32:03,440 --> 00:32:06,360
Speaker 1: lot of competing of factors here, and we have to

651
00:32:06,360 --> 00:32:10,440
Speaker 1: talk about bodily autonomy. And it's not going to translate

652
00:32:10,520 --> 00:32:12,920
Speaker 1: as it never translated as well to the rage of

653
00:32:12,920 --> 00:32:15,880
Speaker 1: am radio, and it doesn't work as well in the algorithms.

654
00:32:15,920 --> 00:32:19,440
Speaker 1: It's structural. Now, I don't think it's inevitable that the

655
00:32:19,520 --> 00:32:22,360
Speaker 1: left has to lose on it. We have to rethink

656
00:32:22,600 --> 00:32:25,760
Speaker 1: the entry point into a lot of these issues. For example,

657
00:32:26,600 --> 00:32:29,760
Speaker 1: if you work, of course, you should be able to

658
00:32:29,800 --> 00:32:33,320
Speaker 1: afford a dignified life in the place where you are working,

659
00:32:33,680 --> 00:32:37,280
Speaker 1: not seventy miles away where it's cheaper, that has a

660
00:32:37,320 --> 00:32:39,360
Speaker 1: little more emotional sailings. And then we can back in

661
00:32:39,440 --> 00:32:41,720
Speaker 1: like what policies are we talking about housing and wages,

662
00:32:41,720 --> 00:32:44,400
Speaker 1: et cetera. It's for people who are better on the

663
00:32:44,440 --> 00:32:46,280
Speaker 1: language stuff than me to kind of figure out. But

664
00:32:46,320 --> 00:32:48,040
Speaker 1: I don't think it's a lost cause. I just don't

665
00:32:48,040 --> 00:32:49,240
Speaker 1: think we're winning with it right now.

666
00:32:49,320 --> 00:32:53,040
Speaker 3: I mean to you sense that you know, Bernie Sanders

667
00:32:53,040 --> 00:32:55,479
Speaker 3: has been effective, I mean just calling out the villain.

668
00:32:55,600 --> 00:32:59,360
Speaker 3: I mean, is that, you know, being able to just

669
00:32:59,400 --> 00:33:03,280
Speaker 3: sort of distill the essence of it's us versus them.

670
00:33:03,400 --> 00:33:05,760
Speaker 3: It's not left and right, it's you know what Terrico

671
00:33:05,840 --> 00:33:09,040
Speaker 3: others are saying, it's it's the top versus the bottom.

672
00:33:09,520 --> 00:33:12,480
Speaker 3: The people on top, the systems riggedes that have the

673
00:33:12,520 --> 00:33:15,840
Speaker 3: emotional segments that actually can compete in that space.

674
00:33:16,000 --> 00:33:18,120
Speaker 1: I think it does. What we're kind of getting into

675
00:33:18,160 --> 00:33:20,680
Speaker 1: now is the populist rhetoric. And the thing I talk

676
00:33:20,720 --> 00:33:23,840
Speaker 1: about about populist rhetoric is that it's not a definitive

677
00:33:23,840 --> 00:33:26,880
Speaker 1: set of policy proposals. And the danger with the populist

678
00:33:26,960 --> 00:33:29,040
Speaker 1: rhetoric is that if you go to Bernie and to

679
00:33:29,080 --> 00:33:33,720
Speaker 1: Tucker Carlson, they will give you a similar diagnosis up front,

680
00:33:34,040 --> 00:33:38,479
Speaker 1: which is there are these empowered elites that are in

681
00:33:38,520 --> 00:33:41,920
Speaker 1: it for themselves. Like you'll get a pretty similar analysis.

682
00:33:42,440 --> 00:33:45,120
Speaker 1: You then go to what are the solutions? And Tucker's

683
00:33:45,160 --> 00:33:48,960
Speaker 1: solutions are pretty ugly in a lot of ways, whereas,

684
00:33:48,960 --> 00:33:51,280
Speaker 1: of course Bernie's are ones that I would agree with more.

685
00:33:51,560 --> 00:33:54,800
Speaker 1: I think the risk of adopting the populist rhetoric, which

686
00:33:54,800 --> 00:33:59,240
Speaker 1: Trump has also adopted, is that then the solution maybe

687
00:33:59,240 --> 00:34:02,360
Speaker 1: one that's actually completely antithetical to the policy and values

688
00:34:02,400 --> 00:34:05,240
Speaker 1: that we support. But on the rhetoric, I think Bernie

689
00:34:05,240 --> 00:34:08,640
Speaker 1: has been very good. You know, it's interesting just you know,

690
00:34:08,680 --> 00:34:09,400
Speaker 1: the issue of.

691
00:34:10,880 --> 00:34:13,959
Speaker 3: Selling fear and anxiety, you know, and issues like crime

692
00:34:14,000 --> 00:34:17,120
Speaker 3: and immigration, and then being able to get away with

693
00:34:17,160 --> 00:34:19,600
Speaker 3: selling common indifference on things like climate change and the

694
00:34:19,600 --> 00:34:22,919
Speaker 3: erosion of our hard earned national rights. Is I mean,

695
00:34:23,120 --> 00:34:25,440
Speaker 3: to me, at the core of this dialectic and the

696
00:34:25,520 --> 00:34:28,319
Speaker 3: challenges we're having as a party and their ability to

697
00:34:28,360 --> 00:34:31,000
Speaker 3: shape shift, their ability to control the narrative, their ability

698
00:34:31,400 --> 00:34:34,680
Speaker 3: to communicate with with taking advantage of so many things

699
00:34:34,680 --> 00:34:37,120
Speaker 3: you highlight in the book or you know, illuminating the

700
00:34:37,160 --> 00:34:39,600
Speaker 3: book as it relates to the algorithms, but also just

701
00:34:39,640 --> 00:34:43,120
Speaker 3: this machine they've built, and not just in one platform,

702
00:34:43,160 --> 00:34:46,640
Speaker 3: across the spectrum of platforms. But you talked about Tucker

703
00:34:46,680 --> 00:34:49,279
Speaker 3: in the context of these platforms that are out there,

704
00:34:49,320 --> 00:34:51,760
Speaker 3: in people and personalities in these platforms that are asserting

705
00:34:51,800 --> 00:34:55,160
Speaker 3: themselves with this notion of independence, and you challenge that

706
00:34:55,280 --> 00:34:58,799
Speaker 3: a little bit. Yes, that no one is truly independent

707
00:34:58,840 --> 00:34:59,480
Speaker 3: in this space.

708
00:34:59,680 --> 00:35:03,439
Speaker 1: Yeah, there's obvious ways, and there's less obvious ways. First

709
00:35:03,480 --> 00:35:05,600
Speaker 1: of all, a lot of times when people talk about independent,

710
00:35:05,640 --> 00:35:07,960
Speaker 1: they either mean I don't have advertisers controlling me or

711
00:35:08,000 --> 00:35:11,160
Speaker 1: I don't have editors controlling me. Okay, even if you

712
00:35:11,160 --> 00:35:15,600
Speaker 1: don't have direct advertisers, if you're monetizing your content through YouTube, Facebook,

713
00:35:15,640 --> 00:35:20,480
Speaker 1: TikTok and other built in monetization platforms, you're still influenced

714
00:35:20,560 --> 00:35:24,719
Speaker 1: to create content that won't violate those monetization rules so

715
00:35:24,760 --> 00:35:27,120
Speaker 1: that you don't make money. So that's still there. But

716
00:35:27,160 --> 00:35:29,120
Speaker 1: there's a lot of other ways that people are not

717
00:35:29,120 --> 00:35:32,800
Speaker 1: truly independent, for example, wanting access to people in power.

718
00:35:33,360 --> 00:35:35,080
Speaker 1: And this is what I think has been very interesting

719
00:35:35,120 --> 00:35:37,799
Speaker 1: about Fox News over the last few months, where they

720
00:35:37,840 --> 00:35:40,840
Speaker 1: are starting, I mean, just two days ago, when we

721
00:35:41,080 --> 00:35:44,520
Speaker 1: learned about more troops tragically killed in the Iran War,

722
00:35:45,440 --> 00:35:48,440
Speaker 1: Fox News didn't really sugarcoat it. They even played a

723
00:35:48,440 --> 00:35:50,640
Speaker 1: clip of Trump saying months ago, this is going to

724
00:35:50,680 --> 00:35:52,480
Speaker 1: be two to three weeks and nobody's going to die.

725
00:35:52,520 --> 00:35:55,080
Speaker 1: And then they've got this. I don't think it's out

726
00:35:55,120 --> 00:35:57,680
Speaker 1: of a desire to kind of plant to flag and

727
00:35:57,719 --> 00:36:00,640
Speaker 1: say we now oppose Trump, but I think it's hedging

728
00:36:00,719 --> 00:36:02,920
Speaker 1: because they don't know what comes next. They don't know

729
00:36:02,960 --> 00:36:04,920
Speaker 1: what's going to happen in November. They don't know if

730
00:36:04,920 --> 00:36:06,799
Speaker 1: this president is going to be the lamest of lame

731
00:36:06,880 --> 00:36:10,200
Speaker 1: ducks for two years and we'll see approval ratings in

732
00:36:10,239 --> 00:36:14,360
Speaker 1: the twenties. So it's about preservation. We also want access

733
00:36:14,400 --> 00:36:17,080
Speaker 1: and to stay in good graces with the Republican Party

734
00:36:17,080 --> 00:36:20,759
Speaker 1: and whoever replaces Trump and so like. Is that really independence?

735
00:36:20,760 --> 00:36:21,719
Speaker 1: I would argue that it's not.

736
00:36:22,560 --> 00:36:24,400
Speaker 3: And how do you how are you able to balance

737
00:36:24,440 --> 00:36:27,799
Speaker 3: that in your own I mean, I mean, what's your

738
00:36:27,920 --> 00:36:33,400
Speaker 3: sort of situational awareness about your own capacity to maintain

739
00:36:33,640 --> 00:36:38,480
Speaker 3: that independence. I mean, you've got advertisers, you've got an audience. Ye,

740
00:36:38,920 --> 00:36:41,600
Speaker 3: you have the same desire to have access to get

741
00:36:41,640 --> 00:36:44,680
Speaker 3: the right guess and be you know, how do you

742
00:36:44,920 --> 00:36:45,960
Speaker 3: how do you work through all that?

743
00:36:46,120 --> 00:36:48,840
Speaker 1: The first thing is I try to never do anything

744
00:36:49,160 --> 00:36:52,640
Speaker 1: that is against my kind of existing framework of values.

745
00:36:53,120 --> 00:36:58,799
Speaker 1: So if I go and interview someone somewhere, I want

746
00:36:58,840 --> 00:37:03,360
Speaker 1: to make sure that I'm not interviewing someone in whatever

747
00:37:03,400 --> 00:37:06,759
Speaker 1: way I would normally do it because of somebody who

748
00:37:06,840 --> 00:37:09,080
Speaker 1: has said, Hey, come to our convention or go to

749
00:37:09,120 --> 00:37:11,160
Speaker 1: this thing, or go to that thing. I'm always going

750
00:37:11,200 --> 00:37:14,479
Speaker 1: to only be upfront with my audience about here's someone

751
00:37:14,480 --> 00:37:17,279
Speaker 1: who's values and policies I support, here's someone who I don't,

752
00:37:17,280 --> 00:37:18,760
Speaker 1: And I'm not going to let any kind of financial

753
00:37:18,760 --> 00:37:21,560
Speaker 1: relationship come in between that. I don't talk to anybody

754
00:37:21,600 --> 00:37:24,319
Speaker 1: from any of my advertisers. I never have conversations with them.

755
00:37:24,640 --> 00:37:28,560
Speaker 1: We've luckily never had an advertiser that got word to me, Hey,

756
00:37:28,600 --> 00:37:31,240
Speaker 1: they didn't really like how you Fortunately it's never happened.

757
00:37:31,239 --> 00:37:34,880
Speaker 1: But I have no conversations with advertisers, And if they

758
00:37:34,920 --> 00:37:37,400
Speaker 1: said something like that, I would say, well, that's not

759
00:37:37,840 --> 00:37:40,600
Speaker 1: how we do the show. The platforms are the platforms.

760
00:37:40,600 --> 00:37:43,480
Speaker 1: There's no doubt that there's content I could do that

761
00:37:43,520 --> 00:37:45,759
Speaker 1: would get me demonetized or even kicked off of the

762
00:37:45,800 --> 00:37:49,160
Speaker 1: platforms if it were extreme enough. Those aren't really the

763
00:37:49,200 --> 00:37:51,080
Speaker 1: sorts of things I believe and do, so the risk

764
00:37:51,160 --> 00:37:53,200
Speaker 1: of that happening is relatively low.

765
00:37:54,320 --> 00:37:57,759
Speaker 3: You talk about us being trapped, and obviously we talk

766
00:37:57,800 --> 00:38:01,600
Speaker 3: about the business model around polarization, and we've highlighted that.

767
00:38:01,719 --> 00:38:04,480
Speaker 3: We've talked about that. You highlight it in a much

768
00:38:04,480 --> 00:38:06,480
Speaker 3: deeper way in one of the chapters in the book.

769
00:38:07,160 --> 00:38:10,360
Speaker 3: But this notion that we're trapped in this feed, you

770
00:38:10,760 --> 00:38:12,799
Speaker 3: picked that apart a little bit in terms of what

771
00:38:12,880 --> 00:38:15,080
Speaker 3: podcasts may mean that we can get out of this

772
00:38:15,120 --> 00:38:17,279
Speaker 3: feed a little bit, but illuminate us more. I mean,

773
00:38:17,280 --> 00:38:20,280
Speaker 3: what do you mean by trapped in the feed?

774
00:38:20,480 --> 00:38:22,560
Speaker 1: Well, to the extent that you want to be a

775
00:38:22,600 --> 00:38:26,080
Speaker 1: participant in some of these town square conversations that are happening.

776
00:38:26,200 --> 00:38:29,320
Speaker 1: They're happening on these platforms. At this point, we've lost

777
00:38:29,360 --> 00:38:33,000
Speaker 1: as a country even the idea of at six pm

778
00:38:33,200 --> 00:38:37,240
Speaker 1: people gather around and watch thirty minutes of the nightly

779
00:38:37,520 --> 00:38:41,040
Speaker 1: news yes, crowd kite right ratings are very low there,

780
00:38:41,360 --> 00:38:43,840
Speaker 1: even with sporting events, I mean, and things are so

781
00:38:44,160 --> 00:38:49,680
Speaker 1: fragmented that the town squares really are happening asynchronously. It's

782
00:38:49,680 --> 00:38:52,000
Speaker 1: not all at the same time, but it's over these

783
00:38:52,000 --> 00:38:54,160
Speaker 1: periods of six twelve, twenty four to forty eight hours

784
00:38:54,239 --> 00:38:57,640
Speaker 1: where these stories build and swell online. So instead of

785
00:38:57,680 --> 00:39:00,000
Speaker 1: like it's the Super Bowl kickoffs at six twenty eight,

786
00:39:00,840 --> 00:39:04,560
Speaker 1: it's forty eight hours of a building story, like a

787
00:39:04,680 --> 00:39:07,120
Speaker 1: ship being pushed up by a swell, and then it

788
00:39:07,200 --> 00:39:09,319
Speaker 1: kind of comes down and we move on to the

789
00:39:09,360 --> 00:39:12,200
Speaker 1: next thing. If you want to be involved in that

790
00:39:12,360 --> 00:39:15,040
Speaker 1: and participate in it, it's on these platforms, so I

791
00:39:15,080 --> 00:39:17,439
Speaker 1: think people are trapped in that sense. And then number two,

792
00:39:17,520 --> 00:39:19,680
Speaker 1: a lot of the platforms used to have these reverse

793
00:39:19,760 --> 00:39:23,520
Speaker 1: chronological feeds. Facebook at the beginning, if you were friends

794
00:39:23,560 --> 00:39:26,680
Speaker 1: with twenty people and you went onto Facebook this is

795
00:39:26,719 --> 00:39:30,200
Speaker 1: a while ago now, you wouldn't see an algorithmic feed

796
00:39:30,239 --> 00:39:32,880
Speaker 1: of what you're most likely to enjoy. You would just

797
00:39:32,960 --> 00:39:36,279
Speaker 1: see reverse chronological of my twenty friends, what's the last

798
00:39:36,280 --> 00:39:38,160
Speaker 1: thing that was posted and the one before that, and

799
00:39:38,200 --> 00:39:40,080
Speaker 1: you would kind of get to the end. There's no

800
00:39:40,280 --> 00:39:42,759
Speaker 1: end anymore. You can always scroll and get to the

801
00:39:42,800 --> 00:39:44,719
Speaker 1: next thing, which is part of why it's very addictive.

802
00:39:45,040 --> 00:39:47,239
Speaker 1: But a lot of those tools that let you kind

803
00:39:47,239 --> 00:39:50,279
Speaker 1: of control the ecosystem you're in have been taken away.

804
00:39:51,640 --> 00:39:54,480
Speaker 3: AI is blowing everything out of the water. And you

805
00:39:54,800 --> 00:39:57,160
Speaker 3: and the book talking a little bit more about AI.

806
00:39:57,200 --> 00:40:01,120
Speaker 3: You begin with that Walker video and and just around

807
00:40:01,120 --> 00:40:04,080
Speaker 3: truth and trust and relationship to artificial intelligence. But you

808
00:40:04,600 --> 00:40:08,920
Speaker 3: commented earlier about sixty to seven percent of there in

809
00:40:09,000 --> 00:40:12,600
Speaker 3: terms of these avatars people using your voice, You using

810
00:40:12,719 --> 00:40:15,000
Speaker 3: your own voice, turning it over and so you ran

811
00:40:15,040 --> 00:40:19,400
Speaker 3: your own experiment, Yes, and it told you what it

812
00:40:20,400 --> 00:40:23,960
Speaker 3: communicated to you. What that you have another six months

813
00:40:24,120 --> 00:40:27,920
Speaker 3: and you're one upgrade away from needing a real job.

814
00:40:28,200 --> 00:40:31,239
Speaker 1: Well, where are we going? I'll get back to how

815
00:40:31,239 --> 00:40:33,240
Speaker 1: I think it'll affect me. So we did two tests,

816
00:40:33,280 --> 00:40:37,239
Speaker 1: one with audio, one with video. The technology is phenomenal.

817
00:40:37,360 --> 00:40:41,080
Speaker 1: If I feed hours of my voice into these systems,

818
00:40:41,680 --> 00:40:44,520
Speaker 1: it'll spit out an avatar that I can be sitting

819
00:40:44,560 --> 00:40:47,839
Speaker 1: on a plane somewhere, type into it a script, it

820
00:40:47,880 --> 00:40:50,520
Speaker 1: will spit out an audio file that even my team

821
00:40:50,640 --> 00:40:51,640
Speaker 1: that listens to my voice.

822
00:40:51,640 --> 00:40:52,840
Speaker 2: Every single difference.

823
00:40:52,600 --> 00:40:55,279
Speaker 1: Can't tell the difference there. That's good enough already. It

824
00:40:55,320 --> 00:40:58,160
Speaker 1: was good enough probably six to twelve months ago. The

825
00:40:58,280 --> 00:41:01,319
Speaker 1: video is a little uncanny that still. We tested a

826
00:41:01,320 --> 00:41:03,640
Speaker 1: couple models where we just upload like an hour of

827
00:41:03,640 --> 00:41:07,480
Speaker 1: my video and then feed it a script. It's weird,

828
00:41:07,920 --> 00:41:11,000
Speaker 1: you know. I think if you didn't know me, you

829
00:41:11,080 --> 00:41:13,360
Speaker 1: might just think this is someone who articulates themselves in

830
00:41:13,360 --> 00:41:15,120
Speaker 1: a strange way. If you know me, I think it's

831
00:41:15,120 --> 00:41:18,560
Speaker 1: obvious that it's AI. But these things are accelerating so

832
00:41:18,680 --> 00:41:21,440
Speaker 1: quickly that it's going to be there very soon. Now

833
00:41:21,440 --> 00:41:23,960
Speaker 1: in terms of how it will affect my job. Right now,

834
00:41:24,080 --> 00:41:26,840
Speaker 1: there is such a movement that is skeptical of this

835
00:41:26,920 --> 00:41:31,720
Speaker 1: sort of thing where people don't want to be getting

836
00:41:31,760 --> 00:41:36,440
Speaker 1: their commentary from someone that they know is an avatar. Now,

837
00:41:36,440 --> 00:41:39,000
Speaker 1: could it get so good that they don't realize it. Well,

838
00:41:39,000 --> 00:41:41,759
Speaker 1: that's a different story, and it probably will happen at

839
00:41:41,760 --> 00:41:43,920
Speaker 1: some point. But I think people are very incentivized to

840
00:41:43,960 --> 00:41:46,920
Speaker 1: seek out real connection, and this is I think one

841
00:41:46,920 --> 00:41:50,000
Speaker 1: of the backlashes to what's happening with these platforms. As

842
00:41:50,040 --> 00:41:52,480
Speaker 1: social as we think we're being, when we're connected to

843
00:41:52,640 --> 00:41:55,640
Speaker 1: twelve hundred friends and dms, and all this different stuff.

844
00:41:56,080 --> 00:42:02,160
Speaker 1: There's this lack of in person conviviality that isn't able

845
00:42:02,200 --> 00:42:05,400
Speaker 1: to be replaced when you're participating in Twitter threads. And

846
00:42:05,480 --> 00:42:07,320
Speaker 1: so I think that there's a movement of people wanting

847
00:42:07,360 --> 00:42:09,359
Speaker 1: to reconnect in the real world that maybe is going

848
00:42:09,400 --> 00:42:12,319
Speaker 1: to push up against the technology as it advances. And

849
00:42:12,360 --> 00:42:14,440
Speaker 1: you talk about pushing up the friction.

850
00:42:14,560 --> 00:42:15,520
Speaker 2: You talk about friction.

851
00:42:15,760 --> 00:42:19,359
Speaker 3: Yeah, and now you need to lean into friction, and

852
00:42:19,400 --> 00:42:21,960
Speaker 3: that's how you conclude the book, right, talk to me

853
00:42:22,000 --> 00:42:22,480
Speaker 3: about that.

854
00:42:22,560 --> 00:42:25,400
Speaker 1: Friction in this sense is good, which is if your

855
00:42:25,520 --> 00:42:28,680
Speaker 1: instinct is when you're in line that the bank to

856
00:42:28,760 --> 00:42:31,760
Speaker 1: take out your phone and watch forty seconds of TikTok videos,

857
00:42:32,160 --> 00:42:33,880
Speaker 1: it's kind of good to resist that and to be

858
00:42:33,960 --> 00:42:36,279
Speaker 1: able to resist that for a lot of reasons. Number one,

859
00:42:36,320 --> 00:42:38,560
Speaker 1: because studies seem to find that people who do that

860
00:42:38,600 --> 00:42:41,680
Speaker 1: are actually less happy in general. But also so that

861
00:42:41,719 --> 00:42:44,560
Speaker 1: you're kind of like working your ability to be bored muscle,

862
00:42:44,600 --> 00:42:46,719
Speaker 1: which is something that we've kind of lost. And so

863
00:42:46,760 --> 00:42:48,960
Speaker 1: there's a lot of people Cal Newport and others who

864
00:42:48,960 --> 00:42:52,160
Speaker 1: write extensively about this stuff. When you get home, maybe

865
00:42:52,200 --> 00:42:54,960
Speaker 1: you leave your phone plugged in on the kitchen counter

866
00:42:55,120 --> 00:42:57,520
Speaker 1: or the foyer instead of it being in your pocket

867
00:42:57,560 --> 00:43:00,960
Speaker 1: the entire time, because it introduces a little bit of friction,

868
00:43:01,600 --> 00:43:04,640
Speaker 1: maybe when you go on Twitter. I'm barely on Twitter,

869
00:43:04,680 --> 00:43:06,680
Speaker 1: but what I do is I have a private list

870
00:43:06,800 --> 00:43:09,719
Speaker 1: of about one hundred people. I only am looking at

871
00:43:09,760 --> 00:43:12,040
Speaker 1: what they've posted. I'm not looking at my for you

872
00:43:12,320 --> 00:43:15,040
Speaker 1: Twitter feed, and I'm not looking at dear God, I'm

873
00:43:15,080 --> 00:43:17,799
Speaker 1: not looking at my replies, which is just horrifying. I'm

874
00:43:17,800 --> 00:43:20,520
Speaker 1: just looking at what are these specific people that's free.

875
00:43:20,600 --> 00:43:23,879
Speaker 1: I've put friction between myself and that feed that's out

876
00:43:23,920 --> 00:43:26,799
Speaker 1: there constantly perpetuating itself. These are the sorts of things

877
00:43:26,800 --> 00:43:28,640
Speaker 1: people can do, and you have also done.

878
00:43:28,680 --> 00:43:30,239
Speaker 3: And what I admire about You've been on Rogan a

879
00:43:30,320 --> 00:43:32,720
Speaker 3: number of times. You've been on a number of these shows.

880
00:43:33,640 --> 00:43:35,960
Speaker 1: Patrick's Show, Patrick Abatt, David.

881
00:43:36,080 --> 00:43:39,800
Speaker 2: Yeah, I know. I sometimes I enjoy watching Full Disclosure.

882
00:43:40,320 --> 00:43:41,400
Speaker 2: Now I may get in trouble.

883
00:43:43,200 --> 00:43:46,000
Speaker 1: I enjoy it because I think he's very interesting on

884
00:43:46,080 --> 00:43:47,879
Speaker 1: the show, even if I agree with very little.

885
00:43:48,120 --> 00:43:50,600
Speaker 3: Yes, right, no, that's what I think. That's what makes different.

886
00:43:50,600 --> 00:43:53,680
Speaker 3: I mean, Rogan I find vacuous. But that's just me,

887
00:43:53,760 --> 00:43:57,040
Speaker 3: and that's not just someone you know, text me on

888
00:43:57,080 --> 00:43:59,879
Speaker 3: a weekly basis, won't have me on, but I find

889
00:44:00,239 --> 00:44:03,959
Speaker 3: more of the Facebook version of podcasters. But that's again

890
00:44:04,000 --> 00:44:06,480
Speaker 3: a personal expression. You can't say that because you've been

891
00:44:06,520 --> 00:44:07,560
Speaker 3: on twice and you want to get.

892
00:44:07,560 --> 00:44:07,919
Speaker 2: Well, I don't.

893
00:44:08,200 --> 00:44:09,560
Speaker 1: This was years ago. I don't think I'll ever have

894
00:44:09,680 --> 00:44:11,200
Speaker 1: me back on at this point. But what is it?

895
00:44:11,239 --> 00:44:13,319
Speaker 3: So speaking of not getting back on, I mean, this

896
00:44:13,400 --> 00:44:15,200
Speaker 3: is the challenge or a time you're on this. You're

897
00:44:15,239 --> 00:44:17,400
Speaker 3: on this blacklist right for the White House? Oh, the

898
00:44:17,440 --> 00:44:20,080
Speaker 3: media offenders, Yeah, media offenders list. I mean, so let's

899
00:44:20,120 --> 00:44:21,920
Speaker 3: talk a little bit about this. I mean, all of

900
00:44:21,920 --> 00:44:24,200
Speaker 3: this then leads to just the obvious. This back to

901
00:44:24,239 --> 00:44:27,040
Speaker 3: the polarization, and again you highlight that and a lot

902
00:44:27,040 --> 00:44:30,719
Speaker 3: of the reasons why we're so polarized and increasingly traumatized

903
00:44:30,719 --> 00:44:33,640
Speaker 3: and just exhausted, and how we're just living in our

904
00:44:33,680 --> 00:44:36,239
Speaker 3: own filter bubble and our own set of facts and

905
00:44:36,280 --> 00:44:37,960
Speaker 3: we don't even share the same set of facts. So

906
00:44:38,280 --> 00:44:40,680
Speaker 3: we've identified all the problems in your desire to get

907
00:44:40,680 --> 00:44:43,080
Speaker 3: out of it physically, which again I admire your willingness

908
00:44:43,080 --> 00:44:45,320
Speaker 3: to speak to people you disagree with. Again on platforms

909
00:44:45,800 --> 00:44:49,040
Speaker 3: where people can be more disagreeable h and also try

910
00:44:49,080 --> 00:44:51,120
Speaker 3: to challenge your own algorithms. And I think all of

911
00:44:51,200 --> 00:44:53,560
Speaker 3: us that's that's a very healthy thing.

912
00:44:54,040 --> 00:44:54,920
Speaker 2: But but you know.

913
00:44:56,400 --> 00:44:59,719
Speaker 1: What, where does all this end? I mean, what's you know?

914
00:45:00,080 --> 00:45:00,400
Speaker 1: Give me?

915
00:45:00,520 --> 00:45:04,279
Speaker 2: I mean, we're just we're in the This is the early.

916
00:45:04,080 --> 00:45:08,600
Speaker 3: Days, the black and white movie days of what AI

917
00:45:08,680 --> 00:45:13,319
Speaker 3: can do in terms of weaponizing these grievances and how

918
00:45:13,320 --> 00:45:17,640
Speaker 3: it becomes almost limitlessly automated. You know, give me your

919
00:45:17,680 --> 00:45:18,480
Speaker 3: over under.

920
00:45:19,080 --> 00:45:23,080
Speaker 1: A couple different things politically, just from the standpoint of

921
00:45:23,400 --> 00:45:25,799
Speaker 1: we've got to get power back from people who have

922
00:45:25,880 --> 00:45:28,480
Speaker 1: terrible ideas. We have to engage, and we have to

923
00:45:28,480 --> 00:45:30,080
Speaker 1: get better at playing the game. So this is like

924
00:45:30,120 --> 00:45:33,319
Speaker 1: the one side, it would be nice if the algorithms

925
00:45:33,360 --> 00:45:37,279
Speaker 1: optimize truth over emotionality. They don't. I don't think there's

926
00:45:37,280 --> 00:45:38,920
Speaker 1: any way to force them to. So it's either you

927
00:45:38,960 --> 00:45:41,400
Speaker 1: get out or you participate and you get better at it.

928
00:45:41,440 --> 00:45:44,719
Speaker 1: That's number one. On the other hand, I do think

929
00:45:44,800 --> 00:45:49,440
Speaker 1: that over time, I'm not an accelerationist by my nature.

930
00:45:49,480 --> 00:45:51,640
Speaker 1: I'm not like a It has to get really bad

931
00:45:51,760 --> 00:45:53,920
Speaker 1: so then we can rebuild it. I don't think historically

932
00:45:53,920 --> 00:45:57,680
Speaker 1: that's worked, But I think inevitably if things keep going

933
00:45:57,719 --> 00:46:00,640
Speaker 1: in the direction they're going, which is life is increasingly

934
00:46:00,719 --> 00:46:05,279
Speaker 1: unaffordable for people. People feel disconnected both from societies and

935
00:46:05,320 --> 00:46:08,040
Speaker 1: from the people in power, and don't feel that anyone's

936
00:46:08,080 --> 00:46:10,680
Speaker 1: really looking out for them, and there's a societal breakdown.

937
00:46:10,719 --> 00:46:12,640
Speaker 1: You know, there's a lot of anti social stuff going on,

938
00:46:12,760 --> 00:46:14,839
Speaker 1: not like the birth rate stuff Elon talks about. As

939
00:46:14,840 --> 00:46:16,960
Speaker 1: countries get wealthier, the birth rate goes down, but I

940
00:46:17,000 --> 00:46:20,600
Speaker 1: mean people dating less, people just staying home, et cetera.

941
00:46:21,160 --> 00:46:24,160
Speaker 1: If that continues to get worse and worse, some kind

942
00:46:24,200 --> 00:46:27,319
Speaker 1: of breakdown is likely to happen. I'm not like a

943
00:46:27,760 --> 00:46:31,920
Speaker 1: futurist gloomer that predicts it will be fires and you know,

944
00:46:31,960 --> 00:46:33,480
Speaker 1: like the day after tomorrow. I don't know what it

945
00:46:33,520 --> 00:46:36,239
Speaker 1: will look like, but there may be some return to

946
00:46:37,680 --> 00:46:41,520
Speaker 1: the kind of socializing society of old before some of

947
00:46:41,560 --> 00:46:43,920
Speaker 1: these platforms. It doesn't mean that they'll go away. They

948
00:46:43,960 --> 00:46:46,960
Speaker 1: may just occupy a different place in society. One example is,

949
00:46:47,320 --> 00:46:50,600
Speaker 1: for a while, the average number of Facebook friends people

950
00:46:50,640 --> 00:46:52,759
Speaker 1: had was going up, up, up, where it was like,

951
00:46:52,920 --> 00:46:55,759
Speaker 1: let me collect all of these people I've met one

952
00:46:55,800 --> 00:46:59,680
Speaker 1: sent acquaintances. The trend now is the opposite. Facebook's worried

953
00:46:59,680 --> 00:47:01,680
Speaker 1: about it because people are saying, you know, I actually

954
00:47:01,719 --> 00:47:03,680
Speaker 1: want to be connected only to people I really know.

955
00:47:04,560 --> 00:47:06,960
Speaker 1: And those are things that I think are pointing in

956
00:47:07,000 --> 00:47:09,120
Speaker 1: the right direction. What form all of it is going

957
00:47:09,160 --> 00:47:11,279
Speaker 1: to take five years out, I don't know, do you?

958
00:47:11,600 --> 00:47:14,440
Speaker 3: What do you make of this loneliness epidemic? I mean,

959
00:47:14,480 --> 00:47:16,920
Speaker 3: exacerbated by the very factors that you highlight in the

960
00:47:16,960 --> 00:47:19,680
Speaker 3: book that we need to quote unquote pay attention to,

961
00:47:20,080 --> 00:47:22,120
Speaker 3: but particularly for young men and boys.

962
00:47:22,200 --> 00:47:23,960
Speaker 2: I mean, is that an area of focus for you?

963
00:47:24,280 --> 00:47:28,080
Speaker 1: It is absolutely And I've talked now for years about

964
00:47:28,080 --> 00:47:32,920
Speaker 1: how even though these manisphere models are not good models

965
00:47:33,000 --> 00:47:35,759
Speaker 1: for young men, we on the left also have to

966
00:47:35,800 --> 00:47:39,960
Speaker 1: acknowledge you have to provide an alternative that's interesting and positive.

967
00:47:40,320 --> 00:47:42,520
Speaker 1: And I don't know that it has really been done.

968
00:47:42,560 --> 00:47:44,560
Speaker 1: And we spoke about this last time we talked a

969
00:47:44,560 --> 00:47:47,040
Speaker 1: little bit. I don't know that that model has really

970
00:47:47,080 --> 00:47:48,880
Speaker 1: been built in a way that can compete.

971
00:47:49,400 --> 00:47:49,560
Speaker 3: Now.

972
00:47:49,640 --> 00:47:52,200
Speaker 1: Part of the reason it can't compete is these, you know,

973
00:47:53,040 --> 00:47:55,759
Speaker 1: extremely interesting characters. I mean, I don't know if you

974
00:47:55,760 --> 00:47:59,080
Speaker 1: saw the video of Andrew Tate being arrested recently, so

975
00:47:59,239 --> 00:48:03,160
Speaker 1: physical appearing and it's extremely it attracts the eye. You know,

976
00:48:03,200 --> 00:48:04,560
Speaker 1: it's unusual, and it's it's.

977
00:48:04,600 --> 00:48:05,960
Speaker 2: Its wearing red or something.

978
00:48:06,000 --> 00:48:09,080
Speaker 1: Back to colors and bales like capri pants. Yeah, the

979
00:48:09,160 --> 00:48:11,879
Speaker 1: pants tasseled low fun like a purple shirt, you.

980
00:48:11,840 --> 00:48:13,440
Speaker 2: Know, purple. Maybe it was perf I remember it was

981
00:48:13,520 --> 00:48:14,120
Speaker 2: very colorful.

982
00:48:14,160 --> 00:48:18,000
Speaker 1: It's interesting, it's visually interesting, very visually interesting. And also

983
00:48:18,160 --> 00:48:20,600
Speaker 1: when you say extreme things, it attract more attention. So

984
00:48:20,719 --> 00:48:22,719
Speaker 1: I don't I don't know what the solution is, but

985
00:48:22,760 --> 00:48:25,160
Speaker 1: we need better models of masculinity. And where I think

986
00:48:25,200 --> 00:48:27,719
Speaker 1: the left has sort of failed is the narrative of

987
00:48:28,360 --> 00:48:33,040
Speaker 1: toxic masculinity is bad as a primary message.

988
00:48:32,800 --> 00:48:33,760
Speaker 2: About people away.

989
00:48:33,800 --> 00:48:35,600
Speaker 1: I think it pushes people away and it only makes

990
00:48:35,640 --> 00:48:38,160
Speaker 1: them more susceptible to being pulled in by people like tape.

991
00:48:38,280 --> 00:48:40,000
Speaker 3: So what do you and I and I appreciate that,

992
00:48:40,040 --> 00:48:41,520
Speaker 3: and I think there's some truth to that that there

993
00:48:41,600 --> 00:48:44,319
Speaker 3: was sort of an over indexinge in that toxic frame

994
00:48:44,360 --> 00:48:48,040
Speaker 3: and we lost folks. And so what is the positive alternative?

995
00:48:48,080 --> 00:48:50,080
Speaker 3: And that's the challenge, how do you make I mean,

996
00:48:50,280 --> 00:48:52,120
Speaker 3: these guys won't have one thing in common. I think

997
00:48:52,120 --> 00:48:56,480
Speaker 3: it's more the boyosphere than the manosphere. From the attention perspective,

998
00:48:56,480 --> 00:48:57,880
Speaker 3: and I think you look at the audience. In some

999
00:48:57,920 --> 00:49:00,840
Speaker 3: respects that's the case. But but and there is a

1000
00:49:00,880 --> 00:49:03,240
Speaker 3: toxicity which you have to one has to acknowledge. Yeah,

1001
00:49:03,280 --> 00:49:05,919
Speaker 3: because they've filled the void. So how do we fill

1002
00:49:05,960 --> 00:49:06,319
Speaker 3: the void?

1003
00:49:06,520 --> 00:49:06,759
Speaker 2: Is there?

1004
00:49:06,800 --> 00:49:08,799
Speaker 3: I mean you say there's we're not there yet. Do

1005
00:49:08,800 --> 00:49:10,920
Speaker 3: you see any contours? Are there?

1006
00:49:10,960 --> 00:49:14,520
Speaker 2: There's some examples of people that are competing in that space.

1007
00:49:14,760 --> 00:49:18,840
Speaker 1: I think, I mean, listen, I since no longer being president,

1008
00:49:18,960 --> 00:49:21,520
Speaker 1: I think President Obama has done a couple of really

1009
00:49:21,560 --> 00:49:24,040
Speaker 1: interesting things in speaking to young young boys and men,

1010
00:49:24,400 --> 00:49:28,000
Speaker 1: and one of them is really creating this frame where

1011
00:49:28,480 --> 00:49:33,440
Speaker 1: it's masculine to raise people up around you and to

1012
00:49:33,520 --> 00:49:36,120
Speaker 1: make people feel better so that they are their best

1013
00:49:36,120 --> 00:49:40,560
Speaker 1: selves in their community. The alpha beta male stuff and

1014
00:49:40,640 --> 00:49:44,120
Speaker 1: these tropes of masculinity that people like Tate and others.

1015
00:49:44,320 --> 00:49:47,719
Speaker 1: How to insult women so that they like you, this

1016
00:49:47,800 --> 00:49:51,759
Speaker 1: sort of stuff. Let's raise people up. What's more masculine

1017
00:49:51,800 --> 00:49:54,560
Speaker 1: than saying, hey, you know what, I have the confidence

1018
00:49:54,719 --> 00:49:57,640
Speaker 1: that raising others up isn't going to diminish me. And

1019
00:49:57,640 --> 00:49:59,799
Speaker 1: it's not zero sum, you know. I think these are

1020
00:50:00,160 --> 00:50:03,760
Speaker 1: of some of the ideas that would much better serve

1021
00:50:04,800 --> 00:50:07,520
Speaker 1: the left and serve young men and boys than the

1022
00:50:07,560 --> 00:50:09,800
Speaker 1: stuff from the manisphere that they're getting on the right.

1023
00:50:09,800 --> 00:50:13,480
Speaker 3: Well said, you speak of serving, I mean, what do

1024
00:50:13,600 --> 00:50:15,800
Speaker 3: public servants? What are people in positions of power and

1025
00:50:15,840 --> 00:50:18,520
Speaker 3: influence those with formal authority. What should we be doing

1026
00:50:18,920 --> 00:50:24,080
Speaker 3: in the context of addressing the systemic issues in this space,

1027
00:50:24,120 --> 00:50:26,759
Speaker 3: moving beyond just the issue of the manosphere and the

1028
00:50:26,880 --> 00:50:29,880
Speaker 3: challenges with men and boys and the issues again that

1029
00:50:29,920 --> 00:50:32,719
Speaker 3: you highlight in this book. What do we need to

1030
00:50:32,719 --> 00:50:36,239
Speaker 3: pay attention to in terms of a regulatory framework or

1031
00:50:36,320 --> 00:50:40,719
Speaker 3: not in terms of leaning in socializing, highlighting creating a

1032
00:50:40,719 --> 00:50:42,920
Speaker 3: different culture construct challenge?

1033
00:50:42,920 --> 00:50:44,600
Speaker 2: I mean, is it FCC? Is it? I mean, what

1034
00:50:45,600 --> 00:50:47,960
Speaker 2: do we need to be doing in this space?

1035
00:50:48,160 --> 00:50:51,800
Speaker 1: The micro answer is different in so many different areas,

1036
00:50:51,800 --> 00:50:54,319
Speaker 1: but I think the macro of it is that there's

1037
00:50:54,360 --> 00:50:57,680
Speaker 1: a feeling. So I mentioned at the beginning of our conversation,

1038
00:50:57,800 --> 00:51:00,359
Speaker 1: a lot of the people I talk to don't vote

1039
00:51:00,400 --> 00:51:03,120
Speaker 1: because they have not yet understood the connection between voting

1040
00:51:03,160 --> 00:51:05,040
Speaker 1: and their day to day lives. We've got to relink

1041
00:51:05,080 --> 00:51:10,280
Speaker 1: that connection once that's done. There's a feeling that governments, state,

1042
00:51:10,360 --> 00:51:15,040
Speaker 1: federal move too slowly to really solve problems for people.

1043
00:51:15,440 --> 00:51:18,000
Speaker 1: And so there's a lot of situations people are in

1044
00:51:18,000 --> 00:51:22,520
Speaker 1: that are urgent issues of housing, out of a job, food, instability,

1045
00:51:22,560 --> 00:51:23,960
Speaker 1: issues with children, et cetera.

1046
00:51:24,080 --> 00:51:27,799
Speaker 3: The bs ES that is then the easy answer and

1047
00:51:27,840 --> 00:51:31,360
Speaker 3: the scapegoat right in the context of the algorithms and

1048
00:51:31,400 --> 00:51:32,600
Speaker 3: the filter bubble world.

1049
00:51:32,600 --> 00:51:34,920
Speaker 1: That's a good point in a way to look at it.

1050
00:51:34,960 --> 00:51:38,000
Speaker 1: I think that if people come to believe that there

1051
00:51:38,040 --> 00:51:41,440
Speaker 1: are systems in place that can respond to the specific

1052
00:51:41,600 --> 00:51:45,680
Speaker 1: problems people are having. Because it's great when someone announces

1053
00:51:45,800 --> 00:51:48,480
Speaker 1: we have just secured X amount of funding which will

1054
00:51:48,480 --> 00:51:52,240
Speaker 1: be distributed over why years to start working on that's great,

1055
00:51:52,320 --> 00:51:54,839
Speaker 1: But there's people who are like, I'm in a crisis. Now,

1056
00:51:54,920 --> 00:51:57,280
Speaker 1: what is available to me? Some people do have services

1057
00:51:57,320 --> 00:51:59,719
Speaker 1: available and they don't know about it. So that's about communication.

1058
00:52:00,080 --> 00:52:01,719
Speaker 1: But I think there's this feeling for a lot of

1059
00:52:01,760 --> 00:52:04,080
Speaker 1: people that even if they vote and they change who's

1060
00:52:04,080 --> 00:52:06,719
Speaker 1: in power, the systems move too slowly and they're too

1061
00:52:06,800 --> 00:52:08,440
Speaker 1: clunky to really help them.

1062
00:52:08,800 --> 00:52:12,200
Speaker 3: And so I mean it's a it's a system delivery issue,

1063
00:52:12,280 --> 00:52:16,760
Speaker 3: is an expectation setting issue. What I mean, it takes

1064
00:52:16,800 --> 00:52:19,000
Speaker 3: time to build a house that's right. Even if you

1065
00:52:19,000 --> 00:52:21,320
Speaker 3: have the permits, even if you have the land use reforms,

1066
00:52:21,680 --> 00:52:24,920
Speaker 3: it takes time to construct it. And we can improve productivity.

1067
00:52:25,520 --> 00:52:30,520
Speaker 3: Focus on modular housing prefab housing. You can eliminate some

1068
00:52:30,600 --> 00:52:33,359
Speaker 3: of that friction, but it still takes time. It is

1069
00:52:33,520 --> 00:52:38,319
Speaker 3: how much of this is just level setting versus, you know,

1070
00:52:38,520 --> 00:52:40,680
Speaker 3: just exploitation of people's grievances.

1071
00:52:40,760 --> 00:52:44,359
Speaker 1: I think a lot of it is level setting and communication.

1072
00:52:44,840 --> 00:52:46,840
Speaker 1: One of the things that I kind of have to

1073
00:52:46,880 --> 00:52:49,400
Speaker 1: admit that Donald Trump has picked up on that's useful

1074
00:52:49,400 --> 00:52:53,239
Speaker 1: politically is to make declarations on truth social and to

1075
00:52:53,320 --> 00:52:56,640
Speaker 1: sign executive orders which are effectively memos asking someone to

1076
00:52:56,680 --> 00:53:01,080
Speaker 1: do something, which make a lot of his fallows believe

1077
00:53:01,360 --> 00:53:03,400
Speaker 1: that he is doing the things he promised when he

1078
00:53:03,480 --> 00:53:07,120
Speaker 1: is actually not. I'm not suggesting that elected officials on

1079
00:53:07,160 --> 00:53:10,160
Speaker 1: the left start deliberately lying about the things that they're

1080
00:53:10,160 --> 00:53:14,200
Speaker 1: going to do, But the lesson is communication, especially if

1081
00:53:14,200 --> 00:53:16,719
Speaker 1: it's honest and it's going to be backed up by action,

1082
00:53:17,320 --> 00:53:19,839
Speaker 1: is a lot. And so you know, when you hear

1083
00:53:19,880 --> 00:53:24,400
Speaker 1: about we're considering writing a strongly worded letter for my audience,

1084
00:53:24,440 --> 00:53:26,480
Speaker 1: that's like, what are you talking about? You've lost me?

1085
00:53:26,800 --> 00:53:30,160
Speaker 2: Yes or not? Ed ye, it's good in the New

1086
00:53:30,239 --> 00:53:30,920
Speaker 2: York Times.

1087
00:53:31,000 --> 00:53:35,600
Speaker 1: It will be one hundred likes, right, I agree with that.

1088
00:53:35,680 --> 00:53:38,279
Speaker 3: So let's I mean, it all touches on where we

1089
00:53:38,320 --> 00:53:40,640
Speaker 3: are as a party and you've been you've called out

1090
00:53:40,640 --> 00:53:42,719
Speaker 3: the Democratic Party, you know, sort of the Sunday Show,

1091
00:53:42,760 --> 00:53:45,919
Speaker 3: buttoned up party versus you know, being able to play

1092
00:53:45,960 --> 00:53:49,600
Speaker 3: in this, you know in the new arena. That is

1093
00:53:49,640 --> 00:53:51,680
Speaker 3: self evident that you've been a huge part of our

1094
00:53:51,719 --> 00:53:54,200
Speaker 3: last twenty plus years. But what, you know, what is

1095
00:53:54,239 --> 00:53:56,480
Speaker 3: the lesson today for the modern Democratic Party?

1096
00:53:56,520 --> 00:53:57,319
Speaker 2: What what would you.

1097
00:53:57,280 --> 00:53:59,520
Speaker 3: Be advising if you were the head of the DNC

1098
00:53:59,719 --> 00:54:02,719
Speaker 3: that the party itself do if there is a or

1099
00:54:02,760 --> 00:54:06,319
Speaker 3: even do you believe in the construct top down or

1100
00:54:06,400 --> 00:54:08,800
Speaker 3: is it really bottom up? And it's about a thousand

1101
00:54:08,880 --> 00:54:11,280
Speaker 3: different points of light, so to speak.

1102
00:54:11,360 --> 00:54:13,640
Speaker 1: I think there's value to structure, but there is a

1103
00:54:13,640 --> 00:54:15,160
Speaker 1: lot of bottom up stuff. I mean, some of the

1104
00:54:15,160 --> 00:54:19,720
Speaker 1: most successful campaigns that just dominate social media are built

1105
00:54:19,719 --> 00:54:21,919
Speaker 1: from the bottom up with people who are really good

1106
00:54:22,000 --> 00:54:26,880
Speaker 1: on social media. I do think that being less structured

1107
00:54:27,080 --> 00:54:30,720
Speaker 1: is something I've told a lot of staffers. They want

1108
00:54:30,880 --> 00:54:33,879
Speaker 1: the questions ahead of time, which we ever do? They

1109
00:54:33,920 --> 00:54:34,920
Speaker 1: want to they say, you.

1110
00:54:34,880 --> 00:54:36,800
Speaker 2: Know, do you still you really get that stuff?

1111
00:54:37,680 --> 00:54:40,280
Speaker 1: We really get. We just had a situation I haven't.

1112
00:54:40,120 --> 00:54:41,600
Speaker 2: Said me and I gave you all the questions.

1113
00:54:41,600 --> 00:54:45,600
Speaker 1: That's this is a special case. Yeah you We recently

1114
00:54:45,680 --> 00:54:49,520
Speaker 1: had a situation where a staffer talked to my producer

1115
00:54:49,560 --> 00:54:51,760
Speaker 1: and said, what are we going to talk about? Seven?

1116
00:54:51,920 --> 00:54:54,040
Speaker 1: Eight things were kind of mentioned. It was a fifteen

1117
00:54:54,040 --> 00:54:56,680
Speaker 1: minute conversation, which I think is also a problem. But

1118
00:54:57,120 --> 00:54:58,959
Speaker 1: how can you talk about eight things in fifteen minutes?

1119
00:54:59,000 --> 00:55:01,480
Speaker 1: We got to two and then my producer got a

1120
00:55:01,480 --> 00:55:04,839
Speaker 1: call saying I was disappointed that the focus was only

1121
00:55:04,840 --> 00:55:06,759
Speaker 1: on those two and say, well, hold on a second. Yeah,

1122
00:55:06,840 --> 00:55:10,640
Speaker 1: gave us fifteen minutes and this was the range of

1123
00:55:10,719 --> 00:55:13,520
Speaker 1: things that would be discussed. I can't force date. I'man

1124
00:55:13,520 --> 00:55:15,880
Speaker 1: not in David's ear saying move on to the next topic.

1125
00:55:16,280 --> 00:55:18,879
Speaker 1: So that stuff, I think makes the find the end

1126
00:55:18,920 --> 00:55:22,719
Speaker 1: product feel extremely stiff. Doesn't people don't relate to That

1127
00:55:22,760 --> 00:55:25,560
Speaker 1: goes the authenticity, That goes to the authenticity piece. And

1128
00:55:25,600 --> 00:55:29,360
Speaker 1: I think being less structured, appearing in less structured situations

1129
00:55:29,600 --> 00:55:32,160
Speaker 1: I think is only good. And you got to hand

1130
00:55:32,200 --> 00:55:34,920
Speaker 1: it to Trump. During the twenty four campaign, he spent

1131
00:55:35,000 --> 00:55:37,400
Speaker 1: three hours with the k Neelk Boys, and he's talking

1132
00:55:37,440 --> 00:55:40,520
Speaker 1: to Lex Friedman and he's with Rogan, and he's not

1133
00:55:40,880 --> 00:55:44,160
Speaker 1: you've been on Lex as well, by the way, as well. Yeah, yeah,

1134
00:55:44,440 --> 00:55:47,320
Speaker 1: I think that that worked. Even if he's telling lies,

1135
00:55:47,600 --> 00:55:50,520
Speaker 1: the fact that he's there and it feels relaxed and

1136
00:55:50,600 --> 00:55:53,040
Speaker 1: unstructured goes a really long way with voters.

1137
00:55:53,680 --> 00:55:56,799
Speaker 2: So so that's one piece of advice. What else I mean?

1138
00:55:56,840 --> 00:56:00,760
Speaker 3: So this notion of abundance, I mean, I think we

1139
00:56:00,880 --> 00:56:02,880
Speaker 3: talked around that. I mean, we haven't used the word abundance,

1140
00:56:02,880 --> 00:56:05,560
Speaker 3: So you didn't use the word abundance. I use it often,

1141
00:56:05,600 --> 00:56:09,080
Speaker 3: and I certainly embrace the frame. People are just sick

1142
00:56:09,120 --> 00:56:13,120
Speaker 3: and tired of process and the paralysis of process. They

1143
00:56:13,160 --> 00:56:16,560
Speaker 3: want to see they want to physically see the results.

1144
00:56:17,080 --> 00:56:20,480
Speaker 3: It's proof of concept that I want to see results.

1145
00:56:20,520 --> 00:56:24,799
Speaker 3: Don't tell me i've how sixty eight thousand people news, which,

1146
00:56:24,880 --> 00:56:28,160
Speaker 3: by the way, we have through Project Homekey. Don't tell

1147
00:56:28,200 --> 00:56:30,240
Speaker 3: me that I want to see it physically on the streets.

1148
00:56:30,320 --> 00:56:34,040
Speaker 3: Otherwise I don't believe you, and we've losing trust. And

1149
00:56:34,880 --> 00:56:38,520
Speaker 3: obviously that is exploited, and obviously it's creating a lot

1150
00:56:38,560 --> 00:56:42,120
Speaker 3: of friction and it's politically challenging. So what else do

1151
00:56:42,160 --> 00:56:44,680
Speaker 3: you advise in the context of the political the Democratic

1152
00:56:45,040 --> 00:56:47,440
Speaker 3: Party in terms of getting back on its feet, getting

1153
00:56:47,560 --> 00:56:50,200
Speaker 3: back into it, sort of send it position, getting off

1154
00:56:50,239 --> 00:56:54,759
Speaker 3: the map. Matt, Obviously there's no you know, for all

1155
00:56:54,960 --> 00:57:00,360
Speaker 3: the animus that has developed, increasing animus not just the

1156
00:57:00,400 --> 00:57:03,279
Speaker 3: Democratic Party and Independence, but increasingly in his own base

1157
00:57:03,800 --> 00:57:04,640
Speaker 3: against Donald Trump.

1158
00:57:04,680 --> 00:57:06,640
Speaker 2: It's not a nerd to the benefit of the Democratic Party.

1159
00:57:07,000 --> 00:57:09,600
Speaker 1: I think that the focus really has to be on

1160
00:57:09,760 --> 00:57:13,520
Speaker 1: the economic situation. One of the mistakes that I saw

1161
00:57:13,640 --> 00:57:16,480
Speaker 1: with President Biden's reelection campaign while it was going on,

1162
00:57:16,600 --> 00:57:18,360
Speaker 1: and then with the Harris campaign when it became the

1163
00:57:18,400 --> 00:57:22,040
Speaker 1: Harris campaign was a lot of pointing to but don't

1164
00:57:22,120 --> 00:57:25,840
Speaker 1: people see the economic numbers. Things are really good, And

1165
00:57:26,000 --> 00:57:27,880
Speaker 1: they may be really good for a bunch of people

1166
00:57:28,080 --> 00:57:30,160
Speaker 1: and not good for a lot of others. But if

1167
00:57:30,200 --> 00:57:33,720
Speaker 1: people don't feel that things are good and you're telling

1168
00:57:33,760 --> 00:57:35,920
Speaker 1: them they are, of course they're not going to think

1169
00:57:35,960 --> 00:57:38,840
Speaker 1: you'll make anything better. You're saying everything's fine to begin with.

1170
00:57:38,920 --> 00:57:41,120
Speaker 1: And this is why I think Barack Obama's twenty twelve

1171
00:57:41,200 --> 00:57:44,960
Speaker 1: campaign did this very well, where he said we've made

1172
00:57:44,960 --> 00:57:47,120
Speaker 1: a lot of progress getting out of the Great Recession,

1173
00:57:47,560 --> 00:57:49,440
Speaker 1: and we still have a long way to go. And

1174
00:57:49,520 --> 00:57:51,560
Speaker 1: hear the three or four things I'm going to focus on,

1175
00:57:52,000 --> 00:57:55,520
Speaker 1: it felt much more like, Okay, I can acknowledge this

1176
00:57:55,600 --> 00:57:58,680
Speaker 1: is no longer two thousand and eight, and also this

1177
00:57:58,720 --> 00:58:00,840
Speaker 1: is still a climb that we are in the middle of.

1178
00:58:01,320 --> 00:58:03,360
Speaker 1: And then you need to have policies you can actually

1179
00:58:03,400 --> 00:58:06,200
Speaker 1: deliver on. So that's where Donald Trump made a huge mistake,

1180
00:58:06,240 --> 00:58:09,280
Speaker 1: which is gas will be down fifty percent, everything will

1181
00:58:09,280 --> 00:58:11,200
Speaker 1: be cheaper. It's going to be a new glory, you know,

1182
00:58:11,280 --> 00:58:14,400
Speaker 1: and gases over four bucks a gallon nationally and much

1183
00:58:14,440 --> 00:58:16,720
Speaker 1: more in certain parts of the country. You have to

1184
00:58:16,760 --> 00:58:20,000
Speaker 1: have some possibility of delivering on what you're asking.

1185
00:58:20,320 --> 00:58:21,840
Speaker 3: Well, I could agree with the more. I mean my

1186
00:58:21,880 --> 00:58:24,440
Speaker 3: own confession. You have a confession chapter. But you know

1187
00:58:24,480 --> 00:58:26,640
Speaker 3: I was out there stumping for Biden, and I was

1188
00:58:26,640 --> 00:58:29,800
Speaker 3: making the same point in face inflation's cooling, you know,

1189
00:58:29,960 --> 00:58:33,280
Speaker 3: economies booming, best jobs market since in nineteen sixties, lowest

1190
00:58:33,320 --> 00:58:36,680
Speaker 3: unemployment for blacks, for women, for those with disabilities. We

1191
00:58:37,120 --> 00:58:40,160
Speaker 3: had record job growth, we were reducing the deficit and debt.

1192
00:58:40,600 --> 00:58:46,400
Speaker 3: We had these unbelievable bipartisan deals, four hundred bipartisan legislative victories,

1193
00:58:46,440 --> 00:58:49,600
Speaker 3: some of the most iconic being you know, I are

1194
00:58:49,840 --> 00:58:54,120
Speaker 3: a the issues around infrastructure, chips and science, and it

1195
00:58:54,160 --> 00:58:57,080
Speaker 3: was all about the aggregate, right, and people don't live

1196
00:58:57,080 --> 00:59:01,600
Speaker 3: in the aggregate, and they weren't feeling it. And you're right,

1197
00:59:01,720 --> 00:59:04,360
Speaker 3: that was I mean, boy, that landed like a thud.

1198
00:59:04,800 --> 00:59:05,040
Speaker 2: Yeah.

1199
00:59:05,080 --> 00:59:08,560
Speaker 1: That and immigration I think were two areas that weren't

1200
00:59:08,640 --> 00:59:13,360
Speaker 1: landing well with a lot of voters, and the here's

1201
00:59:13,400 --> 00:59:16,240
Speaker 1: the progress we've made, but then like here's the north Star.

1202
00:59:16,960 --> 00:59:19,960
Speaker 1: There is a kind of transition there that's relatively smooth,

1203
00:59:20,160 --> 00:59:22,320
Speaker 1: which I think makes people feel a lot more heard

1204
00:59:22,400 --> 00:59:26,160
Speaker 1: and as unrealistic as Donald Trump's promises were, at least

1205
00:59:26,200 --> 00:59:30,880
Speaker 1: they sounded tangible, completely unrealistic, and we all were saying

1206
00:59:31,000 --> 00:59:34,520
Speaker 1: this will never happen, but they sounded like specific, tangible promises.

1207
00:59:34,560 --> 00:59:36,360
Speaker 1: Gas is going to be half the price. Of course

1208
00:59:36,360 --> 00:59:38,240
Speaker 1: it's not going to be, but that sounds tangible. I

1209
00:59:38,240 --> 00:59:39,040
Speaker 1: can imagine what that.

1210
00:59:39,040 --> 00:59:41,880
Speaker 3: Would be like, Yeah, drill, baby, drill. But you know

1211
00:59:42,000 --> 00:59:45,280
Speaker 3: it's interesting, I you know, I then go back to

1212
00:59:45,320 --> 00:59:47,880
Speaker 3: your book. The flip side of that is you also

1213
00:59:47,920 --> 00:59:51,280
Speaker 3: make the point that identity politics works a hell of

1214
00:59:51,320 --> 00:59:55,720
Speaker 3: a lot better than policy, Leiden, you know, five point plans.

1215
00:59:55,960 --> 00:59:59,120
Speaker 3: So we want to talk about the economy, blending an

1216
00:59:59,160 --> 00:59:59,880
Speaker 3: identity frame.

1217
01:00:00,000 --> 01:00:01,880
Speaker 2: Back to my sort of pts on.

1218
01:00:02,400 --> 01:00:06,720
Speaker 3: The immigration, blaming immigrants, blaming Somali's blaming, you know, just

1219
01:00:06,800 --> 01:00:11,840
Speaker 3: blaming the other. The effectiveness of doing so as an

1220
01:00:11,880 --> 01:00:15,640
Speaker 3: economic message. Your rents are high, right because of all

1221
01:00:15,640 --> 01:00:19,439
Speaker 3: of the illegals that Biden has brought over the border. Yeah,

1222
01:00:19,440 --> 01:00:22,400
Speaker 3: and how do you square that circle without becoming them?

1223
01:00:22,800 --> 01:00:26,600
Speaker 1: Well, my view on identity politics has always been I

1224
01:00:26,760 --> 01:00:30,080
Speaker 1: never am in favor of the identity politics that's used

1225
01:00:30,120 --> 01:00:32,640
Speaker 1: as a cudgel to silence people, which is like, hey, listen,

1226
01:00:32,840 --> 01:00:35,880
Speaker 1: I'm a member of X group. I'm the one who

1227
01:00:35,960 --> 01:00:39,640
Speaker 1: gets to speak, decide, and sort of lay down the law.

1228
01:00:40,320 --> 01:00:43,520
Speaker 1: I'm interested in identity in so far as it can

1229
01:00:43,560 --> 01:00:46,520
Speaker 1: be used to bolster an economic message, and that people

1230
01:00:46,520 --> 01:00:49,440
Speaker 1: of certain identities may indeed be the best position to

1231
01:00:49,480 --> 01:00:53,320
Speaker 1: tell us about their experience. And I'm speaking with I'm

1232
01:00:53,320 --> 01:00:55,800
Speaker 1: doing a panel on the Latino vote in a few weeks,

1233
01:00:56,240 --> 01:00:58,680
Speaker 1: and one of the messages that I want to bring

1234
01:00:58,880 --> 01:01:01,960
Speaker 1: is it's great to think about Latino voters as a group,

1235
01:01:02,320 --> 01:01:06,360
Speaker 1: and also we should consider that their economic interests are

1236
01:01:06,400 --> 01:01:09,200
Speaker 1: the same of any voter, and that we need to

1237
01:01:09,200 --> 01:01:13,280
Speaker 1: be thinking about that as let's not necessarily separate them out.

1238
01:01:13,360 --> 01:01:15,520
Speaker 1: As it is, it is a group with a particular

1239
01:01:15,560 --> 01:01:19,640
Speaker 1: background and some shared interests, but also their concerns are

1240
01:01:19,640 --> 01:01:22,320
Speaker 1: the concerns of the average everyday American. So you've got

1241
01:01:22,320 --> 01:01:22,560
Speaker 1: to do.

1242
01:01:22,520 --> 01:01:24,280
Speaker 2: Both, amen.

1243
01:01:24,360 --> 01:01:27,440
Speaker 3: I mean, how many Latino audience I've been in and

1244
01:01:27,440 --> 01:01:30,560
Speaker 3: talking about immigration and people are like, stop, you're patronizing us.

1245
01:01:30,600 --> 01:01:33,160
Speaker 3: That's not the only issue, of course, so much of

1246
01:01:33,200 --> 01:01:37,720
Speaker 3: the issues around immigration have disproportionately obviously impacted our immigrant

1247
01:01:37,760 --> 01:01:42,360
Speaker 3: communities by definition mixed status families and obviously Latino community.

1248
01:01:42,360 --> 01:01:47,320
Speaker 3: But that point is foundational. So back then back up

1249
01:01:47,360 --> 01:01:49,160
Speaker 3: a little bit to the DSA in the context of

1250
01:01:49,240 --> 01:01:53,440
Speaker 3: the sort of emergence of a new narrative, you know,

1251
01:01:53,840 --> 01:01:57,919
Speaker 3: ability to call out the victim the villain a little

1252
01:01:57,960 --> 01:02:02,320
Speaker 3: bit more clearly, communication that seems a little bit more effective.

1253
01:02:02,360 --> 01:02:05,680
Speaker 3: Certainly electorally has been effective in some cases. We can

1254
01:02:06,000 --> 01:02:08,640
Speaker 3: over read, you know, we tend to color things in

1255
01:02:09,040 --> 01:02:11,800
Speaker 3: a few examples then become sort of the dominant normal

1256
01:02:11,840 --> 01:02:15,480
Speaker 3: and the meme that suggests something bigger than itself. But

1257
01:02:15,680 --> 01:02:18,480
Speaker 3: where are you just in terms of you know, you

1258
01:02:18,520 --> 01:02:21,160
Speaker 3: talked about the platform, but where are you in the

1259
01:02:21,200 --> 01:02:25,320
Speaker 3: context of looking at the DSA, in the context of

1260
01:02:25,360 --> 01:02:28,440
Speaker 3: the Democratic Party's future, in terms of the narrative, in

1261
01:02:28,520 --> 01:02:32,200
Speaker 3: terms of sort of being repairs of this party brand.

1262
01:02:32,520 --> 01:02:35,720
Speaker 1: So a couple things. I am not sure what things

1263
01:02:35,760 --> 01:02:38,080
Speaker 1: will look like ten fifty or one hundred years from now.

1264
01:02:38,120 --> 01:02:40,520
Speaker 1: In terms of Donald Trump always says this will never

1265
01:02:40,600 --> 01:02:43,000
Speaker 1: be a socialist or communist country. I don't think it's

1266
01:02:43,000 --> 01:02:44,600
Speaker 1: going to be one in the next five to ten years.

1267
01:02:44,720 --> 01:02:47,120
Speaker 1: Never is a really long term play. I don't know

1268
01:02:47,160 --> 01:02:49,200
Speaker 1: what's going to happen in the next hundred years. I

1269
01:02:49,240 --> 01:02:54,120
Speaker 1: do think that right now, the success in some circles

1270
01:02:54,120 --> 01:02:57,240
Speaker 1: of these DSA candidates should be a red alert for

1271
01:02:57,280 --> 01:03:00,800
Speaker 1: the Democratic Party in that there are many voters who

1272
01:03:00,800 --> 01:03:04,640
Speaker 1: are extraordinarily disaffected with the party. They don't want to

1273
01:03:04,720 --> 01:03:07,600
Speaker 1: vote for Republicans, and there's this other thing that they're

1274
01:03:07,600 --> 01:03:12,720
Speaker 1: finding preferable to the Democratic establishment. Really important message. If

1275
01:03:13,120 --> 01:03:15,560
Speaker 1: you ignore that message, and if Democrats ignore that message,

1276
01:03:15,560 --> 01:03:18,080
Speaker 1: it's like the Republicans ignoring the Tea Party. In twenty ten,

1277
01:03:18,320 --> 01:03:21,840
Speaker 1: we saw what happened. So that's extremely interesting and relevant

1278
01:03:22,480 --> 01:03:25,720
Speaker 1: on the specifics. Ten years ago, when I would interview

1279
01:03:25,920 --> 01:03:29,920
Speaker 1: DSA people, socialists, etc. They would say to me very soberly,

1280
01:03:30,480 --> 01:03:33,440
Speaker 1: they would go, listen, David, I'm a socialist. You're not.

1281
01:03:34,160 --> 01:03:36,760
Speaker 1: But our next stops on this bus are the same.

1282
01:03:37,400 --> 01:03:40,640
Speaker 1: And so I see myself as united with you. If

1283
01:03:40,680 --> 01:03:43,240
Speaker 1: and when we get to social democracy and the things

1284
01:03:43,280 --> 01:03:45,800
Speaker 1: we agree on we get people health care, etc. Then

1285
01:03:45,960 --> 01:03:48,880
Speaker 1: the social democrats and the bona fide socialists can have

1286
01:03:48,920 --> 01:03:51,600
Speaker 1: an argument about whether we go further or not. I

1287
01:03:51,680 --> 01:03:55,120
Speaker 1: really respected that. That was a very interesting conversation to have.

1288
01:03:55,200 --> 01:03:57,400
Speaker 1: There wasn't a litmus test that was imposed on me

1289
01:03:57,840 --> 01:04:01,000
Speaker 1: as someone who is not a socialist. That's very different

1290
01:04:01,040 --> 01:04:03,480
Speaker 1: now where I regularly get emails and see comments for

1291
01:04:03,560 --> 01:04:06,000
Speaker 1: people saying you're with us or against us. It doesn't

1292
01:04:06,000 --> 01:04:09,000
Speaker 1: matter if we agree on universal healthcare and a few

1293
01:04:09,000 --> 01:04:12,240
Speaker 1: other things. We believe housing should be government owned and

1294
01:04:12,280 --> 01:04:14,640
Speaker 1: people are assigned to house and blah blah blah. I go,

1295
01:04:14,840 --> 01:04:17,360
Speaker 1: I don't believe that. Do I think people should be homeless?

1296
01:04:17,600 --> 01:04:17,680
Speaker 3: No?

1297
01:04:18,160 --> 01:04:19,920
Speaker 1: Can I point to things that have been done in

1298
01:04:19,960 --> 01:04:22,040
Speaker 1: Saint Louis and in Salt Lake city to just give

1299
01:04:22,080 --> 01:04:24,200
Speaker 1: people housing and how it's actually cheaper than having them

1300
01:04:24,240 --> 01:04:27,240
Speaker 1: on the streets. Yes, for homeless folks, that absolutely, but

1301
01:04:27,320 --> 01:04:30,760
Speaker 1: I'm not a take take away private ownerships. And then

1302
01:04:31,120 --> 01:04:33,480
Speaker 1: well then you're simply not part of the same movement.

1303
01:04:33,880 --> 01:04:35,360
Speaker 1: This is not everybody. But these are some of the

1304
01:04:35,360 --> 01:04:37,600
Speaker 1: conversations I've had, So I feel like the tone of

1305
01:04:37,640 --> 01:04:41,120
Speaker 1: these conversations is very different today than it was eight

1306
01:04:41,120 --> 01:04:41,760
Speaker 1: ten years ago.

1307
01:04:41,880 --> 01:04:43,440
Speaker 2: So what's I mean so fast forward?

1308
01:04:43,440 --> 01:04:45,800
Speaker 3: I mean, so, I mean, do you believe this is

1309
01:04:46,360 --> 01:04:51,240
Speaker 3: a truly robust movement that will continue to gain momentum

1310
01:04:51,440 --> 01:04:54,720
Speaker 3: or do you feel like it's at peak at the

1311
01:04:54,760 --> 01:04:57,240
Speaker 3: moment on the basis of some of these local elections

1312
01:04:57,840 --> 01:05:01,360
Speaker 3: with national implications and a with Mum Donnis sort of

1313
01:05:01,360 --> 01:05:05,000
Speaker 3: ascendencies as a bright star in the Democratic.

1314
01:05:04,480 --> 01:05:07,160
Speaker 1: Movement, predictions are so tough. I don't think this is

1315
01:05:07,200 --> 01:05:10,160
Speaker 1: the peak, but I don't see a desire right now

1316
01:05:10,200 --> 01:05:13,520
Speaker 1: for this to become widespread in terms of the candidates

1317
01:05:13,520 --> 01:05:17,880
Speaker 1: that the Democratic Party nominates. It's really up to the voters.

1318
01:05:17,920 --> 01:05:19,960
Speaker 1: And so that's where I hesitate to say this will

1319
01:05:19,960 --> 01:05:22,280
Speaker 1: not go further or it will. It'll be up to

1320
01:05:22,360 --> 01:05:24,920
Speaker 1: voters to decide, and part of it also has to

1321
01:05:24,960 --> 01:05:29,640
Speaker 1: do with whether Democrats are putting forward interesting and authentic

1322
01:05:29,680 --> 01:05:35,040
Speaker 1: candidates with good ideas. If the alternative to the DSA

1323
01:05:35,080 --> 01:05:37,440
Speaker 1: actual socialists, which by the way, a lot of them

1324
01:05:37,480 --> 01:05:40,560
Speaker 1: aren't actual socialists, but some of them are, doesn't really matter.

1325
01:05:40,600 --> 01:05:43,200
Speaker 1: A lot of this is labeling. If the alternative is

1326
01:05:43,320 --> 01:05:48,600
Speaker 1: a terrible centrist Democrat, that helps this DSA movement. If

1327
01:05:48,640 --> 01:05:52,280
Speaker 1: there are interesting people that are to the left of

1328
01:05:52,320 --> 01:05:55,840
Speaker 1: the centrist Democrats but not socialists, that's the best thing

1329
01:05:55,920 --> 01:05:57,440
Speaker 1: that they can do in a lot of these districts.

1330
01:05:57,480 --> 01:06:02,560
Speaker 1: The other thing is Michigan and Iowa and Connecticut and

1331
01:06:02,640 --> 01:06:05,280
Speaker 1: New York City are very different places, and this is

1332
01:06:05,280 --> 01:06:07,720
Speaker 1: a huge country with a lot of different people. So

1333
01:06:07,760 --> 01:06:09,919
Speaker 1: I think it's difficult to make any kind of overarching

1334
01:06:10,000 --> 01:06:11,720
Speaker 1: prediction about something like that.

1335
01:06:12,000 --> 01:06:15,160
Speaker 2: What is and what's I mean the word centrist?

1336
01:06:15,400 --> 01:06:19,160
Speaker 3: It's interesting is that what is cent centrist in policy,

1337
01:06:19,240 --> 01:06:20,480
Speaker 3: centrists and attitudes?

1338
01:06:20,600 --> 01:06:25,920
Speaker 2: Centrist is the establishment? Centrist is an incumbent. I think

1339
01:06:26,120 --> 01:06:29,080
Speaker 2: what is the center centrist is a corporate democrat? What

1340
01:06:29,160 --> 01:06:31,920
Speaker 2: is what centrist? What is what is the definite? I'm

1341
01:06:31,960 --> 01:06:33,720
Speaker 2: curious people use the word centrist.

1342
01:06:33,960 --> 01:06:35,480
Speaker 1: I don't use it as a pejorative.

1343
01:06:35,560 --> 01:06:37,360
Speaker 2: Some people do. I think people use it as a

1344
01:06:37,480 --> 01:06:38,000
Speaker 2: for me.

1345
01:06:38,280 --> 01:06:42,560
Speaker 1: Centrist is you're basically happy with how things are status

1346
01:06:42,560 --> 01:06:46,000
Speaker 1: and you're satisfied with the changes you want to make,

1347
01:06:46,280 --> 01:06:48,560
Speaker 1: being really on the fringes.

1348
01:06:49,000 --> 01:06:50,040
Speaker 2: You're an incrementalist.

1349
01:06:50,280 --> 01:06:53,000
Speaker 1: Yeah, and incrementalism I'm okay with. I mean, Ted Kennedy

1350
01:06:53,040 --> 01:06:55,400
Speaker 1: was an incrementalist and he had a lot of incremental

1351
01:06:55,440 --> 01:06:58,640
Speaker 1: successes that he's spearheaded in the Senate. But it's things

1352
01:06:58,720 --> 01:07:01,680
Speaker 1: are basically fine, and I don't want to change much

1353
01:07:01,680 --> 01:07:03,720
Speaker 1: of anything. I think we need more than that. I'm

1354
01:07:03,760 --> 01:07:07,880
Speaker 1: not socialism, have and I'm certainly not communism, but I'm

1355
01:07:07,880 --> 01:07:09,880
Speaker 1: also not like things are basically fine.

1356
01:07:10,360 --> 01:07:11,400
Speaker 2: Radical centrism.

1357
01:07:12,120 --> 01:07:15,400
Speaker 1: Yeah, I've never met one, have you met? I don't

1358
01:07:15,400 --> 01:07:15,920
Speaker 1: know what was?

1359
01:07:16,040 --> 01:07:19,080
Speaker 3: What was Obama in this? And how would we describe

1360
01:07:19,200 --> 01:07:19,720
Speaker 3: him today?

1361
01:07:19,840 --> 01:07:21,320
Speaker 1: Oh boy, depends who you ask.

1362
01:07:21,440 --> 01:07:23,680
Speaker 3: Yeah, you know, I mean, I mean he defends the

1363
01:07:24,040 --> 01:07:27,120
Speaker 3: incremental side of Obamacare. He didn't get everything, but he

1364
01:07:27,160 --> 01:07:29,680
Speaker 3: makes the point we made progress. Don't make enemy that

1365
01:07:29,840 --> 01:07:33,120
Speaker 3: you know, a perfect the enemy. The good framework is

1366
01:07:33,160 --> 01:07:36,120
Speaker 3: that that that that with that play well today.

1367
01:07:35,880 --> 01:07:39,280
Speaker 1: And today it's playing pretty poorly with the left part

1368
01:07:39,360 --> 01:07:42,160
Speaker 1: of the base. I mean, I'm when I in my

1369
01:07:42,200 --> 01:07:45,040
Speaker 1: first book, I talked about the successes of incrementalism, and

1370
01:07:45,080 --> 01:07:47,640
Speaker 1: if you look at the three big eras of advancement

1371
01:07:47,680 --> 01:07:49,520
Speaker 1: for the left in the United States, which were the

1372
01:07:49,520 --> 01:07:52,520
Speaker 1: Progressive era in the early twentieth century, you looked at

1373
01:07:52,640 --> 01:07:55,320
Speaker 1: the New Deal era after World War Two, and you

1374
01:07:55,360 --> 01:07:59,040
Speaker 1: looked at the Civil Rights era. In retrospect, it feels

1375
01:07:59,080 --> 01:08:02,240
Speaker 1: like big change and it was hugely significant changes, but

1376
01:08:02,360 --> 01:08:04,840
Speaker 1: at the time it was a lot of Hey, we

1377
01:08:04,880 --> 01:08:08,439
Speaker 1: got a Supreme Court pick who ten years from now

1378
01:08:08,600 --> 01:08:10,760
Speaker 1: is going to be part of a really important decision

1379
01:08:10,960 --> 01:08:13,640
Speaker 1: either on women's voting or on civil rights or et cetera.

1380
01:08:13,880 --> 01:08:17,519
Speaker 1: It's we've made another tweak to the programs of FDR.

1381
01:08:18,160 --> 01:08:21,600
Speaker 1: So the incrementalism has a pretty strong track record in

1382
01:08:21,640 --> 01:08:25,639
Speaker 1: the United States. It's it's okay to go seemingly slowly

1383
01:08:26,280 --> 01:08:28,320
Speaker 1: as long as you're going in the right direction and

1384
01:08:28,360 --> 01:08:32,520
Speaker 1: you're not basically done making the changes. I'm okay with incrementalism.

1385
01:08:32,560 --> 01:08:35,960
Speaker 1: And I often say to the accelerationists who say we've

1386
01:08:35,960 --> 01:08:39,519
Speaker 1: got to take all businesses and make them government controlled housing,

1387
01:08:39,520 --> 01:08:42,479
Speaker 1: et cetera. Break it all down. I asked them for

1388
01:08:42,520 --> 01:08:46,200
Speaker 1: examples of where that has worked, and so far, nobody's

1389
01:08:46,200 --> 01:08:48,880
Speaker 1: given me any What did you do?

1390
01:08:49,360 --> 01:08:53,560
Speaker 3: Was was Biden's biggest challenge communication.

1391
01:08:53,840 --> 01:08:56,040
Speaker 1: Was he an incrementalist? Was he a centrist?

1392
01:08:56,120 --> 01:08:59,200
Speaker 3: These you think universally people describe them quote unquote as

1393
01:08:59,200 --> 01:09:05,320
Speaker 3: a centrist. But did his policies suggest that or was

1394
01:09:05,360 --> 01:09:07,280
Speaker 3: it the rhetoric the style.

1395
01:09:07,680 --> 01:09:11,439
Speaker 1: I think Biden's style made him seem like a status

1396
01:09:11,520 --> 01:09:15,160
Speaker 1: quo guy. But he ran, on paper to the left

1397
01:09:15,280 --> 01:09:18,720
Speaker 1: of where President Obama ran both in twenty eight and

1398
01:09:18,760 --> 01:09:21,719
Speaker 1: twenty twelve. Times had changed, right and it was twelve

1399
01:09:21,800 --> 01:09:26,080
Speaker 1: years later, eight years later, But I think in policy

1400
01:09:26,760 --> 01:09:30,760
Speaker 1: President Biden was not really just a status quo centrist.

1401
01:09:30,880 --> 01:09:33,320
Speaker 1: He didn't get as much done as I think he

1402
01:09:33,360 --> 01:09:37,360
Speaker 1: would have liked to. But I don't I think he is.

1403
01:09:37,960 --> 01:09:42,160
Speaker 1: He's center left, a step towards left of that, I

1404
01:09:42,160 --> 01:09:42,959
Speaker 1: guess I would.

1405
01:09:42,720 --> 01:09:43,320
Speaker 2: Say, right.

1406
01:09:43,360 --> 01:09:45,639
Speaker 3: So, No, it's just interesting to me because I think about,

1407
01:09:46,000 --> 01:09:49,320
Speaker 3: you know, you know, an industrial policy that's worker centered.

1408
01:09:50,160 --> 01:09:53,519
Speaker 3: Biden delivered on that. I mean that there's populism to that.

1409
01:09:53,880 --> 01:09:54,760
Speaker 2: I mean it's one of the most.

1410
01:09:54,960 --> 01:09:58,560
Speaker 3: America first, you know, America buy America products, first, a

1411
01:09:58,640 --> 01:10:00,160
Speaker 3: framework around actually.

1412
01:10:00,200 --> 01:10:01,799
Speaker 2: Living wages and union wages.

1413
01:10:01,840 --> 01:10:04,400
Speaker 3: The guy walk picket lines, save pensions. I mean, he

1414
01:10:04,520 --> 01:10:07,160
Speaker 3: was a populist in that respect and actually delivered on

1415
01:10:07,160 --> 01:10:09,960
Speaker 3: all those things. Sort of interesting to me. I mean,

1416
01:10:10,000 --> 01:10:12,599
Speaker 3: what would you do back to the policies, not the rhetoric.

1417
01:10:12,720 --> 01:10:13,240
Speaker 2: What would you do.

1418
01:10:13,320 --> 01:10:15,160
Speaker 3: You would try to mimic some of those things. You

1419
01:10:15,360 --> 01:10:17,439
Speaker 3: take the chips and science, actually try to bring supply

1420
01:10:17,560 --> 01:10:19,080
Speaker 3: chains back home. You would try to focus on the

1421
01:10:19,120 --> 01:10:22,040
Speaker 3: blue collar workers. You try to deliver on low carbon,

1422
01:10:22,080 --> 01:10:23,600
Speaker 3: green growth. I mean, the Green New Deal in so

1423
01:10:23,600 --> 01:10:27,599
Speaker 3: many respects was reflected in his policies in terms of

1424
01:10:27,760 --> 01:10:31,080
Speaker 3: the incentives and the tax structures that he provided. Those

1425
01:10:31,120 --> 01:10:33,960
Speaker 3: seem to be a lot of things that the left

1426
01:10:34,040 --> 01:10:38,800
Speaker 3: is promoting that he actually delivered. Situationally, I think on

1427
01:10:38,800 --> 01:10:40,280
Speaker 3: that That's where I'm trying to sort of figure out

1428
01:10:40,360 --> 01:10:42,439
Speaker 3: is But was he the sellout?

1429
01:10:42,760 --> 01:10:44,160
Speaker 2: I mean, what am I missing on that?

1430
01:10:44,360 --> 01:10:47,599
Speaker 1: No? I think he President Biden was probably the most

1431
01:10:47,800 --> 01:10:53,120
Speaker 1: pro organized labor president in my lifetime, probably, But I mean,

1432
01:10:53,160 --> 01:10:57,280
Speaker 1: for a while only president to walk an active picket line.

1433
01:10:57,360 --> 01:11:02,120
Speaker 1: It's sort of lame. And to say he was limited

1434
01:11:02,360 --> 01:11:05,760
Speaker 1: by the House and Senate and the political environment in

1435
01:11:05,800 --> 01:11:08,200
Speaker 1: what he could get done. But that is a reality

1436
01:11:08,320 --> 01:11:12,640
Speaker 1: to some degree. It's hard, you know, but Biden was not,

1437
01:11:13,200 --> 01:11:16,880
Speaker 1: from a personality standpoint, the type of person that would

1438
01:11:16,960 --> 01:11:19,960
Speaker 1: get the further left excited even if he delivered on

1439
01:11:20,000 --> 01:11:22,920
Speaker 1: some important Yeah. I think that's the truth of it.

1440
01:11:23,160 --> 01:11:27,040
Speaker 3: So that gets to just back to style rhetoric, the

1441
01:11:27,080 --> 01:11:30,639
Speaker 3: ability to communicate, the ability to communicate in this new

1442
01:11:31,000 --> 01:11:36,440
Speaker 3: medium that we need to quote unquote pay attention to clips, virality,

1443
01:11:36,920 --> 01:11:41,520
Speaker 3: social media, mom donnings, ascendancy. So much of that attached

1444
01:11:42,000 --> 01:11:44,880
Speaker 3: to his appeal in that space, So much of AOC's

1445
01:11:45,080 --> 01:11:49,400
Speaker 3: appeal in that space. Obviously the movement that is, you know,

1446
01:11:49,520 --> 01:11:53,639
Speaker 3: was Howard Dean was, you know, my Barack Obama dot com?

1447
01:11:53,760 --> 01:11:58,160
Speaker 3: Self organized communities that is all things Bernie Sanders. So

1448
01:11:58,280 --> 01:12:01,679
Speaker 3: much of that again is self organized and is driven

1449
01:12:01,720 --> 01:12:05,920
Speaker 3: by these algorithms, driven by these clips virality, driven by

1450
01:12:05,960 --> 01:12:07,759
Speaker 3: these filter bubbles as well.

1451
01:12:08,080 --> 01:12:10,080
Speaker 1: So is that I mean, what do we learn?

1452
01:12:10,120 --> 01:12:13,439
Speaker 3: What's the takeaway as we start to knit together what

1453
01:12:13,560 --> 01:12:16,639
Speaker 3: you're communicating here that we all need to pay attention

1454
01:12:16,680 --> 01:12:20,360
Speaker 3: to in terms of how are you know we've moved

1455
01:12:20,400 --> 01:12:22,960
Speaker 3: from search to suggest and how all of a sudden,

1456
01:12:23,320 --> 01:12:28,920
Speaker 3: now our behaviors are not only just commoditized, but we're

1457
01:12:28,920 --> 01:12:32,120
Speaker 3: becoming perfect, perfect little sheep in some respects to the machine.

1458
01:12:32,120 --> 01:12:35,439
Speaker 3: How do we start to knit together a frame around

1459
01:12:35,680 --> 01:12:41,519
Speaker 3: restoring and repairing our democracy, democratizing our economy so we

1460
01:12:41,520 --> 01:12:44,960
Speaker 3: can save our democracy, uh, and knit back a political

1461
01:12:45,360 --> 01:12:48,800
Speaker 3: framework that actually could build a majority into still a

1462
01:12:48,840 --> 01:12:52,479
Speaker 3: sense of well being at a time we're so desperate

1463
01:12:52,920 --> 01:12:57,200
Speaker 3: to you know, just just take a deep breath and

1464
01:12:57,240 --> 01:12:57,800
Speaker 3: breathe again.

1465
01:12:58,280 --> 01:13:01,040
Speaker 1: I think at the individual level, people should understand how

1466
01:13:01,040 --> 01:13:04,400
Speaker 1: they're being manipulated by these algorithms. That's something every single

1467
01:13:04,400 --> 01:13:07,880
Speaker 1: person who's on these platforms should do. Democrats, the left,

1468
01:13:08,240 --> 01:13:12,040
Speaker 1: elected officials, candidates need to become better at using these platforms.

1469
01:13:12,520 --> 01:13:16,639
Speaker 1: And I don't think there's any you know, moral high

1470
01:13:16,680 --> 01:13:19,200
Speaker 1: ground to be gained by saying we're not going to

1471
01:13:19,280 --> 01:13:21,559
Speaker 1: do that and then we'll just lose. I don't think

1472
01:13:21,560 --> 01:13:23,719
Speaker 1: that's good for the average person living in this country.

1473
01:13:23,760 --> 01:13:25,559
Speaker 1: I don't think that's good for anybody that just seeds

1474
01:13:25,600 --> 01:13:28,920
Speaker 1: power to some of the worst people. The difficult one

1475
01:13:28,960 --> 01:13:33,760
Speaker 1: is the regulation piece. There are really varied appetites as

1476
01:13:33,479 --> 01:13:38,960
Speaker 1: to what degree should there be regulation of AI, large

1477
01:13:39,040 --> 01:13:42,360
Speaker 1: language models and all of this stuff. I don't know

1478
01:13:42,439 --> 01:13:45,840
Speaker 1: that there. I don't believe the immediate solution is going

1479
01:13:45,880 --> 01:13:49,000
Speaker 1: to come from regulation, especially with the people that are

1480
01:13:49,000 --> 01:13:51,840
Speaker 1: in power right now, and so it would be nice

1481
01:13:51,840 --> 01:13:54,280
Speaker 1: to have a regulatory framework that makes sense. You know

1482
01:13:54,360 --> 01:13:59,080
Speaker 1: Neil Postman, who is a technologist, he would write, time

1483
01:13:59,200 --> 01:14:02,920
Speaker 1: spent a pose new technologies is basically worthless. This is

1484
01:14:02,960 --> 01:14:07,280
Speaker 1: my paraphrasing. What society needs to do is figure out

1485
01:14:07,280 --> 01:14:10,480
Speaker 1: the right type and level of regulation of new technologies

1486
01:14:10,920 --> 01:14:14,280
Speaker 1: and how to maximize the good while limiting the bad.

1487
01:14:14,680 --> 01:14:18,040
Speaker 1: That's essentially my view on these algorithms, these platforms, and

1488
01:14:18,160 --> 01:14:21,679
Speaker 1: on AI. I don't think that the idea of stopping

1489
01:14:21,720 --> 01:14:25,000
Speaker 1: them dead in their tracks and eliminating them is even plausible.

1490
01:14:25,200 --> 01:14:28,519
Speaker 1: And no matter what the United States does, some other

1491
01:14:28,560 --> 01:14:30,720
Speaker 1: countries aren't going to do that, and it's going to

1492
01:14:30,760 --> 01:14:32,760
Speaker 1: be there, it's going to spread. So I would rather

1493
01:14:32,920 --> 01:14:36,240
Speaker 1: skip to the let's maximize the good, figure out what

1494
01:14:36,360 --> 01:14:38,600
Speaker 1: level of regulation we need to limit the bad, and

1495
01:14:38,880 --> 01:14:41,200
Speaker 1: educate people. I mean a lot of kids don't even

1496
01:14:41,240 --> 01:14:44,639
Speaker 1: get media literacy anymore at all. It's just not taught

1497
01:14:44,680 --> 01:14:47,840
Speaker 1: in school. Educate people, so that they understand how these

1498
01:14:47,840 --> 01:14:51,400
Speaker 1: algorithms work. We have a sort of understanding that advertising

1499
01:14:51,439 --> 01:14:54,920
Speaker 1: wants to influence us. When we see advertising messages when

1500
01:14:54,960 --> 01:14:57,640
Speaker 1: we recognize them. Sometimes they're hidden, but when we see advertising,

1501
01:14:57,880 --> 01:15:00,800
Speaker 1: we understand this is an influence cam pain to get

1502
01:15:00,880 --> 01:15:03,479
Speaker 1: me to believe something, buy something a service product. If

1503
01:15:03,520 --> 01:15:05,040
Speaker 1: your kid go and tell mom and dad, this is

1504
01:15:05,040 --> 01:15:07,240
Speaker 1: what I want. We need people to understand how the

1505
01:15:07,280 --> 01:15:10,080
Speaker 1: algorithms work and the platforms in the same way, so

1506
01:15:10,120 --> 01:15:14,000
Speaker 1: that they realize this is not just naturally surfacing content

1507
01:15:14,040 --> 01:15:16,919
Speaker 1: to my interest. This is stuff that is being ABC

1508
01:15:17,120 --> 01:15:21,800
Speaker 1: tested constantly for emotional salience and attachment and then fed

1509
01:15:21,840 --> 01:15:24,559
Speaker 1: to you. And if people understood that a lot of

1510
01:15:24,560 --> 01:15:26,720
Speaker 1: these manipulations would be less effective.

1511
01:15:26,880 --> 01:15:28,680
Speaker 3: So this is your prescription as the head of the

1512
01:15:28,800 --> 01:15:33,200
Speaker 3: DNC that we take advantage of these tools. We don't

1513
01:15:33,240 --> 01:15:37,600
Speaker 3: act taller than thou. We recognize that we deal with

1514
01:15:37,640 --> 01:15:40,800
Speaker 3: the cards that have been dealt. Absolutely, we're pragmatists. Have

1515
01:15:40,920 --> 01:15:43,760
Speaker 3: to be and listen. I think that there are campaigns

1516
01:15:43,840 --> 01:15:44,760
Speaker 3: that have figured it out.

1517
01:15:44,840 --> 01:15:46,680
Speaker 1: There are elected officials that have figured it out, that

1518
01:15:46,720 --> 01:15:48,680
Speaker 1: have really good digital offices. I mean, I think what

1519
01:15:48,720 --> 01:15:51,040
Speaker 1: your office has done with the reflecting back to Trump,

1520
01:15:51,320 --> 01:15:55,920
Speaker 1: the way he communicates has been interesting. And it's when

1521
01:15:55,960 --> 01:15:58,600
Speaker 1: you see that right all caps, Gavin, seeing you some

1522
01:15:58,680 --> 01:16:01,680
Speaker 1: all that stuff, it trigger something where it's like, oh,

1523
01:16:01,720 --> 01:16:04,599
Speaker 1: I recognize this style. Oh but it's not Trump. At

1524
01:16:04,680 --> 01:16:08,560
Speaker 1: least people are stopping and thinking and that's something, And

1525
01:16:09,120 --> 01:16:11,559
Speaker 1: so I think that being creative about that is important.

1526
01:16:11,680 --> 01:16:15,600
Speaker 3: Yeah. No, well I obviously appreciate that. What you know,

1527
01:16:15,640 --> 01:16:18,600
Speaker 3: what it just as we you know what, what do

1528
01:16:18,600 --> 01:16:23,560
Speaker 3: you hope people will appreciate about this book? What ultimately is?

1529
01:16:23,560 --> 01:16:25,879
Speaker 3: Is it just to illuminate? It is to change behavior?

1530
01:16:25,920 --> 01:16:27,680
Speaker 3: Is it to sort of begin to act with the

1531
01:16:27,760 --> 01:16:30,639
Speaker 3: kind of friction that you try to highlight in here?

1532
01:16:30,760 --> 01:16:33,240
Speaker 2: Is it to step outside? Take it deep? I mean,

1533
01:16:33,280 --> 01:16:34,960
Speaker 2: what's what's the ultimate.

1534
01:16:35,120 --> 01:16:38,000
Speaker 1: Action that you hope this inspires?

1535
01:16:38,000 --> 01:16:41,160
Speaker 3: You didn't just write it for the intellectual exercise.

1536
01:16:41,160 --> 01:16:43,760
Speaker 2: I'm you're you're a doer, not just a dreamer in

1537
01:16:43,760 --> 01:16:45,960
Speaker 2: that respect. What what's the takeaway?

1538
01:16:46,040 --> 01:16:49,000
Speaker 1: I think three things, depending on the position people are in. One,

1539
01:16:49,040 --> 01:16:52,000
Speaker 1: if you're just an individual on these platforms or you

1540
01:16:52,000 --> 01:16:54,400
Speaker 1: have kids who are on these platforms, you have to

1541
01:16:54,479 --> 01:16:56,519
Speaker 1: understand how they work and how they're trying to influence

1542
01:16:56,560 --> 01:16:58,200
Speaker 1: you in order to take control of them. So that's

1543
01:16:58,280 --> 01:17:02,000
Speaker 1: number one. Number two, when it comes to the political system,

1544
01:17:02,000 --> 01:17:04,599
Speaker 1: which I have an interest in, I want good people

1545
01:17:04,600 --> 01:17:07,880
Speaker 1: in power putting in policies that I want that I

1546
01:17:07,880 --> 01:17:11,200
Speaker 1: think are good policies for people. That group needs to

1547
01:17:11,640 --> 01:17:14,760
Speaker 1: also get better at using these platforms. That's number two.

1548
01:17:15,439 --> 01:17:18,599
Speaker 1: And then number three understanding at a systemic level why

1549
01:17:18,640 --> 01:17:21,280
Speaker 1: the right has been better at this, because if you

1550
01:17:21,280 --> 01:17:23,880
Speaker 1: don't understand that, you can't possibly change it. So those

1551
01:17:23,920 --> 01:17:24,719
Speaker 1: are the three things.

1552
01:17:25,800 --> 01:17:32,400
Speaker 3: Is politics, don't we also need to just politics has

1553
01:17:32,439 --> 01:17:34,720
Speaker 3: infected every part of our life, hasn't it. Yes, I

1554
01:17:34,800 --> 01:17:37,040
Speaker 3: mean we talked about Trump, we were talking about obviously

1555
01:17:37,040 --> 01:17:41,040
Speaker 3: the world. I mean I used to love sports because

1556
01:17:41,080 --> 01:17:43,400
Speaker 3: it wasn't political. It's one place to get good brief bread.

1557
01:17:43,400 --> 01:17:45,840
Speaker 3: And now it's everything thinks political. You can have a

1558
01:17:45,840 --> 01:17:48,880
Speaker 3: conversation our lives. So fishing is political and what fill

1559
01:17:48,880 --> 01:17:50,880
Speaker 3: in the blank, whatever the issue is, it has now

1560
01:17:50,880 --> 01:17:53,639
Speaker 3: it's become I mean is that also something we need

1561
01:17:53,680 --> 01:17:55,000
Speaker 3: to start to address fundamentally?

1562
01:17:55,120 --> 01:17:57,720
Speaker 1: Yeah, I think we need a detox I polish I

1563
01:17:57,760 --> 01:18:01,240
Speaker 1: could say, I think politics has been more for longer

1564
01:18:01,280 --> 01:18:04,639
Speaker 1: than maybe we want to acknowledge. But what we've lost

1565
01:18:05,040 --> 01:18:09,040
Speaker 1: is the ability to have disagreements that don't need to

1566
01:18:09,200 --> 01:18:13,080
Speaker 1: ruin interpersonal relationships, and that I think. You know, there's

1567
01:18:13,080 --> 01:18:15,720
Speaker 1: a lot of people now who are very uncomfortable with

1568
01:18:15,760 --> 01:18:18,200
Speaker 1: the fact that there's a disagreement. And sometimes I'll say,

1569
01:18:18,439 --> 01:18:20,320
Speaker 1: you know, I know X person in real life and

1570
01:18:20,400 --> 01:18:23,000
Speaker 1: we disagree, but we're able to get along. How is

1571
01:18:23,040 --> 01:18:27,559
Speaker 1: that possible? Well, because there's multiple dimensions to people, and

1572
01:18:27,800 --> 01:18:30,360
Speaker 1: maybe you don't relate to someone as an elected official,

1573
01:18:30,400 --> 01:18:32,280
Speaker 1: but you relate to them as a parent, or you

1574
01:18:32,320 --> 01:18:35,360
Speaker 1: relate to them as a Latino person or in some

1575
01:18:35,479 --> 01:18:39,599
Speaker 1: other way. And it's become very toxic, accelerated by these

1576
01:18:39,640 --> 01:18:42,400
Speaker 1: platforms where because all you do is argue on Twitter.

1577
01:18:43,000 --> 01:18:46,000
Speaker 1: When you get together and there's a sporting event or

1578
01:18:46,040 --> 01:18:49,080
Speaker 1: an entertainment thing, the assumption is we have to have

1579
01:18:49,120 --> 01:18:51,320
Speaker 1: bad blood and we can't just sit in the same room.

1580
01:18:51,680 --> 01:18:54,120
Speaker 1: We've got to do away with that, and again, the

1581
01:18:54,160 --> 01:18:57,960
Speaker 1: whole the interactions online are toxic. The interactions in person

1582
01:18:58,000 --> 01:19:01,200
Speaker 1: are very polite and respectful. I think the in person

1583
01:19:01,240 --> 01:19:02,600
Speaker 1: has a lot to do with that.

1584
01:19:02,720 --> 01:19:05,320
Speaker 3: Do you think there's a business model for point counterpoint

1585
01:19:05,360 --> 01:19:08,599
Speaker 3: crossfire today? Or is just I don't want to hear

1586
01:19:08,640 --> 01:19:12,479
Speaker 3: the other side. I mean, honestly, as a business proposition.

1587
01:19:12,000 --> 01:19:14,479
Speaker 1: There are a lot of shows where were a lot

1588
01:19:14,520 --> 01:19:16,560
Speaker 1: of show going back and forth. There's a lot of

1589
01:19:16,560 --> 01:19:19,160
Speaker 1: shows out there like that. Right now, I think that

1590
01:19:19,240 --> 01:19:22,719
Speaker 1: they are diminishing a little bit. A year to eighteen

1591
01:19:22,760 --> 01:19:27,040
Speaker 1: months ago, I would have said these inflammatory debates, and

1592
01:19:27,120 --> 01:19:29,240
Speaker 1: some of them are one on one, some are four

1593
01:19:29,320 --> 01:19:31,559
Speaker 1: on four, some are one on twenty. This is what

1594
01:19:31,600 --> 01:19:34,759
Speaker 1: people want. The thing about debates that I've talked about

1595
01:19:34,920 --> 01:19:37,960
Speaker 1: is that they rarely are adjudications of who's right, are

1596
01:19:37,960 --> 01:19:41,880
Speaker 1: the best ideas? There are adjudications of who's most articulate

1597
01:19:42,240 --> 01:19:45,479
Speaker 1: and most prepared for the debate true, and that might

1598
01:19:45,600 --> 01:19:48,920
Speaker 1: line up with what's right and what's true. But the algorithms,

1599
01:19:48,960 --> 01:19:51,320
Speaker 1: as we find out, they don't surface what's accurate. They

1600
01:19:51,320 --> 01:19:54,040
Speaker 1: surface what gets an emotional reaction from people. So I

1601
01:19:54,080 --> 01:19:56,280
Speaker 1: don't know that that's the way to figure out.

1602
01:19:56,080 --> 01:19:56,720
Speaker 2: What we need to do.

1603
01:19:56,880 --> 01:19:58,519
Speaker 3: It's so true about I mean, I just think about

1604
01:19:58,520 --> 01:20:00,960
Speaker 3: debates that I've been I did one Ron DeSantis and

1605
01:20:01,000 --> 01:20:03,719
Speaker 3: again back into the filter bubble. A few people actually

1606
01:20:03,800 --> 01:20:07,240
Speaker 3: watched the entire thing. What most people said that they

1607
01:20:07,240 --> 01:20:10,000
Speaker 3: watched it, they saw the clips that were shared within

1608
01:20:10,040 --> 01:20:15,280
Speaker 3: their feed with only reinforced and expressed their pre existing bias.

1609
01:20:15,720 --> 01:20:17,600
Speaker 3: So the point of view is you got crushed or

1610
01:20:17,880 --> 01:20:22,400
Speaker 3: you crushed it. When there's nuance, there's and we've lost

1611
01:20:22,479 --> 01:20:25,240
Speaker 3: so much of that nuance. But again, nuance doesn't sell.

1612
01:20:25,439 --> 01:20:29,000
Speaker 1: I remember watching the entire thing, and there actually was

1613
01:20:29,240 --> 01:20:33,679
Speaker 1: some deeper discussion of policy, which I found interesting missing

1614
01:20:33,760 --> 01:20:35,960
Speaker 1: from all of the clips that each side made to

1615
01:20:36,040 --> 01:20:38,559
Speaker 1: kind of reinforce. Yeah, it's I don't know how we

1616
01:20:38,640 --> 01:20:42,120
Speaker 1: move forward on what's best for the country when that's

1617
01:20:42,160 --> 01:20:43,880
Speaker 1: the kind of media environment that we live in.

1618
01:20:44,080 --> 01:20:47,040
Speaker 3: Well, you were supposed to be able to answer that question,

1619
01:20:47,560 --> 01:20:50,559
Speaker 3: but you've just posed yet another question for your next book.

1620
01:20:50,600 --> 01:20:55,200
Speaker 3: But in September, this book, which technically is your next

1621
01:20:55,200 --> 01:20:58,040
Speaker 3: book already written, pay attention how the algorithms and media

1622
01:20:58,080 --> 01:21:03,120
Speaker 3: wars are suppressing truth and re wiring our brain.

1623
01:21:03,560 --> 01:21:05,360
Speaker 2: David, it's been great to have you, my pleasure. Thank

1624
01:21:05,400 --> 01:21:05,800
Speaker 2: you so much.

1625
01:21:05,880 --> 01:21:06,439
Speaker 1: Thanks for being