1
00:00:03,240 --> 00:00:05,200
Speaker 1: Welcome back to a Numbers Name with Ryan Gradski. Thank

2
00:00:05,200 --> 00:00:08,600
Speaker 1: you guys for being here. How many of you regret

3
00:00:08,720 --> 00:00:11,560
Speaker 1: your vote for Donald Trump? Who are my conservative listeners?

4
00:00:11,760 --> 00:00:14,000
Speaker 1: That's the question I want to pose to you in

5
00:00:14,040 --> 00:00:17,200
Speaker 1: this episode. If you listen to progressives in the media

6
00:00:17,360 --> 00:00:20,640
Speaker 1: or on television, somehow, they all have tons of friends

7
00:00:20,680 --> 00:00:22,880
Speaker 1: that voted for Trump in November and they just regret

8
00:00:22,880 --> 00:00:26,000
Speaker 1: if they can't live with themselves, they're so upset, they're like, wow,

9
00:00:26,040 --> 00:00:28,240
Speaker 1: we got a row. Maybe they'll support AOC in twenty

10
00:00:28,320 --> 00:00:32,440
Speaker 1: twenty eight. That's what the narrative is going into, you know,

11
00:00:32,479 --> 00:00:34,760
Speaker 1: the midterm elections. I have a lot of friends who

12
00:00:34,800 --> 00:00:37,120
Speaker 1: vote for Donald Trump, and I racked my brains ahead

13
00:00:37,120 --> 00:00:39,560
Speaker 1: of this podcast taping to say how many would have

14
00:00:39,560 --> 00:00:43,640
Speaker 1: switched their votes, And I'm I don't really know any.

15
00:00:43,760 --> 00:00:46,000
Speaker 1: And I'm sure there are a few who maybe maybe

16
00:00:46,080 --> 00:00:48,239
Speaker 1: not are vocalizing it, or certainly there's a lot who

17
00:00:48,280 --> 00:00:50,200
Speaker 1: don't agree with everything he does. I think that's everybody

18
00:00:50,240 --> 00:00:53,680
Speaker 1: doesn't everything that everyone does. But progressives in the media

19
00:00:53,840 --> 00:00:56,560
Speaker 1: are a treasure trove of people who are you know,

20
00:00:56,600 --> 00:00:59,840
Speaker 1: they have an endless supply of Trump voters who regret

21
00:00:59,880 --> 00:01:01,600
Speaker 1: it and won't do you know, they're going to do

22
00:01:01,680 --> 00:01:04,200
Speaker 1: better next time. They're not going to They're all Alissa Faras,

23
00:01:04,240 --> 00:01:06,000
Speaker 1: They're all going to sit there and just change their way.

24
00:01:06,000 --> 00:01:09,200
Speaker 1: Alissa Fair is a conservative on the view who voted

25
00:01:09,240 --> 00:01:12,560
Speaker 1: for Kamala But what does the data say? Fox News

26
00:01:12,640 --> 00:01:14,480
Speaker 1: is a poll out that was conducted by Beacon and

27
00:01:14,520 --> 00:01:16,680
Speaker 1: Shaw Research. They do all the Fox News polls and

28
00:01:16,720 --> 00:01:19,240
Speaker 1: they're you know, they're fine, They're good. The polls on

29
00:01:19,240 --> 00:01:21,880
Speaker 1: that Trump's approve writing stands at forty four percent favorable,

30
00:01:22,160 --> 00:01:25,319
Speaker 1: fifty six percent unfairble one of the better polls for

31
00:01:25,360 --> 00:01:27,559
Speaker 1: the president, I might say among people that have voted

32
00:01:27,560 --> 00:01:31,240
Speaker 1: for him. The number is eighty four percent approval writing.

33
00:01:31,760 --> 00:01:34,280
Speaker 1: That's almost identical to the eighty six percent in the

34
00:01:34,280 --> 00:01:36,840
Speaker 1: New York Times that they found just last week, eighty

35
00:01:36,840 --> 00:01:38,720
Speaker 1: one percent in You Go, of eighty seven percent in

36
00:01:38,800 --> 00:01:41,959
Speaker 1: Morning Consult and eighty six percent in the latest Emerson Pole.

37
00:01:42,720 --> 00:01:46,639
Speaker 1: Usually data drives narratives in the media. People in the media,

38
00:01:46,840 --> 00:01:49,680
Speaker 1: or you know, influencers will find special cross tabs. They'll

39
00:01:49,720 --> 00:01:52,320
Speaker 1: find a crossu they'll say, you know, they'll find a

40
00:01:52,320 --> 00:01:54,520
Speaker 1: cross tab of a pole that has a sample size

41
00:01:54,520 --> 00:01:57,520
Speaker 1: of twenty. You know, Black Americans, and fifty of them

42
00:01:57,520 --> 00:01:59,440
Speaker 1: will vote for Trump. Will say you swing, Trump's one

43
00:01:59,520 --> 00:02:01,160
Speaker 1: the majority of the Black vote, even though they're not

44
00:02:01,240 --> 00:02:04,760
Speaker 1: going to But they use these cross tabs with these

45
00:02:04,880 --> 00:02:08,560
Speaker 1: minor numbers just that they're in show that they're there

46
00:02:08,760 --> 00:02:12,520
Speaker 1: to have a narrative that's not this case. The cross

47
00:02:12,520 --> 00:02:16,160
Speaker 1: tabs are very almost nearly identical. Eighty six, eighty six,

48
00:02:16,280 --> 00:02:19,880
Speaker 1: eighty six, eighty seven that they support Donald Trump. I

49
00:02:19,880 --> 00:02:22,000
Speaker 1: think in eighty four is the other one. They support

50
00:02:22,000 --> 00:02:23,720
Speaker 1: Donald Trump. They voted for him. They're going to vote

51
00:02:23,720 --> 00:02:29,720
Speaker 1: for the Republican again in midterm elections. Nonetheless, the left

52
00:02:29,800 --> 00:02:32,600
Speaker 1: is really jumping on this and making something completely out

53
00:02:32,600 --> 00:02:38,080
Speaker 1: of whole cloth. They're offering something to liberal audiences because

54
00:02:38,080 --> 00:02:40,600
Speaker 1: they're still smarting over the election and they can't believe

55
00:02:40,720 --> 00:02:43,880
Speaker 1: still that they lost. I think losing the popular vote

56
00:02:43,919 --> 00:02:46,000
Speaker 1: was even worse than losing the White House. Because there

57
00:02:46,080 --> 00:02:49,000
Speaker 1: is a narrative among progressives that I like to listen

58
00:02:49,000 --> 00:02:51,760
Speaker 1: to progressives and social media so like that, and influencers

59
00:02:51,800 --> 00:02:54,560
Speaker 1: and mainstream media outlets. They like to have this narrative

60
00:02:54,600 --> 00:02:57,000
Speaker 1: saying there are more of them than there are, Sorry,

61
00:02:57,000 --> 00:02:58,840
Speaker 1: there's more of us than there are of them, that

62
00:02:58,880 --> 00:03:02,120
Speaker 1: there are more liberals there are of conservatives, and this

63
00:03:02,320 --> 00:03:07,640
Speaker 1: narrative persists among progressives to this day in spite of

64
00:03:07,680 --> 00:03:11,359
Speaker 1: the election results. So now the narrative is theyre won

65
00:03:11,400 --> 00:03:14,120
Speaker 1: the popular vote, maybe it was stolen. I mean, Kathy

66
00:03:14,120 --> 00:03:18,680
Speaker 1: Griffin and Rose o'donald, other celebrities, you know, comedians and

67
00:03:18,840 --> 00:03:21,160
Speaker 1: entertainers said the election might have instolen my a la musque.

68
00:03:21,360 --> 00:03:24,959
Speaker 1: That's their conspiracy. But the mainstream was was say, maybe, yeah,

69
00:03:25,080 --> 00:03:28,040
Speaker 1: they won the popular vote, but so many people have left,

70
00:03:28,320 --> 00:03:31,600
Speaker 1: you know, are banning him left and right, that it's

71
00:03:31,680 --> 00:03:34,040
Speaker 1: it's all over, you know, the walls have finally closing in,

72
00:03:34,080 --> 00:03:36,520
Speaker 1: and there are supporters now and now we have the majority,

73
00:03:36,560 --> 00:03:39,280
Speaker 1: and it's all a cope. If you look at the data,

74
00:03:39,640 --> 00:03:42,720
Speaker 1: it's only between ten to fifteen percent of Trump voters

75
00:03:42,760 --> 00:03:46,320
Speaker 1: have a disapproval of where Trump, of how Trump is

76
00:03:46,360 --> 00:03:51,000
Speaker 1: performing as the president. That mirrors past presidents. At the

77
00:03:51,080 --> 00:03:54,280
Speaker 1: end of January twenty fourteen, President Obama had a forty

78
00:03:54,320 --> 00:03:57,440
Speaker 1: percent of approval rating according to Gallup, and support among

79
00:03:57,520 --> 00:04:00,320
Speaker 1: Democrats was about eighty percent, and that among the penance

80
00:04:00,400 --> 00:04:04,680
Speaker 1: was thirty percent. That's very close where Donald Trump is today. Actually,

81
00:04:04,720 --> 00:04:07,760
Speaker 1: Trump has a higher level of support among his members

82
00:04:07,800 --> 00:04:11,560
Speaker 1: of his party than Obama had of Democrats. Other posters

83
00:04:11,600 --> 00:04:14,760
Speaker 1: at the time CNN Maris Pew Research all had Obama's

84
00:04:14,760 --> 00:04:18,000
Speaker 1: approve ratings at similar places. A lot of people are

85
00:04:18,040 --> 00:04:22,279
Speaker 1: working diligently to forecast the twenty twenty six mid terms,

86
00:04:22,400 --> 00:04:24,760
Speaker 1: trying to sit there and show this giant rebuke of

87
00:04:24,800 --> 00:04:28,120
Speaker 1: Trump by his own voters. Basically, Trump is Caesar and

88
00:04:28,160 --> 00:04:30,560
Speaker 1: the seventy seven point three million people of him that

89
00:04:30,640 --> 00:04:32,400
Speaker 1: vote for him were all brutus. They're all going to

90
00:04:32,400 --> 00:04:34,600
Speaker 1: sit there and stab him in the back. That is

91
00:04:34,640 --> 00:04:39,599
Speaker 1: so heavily overstated and so, you know, obviously false. They're

92
00:04:39,680 --> 00:04:42,000
Speaker 1: trying to say early on, there's going to be a

93
00:04:42,080 --> 00:04:45,039
Speaker 1: lesson to learn from people souring on Trump, And to

94
00:04:45,120 --> 00:04:47,960
Speaker 1: a degree, yeah, there's true. That's that's probably true. American

95
00:04:48,040 --> 00:04:50,839
Speaker 1: voters probably don't like one or two things that he's

96
00:04:50,880 --> 00:04:54,040
Speaker 1: doing in a large degree, especially on tariffs. Tariffs are

97
00:04:54,279 --> 00:04:56,760
Speaker 1: he is really really negative in tariffs on the polls.

98
00:04:57,320 --> 00:05:00,679
Speaker 1: But American voters are very fickle. They like the wind.

99
00:05:01,040 --> 00:05:03,760
Speaker 1: It's what they do, it's what we do. So don't

100
00:05:03,760 --> 00:05:06,359
Speaker 1: be fooled by this idea that a third or a

101
00:05:06,440 --> 00:05:08,640
Speaker 1: quarter of Trump's space is just leaving him. It's not.

102
00:05:09,040 --> 00:05:13,359
Speaker 1: It's actually much lower than past presence, including Obama. Progresses

103
00:05:13,400 --> 00:05:15,840
Speaker 1: are signaling to their voters by the way that they

104
00:05:15,839 --> 00:05:20,600
Speaker 1: are so outraged at what Trump's doing. And you know,

105
00:05:20,640 --> 00:05:23,080
Speaker 1: you have people like Mayor Jacob Fryes saying we're not

106
00:05:23,120 --> 00:05:26,560
Speaker 1: even going to work with ICE on deporting criminals that

107
00:05:26,600 --> 00:05:31,200
Speaker 1: Trump is. They've always say he's like a dictator, a Nazi,

108
00:05:31,240 --> 00:05:34,080
Speaker 1: the ICE is like Estapo's. But I want to remind

109
00:05:34,160 --> 00:05:38,160
Speaker 1: everybody that not that long ago, in my lifetime and

110
00:05:38,440 --> 00:05:40,919
Speaker 1: my lifetime where I was an adults, not a child,

111
00:05:41,160 --> 00:05:45,799
Speaker 1: Democrats sounded a lot like Republicans. They sounded a lot

112
00:05:45,839 --> 00:05:48,360
Speaker 1: like what Donald Trump says, not completely, but a lot

113
00:05:48,400 --> 00:05:51,360
Speaker 1: of it. Here's a Amy Klobuchar twenty years ago, two

114
00:05:51,400 --> 00:05:53,599
Speaker 1: thousand and six. I was an adult, and it's a

115
00:05:53,640 --> 00:05:56,239
Speaker 1: long time ago, but most people are voting. We're around

116
00:05:56,240 --> 00:05:58,080
Speaker 1: in two thousand and six and voting in two thousand

117
00:05:58,080 --> 00:06:01,480
Speaker 1: and six not only support a border fence or as

118
00:06:01,520 --> 00:06:04,760
Speaker 1: we all currently know, a border wall, but saying we

119
00:06:04,800 --> 00:06:07,440
Speaker 1: need to go after companies that hire illegal aliens in

120
00:06:07,480 --> 00:06:09,800
Speaker 1: the United States that hire illegals to do the jobs

121
00:06:09,880 --> 00:06:13,279
Speaker 1: quot unquote Americans won't do, Amy Klobachar, here's the clip

122
00:06:13,360 --> 00:06:14,720
Speaker 1: now is clobyshar.

123
00:06:14,920 --> 00:06:18,760
Speaker 2: Thursday, President Bush signed a law approving a seven hundred

124
00:06:18,760 --> 00:06:22,200
Speaker 2: mile fence on the US Mexican border. Is a fence

125
00:06:22,320 --> 00:06:26,000
Speaker 2: good immigration policy or just good politics.

126
00:06:27,240 --> 00:06:30,080
Speaker 3: I do believe that we need more resources at the border,

127
00:06:30,120 --> 00:06:32,960
Speaker 3: and that that includes offence. What we have now we

128
00:06:33,040 --> 00:06:37,159
Speaker 3: have people waiting to come in legally, thousands of people

129
00:06:37,160 --> 00:06:39,280
Speaker 3: waiting to come in legally to this country, and we

130
00:06:39,360 --> 00:06:42,480
Speaker 3: have people coming in illegally. That's not right. We need

131
00:06:42,520 --> 00:06:45,359
Speaker 3: to get order at the border. But we also have

132
00:06:45,480 --> 00:06:49,839
Speaker 3: to stop giving amnesty to companies that are hiring illegal immigrants.

133
00:06:50,360 --> 00:06:53,920
Speaker 3: Under this administration, the number of prosecutions of companies has

134
00:06:53,960 --> 00:06:56,200
Speaker 3: gone way down. That has to change.

135
00:06:56,279 --> 00:06:59,599
Speaker 1: The slide from Klobuchar in two thousand and six to

136
00:07:00,080 --> 00:07:05,280
Speaker 1: may Or Fry, to Abagail Spamberger to Amy Klobuchar, and

137
00:07:05,400 --> 00:07:08,800
Speaker 1: twenty twenty six to Chuck Schumer in twenty twenty six,

138
00:07:09,080 --> 00:07:13,080
Speaker 1: who was refusing to even turn over criminal aliens to

139
00:07:13,120 --> 00:07:15,480
Speaker 1: Ice is so dramatic, and it's the American people don't

140
00:07:15,520 --> 00:07:18,840
Speaker 1: want so if you hear Democrats in the media saying

141
00:07:18,880 --> 00:07:22,080
Speaker 1: that the midterms are abuke against Trump and specifically that

142
00:07:22,160 --> 00:07:26,240
Speaker 1: Americans really don't want enforcement of current immigration laws. They're lying,

143
00:07:26,600 --> 00:07:30,400
Speaker 1: plain and simple. Poll show at data shows it. Republicans

144
00:07:30,600 --> 00:07:35,120
Speaker 1: are not going to lose the mid terms because of immigration.

145
00:07:35,800 --> 00:07:38,720
Speaker 1: Republicans are likely to lose the mid terms because that's

146
00:07:38,720 --> 00:07:42,760
Speaker 1: political gravity in America. Political gravity says every other the

147
00:07:42,760 --> 00:07:45,320
Speaker 1: party loses, the swings against them, The nation swings against

148
00:07:45,320 --> 00:07:48,200
Speaker 1: the party in power. It just does. Even Biden, who

149
00:07:48,200 --> 00:07:50,720
Speaker 1: had a good midterm quote unquote good mid term, still

150
00:07:50,760 --> 00:07:53,800
Speaker 1: lost the House. Speaking of immigration and elections, let's talk

151
00:07:53,800 --> 00:07:57,760
Speaker 1: about what's going on overseas, specifically in Spain, because this

152
00:07:57,840 --> 00:08:00,920
Speaker 1: is a preview of what's going to happen in America

153
00:08:01,000 --> 00:08:04,280
Speaker 1: if the Democrats win back all three branches of the government.

154
00:08:04,760 --> 00:08:07,360
Speaker 1: Spain is a parliamentary system and the government is governed

155
00:08:07,400 --> 00:08:10,360
Speaker 1: by the Spanish Socialist Workers' Party. Though they are not

156
00:08:10,400 --> 00:08:12,280
Speaker 1: the largest party, they are a minority party and they

157
00:08:12,320 --> 00:08:14,480
Speaker 1: work with other far left parties to sit there and

158
00:08:14,520 --> 00:08:18,160
Speaker 1: have a government. Well, they're likely to lose their next election,

159
00:08:18,200 --> 00:08:21,440
Speaker 1: which is in twenty twenty seven. Polls show them sinking

160
00:08:21,480 --> 00:08:24,200
Speaker 1: they're currently twenty six percent of the polls. They used

161
00:08:24,200 --> 00:08:26,720
Speaker 1: to be a thirty two percent. And the Vox Party,

162
00:08:26,760 --> 00:08:31,480
Speaker 1: which is a nationalist conservative party much like Georgia Maloney,

163
00:08:31,560 --> 00:08:35,520
Speaker 1: much like Reform UK, much like Marine Leapen. They are

164
00:08:35,559 --> 00:08:37,920
Speaker 1: surging in the polls. They're in third place, but they're

165
00:08:38,080 --> 00:08:40,240
Speaker 1: very close to being in second, with the center right

166
00:08:40,280 --> 00:08:45,080
Speaker 1: Conservative Party being in first, so facing an oncoming defeat

167
00:08:45,240 --> 00:08:49,000
Speaker 1: and the surging Box Party. What has the Spanish Prime

168
00:08:49,040 --> 00:08:51,880
Speaker 1: Minister and his Socialist party decided to do. They are

169
00:08:51,960 --> 00:08:56,319
Speaker 1: legalizing and giving an ambassy to five hundred thousand illegal aliens,

170
00:08:56,320 --> 00:08:59,199
Speaker 1: which is gigantic in a country the size of Spain.

171
00:08:59,360 --> 00:09:01,440
Speaker 1: This is from the Telegraph in the UK. Spain has

172
00:09:01,480 --> 00:09:05,000
Speaker 1: started to legalize five hundred thousand undocumented migrants and give

173
00:09:05,040 --> 00:09:08,120
Speaker 1: them immediate right to work in a move to quote

174
00:09:08,280 --> 00:09:11,600
Speaker 1: fight against the advance of the far right end quote,

175
00:09:11,679 --> 00:09:14,640
Speaker 1: a government spokesman said, we not only intend to remain

176
00:09:14,679 --> 00:09:16,800
Speaker 1: a beacon, but I want to believe that we are.

177
00:09:16,960 --> 00:09:19,240
Speaker 1: We will be a seed and a germ to fight

178
00:09:19,280 --> 00:09:21,320
Speaker 1: against the advance of the far right wave that is

179
00:09:21,320 --> 00:09:23,760
Speaker 1: trying to gain ground and against do everything in our

180
00:09:23,800 --> 00:09:26,120
Speaker 1: power to stop it. The other far left party is

181
00:09:26,160 --> 00:09:29,959
Speaker 1: called pedomas they said the legislation would help dismantle institutional

182
00:09:30,080 --> 00:09:34,040
Speaker 1: racism that fuels the explosion of racist hatred, while the

183
00:09:34,080 --> 00:09:36,559
Speaker 1: government casts the move as a political challenge to the

184
00:09:36,640 --> 00:09:39,160
Speaker 1: right wing Box Party, which has been steadily rising in

185
00:09:39,160 --> 00:09:42,040
Speaker 1: the polls under the scheme, this is important. Under the scheme,

186
00:09:42,080 --> 00:09:44,560
Speaker 1: illegal aliens and asylum seekers and those who've been living

187
00:09:44,559 --> 00:09:48,880
Speaker 1: in Spain for five months since December verse twenty twenty

188
00:09:48,920 --> 00:09:51,640
Speaker 1: five will be eligible to apply for legal status at

189
00:09:51,679 --> 00:09:54,520
Speaker 1: the beginning of April and June thirtieth of this year.

190
00:09:54,559 --> 00:09:57,880
Speaker 1: Applicants with the criminal records will be excluded. Applicants will

191
00:09:57,880 --> 00:10:02,120
Speaker 1: be assessed within fifteen days after. A successful candidate will

192
00:10:02,120 --> 00:10:05,040
Speaker 1: be allowed to work in any sector, anywhere and Spain,

193
00:10:05,120 --> 00:10:09,560
Speaker 1: according to the Migration Minister. Okay, five months, it's all.

194
00:10:09,559 --> 00:10:11,679
Speaker 1: You got to be there for five months, not twenty years,

195
00:10:11,720 --> 00:10:13,600
Speaker 1: not thirty years. You know, you have a family, there

196
00:10:13,600 --> 00:10:15,920
Speaker 1: are five months. You give have a baby, five months.

197
00:10:15,920 --> 00:10:19,200
Speaker 1: You've been there for five months. You snuck in, you know,

198
00:10:19,960 --> 00:10:23,600
Speaker 1: more recently than the last Olympics. Five months and you

199
00:10:23,720 --> 00:10:26,200
Speaker 1: are You're going to live and work in Spain, no

200
00:10:26,240 --> 00:10:29,120
Speaker 1: matter where you're from as long as they don't have

201
00:10:29,120 --> 00:10:31,920
Speaker 1: a documented case of a crime, which, guess what, it's

202
00:10:32,080 --> 00:10:34,720
Speaker 1: very easy for illegal aliens, especially those who prey on

203
00:10:34,760 --> 00:10:38,000
Speaker 1: other illegal aliens who don't report crimes, to commit crimes.

204
00:10:38,120 --> 00:10:42,440
Speaker 1: This is a disaster. And fifteen days, fifteen days, how

205
00:10:42,480 --> 00:10:45,280
Speaker 1: are you Let's say, let's say one hundred thousand people

206
00:10:45,360 --> 00:10:47,560
Speaker 1: apply it, there will fifty thousand people apply with a day.

207
00:10:47,800 --> 00:10:50,960
Speaker 1: Fifty thousand people have to have their applications approved in

208
00:10:51,000 --> 00:10:53,439
Speaker 1: fifteen days. How do you even vet that kind of

209
00:10:53,520 --> 00:10:56,280
Speaker 1: number when you're a nation of like thirty five million people.

210
00:10:57,040 --> 00:11:03,240
Speaker 1: This is a disaster. Spain is absolutely creating a disaster.

211
00:11:03,320 --> 00:11:05,400
Speaker 1: It's all to get the rights to vote. It's all

212
00:11:05,480 --> 00:11:08,440
Speaker 1: for the rights to vote, to stop nationalists, to stop

213
00:11:08,480 --> 00:11:11,320
Speaker 1: populous for winning their election. This is what the left

214
00:11:11,360 --> 00:11:13,240
Speaker 1: is doing in Spain. They want to do it across

215
00:11:13,320 --> 00:11:17,920
Speaker 1: Europe and America, Australia, Canada, the entire Western world. At

216
00:11:17,960 --> 00:11:21,840
Speaker 1: this point, the very far left cannot win over because

217
00:11:21,840 --> 00:11:25,080
Speaker 1: of issues of identity and immigration that they are drunk on.

218
00:11:25,280 --> 00:11:29,280
Speaker 1: They are absolutely high on their own supply, drunk on.

219
00:11:29,720 --> 00:11:31,839
Speaker 1: So what do they want to do. They want to

220
00:11:31,880 --> 00:11:35,520
Speaker 1: bring in new voters because they can't win with the

221
00:11:35,600 --> 00:11:39,040
Speaker 1: old ones. That is just the state of affairs right

222
00:11:39,080 --> 00:11:42,520
Speaker 1: now in the West, and it is it is of

223
00:11:42,520 --> 00:11:46,400
Speaker 1: the utmost important that the Democratic Party, the Socialist Party,

224
00:11:46,440 --> 00:11:51,360
Speaker 1: the Progressive Party, whichever groups you have it are blocked

225
00:11:51,360 --> 00:11:54,000
Speaker 1: from governing right now until they sit there and learn

226
00:11:54,160 --> 00:11:56,760
Speaker 1: a lesson over the issues of identity and immigration. They

227
00:11:56,800 --> 00:12:00,640
Speaker 1: have to change their ways because the Jacob Rise of

228
00:12:00,679 --> 00:12:03,280
Speaker 1: the world, the mayor of Minneapolis, or the other far

229
00:12:03,360 --> 00:12:06,320
Speaker 1: left they are reject aiming even klobd Shar of two

230
00:12:06,360 --> 00:12:09,080
Speaker 1: thousand and six would be called a Nazi today. That's

231
00:12:09,080 --> 00:12:13,440
Speaker 1: what they believe right now. So with me today on

232
00:12:13,480 --> 00:12:17,320
Speaker 1: this podcast is a independent writer named Leif Fang. He's

233
00:12:17,360 --> 00:12:19,880
Speaker 1: a progressive journalist. He's actually of the left big fantasies

234
00:12:19,920 --> 00:12:21,839
Speaker 1: for a long time. He talks about Silicon Valley and

235
00:12:21,880 --> 00:12:24,440
Speaker 1: the Democratic Party and we talk about identity politics and

236
00:12:24,480 --> 00:12:31,520
Speaker 1: how that identity thought process immigration thought process among the

237
00:12:31,600 --> 00:12:34,120
Speaker 1: left has been so cancerous. And he's called actually for

238
00:12:34,400 --> 00:12:38,120
Speaker 1: the Democratic Party to release an apology letter to voters

239
00:12:38,160 --> 00:12:41,920
Speaker 1: over what they did during Joe Biden's policies. Very smart guy,

240
00:12:42,080 --> 00:12:45,079
Speaker 1: super interesting. A little side note about him person that

241
00:12:45,120 --> 00:12:46,400
Speaker 1: I want to just bring up I don't want to

242
00:12:46,400 --> 00:12:48,320
Speaker 1: talk about during the interview, but I want to just

243
00:12:48,400 --> 00:12:51,480
Speaker 1: mention it. He was actually canceled over the issues of identity.

244
00:12:51,520 --> 00:12:55,320
Speaker 1: He shared Martin Luther King Junior about non violence during

245
00:12:55,320 --> 00:12:58,720
Speaker 1: the George Floyd riots, and he was accused of racism

246
00:12:58,760 --> 00:13:01,280
Speaker 1: and canceled by the far left. So someone who understands

247
00:13:01,280 --> 00:13:02,959
Speaker 1: the consequences even though he believes in a lot of

248
00:13:03,040 --> 00:13:05,760
Speaker 1: leveling policies. But he's super bright. It's a great conversation

249
00:13:06,200 --> 00:13:11,000
Speaker 1: that's going to up next. Stay tuned. Lee Fang is

250
00:13:11,000 --> 00:13:13,800
Speaker 1: an independent journalist at previously an investigative reporter for a

251
00:13:13,880 --> 00:13:16,800
Speaker 1: number of progressive outlets, including The Intercept and The Nation. Lee,

252
00:13:16,840 --> 00:13:18,760
Speaker 1: I've been a big fan of yours since. I mean,

253
00:13:18,840 --> 00:13:21,080
Speaker 1: I think Occupy Wall Street is when I really started

254
00:13:21,120 --> 00:13:25,040
Speaker 1: getting apptuned to your work. You tweeted something I thought

255
00:13:25,080 --> 00:13:27,600
Speaker 1: was really fascinating. I wanted to talk to you about.

256
00:13:28,160 --> 00:13:30,760
Speaker 1: You said pretty much every normal dem is tired of

257
00:13:30,800 --> 00:13:34,760
Speaker 1: identity politics dogma. But donors like Carla Jervertsen I believe

258
00:13:34,800 --> 00:13:37,559
Speaker 1: you said her name and Liz Simons, who have divorced

259
00:13:37,559 --> 00:13:40,320
Speaker 1: and inherited their money, have billions to keep the train going.

260
00:13:40,840 --> 00:13:43,760
Speaker 1: So here we are. This is about Carla Jervartsen, who

261
00:13:43,800 --> 00:13:47,720
Speaker 1: is a funding Jazz and Crocketts campaign. How much does

262
00:13:47,880 --> 00:13:53,800
Speaker 1: nonprofit and NGOs would that apparatus go towards funding things

263
00:13:53,880 --> 00:13:55,400
Speaker 1: like the identity politics train.

264
00:13:56,400 --> 00:13:58,960
Speaker 4: Look, it's hard to parse out the exact kind of

265
00:13:59,040 --> 00:14:03,000
Speaker 4: percentage of call effect of how much of kind of

266
00:14:03,280 --> 00:14:08,240
Speaker 4: extreme identity politics comes from culture or academia or the

267
00:14:08,280 --> 00:14:15,320
Speaker 4: media versus these billionaire and NGO donors. But the donor

268
00:14:15,400 --> 00:14:19,080
Speaker 4: influence is hard to ignore. You look at almost any poll,

269
00:14:19,200 --> 00:14:23,160
Speaker 4: even of committed Democrats, there isn't a lot of support

270
00:14:23,520 --> 00:14:26,400
Speaker 4: for abolish the Police, even in the kind of peak

271
00:14:26,480 --> 00:14:29,920
Speaker 4: of twenty twenty, when after the Floyd protests and riots,

272
00:14:30,720 --> 00:14:33,080
Speaker 4: you had, you know, growing demands for this type of thing.

273
00:14:34,040 --> 00:14:38,000
Speaker 4: Despite the very low pulling numbers that abolished Police ever had,

274
00:14:38,840 --> 00:14:43,560
Speaker 4: you had a small click of mega millionaire and billionaire donors,

275
00:14:43,840 --> 00:14:49,000
Speaker 4: people like Liz Simon's, who were cutting checks to a

276
00:14:49,080 --> 00:14:53,040
Speaker 4: variety of abolish the Police groups. So around the country,

277
00:14:53,080 --> 00:14:55,160
Speaker 4: if you look at the funding, you look at the

278
00:14:55,200 --> 00:14:59,760
Speaker 4: kind of extreme activists, you know it's not the every

279
00:14:59,840 --> 00:15:03,920
Speaker 4: day middle class Democrats who are supporting this. It seems

280
00:15:03,960 --> 00:15:07,720
Speaker 4: to be largely an elite interests of folks who are

281
00:15:08,400 --> 00:15:12,120
Speaker 4: literal billionaires like Liz Simon's or other major foundations that

282
00:15:12,160 --> 00:15:12,760
Speaker 4: support them.

283
00:15:12,920 --> 00:15:15,400
Speaker 1: Yeah, and if you look at even a more unpopular policy,

284
00:15:15,440 --> 00:15:19,160
Speaker 1: which was reparations for slavery that never pulled well even

285
00:15:19,160 --> 00:15:22,560
Speaker 1: in George Floyd time, any time, the amount of people

286
00:15:22,800 --> 00:15:26,920
Speaker 1: like in California and San Francisco pushed a reparations policy

287
00:15:27,000 --> 00:15:29,400
Speaker 1: a state that never really had slavery, I don't think,

288
00:15:29,840 --> 00:15:33,800
Speaker 1: you know, to any degree that was serious and how long,

289
00:15:33,880 --> 00:15:36,400
Speaker 1: how far they went with it, it would have bankrupted

290
00:15:36,400 --> 00:15:38,280
Speaker 1: the state. I think San Francisco did some kind of policy.

291
00:15:38,320 --> 00:15:40,200
Speaker 1: They're kind of trying to backtrack as they don't have

292
00:15:40,560 --> 00:15:44,720
Speaker 1: the money for it now. But I always wondered where

293
00:15:44,840 --> 00:15:47,600
Speaker 1: that kind of stuff came because California has limited a

294
00:15:47,640 --> 00:15:50,560
Speaker 1: blown black population, and they're the only group that was

295
00:15:50,640 --> 00:15:55,560
Speaker 1: very supportive of it. And it's not it's it's not

296
00:15:55,600 --> 00:15:58,200
Speaker 1: on anyone's top thirty issues that they really are kind

297
00:15:58,200 --> 00:16:00,680
Speaker 1: of get behind. And I never really undertoo why and

298
00:16:00,720 --> 00:16:03,040
Speaker 1: why Jasmine Crockett became like a thing, you know what

299
00:16:03,040 --> 00:16:05,480
Speaker 1: I mean? Jasmine Crockett is a big thing because she's

300
00:16:05,520 --> 00:16:08,400
Speaker 1: in part the only person really talking about rais as

301
00:16:08,440 --> 00:16:11,720
Speaker 1: the main issue I like to lead her.

302
00:16:12,160 --> 00:16:13,800
Speaker 4: Well, I think there are a few things going on here.

303
00:16:14,440 --> 00:16:19,000
Speaker 4: The main dynamic here is that there are democratic leaders.

304
00:16:19,000 --> 00:16:21,480
Speaker 4: And this happens on both sides of the aisle. But

305
00:16:21,680 --> 00:16:26,200
Speaker 4: on the Democratic side, there are certain issues that are unmovable,

306
00:16:26,240 --> 00:16:29,640
Speaker 4: that are unpopular, unworkable. They don't make make a lot

307
00:16:29,640 --> 00:16:36,400
Speaker 4: of sense, like reparations here in California, but they are polarizing,

308
00:16:36,560 --> 00:16:40,560
Speaker 4: they are emotionally very powerful. You know, in California, we

309
00:16:40,600 --> 00:16:42,880
Speaker 4: have a intractable housing crisis.

310
00:16:43,280 --> 00:16:45,440
Speaker 1: We have you know, high cost of healthcare.

311
00:16:45,600 --> 00:16:47,960
Speaker 4: We have a public safety kind of crisis, we have

312
00:16:48,000 --> 00:16:50,480
Speaker 4: homeless issues. We have all these problems that we'd like

313
00:16:50,520 --> 00:16:53,280
Speaker 4: our leaders to deal with. But if they hold out

314
00:16:53,440 --> 00:16:57,720
Speaker 4: these kind of impossible to fix problems that are emotionally

315
00:16:57,800 --> 00:17:00,920
Speaker 4: laid in, like reparations, they can see public opinion. They

316
00:17:00,920 --> 00:17:03,080
Speaker 4: can say, hey, we're the good guys, we're the public servants.

317
00:17:03,080 --> 00:17:05,840
Speaker 4: We're doing something that no other leader has done, even

318
00:17:05,840 --> 00:17:08,600
Speaker 4: though they know in their hearts that nothing will pass.

319
00:17:09,480 --> 00:17:12,679
Speaker 4: You know, they attached no funding mechanism. They kind of

320
00:17:13,040 --> 00:17:15,879
Speaker 4: bury language in all these bills to make sure that

321
00:17:15,960 --> 00:17:19,880
Speaker 4: nothing actually happens. But it's designed to kind of show

322
00:17:19,920 --> 00:17:23,080
Speaker 4: their moral leadership, that they are good people, that they

323
00:17:23,080 --> 00:17:26,440
Speaker 4: are kind of icons of history and you know, championing

324
00:17:26,560 --> 00:17:29,560
Speaker 4: kind of the long march of civil rights, even though

325
00:17:29,800 --> 00:17:32,320
Speaker 4: these issues are completely meaningless in the sense that they

326
00:17:32,320 --> 00:17:34,680
Speaker 4: are never designed to pass. I mean, it's a lot

327
00:17:34,720 --> 00:17:37,960
Speaker 4: like the single payer debate. Gavin Newsom campaigned when he

328
00:17:37,960 --> 00:17:41,280
Speaker 4: first ran for governor here for He's going to enact

329
00:17:41,320 --> 00:17:43,159
Speaker 4: single payer. It's how he got the nurses union and

330
00:17:43,200 --> 00:17:44,840
Speaker 4: others to back him. It's how he kind of got

331
00:17:44,960 --> 00:17:48,000
Speaker 4: the progressive to get on board with his gubernatorial campaign.

332
00:17:48,160 --> 00:17:50,080
Speaker 4: He knew that there would be no chance for a

333
00:17:50,119 --> 00:17:53,240
Speaker 4: single payer in California, and indeed, when he became governor,

334
00:17:53,400 --> 00:17:56,159
Speaker 4: he took no actions to actually pass it. Reparations is

335
00:17:56,240 --> 00:17:58,840
Speaker 4: very similar. There's a committee to study it and another

336
00:17:58,840 --> 00:18:01,879
Speaker 4: committee to study it. This is all designed just to

337
00:18:01,960 --> 00:18:04,520
Speaker 4: kind of keep the medium wheel going. It kind of

338
00:18:04,880 --> 00:18:07,600
Speaker 4: leads to outrage on the right for very good reason,

339
00:18:07,640 --> 00:18:10,240
Speaker 4: because a lot of this stuff is preposterous, and it

340
00:18:10,400 --> 00:18:15,240
Speaker 4: leads to kind of the symbolic moral leadership for Democrats

341
00:18:15,320 --> 00:18:18,480
Speaker 4: who actually get nothing done on much more thorny, difficult

342
00:18:18,520 --> 00:18:21,879
Speaker 4: to tackle issues like housing, like healthcare like jobs like homelessness.

343
00:18:22,240 --> 00:18:24,439
Speaker 1: Yeah, and what is the there's a progress there's a

344
00:18:24,440 --> 00:18:27,239
Speaker 1: saying that progresses have to say, is that the arc

345
00:18:27,320 --> 00:18:29,720
Speaker 1: of history bends towards justice. I think that's why they

346
00:18:29,800 --> 00:18:33,320
Speaker 1: sit there and say that's what I think. That's I

347
00:18:33,359 --> 00:18:36,600
Speaker 1: think what this main movable thing is that they feel

348
00:18:36,640 --> 00:18:39,960
Speaker 1: like this is one thing towards justice and that they

349
00:18:40,000 --> 00:18:42,600
Speaker 1: are part of that wheel. Like, you know, we may

350
00:18:42,640 --> 00:18:44,840
Speaker 1: not have been alive or active in the nineteen sixties

351
00:18:44,920 --> 00:18:47,360
Speaker 1: during the civil rights move, but now we're actually getting that,

352
00:18:47,480 --> 00:18:50,880
Speaker 1: you know, getting on the bandwagon in our own respect

353
00:18:50,920 --> 00:18:52,879
Speaker 1: and whatever issue it is. I think it's that. What

354
00:18:53,000 --> 00:18:57,800
Speaker 1: is your opinion of Gavenue sum.

355
00:18:56,080 --> 00:19:00,679
Speaker 4: Look, he's a crafty politician, of he's he's great at

356
00:19:00,760 --> 00:19:03,439
Speaker 4: kind of playing the national media, and that's how he

357
00:19:03,480 --> 00:19:07,360
Speaker 4: gets elected so effectively. You know, he basically chose his

358
00:19:07,440 --> 00:19:11,040
Speaker 4: Republican opponent in the last two elections because we have

359
00:19:11,040 --> 00:19:13,480
Speaker 4: the jungle primary the top two in California. He ran

360
00:19:13,520 --> 00:19:17,400
Speaker 4: ads in the Republican primary to basically trick them Republican

361
00:19:17,480 --> 00:19:21,080
Speaker 4: voters and independence into selecting who he wanted to run against,

362
00:19:21,080 --> 00:19:24,200
Speaker 4: so we could run against a very weak opponents, very

363
00:19:24,200 --> 00:19:27,720
Speaker 4: clever in that sense, but overall he's been a failure

364
00:19:27,760 --> 00:19:29,800
Speaker 4: on the on the issues I just mentioned. You know,

365
00:19:29,920 --> 00:19:32,320
Speaker 4: there's a news story just in the last week that

366
00:19:32,400 --> 00:19:36,760
Speaker 4: his signature kind of special courts to deal with mental

367
00:19:36,800 --> 00:19:40,280
Speaker 4: illness and drug addiction for homelessness has failed. It was

368
00:19:40,320 --> 00:19:43,120
Speaker 4: supposed to handle thousands of cases per year. It's only

369
00:19:43,119 --> 00:19:47,520
Speaker 4: handled a few hundred. Look at the housing dynamic. We

370
00:19:47,560 --> 00:19:50,760
Speaker 4: haven't been able to build housing healthcare. You know, he's

371
00:19:50,800 --> 00:19:53,160
Speaker 4: got he's gotten a little bit done on an insulin prices,

372
00:19:53,240 --> 00:19:55,720
Speaker 4: but basically everything else has been a failure.

373
00:19:56,240 --> 00:19:58,399
Speaker 1: Price is like the thing that every politician seems to

374
00:19:58,440 --> 00:20:00,800
Speaker 1: have gone to recently. If you noticed im from Trump

375
00:20:00,920 --> 00:20:03,080
Speaker 1: to Biden, everyone's like, we're going to tackle insulin. Not

376
00:20:03,080 --> 00:20:05,760
Speaker 1: that insulin is not important, but I wonder why that

377
00:20:05,920 --> 00:20:10,880
Speaker 1: is the drug that everyone's moving towards over other drugs

378
00:20:10,920 --> 00:20:13,000
Speaker 1: which are just like cancer drugs like that.

379
00:20:13,000 --> 00:20:16,400
Speaker 4: There are a lot of overweight Americans who are insulin dependent.

380
00:20:17,160 --> 00:20:18,560
Speaker 1: Diabetes is a big issue.

381
00:20:18,800 --> 00:20:22,760
Speaker 4: And look, actually, Eli Lilly, the biggest maker makers of insulin,

382
00:20:22,800 --> 00:20:26,919
Speaker 4: have moved on as a business model towards GOPS. So

383
00:20:27,240 --> 00:20:29,200
Speaker 4: you know, I think this is actually an issue that's

384
00:20:29,560 --> 00:20:33,359
Speaker 4: going to be in the review mirror moving forward. But

385
00:20:34,080 --> 00:20:37,760
Speaker 4: you know, there are a lot of promises around drug prices,

386
00:20:37,840 --> 00:20:41,800
Speaker 4: around healthcare costs, and you know this is a salient one,

387
00:20:41,920 --> 00:20:44,760
Speaker 4: just like you know, price of milk or price of gas.

388
00:20:44,800 --> 00:20:49,560
Speaker 4: But again, overall, look at the big picture, how much

389
00:20:49,760 --> 00:20:54,840
Speaker 4: California spends on pensions, on healthcare, how expensive housing is.

390
00:20:55,119 --> 00:20:56,560
Speaker 4: You know, he hasn't really moved the needle.

391
00:20:57,200 --> 00:20:59,000
Speaker 1: Yeah, and I think that you said something else on

392
00:20:59,040 --> 00:21:00,800
Speaker 1: Twitter that was very I spent a lot of time

393
00:21:00,840 --> 00:21:03,960
Speaker 1: scrolling your stuff, so that's a lot of I write

394
00:21:04,000 --> 00:21:06,160
Speaker 1: your old articles too in some of your recent videos.

395
00:21:06,400 --> 00:21:08,480
Speaker 1: But you said things on Twitter that I thought was

396
00:21:08,760 --> 00:21:11,360
Speaker 1: very interesting. You said that Kanye asked for those who

397
00:21:11,400 --> 00:21:14,080
Speaker 1: don't know, wrote a large apology to the Jewish community

398
00:21:14,080 --> 00:21:15,919
Speaker 1: in cite his mental health is the reason he was

399
00:21:15,920 --> 00:21:19,320
Speaker 1: so anti Semitic, And you said the Democrats need a

400
00:21:19,440 --> 00:21:24,879
Speaker 1: similar style apology around the border and immigration, right because

401
00:21:24,960 --> 00:21:29,240
Speaker 1: they are the Republicans. Despite Ice being down in the polls,

402
00:21:29,680 --> 00:21:32,679
Speaker 1: voter still trust Republicans want the Democrats on immigration because

403
00:21:32,720 --> 00:21:34,879
Speaker 1: of the in part large part is of Joe Biden

404
00:21:34,920 --> 00:21:37,520
Speaker 1: forty years in office, and there are still Democrats like

405
00:21:38,920 --> 00:21:41,480
Speaker 1: Jacob fry Over in Minneapolis, who are like, we're not

406
00:21:41,520 --> 00:21:44,400
Speaker 1: even going to let criminals who are in prison being deported.

407
00:21:45,160 --> 00:21:48,600
Speaker 1: How close is the party to getting there, to actually

408
00:21:48,680 --> 00:21:51,560
Speaker 1: acknowledging and doing something hardline, at least on the border,

409
00:21:51,600 --> 00:21:53,000
Speaker 1: do you think? Well?

410
00:21:53,040 --> 00:21:55,639
Speaker 4: Bernie Sanders has praised Donald Trump, saying he's done a

411
00:21:55,640 --> 00:21:59,840
Speaker 4: good job on border security. Look, twenty years ago when

412
00:21:59,840 --> 00:22:03,000
Speaker 4: I was in college, Democrats dominated Arkansas, they had a

413
00:22:03,040 --> 00:22:08,639
Speaker 4: majority of congressional seats in Appalachia, the Dakotas we're controlled

414
00:22:08,640 --> 00:22:11,359
Speaker 4: by Democrats. You know, the Democratic Party used to be

415
00:22:11,400 --> 00:22:14,159
Speaker 4: a rural and working class party.

416
00:22:14,200 --> 00:22:15,240
Speaker 1: It's kind of flipped.

417
00:22:15,560 --> 00:22:20,520
Speaker 4: We've had, you know, class and regional polarization in this country,

418
00:22:20,920 --> 00:22:23,040
Speaker 4: and a big part of that comes down to its

419
00:22:23,080 --> 00:22:28,040
Speaker 4: position on border security, on identity politics, on public safety.

420
00:22:28,440 --> 00:22:30,679
Speaker 4: And you know what's popular on social media. You know,

421
00:22:30,720 --> 00:22:34,399
Speaker 4: both you and I are addicted to social media, but

422
00:22:34,480 --> 00:22:38,160
Speaker 4: it's popular these days to say, never apologize if you're wrong,

423
00:22:38,280 --> 00:22:40,760
Speaker 4: you know, never let the haters get to you. Just

424
00:22:40,880 --> 00:22:44,040
Speaker 4: keep going about your way. You know, I don't think

425
00:22:44,080 --> 00:22:48,320
Speaker 4: that's true for human psychology. It works for Twitter, but

426
00:22:48,400 --> 00:22:50,960
Speaker 4: it doesn't work if you're in a family, if you're

427
00:22:51,000 --> 00:22:53,199
Speaker 4: in a workplace, if you're in a community and you're

428
00:22:53,240 --> 00:22:56,399
Speaker 4: asking for someone's vote, the Democrats messed up. If they

429
00:22:56,440 --> 00:22:59,840
Speaker 4: want to earn back the trust of working class voters,

430
00:23:00,119 --> 00:23:03,080
Speaker 4: voters in rural communities, I don't think an apology hurts.

431
00:23:03,800 --> 00:23:06,000
Speaker 4: They can say they messed up over the last ten years.

432
00:23:06,119 --> 00:23:08,639
Speaker 4: In fact, the party has been hijacked by billionaires and

433
00:23:08,680 --> 00:23:11,920
Speaker 4: special interest groups that don't care about these issues. In fact,

434
00:23:11,920 --> 00:23:14,399
Speaker 4: they're on the wrong side of these issues. But for

435
00:23:14,480 --> 00:23:19,160
Speaker 4: Democrats to reconnect with their working class roots, I think

436
00:23:19,720 --> 00:23:23,360
Speaker 4: just starting the process with an apology, with a refocus

437
00:23:23,720 --> 00:23:27,600
Speaker 4: on kind of meat and potato issues of middle class wages,

438
00:23:27,720 --> 00:23:31,439
Speaker 4: on labor unions, on holding corporations accountable, holding Trump accountable,

439
00:23:31,760 --> 00:23:35,760
Speaker 4: on making sure that America is affordable. That's where I

440
00:23:35,760 --> 00:23:38,160
Speaker 4: think the party historically has been in the twentieth century,

441
00:23:38,400 --> 00:23:41,879
Speaker 4: from the New Deal onwards. There's no reason it can't

442
00:23:41,920 --> 00:23:45,520
Speaker 4: reconnect with those roots except for the influence of folks

443
00:23:45,600 --> 00:23:48,800
Speaker 4: like Liz Simon's and a few other kind of special

444
00:23:48,800 --> 00:23:49,960
Speaker 4: interest activists.

445
00:23:49,600 --> 00:23:51,320
Speaker 1: In the yeah. I think also the problem is a

446
00:23:51,359 --> 00:23:54,639
Speaker 1: lot of staffers are really addicted to social media. Like

447
00:23:54,760 --> 00:23:58,080
Speaker 1: Tim Waltz's Transformation from a congressman to a governor is

448
00:23:58,880 --> 00:24:01,880
Speaker 1: night and day. I think in part he was chasing

449
00:24:01,920 --> 00:24:06,280
Speaker 1: social media, and it's so toxic for elected officials to

450
00:24:06,359 --> 00:24:09,359
Speaker 1: chase social media trends. I want to switch gears for

451
00:24:09,400 --> 00:24:11,600
Speaker 1: a second. So I watched a video you had the

452
00:24:11,680 --> 00:24:14,760
Speaker 1: university on your podcast. You had an interview with the

453
00:24:14,840 --> 00:24:19,600
Speaker 1: University of Montreal system professor David Krueger about AI. This

454
00:24:19,760 --> 00:24:22,720
Speaker 1: interview gave me an anxiety attack. I just want you

455
00:24:22,760 --> 00:24:28,560
Speaker 1: to know, very difficult time sleeping afterwards. So you're in

456
00:24:28,600 --> 00:24:33,520
Speaker 1: the valley, You're in Silicon Valley territory. How responsible do

457
00:24:33,600 --> 00:24:35,760
Speaker 1: you think? And I'm sure you have contact someone in

458
00:24:35,760 --> 00:24:39,119
Speaker 1: the Silicon Valley world. How responsible is Silicon Valley being

459
00:24:39,160 --> 00:24:39,800
Speaker 1: around AI.

460
00:24:40,720 --> 00:24:46,040
Speaker 4: I think there's no guardrails. People are pursuing self interest,

461
00:24:46,080 --> 00:24:46,680
Speaker 4: which is fine.

462
00:24:46,720 --> 00:24:46,879
Speaker 1: You know.

463
00:24:47,160 --> 00:24:50,240
Speaker 4: The way for any kind of new frontier technology to

464
00:24:50,320 --> 00:24:54,080
Speaker 4: develop is for entrepreneurs and scientists and researchers to kind

465
00:24:54,119 --> 00:24:56,879
Speaker 4: of push the boundaries as far as possible. The thing is,

466
00:24:56,920 --> 00:25:00,639
Speaker 4: this is very different from developing a new medicaid or

467
00:25:00,680 --> 00:25:04,680
Speaker 4: a new energy source. This is a fundamentally transformative technology

468
00:25:05,440 --> 00:25:09,879
Speaker 4: that could change all of human civilization. We could become

469
00:25:09,880 --> 00:25:12,480
Speaker 4: completely dependent upon it. We could this is something that

470
00:25:12,520 --> 00:25:14,639
Speaker 4: could kill all of us. I mean, even according to

471
00:25:14,720 --> 00:25:18,400
Speaker 4: the folks who are leading the AI companies, people who

472
00:25:18,560 --> 00:25:21,040
Speaker 4: found it, anthropic who makes Claude, or even Elon Musk.

473
00:25:21,080 --> 00:25:24,280
Speaker 4: Elon Musk says, there's a twenty percent chance that AI

474
00:25:24,440 --> 00:25:28,080
Speaker 4: kills all of us and he's developing it. So that's

475
00:25:28,119 --> 00:25:31,879
Speaker 4: a pretty high probability. And you know, you can you know,

476
00:25:31,920 --> 00:25:34,560
Speaker 4: the interview I think goes through a lot of the

477
00:25:34,560 --> 00:25:37,080
Speaker 4: different stages of this that that could be a dependency thing,

478
00:25:37,119 --> 00:25:39,399
Speaker 4: that we become so dependent on AI we kind of

479
00:25:39,400 --> 00:25:42,080
Speaker 4: lose our own humanity. And if then something happens where

480
00:25:42,119 --> 00:25:44,879
Speaker 4: the AI sees us as disposable, it could get rid

481
00:25:44,920 --> 00:25:49,119
Speaker 4: of us. It could invent thousands of new viruses like

482
00:25:49,600 --> 00:25:53,520
Speaker 4: you know, super covid nineteens that are designed to kill us.

483
00:25:53,840 --> 00:25:55,439
Speaker 4: I mean, there's so many ways to look at this,

484
00:25:55,880 --> 00:25:58,320
Speaker 4: and I'm not someone who says, Okay, the government needs

485
00:25:58,359 --> 00:26:00,560
Speaker 4: to control all of this. We need we need, you know,

486
00:26:00,880 --> 00:26:03,919
Speaker 4: strict regulations on everything, but we need a conversation.

487
00:26:04,320 --> 00:26:06,200
Speaker 1: We need policy.

488
00:26:05,840 --> 00:26:10,280
Speaker 4: Makers who are independent minded, who are taking these risk

489
00:26:10,359 --> 00:26:16,000
Speaker 4: factors into consideration. And we're at least looking at this

490
00:26:16,080 --> 00:26:19,040
Speaker 4: in a responsible way. Right now, the AI companies, the

491
00:26:19,160 --> 00:26:21,880
Speaker 4: venture capitalists, and the big tech companies that control them

492
00:26:22,119 --> 00:26:23,680
Speaker 4: are buying off all the politicians.

493
00:26:23,960 --> 00:26:25,400
Speaker 1: Look at all the members.

494
00:26:25,040 --> 00:26:28,120
Speaker 4: Of Congress who retired in twenty twenty four, So many

495
00:26:28,200 --> 00:26:31,240
Speaker 4: of them are going to law firms and trade associations

496
00:26:31,600 --> 00:26:35,800
Speaker 4: representing the AI companies. Kristen Cinema is one of them,

497
00:26:35,840 --> 00:26:38,480
Speaker 4: but there are many others. Look at how much they

498
00:26:38,480 --> 00:26:41,600
Speaker 4: are buying politician post senate.

499
00:26:41,760 --> 00:26:44,040
Speaker 1: She's doing very well for her, she's doing very well.

500
00:26:45,840 --> 00:26:49,399
Speaker 4: And of course, you know, for the AI companies this

501
00:26:50,119 --> 00:26:52,359
Speaker 4: is I mean for the amount of money that they're

502
00:26:52,440 --> 00:26:56,720
Speaker 4: raising buying a few hundred former lawmakers and regulators, this

503
00:26:56,800 --> 00:26:58,600
Speaker 4: is chump change for them because it's a few million

504
00:26:58,640 --> 00:27:01,600
Speaker 4: dollars while they're spending tens of millions just hiring a

505
00:27:01,640 --> 00:27:03,879
Speaker 4: research scientist to develop these models.

506
00:27:04,320 --> 00:27:06,920
Speaker 1: Yeah, I'll tell you, as a consultant on the Republican

507
00:27:06,960 --> 00:27:09,480
Speaker 1: side of the aisle, the amount of money in bitcoin

508
00:27:09,640 --> 00:27:15,320
Speaker 1: and in AI is astronomical. It is astronomical. They're throwing

509
00:27:15,359 --> 00:27:19,240
Speaker 1: around eight ten million dollars for a house or Senate

510
00:27:19,320 --> 00:27:23,760
Speaker 1: race like it's nothing, and they it is nothing to them.

511
00:27:24,160 --> 00:27:28,159
Speaker 1: But the amount of money is preposterous. And given the polls,

512
00:27:28,200 --> 00:27:30,240
Speaker 1: like the Fox News poll races that sixty five percent

513
00:27:30,280 --> 00:27:34,760
Speaker 1: of Americans are are have anxiety, but AI that that's

514
00:27:34,800 --> 00:27:37,440
Speaker 1: a huge amount. That's those are those are those are

515
00:27:37,640 --> 00:27:41,080
Speaker 1: the trans women in sports numbers, those are gun control numbers.

516
00:27:41,080 --> 00:27:45,440
Speaker 1: Those are very lopsided numbers on one side. There is

517
00:27:45,480 --> 00:27:49,040
Speaker 1: not even a conversation happening like there. And I've gotten

518
00:27:49,080 --> 00:27:51,320
Speaker 1: to arguments on Twitter with David Sachs, who I know

519
00:27:51,600 --> 00:27:54,439
Speaker 1: a little bit and like I've met him before, and

520
00:27:54,480 --> 00:27:57,080
Speaker 1: he said, you know, we need a national level, not

521
00:27:57,240 --> 00:28:00,600
Speaker 1: state by state on AI. Okay, fine, I said, name

522
00:28:00,760 --> 00:28:04,280
Speaker 1: the AI regulation you support. Just give me one, give

523
00:28:04,320 --> 00:28:07,200
Speaker 1: me what you want. Don't tell me like kids in pornography.

524
00:28:07,280 --> 00:28:11,480
Speaker 1: Tell me a real AI regulation that you support. And

525
00:28:11,560 --> 00:28:14,280
Speaker 1: there was no response. And I think that that is

526
00:28:14,440 --> 00:28:21,639
Speaker 1: this accelerationist opinion by especially Republicans right now, that AI

527
00:28:21,800 --> 00:28:23,879
Speaker 1: is going to be not only this mass job creator

528
00:28:23,920 --> 00:28:25,800
Speaker 1: because they do things, it's going to create jobs. I'm

529
00:28:25,840 --> 00:28:28,800
Speaker 1: not exactly sure how, but I'm not also not an experts.

530
00:28:28,840 --> 00:28:31,640
Speaker 1: I'm willing to open my ears and listen. But they

531
00:28:31,640 --> 00:28:33,639
Speaker 1: also think it's going to fix the deficit. Problem, the

532
00:28:33,640 --> 00:28:35,359
Speaker 1: budget problem. Are going to make so much money that

533
00:28:35,400 --> 00:28:37,800
Speaker 1: we'll be able to pay off our deficit and debt.

534
00:28:38,040 --> 00:28:41,240
Speaker 1: That sounds like a wonderful idea. But every action has

535
00:28:41,240 --> 00:28:43,480
Speaker 1: a consequence. So what's the consequence. I just want to

536
00:28:43,520 --> 00:28:45,560
Speaker 1: hear it. I'm not going to close the door to something,

537
00:28:45,680 --> 00:28:47,600
Speaker 1: not saying I actually just go away. I think it

538
00:28:47,640 --> 00:28:51,600
Speaker 1: will do great things in certain respects. I just for

539
00:28:51,680 --> 00:28:53,280
Speaker 1: every chance that there's going to be they're going to

540
00:28:53,360 --> 00:28:56,520
Speaker 1: discover the cure for AIDS and cancer, are they also

541
00:28:56,560 --> 00:28:58,480
Speaker 1: going to be the terminator? And I want to know

542
00:28:58,680 --> 00:29:00,640
Speaker 1: what are the odds of either which happening, and how

543
00:29:00,640 --> 00:29:02,200
Speaker 1: do we safeguard one from the other.

544
00:29:02,760 --> 00:29:04,200
Speaker 4: You know, it sounds a lot like, you know, when

545
00:29:04,200 --> 00:29:07,040
Speaker 4: I was a CUB reporter in my early twenties, I

546
00:29:07,080 --> 00:29:12,160
Speaker 4: was covering the Obama Clean Power Plan back in two ten,

547
00:29:12,200 --> 00:29:15,680
Speaker 4: twenty eleven. And what this sounds a lot like to

548
00:29:15,720 --> 00:29:19,840
Speaker 4: me are the earnest opinions that I heard from the

549
00:29:19,960 --> 00:29:23,080
Speaker 4: various clean energy lobbyists who claimed that as we shifted

550
00:29:23,120 --> 00:29:25,680
Speaker 4: away from coal, all these folks in West Virginia were

551
00:29:25,720 --> 00:29:28,000
Speaker 4: going to learn the code. I mean, that's literally what

552
00:29:28,000 --> 00:29:30,320
Speaker 4: they said, that they would go and they'd go to skill,

553
00:29:30,520 --> 00:29:33,760
Speaker 4: go to the special community colleges that the administration was

554
00:29:33,800 --> 00:29:36,200
Speaker 4: going to set up in these vocational schools, and they

555
00:29:36,200 --> 00:29:37,480
Speaker 4: would just shift industries.

556
00:29:37,840 --> 00:29:38,680
Speaker 1: And look what happened.

557
00:29:38,760 --> 00:29:41,200
Speaker 4: You know, as we shifted away from coal without a

558
00:29:41,240 --> 00:29:45,160
Speaker 4: true economic stimulus for Kentucky and West Virginia, thousands of

559
00:29:45,160 --> 00:29:47,680
Speaker 4: people died. They got addicted to drugs, and they died.

560
00:29:48,320 --> 00:29:52,440
Speaker 4: And what AI will do is one hundred thousand times

561
00:29:52,720 --> 00:29:55,160
Speaker 4: more powerful than the shift away from coal. This is

562
00:29:55,200 --> 00:29:58,000
Speaker 4: a shift away from driving. We won't have truck drivers.

563
00:29:58,040 --> 00:29:59,720
Speaker 4: This is a shift away from factories, we won't have

564
00:29:59,760 --> 00:30:00,600
Speaker 4: fact free workers.

565
00:30:00,800 --> 00:30:00,960
Speaker 1: You know.

566
00:30:01,000 --> 00:30:04,120
Speaker 4: This is a shift away from slaughterhouses. You know, the

567
00:30:04,240 --> 00:30:07,880
Speaker 4: robots will be doing this slaughtering, and uh, we don't

568
00:30:07,920 --> 00:30:11,320
Speaker 4: really have an answer for that. And for uh, National Republicans,

569
00:30:11,440 --> 00:30:14,920
Speaker 4: I think folks like Josh Holly and Marsha Blackburn really

570
00:30:14,960 --> 00:30:18,840
Speaker 4: saved the party by pulling this kind of federalization of

571
00:30:18,880 --> 00:30:21,600
Speaker 4: AI policy out of the One Big Beautiful Bill, because

572
00:30:21,600 --> 00:30:24,160
Speaker 4: I think that would have been an albatross for publicans

573
00:30:24,200 --> 00:30:27,600
Speaker 4: moving into the in the midterms. As you're as you're mentioning,

574
00:30:28,560 --> 00:30:32,480
Speaker 4: public opinion is really just soaring in terms of this

575
00:30:32,600 --> 00:30:35,720
Speaker 4: backlash to AI. It's just right now, there isn't a

576
00:30:36,080 --> 00:30:39,160
Speaker 4: lobby group or an interest group that's harnessing this anger.

577
00:30:39,600 --> 00:30:41,680
Speaker 4: A lot of the anger is kind of being directed

578
00:30:41,680 --> 00:30:44,440
Speaker 4: towards data centers, which makes sense. They're the most tangible thing,

579
00:30:44,880 --> 00:30:46,960
Speaker 4: but it is very volatile. I think you're you're on

580
00:30:47,000 --> 00:30:50,320
Speaker 4: the money here talking about where you know this is, uh,

581
00:30:50,800 --> 00:30:52,720
Speaker 4: you know trans women in sports numbers.

582
00:30:53,080 --> 00:30:56,280
Speaker 1: YEA Rocanna when he was on this podcast, said you

583
00:30:56,280 --> 00:31:00,920
Speaker 1: know he wants this, Uh what was FDR's not great

584
00:31:00,960 --> 00:31:03,120
Speaker 1: society the new Deal wants He wants an AI new

585
00:31:03,160 --> 00:31:07,400
Speaker 1: Deal where basically money is redistributed to people from AI

586
00:31:07,480 --> 00:31:10,560
Speaker 1: companies out there making a lot of money. What I

587
00:31:10,560 --> 00:31:15,520
Speaker 1: couldn't get him to comprehend, which was the roadblock, was Okay,

588
00:31:15,600 --> 00:31:17,480
Speaker 1: if we're gonna have to redistribute money because some man

589
00:31:17,480 --> 00:31:19,840
Speaker 1: people unemployed, why are we going to have to have

590
00:31:19,920 --> 00:31:24,040
Speaker 1: high immigration at the same time? And he he wouldn't

591
00:31:24,080 --> 00:31:26,320
Speaker 1: go there, Like he was just like I hit the

592
00:31:26,320 --> 00:31:30,680
Speaker 1: brick wall and there was no moving from progressive dogma.

593
00:31:30,720 --> 00:31:33,640
Speaker 1: And I was like, let's have like an actual thoughtful conversation.

594
00:31:34,080 --> 00:31:35,920
Speaker 1: But I think he's running for president, so I understand

595
00:31:35,960 --> 00:31:37,440
Speaker 1: why he has to come out and be in certain

596
00:31:37,480 --> 00:31:40,120
Speaker 1: kind types of limitations. But I think that for if

597
00:31:40,160 --> 00:31:43,160
Speaker 1: there was a Ui Long style politician reulliance AI because

598
00:31:43,200 --> 00:31:45,240
Speaker 1: look at all the unemployed young people. I know so

599
00:31:45,400 --> 00:31:48,480
Speaker 1: many young people who cannot find a job, and it's

600
00:31:48,480 --> 00:31:49,960
Speaker 1: not because they're lazy, and it's not because they got

601
00:31:49,960 --> 00:31:50,680
Speaker 1: degrees in nothing.

602
00:31:51,560 --> 00:31:54,760
Speaker 4: Yeah no, And I think you're right that this kind

603
00:31:54,800 --> 00:31:58,000
Speaker 4: of solves and it feels weird to use that terminology

604
00:31:58,040 --> 00:32:01,400
Speaker 4: that the immigration issue. We've had decades of this kind

605
00:32:01,400 --> 00:32:04,920
Speaker 4: of gray market dynamic in the US. We're both Democrats

606
00:32:04,920 --> 00:32:09,480
Speaker 4: and Republicans tacitly supported mass migration because they are the

607
00:32:09,560 --> 00:32:12,520
Speaker 4: underclass in America that do all these kind of manual labor,

608
00:32:13,040 --> 00:32:19,600
Speaker 4: low education jobs, you know, housekeeping, construction, agriculture, that sort

609
00:32:19,680 --> 00:32:23,360
Speaker 4: of thing. And you know, if we have robots that

610
00:32:23,880 --> 00:32:26,440
Speaker 4: essentially replaces all of this work, so the need for

611
00:32:26,480 --> 00:32:31,440
Speaker 4: this gray market migration goes away, and it completely changes

612
00:32:31,480 --> 00:32:33,680
Speaker 4: the politics of immigration because you don't have this kind

613
00:32:33,680 --> 00:32:38,800
Speaker 4: of chamber of commerce, you know, business lobby constantly demanding it.

614
00:32:39,520 --> 00:32:41,280
Speaker 1: And this is I.

615
00:32:41,200 --> 00:32:43,680
Speaker 4: Don't think this should be controversial for a progressive to say,

616
00:32:43,880 --> 00:32:45,960
Speaker 4: because at the end of the day, the other side,

617
00:32:46,000 --> 00:32:47,640
Speaker 4: what Conna is saying is right, like, Okay, if we're

618
00:32:47,640 --> 00:32:52,000
Speaker 4: going to have massive new wealth concentrations of wealth, we

619
00:32:52,040 --> 00:32:54,640
Speaker 4: should figure out how to build a society where everyone

620
00:32:54,680 --> 00:32:55,600
Speaker 4: prospers under it.

621
00:32:55,960 --> 00:32:59,640
Speaker 1: That shouldn't be complicated. Yeah, I think that's how I

622
00:32:59,640 --> 00:33:03,680
Speaker 1: think row as a political mind, as someone who works

623
00:33:03,680 --> 00:33:07,600
Speaker 1: on campaigns goes. I think that issue is going to

624
00:33:07,680 --> 00:33:11,520
Speaker 1: be the most salient for Democrats is to have a

625
00:33:11,600 --> 00:33:13,840
Speaker 1: true socialist policy. I think it's going to be through

626
00:33:13,920 --> 00:33:16,720
Speaker 1: the AI think because it will just serve the market

627
00:33:16,760 --> 00:33:20,320
Speaker 1: to such a degree, especially for young people. But not

628
00:33:20,360 --> 00:33:23,560
Speaker 1: only for young people. It's for their gen X parents.

629
00:33:24,440 --> 00:33:26,120
Speaker 1: The gen X parents who want their kid out of

630
00:33:26,120 --> 00:33:27,640
Speaker 1: the house, who want their kid to have a job,

631
00:33:28,040 --> 00:33:30,600
Speaker 1: who are the most supportive of Donald Trump, are the

632
00:33:30,600 --> 00:33:32,920
Speaker 1: ones who will be energized to sit there in some

633
00:33:33,000 --> 00:33:36,040
Speaker 1: kind of change. People forget the student loan controversies or

634
00:33:36,080 --> 00:33:38,640
Speaker 1: student loan debate rather is not so much a debate

635
00:33:38,680 --> 00:33:40,920
Speaker 1: for young people. It is, but it's their boomer parents

636
00:33:40,960 --> 00:33:43,720
Speaker 1: who co sign their loans. Like That's what moves a

637
00:33:43,720 --> 00:33:45,640
Speaker 1: lot of these needles is people have parents and their

638
00:33:45,680 --> 00:33:47,640
Speaker 1: parents when their kids to succeed, and that's just a

639
00:33:47,640 --> 00:33:49,920
Speaker 1: fundamental part of it. It's not all just blue haired

640
00:33:50,240 --> 00:33:52,320
Speaker 1: you know they them's. It's a lot of it is

641
00:33:52,360 --> 00:33:53,600
Speaker 1: families and parents.

642
00:33:53,960 --> 00:33:56,880
Speaker 4: And you know who's paving the road towards this, it's

643
00:33:56,880 --> 00:34:00,240
Speaker 4: Donald Trump. You know, it would be an anathema for

644
00:34:00,280 --> 00:34:02,840
Speaker 4: any other president to demand a golden share or an

645
00:34:02,880 --> 00:34:06,760
Speaker 4: equity stake in a major corporation. Trump has broken that

646
00:34:06,880 --> 00:34:11,320
Speaker 4: precedent now that he's kind of created that norm where

647
00:34:11,360 --> 00:34:13,840
Speaker 4: he's taking a golden share or an equity share in

648
00:34:13,920 --> 00:34:15,960
Speaker 4: corporations left and right every other month.

649
00:34:16,880 --> 00:34:17,680
Speaker 1: We're no Democrat.

650
00:34:17,920 --> 00:34:21,440
Speaker 4: Could you imagine Biden or Obama doing this? No, But

651
00:34:21,520 --> 00:34:24,319
Speaker 4: now that he's kind of created the norm, I think

652
00:34:24,360 --> 00:34:27,480
Speaker 4: that's the only way for a Democrat in the future

653
00:34:27,880 --> 00:34:30,759
Speaker 4: to take a share of this Ai wealth. This is

654
00:34:30,920 --> 00:34:33,520
Speaker 4: just demand an equity stake, demanded golden share controlled by

655
00:34:33,560 --> 00:34:35,359
Speaker 4: the government. And you could think of ways that are

656
00:34:35,560 --> 00:34:39,240
Speaker 4: that this could be done in a non corrupt way.

657
00:34:39,600 --> 00:34:42,799
Speaker 4: Look at the Alaska Permanent Fund that takes part of

658
00:34:42,840 --> 00:34:46,920
Speaker 4: the the Oily royalties and redistributes it to Alaska residents.

659
00:34:46,920 --> 00:34:50,839
Speaker 4: That's actually very successful, very popular. Norway does a great job.

660
00:34:51,600 --> 00:34:53,160
Speaker 4: There are some countries that do a very bad job

661
00:34:53,160 --> 00:34:57,800
Speaker 4: of this, by the way, socializing.

662
00:34:56,120 --> 00:34:57,759
Speaker 1: Resources, So let's speak clear.

663
00:34:57,760 --> 00:34:59,920
Speaker 4: It's not always done well, but there are there are,

664
00:35:00,000 --> 00:35:01,200
Speaker 4: there are good examples out there.

665
00:35:01,440 --> 00:35:03,799
Speaker 1: Okay, So my last question to you, because I did

666
00:35:03,840 --> 00:35:08,000
Speaker 1: not know this until I scrolled through your Twitter account,

667
00:35:08,960 --> 00:35:12,840
Speaker 1: you said, and is there any events that social media

668
00:35:12,920 --> 00:35:15,000
Speaker 1: companies who have warmed up to Trump now that he's

669
00:35:15,040 --> 00:35:18,839
Speaker 1: president who hated him four years ago are kind of

670
00:35:18,960 --> 00:35:23,759
Speaker 1: muting or socially are I guess muting is the right word,

671
00:35:23,960 --> 00:35:29,160
Speaker 1: muting anti ICE demonstrators comments or you said that they

672
00:35:29,200 --> 00:35:35,360
Speaker 1: were basically shadow banning people that were sending like routes

673
00:35:35,360 --> 00:35:37,680
Speaker 1: to ICE or ICE agents were or trying to disrupt

674
00:35:37,680 --> 00:35:39,759
Speaker 1: federal agents. Yeah.

675
00:35:39,960 --> 00:35:44,680
Speaker 4: Yeah, I know several accounts, some of whom have over

676
00:35:44,719 --> 00:35:48,880
Speaker 4: a million followers, who attempted this week to share memes

677
00:35:49,080 --> 00:35:53,520
Speaker 4: and posters and online content around the proposed strike on

678
00:35:53,600 --> 00:35:57,600
Speaker 4: January thirtieth and solidarity with Minnesota activists around ICE. I

679
00:35:57,640 --> 00:36:01,600
Speaker 4: couldn't do it, or if they did do it, they

680
00:36:01,640 --> 00:36:03,680
Speaker 4: had no views. Like these were people with over a

681
00:36:03,680 --> 00:36:06,720
Speaker 4: million followers who at a minimum receive over one hundred

682
00:36:06,719 --> 00:36:09,880
Speaker 4: thousand views on their content. They would get maybe a

683
00:36:09,920 --> 00:36:13,279
Speaker 4: few dozen. Look I covered the Twitter file as I

684
00:36:13,320 --> 00:36:17,680
Speaker 4: covered WikiLeaks. I covered a lot of the social media suppression.

685
00:36:17,920 --> 00:36:19,880
Speaker 4: I covered a lot of the stuff coming out of

686
00:36:19,920 --> 00:36:22,000
Speaker 4: the Biden administration and how they were kind of reaching

687
00:36:22,040 --> 00:36:25,279
Speaker 4: into Facebook and and old Twitter, around COVID around the

688
00:36:25,320 --> 00:36:31,160
Speaker 4: twenty twenty election and suppressing content algorithmically. It's very clear

689
00:36:31,200 --> 00:36:33,319
Speaker 4: something's happening here. We don't have all the facts. We

690
00:36:33,320 --> 00:36:35,439
Speaker 4: don't know exactly what's coming out of the companies because

691
00:36:35,480 --> 00:36:37,480
Speaker 4: it is kind of a black box. You need someone

692
00:36:37,480 --> 00:36:39,920
Speaker 4: like Elon must have forced things open, or like a

693
00:36:39,960 --> 00:36:44,400
Speaker 4: federal investigation. But it's obvious that someone's playing with the

694
00:36:44,400 --> 00:36:45,279
Speaker 4: algorithm right now.

695
00:36:46,080 --> 00:36:47,839
Speaker 1: All right, Lee, thank you for coming this podcast. I

696
00:36:47,880 --> 00:36:49,680
Speaker 1: really appreciate it. Where can people go to read more

697
00:36:49,719 --> 00:36:51,239
Speaker 1: about your stuff, watch your interviews?

698
00:36:51,960 --> 00:36:55,240
Speaker 4: Just leefong dot com and Lhfang on Twitter.

699
00:36:55,440 --> 00:36:57,480
Speaker 1: All right, awesome, thank you coming on. I appreciate it.

700
00:36:57,760 --> 00:37:03,360
Speaker 1: Thanks Ryan. Now it's time to Ask Me Anything segment.

701
00:37:03,360 --> 00:37:04,840
Speaker 1: If you want to be part of the Ask Me

702
00:37:04,880 --> 00:37:08,160
Speaker 1: Anything segment, email me Ryan at numbers gamepodcast dot com.

703
00:37:08,160 --> 00:37:10,600
Speaker 1: That's Ryan at numbers gamepodcast dot com. I got rid.

704
00:37:10,880 --> 00:37:13,920
Speaker 1: I have this one email that's been sitting in my inbox.

705
00:37:13,960 --> 00:37:16,000
Speaker 1: For like a week now from one of my listeners

706
00:37:16,719 --> 00:37:20,280
Speaker 1: who asks one of the hardest questions and smartest questions

707
00:37:20,280 --> 00:37:22,600
Speaker 1: for me to answer, So I put it on the backgrounder.

708
00:37:22,640 --> 00:37:24,600
Speaker 1: I'm going to get to that on next week's episode

709
00:37:24,640 --> 00:37:27,360
Speaker 1: because it's very intelligent and involves a ton of research.

710
00:37:27,360 --> 00:37:30,160
Speaker 1: With these involved less research. So if you haven't heard

711
00:37:30,280 --> 00:37:33,200
Speaker 1: your answer being asked yet answered yet, I will get

712
00:37:33,200 --> 00:37:35,399
Speaker 1: to it. Some of you guys ask really difficult ones

713
00:37:35,400 --> 00:37:37,640
Speaker 1: and involve a lot of research from me in perspective,

714
00:37:37,719 --> 00:37:39,560
Speaker 1: so if you haven't heard it, stay tuned. I will

715
00:37:39,600 --> 00:37:41,960
Speaker 1: get to them. I promise. This one comes from Kevin.

716
00:37:42,000 --> 00:37:43,680
Speaker 1: He says Ryan. I'm sure you will hate me for this,

717
00:37:43,760 --> 00:37:46,920
Speaker 1: but why don't I fill out forms anything service polls.

718
00:37:46,960 --> 00:37:48,759
Speaker 1: I never answered the question of my race leading a

719
00:37:48,840 --> 00:37:51,319
Speaker 1: plank or if it's required I write other am I

720
00:37:51,360 --> 00:37:54,200
Speaker 1: an outlier is a specifically significant number of people who

721
00:37:54,239 --> 00:37:56,279
Speaker 1: do this. Love the podcast, Kevin, love you for loving

722
00:37:56,320 --> 00:37:58,799
Speaker 1: the podcast, So you're not an outlier. I know other

723
00:37:58,840 --> 00:38:00,720
Speaker 1: people who do it. To people who lie on poles

724
00:38:00,719 --> 00:38:02,520
Speaker 1: that they are white, They'll say they're black or whatever.

725
00:38:02,800 --> 00:38:06,120
Speaker 1: Is it significant? I don't think so. I don't lie

726
00:38:06,160 --> 00:38:09,080
Speaker 1: on that on that information. I think that it's important

727
00:38:09,160 --> 00:38:12,960
Speaker 1: that the data is correct when people are looking to

728
00:38:12,960 --> 00:38:16,640
Speaker 1: create policies or look for answers, or see the general

729
00:38:16,680 --> 00:38:18,960
Speaker 1: feel of the populace. I don't hate you for it.

730
00:38:18,960 --> 00:38:21,120
Speaker 1: It's just kind of you rate others, so at least

731
00:38:21,160 --> 00:38:23,120
Speaker 1: it's not a complete lie. But I think that I

732
00:38:23,160 --> 00:38:25,799
Speaker 1: think that whatever. I think that it's it's easier to

733
00:38:25,840 --> 00:38:28,319
Speaker 1: get more accurate information if you tell the truth. It's

734
00:38:28,320 --> 00:38:30,360
Speaker 1: not used against you. If you're feeling out the form anyway,

735
00:38:30,360 --> 00:38:32,680
Speaker 1: which I love when you answer polls, I think that

736
00:38:33,040 --> 00:38:35,279
Speaker 1: you might as well just tell the accurate race. And

737
00:38:35,280 --> 00:38:37,640
Speaker 1: it's not like no one does it. But you're more

738
00:38:37,680 --> 00:38:40,760
Speaker 1: of an outlier than you are of the regular person anyway.

739
00:38:40,880 --> 00:38:42,359
Speaker 1: But in your opinion, I don't hate you for it.

740
00:38:42,640 --> 00:38:44,879
Speaker 1: You know it is what it is. Next question comes

741
00:38:44,880 --> 00:38:47,200
Speaker 1: from Anthony. He says, Hey, Ryan, love your podcast. I

742
00:38:47,239 --> 00:38:51,320
Speaker 1: listen to every episode, Anthony, you are a star. Ignore

743
00:38:51,360 --> 00:38:54,359
Speaker 1: the grammar pronunciation police. We all have the things we

744
00:38:54,440 --> 00:38:59,520
Speaker 1: say wrong. I am absolutely being tortured over this. I

745
00:38:59,560 --> 00:39:01,800
Speaker 1: know I pronounce a lot of things wrong. I'm sorry.

746
00:39:01,840 --> 00:39:03,520
Speaker 1: I have a New York accent. And what I have

747
00:39:03,760 --> 00:39:07,000
Speaker 1: managed to do is I really avoid it being so

748
00:39:07,200 --> 00:39:11,440
Speaker 1: pronounced unless I'm very angry or I'm talking to a

749
00:39:11,480 --> 00:39:13,880
Speaker 1: friend from from the neighborhood. If I had a friend

750
00:39:13,920 --> 00:39:15,759
Speaker 1: like one of my close friends from my neighborhood on

751
00:39:15,840 --> 00:39:18,400
Speaker 1: this podcast, you would need subtitles every one of you.

752
00:39:18,480 --> 00:39:22,200
Speaker 1: It would just go it would go south really fast.

753
00:39:22,239 --> 00:39:24,520
Speaker 1: We would make duck Dynasty look like the King's speech.

754
00:39:24,560 --> 00:39:27,319
Speaker 1: I mean, it's just we are, we are, we get

755
00:39:27,360 --> 00:39:30,120
Speaker 1: into it, and it's it's forever anyway, he says. Now,

756
00:39:30,160 --> 00:39:32,680
Speaker 1: my question. I regularly hear clips of Harry Inton on

757
00:39:32,719 --> 00:39:35,120
Speaker 1: CNN talking about how unpopular Democrats are and how they

758
00:39:35,120 --> 00:39:37,120
Speaker 1: have a record low approval rating. Yet I hear from

759
00:39:37,160 --> 00:39:39,040
Speaker 1: you and others how Democrats are likely to take the

760
00:39:39,080 --> 00:39:41,640
Speaker 1: House and the generic polls. Can you explain how both

761
00:39:41,680 --> 00:39:43,960
Speaker 1: can be true? Blessings Anthony, Yes, Anthony, this is a

762
00:39:43,960 --> 00:39:47,600
Speaker 1: great question. So we have a we have two party system, right,

763
00:39:47,719 --> 00:39:49,160
Speaker 1: if you don't like wanting to vote for the other,

764
00:39:49,360 --> 00:39:52,600
Speaker 1: that's a big part of it. Even if you dislike them,

765
00:39:52,840 --> 00:39:57,279
Speaker 1: both parties are unpopular. Democrats are more so unpopular, right,

766
00:39:57,360 --> 00:40:01,040
Speaker 1: But there's a certain percentage of the popation that are

767
00:40:01,120 --> 00:40:03,480
Speaker 1: voting with the intention of showing the president, they are

768
00:40:03,480 --> 00:40:07,480
Speaker 1: dissatisfied with the performance because it is not so if

769
00:40:07,520 --> 00:40:09,400
Speaker 1: you're voting for the average Republican and a lot of

770
00:40:09,440 --> 00:40:12,480
Speaker 1: times you're voting for or against Donald Trump, you are

771
00:40:12,520 --> 00:40:16,160
Speaker 1: not necessarily voting for or against your congressman, for or

772
00:40:16,200 --> 00:40:21,120
Speaker 1: against your senator. Which is why the days of you know,

773
00:40:21,760 --> 00:40:24,680
Speaker 1: Ronald Reagan or George H. W. Bush or Bill Clinton

774
00:40:24,800 --> 00:40:27,360
Speaker 1: having members of his party having members of the opposite

775
00:40:27,360 --> 00:40:29,919
Speaker 1: party in seats that he won, have kind of gone away.

776
00:40:29,960 --> 00:40:33,040
Speaker 1: You're voting for or against the president, You're not really

777
00:40:33,120 --> 00:40:36,200
Speaker 1: voting for the individual person. That's why Susan Collins is

778
00:40:36,239 --> 00:40:40,000
Speaker 1: such an outlier because they're still vote for Susan Collins

779
00:40:40,080 --> 00:40:42,680
Speaker 1: in May and they don't vote necessarily for or against Trump.

780
00:40:43,000 --> 00:40:46,520
Speaker 1: But those are unique, unique, unique cases, and that's really

781
00:40:46,600 --> 00:40:49,320
Speaker 1: why it's why Democrats are likely to win the House

782
00:40:49,360 --> 00:40:52,000
Speaker 1: over who knows what the Senate. Senate looks more favorable

783
00:40:52,040 --> 00:40:54,920
Speaker 1: for Republicans, but you know who knows. The difference though,

784
00:40:55,480 --> 00:40:57,640
Speaker 1: is when it comes to president. When it comes to

785
00:40:57,680 --> 00:41:01,839
Speaker 1: president and there's a nationally identified person person, then support

786
00:41:02,040 --> 00:41:05,640
Speaker 1: for or against a party matters a lot less. I

787
00:41:05,640 --> 00:41:07,600
Speaker 1: would go back to the last time that it would

788
00:41:07,680 --> 00:41:11,080
Speaker 1: really matter was probably it was probably George W. Bush

789
00:41:11,120 --> 00:41:13,200
Speaker 1: in two thousand and eight where the Republican Party was

790
00:41:13,239 --> 00:41:16,080
Speaker 1: in such bad shape, you know, two thousand and eight,

791
00:41:16,120 --> 00:41:18,719
Speaker 1: I think they were looking at the low twenties or

792
00:41:18,719 --> 00:41:21,440
Speaker 1: maybe even teens as far as support. It was basically regional.

793
00:41:21,480 --> 00:41:24,960
Speaker 1: There was a Time magazine cover about cold extinct species

794
00:41:25,000 --> 00:41:28,839
Speaker 1: and it was a picture of the GOP elephant saying

795
00:41:28,840 --> 00:41:31,080
Speaker 1: it was a regional party in the South. That is

796
00:41:31,400 --> 00:41:33,840
Speaker 1: that's really why it's really because you're voting four or

797
00:41:33,840 --> 00:41:37,800
Speaker 1: against Donald Trump and the Mike Lawlers, the Brian Fitzpatricks,

798
00:41:37,880 --> 00:41:42,320
Speaker 1: the Don Bacans and Susan Collins. Those Republicans in blue seeds,

799
00:41:42,600 --> 00:41:46,040
Speaker 1: they're few and far between, and they have to work

800
00:41:46,080 --> 00:41:50,400
Speaker 1: harder and campaign harder. But that's why almost every seat

801
00:41:50,520 --> 00:41:53,440
Speaker 1: that Kamala one is represented by a Democrat. Almost every

802
00:41:53,760 --> 00:41:56,200
Speaker 1: Trump one is represented by a Republican. And I think

803
00:41:56,320 --> 00:41:59,640
Speaker 1: maybe there's ten that kind of broke that three Republicans.

804
00:41:59,680 --> 00:42:02,680
Speaker 1: I think seven Democrats or maybe even know they're thirteen.

805
00:42:02,719 --> 00:42:05,600
Speaker 1: There's ten Democrats. What year is it, it's twenty twenty six.

806
00:42:05,760 --> 00:42:08,480
Speaker 1: There are twelve Democrats three I mean more because it

807
00:42:08,520 --> 00:42:11,200
Speaker 1: was double twelve Democrats are three Republicans, fifteen in total,

808
00:42:11,239 --> 00:42:16,239
Speaker 1: one Senator Susan Collins. That's that's for the election this year.

809
00:42:16,440 --> 00:42:19,160
Speaker 1: That is uh, That's why it's just people fall into

810
00:42:19,160 --> 00:42:22,400
Speaker 1: tribal nature for and against the president. The Democrat Party

811
00:42:22,480 --> 00:42:24,960
Speaker 1: is super unpopular and they will be even more unpopular

812
00:42:25,040 --> 00:42:27,800
Speaker 1: unless they sit there and they learn from anything the

813
00:42:27,880 --> 00:42:31,200
Speaker 1: last five years. Who knows if they will. We'll see, guys.

814
00:42:31,200 --> 00:42:33,000
Speaker 1: Thank you for this podcast, Thank you for guys listening.

815
00:42:33,080 --> 00:42:35,600
Speaker 1: I will be back on Monday. We are having an

816
00:42:35,680 --> 00:42:40,920
Speaker 1: episode on Monday about the craziest Republican primary in the country.

817
00:42:40,960 --> 00:42:43,560
Speaker 1: It's in the house race in Florida. You guys probably

818
00:42:43,560 --> 00:42:46,560
Speaker 1: haven't heard of it. I'm gonna just leap into it,

819
00:42:46,719 --> 00:42:49,600
Speaker 1: into the insanity that's going on in Florida right now.

820
00:42:49,640 --> 00:42:53,000
Speaker 1: Florida is being Florida like they have it in quite

821
00:42:53,040 --> 00:42:55,160
Speaker 1: some time. If you like this podcast, please like and

822
00:42:55,200 --> 00:42:57,759
Speaker 1: subscribe on the iHeartRadio app Apple podcast, where we get

823
00:42:57,760 --> 00:42:59,800
Speaker 1: your podcast. Please subscribe on YouTube if you like to

824
00:42:59,800 --> 00:43:02,080
Speaker 1: get yeah your podcast there, and I will talk to

825
00:43:02,080 --> 00:43:03,800
Speaker 1: you guys on Monday.