1
00:00:00,160 --> 00:00:10,400
Speaker 1: And oh loll back down.

2
00:00:11,960 --> 00:00:14,040
Speaker 2: Hey everybody, thanks so much for joining us right here

3
00:00:14,080 --> 00:00:16,639
Speaker 2: on the right view tonight, we're joined by the CEO

4
00:00:16,920 --> 00:00:20,319
Speaker 2: of Eyes Over, Chris Wilson. Chris, welcome to the show.

5
00:00:20,400 --> 00:00:23,959
Speaker 2: Thank you so much for joining. In your recent op ed,

6
00:00:24,120 --> 00:00:28,760
Speaker 2: you argue that Gallup's decision to stop tracking presidential approval

7
00:00:28,840 --> 00:00:33,040
Speaker 2: ratings isn't just a business move, but maybe a sign

8
00:00:33,159 --> 00:00:37,080
Speaker 2: of deeper issues in polling. So can you elaborate on

9
00:00:37,280 --> 00:00:42,400
Speaker 2: why you see this as an acknowledgment of perhaps systemic failures.

10
00:00:45,880 --> 00:00:50,479
Speaker 3: Yeah, the problem with what Gallup was doing is that

11
00:00:50,760 --> 00:00:54,040
Speaker 3: polling is no longer built to measure those types of issues,

12
00:00:54,080 --> 00:00:56,080
Speaker 3: and that was they said they were going to stop

13
00:00:56,080 --> 00:00:59,600
Speaker 3: measuring presidential approval, and that's based on a lot of issues,

14
00:01:00,120 --> 00:01:03,200
Speaker 3: primarily its response rates. It's kind of things that made

15
00:01:03,280 --> 00:01:07,440
Speaker 3: polling wrong in twenty sixteen, and from that it has

16
00:01:07,560 --> 00:01:12,880
Speaker 3: become a challenge for them to report on anything correctly.

17
00:01:13,440 --> 00:01:16,600
Speaker 3: And so when response rates are low, you rely heavily

18
00:01:16,640 --> 00:01:19,000
Speaker 3: on who picks up the phone, who fills out a survey.

19
00:01:19,520 --> 00:01:22,920
Speaker 3: Higher trust, higher institutional engagement, voters are more likely to respond,

20
00:01:23,360 --> 00:01:25,840
Speaker 3: and frankly, that ends up skewing more Democrat as we've

21
00:01:25,840 --> 00:01:28,720
Speaker 3: seen in twenty sixteen and twenty twenty and the other

22
00:01:28,760 --> 00:01:31,440
Speaker 3: issues have been factor into it that I could bring

23
00:01:31,520 --> 00:01:32,800
Speaker 3: up and I want to put your listeners to sleep

24
00:01:32,840 --> 00:01:35,720
Speaker 3: too early in the segment, but education waiting, likely voter screens,

25
00:01:35,760 --> 00:01:38,039
Speaker 3: things like that. So all of that came together to

26
00:01:38,480 --> 00:01:41,800
Speaker 3: cause Gallup to make a decision that frankly, I made

27
00:01:41,840 --> 00:01:44,160
Speaker 3: the decision myself a few years back. I was named

28
00:01:44,200 --> 00:01:47,000
Speaker 3: Polster the Year in twenty twenty one after Glenn Youngkin's

29
00:01:47,040 --> 00:01:50,760
Speaker 3: victory in Virginia, and I saw firsthand at that point

30
00:01:51,280 --> 00:01:55,600
Speaker 3: that polling had become problematic, if not impossible, to be

31
00:01:55,600 --> 00:01:58,760
Speaker 3: able to measure what it has was originally designed to measure.

32
00:01:59,080 --> 00:02:00,680
Speaker 4: And so that brings us full circle. And that's what

33
00:02:00,760 --> 00:02:02,080
Speaker 4: Gallup is kind of just announced.

34
00:02:02,080 --> 00:02:04,560
Speaker 3: And I'd notice how a while back and begin making

35
00:02:04,600 --> 00:02:07,120
Speaker 3: them move into a different area of my career, which

36
00:02:07,160 --> 00:02:08,839
Speaker 3: is a CEO of I's over now.

37
00:02:09,720 --> 00:02:13,160
Speaker 2: So it's it's very interesting because you go back to

38
00:02:13,600 --> 00:02:17,359
Speaker 2: what President Trump has said maybe for a decade now,

39
00:02:17,440 --> 00:02:21,239
Speaker 2: which is that the polling in this country is absolutely off,

40
00:02:21,280 --> 00:02:24,840
Speaker 2: that it is not reflective in many senses of the

41
00:02:24,919 --> 00:02:28,639
Speaker 2: general sentiment of the population and I saw this firsthand

42
00:02:29,080 --> 00:02:31,920
Speaker 2: in twenty sixteen myself. You know, we as a family,

43
00:02:31,919 --> 00:02:35,120
Speaker 2: were traveling all over the country campaigning for my father

44
00:02:35,160 --> 00:02:37,880
Speaker 2: in law. And it was funny because I would go

45
00:02:38,000 --> 00:02:39,960
Speaker 2: out and I would be in all of these different areas.

46
00:02:40,000 --> 00:02:42,919
Speaker 2: I'd be in Iowa and Ohio and North Carolina and Florida,

47
00:02:43,440 --> 00:02:47,240
Speaker 2: and I would see the enthusiasm out on the ground,

48
00:02:47,320 --> 00:02:50,040
Speaker 2: the lines of people that had gathered to come to

49
00:02:50,080 --> 00:02:54,000
Speaker 2: an event I was hosting. I was not even the candidate,

50
00:02:54,040 --> 00:02:56,080
Speaker 2: you know. And so then I would go back to

51
00:02:56,160 --> 00:02:57,919
Speaker 2: and my husband and I have this story we always

52
00:02:57,919 --> 00:03:00,680
Speaker 2: tell people we go back to our hotel rooms that night,

53
00:03:00,720 --> 00:03:03,160
Speaker 2: we'd call each other and I would say, how was

54
00:03:03,200 --> 00:03:05,200
Speaker 2: your day? And he would say it was insane, the

55
00:03:05,280 --> 00:03:08,200
Speaker 2: lines were crazy, that the crowds were amazing. And I

56
00:03:08,240 --> 00:03:09,959
Speaker 2: would say the same thing. And then we'd both turn

57
00:03:10,000 --> 00:03:12,760
Speaker 2: on the news and we would get thoroughly depressed because

58
00:03:12,800 --> 00:03:14,680
Speaker 2: we would say, wait a minute, what is it that

59
00:03:14,720 --> 00:03:18,720
Speaker 2: they're missing that we're seeing. But it has been wrong,

60
00:03:18,960 --> 00:03:23,079
Speaker 2: as you point out, for so long. President Trump, though,

61
00:03:23,160 --> 00:03:25,800
Speaker 2: has called this out, and he's been given quite a

62
00:03:25,840 --> 00:03:29,280
Speaker 2: hard time about it by the legacy media. It sounds

63
00:03:29,320 --> 00:03:32,920
Speaker 2: like you're saying he's pretty accurate whenever he says something

64
00:03:32,960 --> 00:03:34,280
Speaker 2: is off with the polling.

65
00:03:36,920 --> 00:03:37,480
Speaker 4: Well he is.

66
00:03:37,920 --> 00:03:39,600
Speaker 3: And kind of the point you made, I think is

67
00:03:39,640 --> 00:03:43,200
Speaker 3: exactly the issue with polling. You mentioned going to individual

68
00:03:43,240 --> 00:03:46,160
Speaker 3: states and then the polling was off in those states.

69
00:03:46,480 --> 00:03:48,680
Speaker 3: And so I think what twenty sixteen proved, and it's

70
00:03:48,680 --> 00:03:51,200
Speaker 3: a was the beginning of the end for me and

71
00:03:51,280 --> 00:03:53,960
Speaker 3: seeing this is that to prove the polling has major

72
00:03:54,000 --> 00:03:56,760
Speaker 3: blind spots national polls, as you know, we're pretty close.

73
00:03:57,240 --> 00:04:00,800
Speaker 3: Where the industry had struggled was measured intensity turnout behavior

74
00:04:00,840 --> 00:04:02,880
Speaker 3: in key states, which is what you saw when you're

75
00:04:02,920 --> 00:04:05,440
Speaker 3: on the ground, and that's really a different problem. I

76
00:04:05,440 --> 00:04:09,560
Speaker 3: think twenty sixteen began the exposure of that your father

77
00:04:09,600 --> 00:04:13,640
Speaker 3: in law saw was that there is an energy asymmetry,

78
00:04:13,680 --> 00:04:17,600
Speaker 3: asymmetry between traditional surveys that traditional surveys didn't capture. Again,

79
00:04:17,680 --> 00:04:20,039
Speaker 3: what you were feeling on the ground, and President Trumps

80
00:04:20,040 --> 00:04:24,080
Speaker 3: support wasn't just preference, it was intensity, it was emotional activation.

81
00:04:24,800 --> 00:04:27,400
Speaker 3: And intensity is a lot harder model when sproant's rates

82
00:04:27,400 --> 00:04:31,120
Speaker 3: are declining and certain voters distrust institutions enough not to

83
00:04:31,160 --> 00:04:34,279
Speaker 3: even answer surveys. And so that's why I moved into

84
00:04:34,320 --> 00:04:36,920
Speaker 3: this real time sentiment work, and so if you're measuring

85
00:04:37,240 --> 00:04:41,120
Speaker 3: narrative energy and emotional volatility, you see those shifts earlier.

86
00:04:41,480 --> 00:04:44,599
Speaker 3: Polling tells you what people say when they're asked, and

87
00:04:44,680 --> 00:04:47,400
Speaker 3: what sentiment shows you is how strongly they feel about

88
00:04:47,440 --> 00:04:50,520
Speaker 3: something when they're being asked. And that's exactly what you

89
00:04:50,600 --> 00:04:53,520
Speaker 3: saw in each of those states. And that's why I'll

90
00:04:53,600 --> 00:04:56,640
Speaker 3: jump forward to a twenty twenty example where you see

91
00:04:56,960 --> 00:04:59,279
Speaker 3: Washington post to a poll a week after the election

92
00:04:59,360 --> 00:05:01,039
Speaker 3: that has by up eighteen.

93
00:05:01,160 --> 00:05:03,080
Speaker 4: He was never up eighteen. It was just wrong.

94
00:05:03,600 --> 00:05:05,600
Speaker 3: And I don't think anybody sat around in a room

95
00:05:05,640 --> 00:05:07,680
Speaker 3: to try and make something up. I think what they

96
00:05:07,680 --> 00:05:11,000
Speaker 3: were doing was they lost the ability to measure what

97
00:05:11,200 --> 00:05:13,000
Speaker 3: is happening that you feel when you're on the ground

98
00:05:13,040 --> 00:05:13,680
Speaker 3: in a campaign.

99
00:05:14,440 --> 00:05:18,400
Speaker 2: There are implications though to what these polls will do

100
00:05:19,120 --> 00:05:24,039
Speaker 2: to an electorate though, right, because you've written about voter perceptions,

101
00:05:25,000 --> 00:05:28,960
Speaker 2: you know you have these polls where they say, well,

102
00:05:29,080 --> 00:05:31,560
Speaker 2: this candidate has no shot, right, I mean, look at

103
00:05:31,560 --> 00:05:34,719
Speaker 2: Donald Trump in twenty sixteen. My god, by all accounts,

104
00:05:34,760 --> 00:05:36,480
Speaker 2: he should have just given up and thrown in the

105
00:05:36,520 --> 00:05:39,560
Speaker 2: towel early on. But if you listen to a lot

106
00:05:39,600 --> 00:05:42,400
Speaker 2: of the polls that were out there, right, So that

107
00:05:42,839 --> 00:05:48,200
Speaker 2: actually does weigh on voters. The way that these polls

108
00:05:48,200 --> 00:05:51,760
Speaker 2: are designed to according to a lot of people, does

109
00:05:51,839 --> 00:05:56,360
Speaker 2: have an influence on public opinion in a very big way, right,

110
00:05:59,480 --> 00:06:00,520
Speaker 2: ohold does.

111
00:06:00,560 --> 00:06:03,200
Speaker 3: And I think going back to that sixteen point Wisconsin poll,

112
00:06:06,000 --> 00:06:07,520
Speaker 3: it wasn't an outlier, it was the norm.

113
00:06:07,760 --> 00:06:10,480
Speaker 4: And because of that, the media promotes it.

114
00:06:10,560 --> 00:06:12,200
Speaker 3: And then what do you do if you're a Donald

115
00:06:12,200 --> 00:06:13,960
Speaker 3: Trump voter in Wisconsin, Like, well, he's going to lose

116
00:06:14,000 --> 00:06:16,359
Speaker 3: my double digits, why do I even get out and vote?

117
00:06:16,360 --> 00:06:18,239
Speaker 3: And of course that cost him at least a percentage

118
00:06:18,279 --> 00:06:20,800
Speaker 3: point there, and you give examples of that that happened in.

119
00:06:20,760 --> 00:06:21,600
Speaker 4: Lots of other states.

120
00:06:21,640 --> 00:06:23,599
Speaker 3: But I started doing this earlier, and I feel like

121
00:06:23,600 --> 00:06:26,839
Speaker 3: for your listeners and viewers that is important understand when

122
00:06:26,880 --> 00:06:29,000
Speaker 3: response rates are very low, and this is what Gallup

123
00:06:29,040 --> 00:06:31,680
Speaker 3: wrote about, you rely heavily just on who picks up

124
00:06:31,680 --> 00:06:34,800
Speaker 3: the phone, who fills out a survey, and that does

125
00:06:34,880 --> 00:06:37,000
Speaker 3: skew toward Democrat leaning voters.

126
00:06:37,520 --> 00:06:38,480
Speaker 4: Republicans are more.

127
00:06:38,400 --> 00:06:41,640
Speaker 3: Distrustful of big institutions, and I think your father in

128
00:06:41,720 --> 00:06:44,479
Speaker 3: law's doing a lot to fix that. But having said that,

129
00:06:44,520 --> 00:06:49,560
Speaker 3: we are just naturally more distrustful of them, and we

130
00:06:49,560 --> 00:06:51,479
Speaker 3: don't want to talk to somebody who calls us on

131
00:06:51,520 --> 00:06:53,599
Speaker 3: the phone and tell those things, because look what happened

132
00:06:53,600 --> 00:06:55,760
Speaker 3: in twenty twenty during COVID. You tell somebody something secret,

133
00:06:55,760 --> 00:06:57,560
Speaker 3: next thing you know, you lose your job. And the

134
00:06:57,600 --> 00:07:00,320
Speaker 3: other aspects of this education waiting. I mentioned this back

135
00:07:00,320 --> 00:07:01,760
Speaker 3: that I'll go back to it. In twenty sixteen and

136
00:07:01,800 --> 00:07:05,599
Speaker 3: twenty twenty one major issue was the underweighting of non

137
00:07:05,640 --> 00:07:09,400
Speaker 3: college voters in certain states, and when that correction wasn't

138
00:07:09,440 --> 00:07:14,840
Speaker 3: accounted for, it inflated Democrat margins in places like Wisconsin, Michigan, Pennsylvania.

139
00:07:15,640 --> 00:07:18,960
Speaker 3: And that's another aspect of what I like about cinema analysis.

140
00:07:19,080 --> 00:07:22,120
Speaker 3: We look at the entire population of conversations, we don't

141
00:07:22,120 --> 00:07:23,120
Speaker 3: actually just look.

142
00:07:22,960 --> 00:07:25,560
Speaker 4: At a specific segment of them, and then.

143
00:07:25,440 --> 00:07:28,840
Speaker 3: Likely voter screens generic ballot and again your father must

144
00:07:28,840 --> 00:07:30,560
Speaker 3: talk a lot about this and some of the poland

145
00:07:30,560 --> 00:07:33,040
Speaker 3: that's been out and looking toward the midterm election. Generic

146
00:07:33,080 --> 00:07:38,400
Speaker 3: ballot and approval questions measure preference, but elections are decided

147
00:07:38,440 --> 00:07:41,800
Speaker 3: by turnout, and if one side has higher intensity, they

148
00:07:41,800 --> 00:07:44,840
Speaker 3: can outperform top line preference numbers. I mean candidly, we

149
00:07:44,880 --> 00:07:47,800
Speaker 3: saw that work against Republicans in twenty twenty two. I

150
00:07:47,840 --> 00:07:49,720
Speaker 3: think you're going to see it work for Republicans in

151
00:07:49,720 --> 00:07:50,600
Speaker 3: twenty twenty six.

152
00:07:50,960 --> 00:07:53,600
Speaker 2: Okay, well this is interesting because everybody wants to hear

153
00:07:53,640 --> 00:07:56,840
Speaker 2: about the midterms. So first of all, tell me how

154
00:07:56,880 --> 00:07:59,200
Speaker 2: what you think you're going to see in twenty twenty six.

155
00:07:59,280 --> 00:08:03,640
Speaker 2: And look at the group that everybody is always vying

156
00:08:03,680 --> 00:08:07,760
Speaker 2: for are those independent voters. And we know the landscape

157
00:08:07,800 --> 00:08:11,960
Speaker 2: of politics has changed significantly, but everyone is looking for

158
00:08:12,000 --> 00:08:16,160
Speaker 2: what strategies they should use to appeal to independent voters.

159
00:08:16,160 --> 00:08:19,080
Speaker 2: So what advice would you give maybe Republicans right now

160
00:08:19,120 --> 00:08:20,640
Speaker 2: and what do you think we're going to see in

161
00:08:21,080 --> 00:08:22,720
Speaker 2: twenty twenty six in these midterms?

162
00:08:25,520 --> 00:08:27,160
Speaker 3: Well, if I knew the answer that, I'd go make

163
00:08:27,160 --> 00:08:33,000
Speaker 3: myself Richard Paul Market. So I do think that Republicans.

164
00:08:33,640 --> 00:08:37,440
Speaker 3: I think that Republicans who are addressing affordability and talking

165
00:08:37,480 --> 00:08:39,400
Speaker 3: about the issues that matter. And we really have three

166
00:08:39,480 --> 00:08:42,199
Speaker 3: kind of key issues that are impacting the electric right now.

167
00:08:42,200 --> 00:08:46,559
Speaker 3: You have affordability, which the President is dealing with very effectively,

168
00:08:46,600 --> 00:08:49,480
Speaker 3: and I think you're starting to see the economy strengthen again,

169
00:08:49,520 --> 00:08:51,560
Speaker 3: and you're seeing job numbers come back up, you're seeing

170
00:08:51,559 --> 00:08:53,800
Speaker 3: house and starts go up, and that all plays toward

171
00:08:54,760 --> 00:08:59,040
Speaker 3: toward Republicans. The second thing you're seeing is institutional distrust

172
00:09:00,200 --> 00:09:03,880
Speaker 3: like a BIGS again. And then the third thing is immigration.

173
00:09:04,000 --> 00:09:06,600
Speaker 3: Immigration is a spark on all of this. And so

174
00:09:07,120 --> 00:09:09,719
Speaker 3: I feel like right now Republicans have the edge on

175
00:09:09,760 --> 00:09:12,680
Speaker 3: those issues because they are able to show proof, show

176
00:09:12,800 --> 00:09:16,160
Speaker 3: proof of success. But the challenge is the communicating of

177
00:09:16,160 --> 00:09:18,720
Speaker 3: that proof of success. I remember hearing Tim Scott give

178
00:09:18,760 --> 00:09:22,800
Speaker 3: a speech after is right after the presidential election in

179
00:09:22,840 --> 00:09:25,960
Speaker 3: twenty twenty it was like early twenty twenty one. He said,

180
00:09:25,960 --> 00:09:28,800
Speaker 3: you know, we did amazing things under President Trump. The

181
00:09:28,840 --> 00:09:31,800
Speaker 3: problem was we didn't tell anybody. And it was a

182
00:09:31,800 --> 00:09:33,719
Speaker 3: great talk because you kind of sent back and said, yeah,

183
00:09:33,720 --> 00:09:35,280
Speaker 3: we didn't do a great job of that. And I

184
00:09:35,280 --> 00:09:37,760
Speaker 3: think that is where Republicans have a bit of a

185
00:09:37,840 --> 00:09:39,760
Speaker 3: challenge in what work to do is we've got to

186
00:09:39,760 --> 00:09:43,720
Speaker 3: tell the success story. And I'll get back to my

187
00:09:43,760 --> 00:09:46,280
Speaker 3: whole point here is be able to understand how the

188
00:09:46,280 --> 00:09:47,640
Speaker 3: public is responding to it.

189
00:09:47,760 --> 00:09:51,240
Speaker 4: And I'm gonna i'll talk about from polling. Polling still

190
00:09:51,240 --> 00:09:51,800
Speaker 4: has value.

191
00:09:52,040 --> 00:09:55,320
Speaker 3: Palling is like if you're watching a basketball game, polling

192
00:09:55,440 --> 00:09:57,520
Speaker 3: is the scoreboard. But if you've ever been to a

193
00:09:57,559 --> 00:09:59,400
Speaker 3: basketball game, you know the scoreboard is only one part

194
00:09:59,440 --> 00:10:00,839
Speaker 3: of the story. The other part of the story is

195
00:10:00,840 --> 00:10:03,520
Speaker 3: the momentum on the court. Who's got the who's get

196
00:10:03,520 --> 00:10:06,040
Speaker 3: the run. You see teams going ten put ten zero runs,

197
00:10:06,080 --> 00:10:07,520
Speaker 3: and it's like, wait a second, they were up, now

198
00:10:07,679 --> 00:10:08,040
Speaker 3: they were down.

199
00:10:08,120 --> 00:10:10,160
Speaker 4: Now they're up because they had momentum. And that's what

200
00:10:10,280 --> 00:10:11,160
Speaker 4: centem analysis is.

201
00:10:11,200 --> 00:10:12,880
Speaker 3: That's why I've made the shift into this side of

202
00:10:12,880 --> 00:10:14,839
Speaker 3: the industry and the piece that you referenced I was

203
00:10:14,880 --> 00:10:18,040
Speaker 3: writing about because that is what's important. And if Republicans

204
00:10:18,080 --> 00:10:21,240
Speaker 3: can get the momentum going into the midterm elections, I

205
00:10:21,280 --> 00:10:22,480
Speaker 3: feel like they'll be fine.

206
00:10:22,559 --> 00:10:24,439
Speaker 4: But it is if they're not measuring that.

207
00:10:24,679 --> 00:10:26,760
Speaker 3: If there's a candidate for office who's only relying on

208
00:10:26,800 --> 00:10:29,960
Speaker 3: the old tools of understanding where opinion is measured, then

209
00:10:29,960 --> 00:10:32,760
Speaker 3: they're gonna be caught flat footed, and that is where

210
00:10:32,760 --> 00:10:33,640
Speaker 3: we lose elections.

211
00:10:33,920 --> 00:10:36,400
Speaker 2: Yeah, the old way in a lot of respects I

212
00:10:36,400 --> 00:10:39,400
Speaker 2: think is debt. You know, And something that you also

213
00:10:39,480 --> 00:10:43,920
Speaker 2: talk about in the op ed is real time information

214
00:10:44,360 --> 00:10:47,719
Speaker 2: feedback loops in digital media. You know, we're looking at

215
00:10:47,760 --> 00:10:51,560
Speaker 2: things like viral clips algorithms. How does that?

216
00:10:51,960 --> 00:10:52,200
Speaker 4: You know?

217
00:10:52,559 --> 00:10:57,040
Speaker 2: It kind of makes traditional polling obsolete. It We're in

218
00:10:57,080 --> 00:10:59,280
Speaker 2: a whole new era. This is a whole new way

219
00:10:59,800 --> 00:11:03,760
Speaker 2: of of disseminating information, getting things to catch on grabbing

220
00:11:03,800 --> 00:11:06,360
Speaker 2: people's attention. Right, So what do we need to know

221
00:11:06,400 --> 00:11:07,280
Speaker 2: about that space?

222
00:11:10,640 --> 00:11:13,640
Speaker 3: So I'm glad you ask at a technical level what

223
00:11:13,720 --> 00:11:16,840
Speaker 3: we do when we measure the online conversations and millions

224
00:11:16,880 --> 00:11:20,600
Speaker 3: and millions of real time public expressions across every digital platform.

225
00:11:20,880 --> 00:11:23,480
Speaker 3: And we don't just measure positive or negative. We measure

226
00:11:23,559 --> 00:11:28,559
Speaker 3: emotional intensity. We measure narrative clustering. We measure velocity of messaging.

227
00:11:28,840 --> 00:11:32,040
Speaker 3: And so the system is identifying what issues are rising

228
00:11:32,160 --> 00:11:36,400
Speaker 3: in salients, what emotional tone is attached to them, which

229
00:11:36,480 --> 00:11:40,200
Speaker 3: narratives are consolidating or fragmenting, and how quickly those narratives

230
00:11:40,240 --> 00:11:43,520
Speaker 3: are spreading. And it's not just sentiment, it's structure and speed.

231
00:11:44,000 --> 00:11:46,439
Speaker 3: And so we build what we call narrative clusters. The

232
00:11:47,000 --> 00:11:51,200
Speaker 3: artificial intelligence built in our system groups conversations into thematic

233
00:11:51,240 --> 00:11:54,240
Speaker 3: ecosystems instead of keywords, and this allows us to see

234
00:11:54,240 --> 00:11:57,840
Speaker 3: when a story shifts from say a policy debate to

235
00:11:57,920 --> 00:12:02,400
Speaker 3: a competence question, or so for law enforcement to fairness.

236
00:12:02,840 --> 00:12:06,520
Speaker 3: That shift is often invisible in polling, but obvious and

237
00:12:06,600 --> 00:12:09,640
Speaker 3: sentiment flow. And it also the other problem with polling

238
00:12:09,679 --> 00:12:11,040
Speaker 3: is unless you're in the field of asking at the

239
00:12:11,080 --> 00:12:12,800
Speaker 3: exact right moment, you're not going to see it occur.

240
00:12:13,080 --> 00:12:16,680
Speaker 4: Some analysis is real time and running at all time.

241
00:12:17,200 --> 00:12:20,520
Speaker 3: And I'll give you a perfect example where our friend

242
00:12:20,760 --> 00:12:23,800
Speaker 3: Brad Parscale happened to call me in the twenty twenty

243
00:12:23,800 --> 00:12:24,320
Speaker 3: four election.

244
00:12:25,080 --> 00:12:25,760
Speaker 4: I was working for a.

245
00:12:25,800 --> 00:12:29,040
Speaker 3: United States Senator who had a dip in on eyes

246
00:12:29,080 --> 00:12:31,440
Speaker 3: over and Brad Cen's between goes, hey, this is the problem.

247
00:12:31,440 --> 00:12:33,439
Speaker 4: You guys need to deal with it. We hadn't seen it.

248
00:12:33,480 --> 00:12:36,240
Speaker 3: We didn't see it in our polling until five days later,

249
00:12:36,520 --> 00:12:38,520
Speaker 3: and in fact, Brad gave me some advice on how.

250
00:12:38,440 --> 00:12:38,880
Speaker 4: To fix it.

251
00:12:38,960 --> 00:12:41,280
Speaker 3: We did, and so we were able to call me

252
00:12:41,400 --> 00:12:43,200
Speaker 3: like three days later and we fixed it. And I

253
00:12:43,240 --> 00:12:45,160
Speaker 3: didn't actually see it in our polling until a day

254
00:12:45,200 --> 00:12:47,280
Speaker 3: after he told me we'd already fixed it. And you

255
00:12:47,320 --> 00:12:49,559
Speaker 3: think about if those things are happening to you when

256
00:12:49,559 --> 00:12:51,600
Speaker 3: you're doing polling and you're working for and in come

257
00:12:51,600 --> 00:12:52,360
Speaker 3: at United States.

258
00:12:52,200 --> 00:12:54,280
Speaker 4: Center and you're doing you're doing.

259
00:12:54,200 --> 00:12:57,079
Speaker 3: Tracking every single night. You can imagine the blind spots

260
00:12:57,080 --> 00:13:00,160
Speaker 3: that are created by just looking at things the old way.

261
00:13:00,200 --> 00:13:02,120
Speaker 3: And I think that's really the key that we have

262
00:13:02,160 --> 00:13:04,720
Speaker 3: to look at moving into these next election cycles for

263
00:13:05,200 --> 00:13:07,079
Speaker 3: candiateer running what I would call a state of the

264
00:13:07,160 --> 00:13:07,760
Speaker 3: art campaign.

265
00:13:08,360 --> 00:13:11,559
Speaker 2: Well, you say that, you know, polling is still valuable,

266
00:13:11,760 --> 00:13:15,880
Speaker 2: that we shouldn't just kind of discard polls completely. But

267
00:13:16,160 --> 00:13:19,760
Speaker 2: in kind of this nuanced environment where obviously things are

268
00:13:19,840 --> 00:13:23,240
Speaker 2: changing all the time, how do we, Chris, make polling

269
00:13:23,320 --> 00:13:26,960
Speaker 2: more reliable, less susceptible to bias. What would you say

270
00:13:27,000 --> 00:13:30,079
Speaker 2: needs to happen so that twenty twenty six, twenty twenty

271
00:13:30,080 --> 00:13:33,120
Speaker 2: eight and beyond we feel pretty solid in our polling.

272
00:13:36,120 --> 00:13:38,720
Speaker 3: Well, I think you have to understand the place of polling.

273
00:13:38,800 --> 00:13:42,800
Speaker 3: Pelling tells you what people say when they're asked. So

274
00:13:42,920 --> 00:13:45,480
Speaker 3: back to my comparison, the sentiment shows how strongly they

275
00:13:45,520 --> 00:13:47,840
Speaker 3: feel even if they are being asked, and so you

276
00:13:47,840 --> 00:13:52,520
Speaker 3: need to understand the place of it. And polling is,

277
00:13:52,720 --> 00:13:56,719
Speaker 3: as itself, is an incomplete model. Again, when you only

278
00:13:56,760 --> 00:13:59,160
Speaker 3: fewer than five percent of people are participating or answering

279
00:13:59,160 --> 00:14:01,640
Speaker 3: a survey, you're depending heavily.

280
00:14:01,280 --> 00:14:02,360
Speaker 4: On waiting assumptions.

281
00:14:02,400 --> 00:14:05,439
Speaker 3: It kind of becomes an extrapolation of the pollster's imagination.

282
00:14:05,960 --> 00:14:08,760
Speaker 3: And so if the voters who are least trusting of

283
00:14:08,800 --> 00:14:12,360
Speaker 3: institutions are also the least likely to respond, that creates

284
00:14:12,360 --> 00:14:15,120
Speaker 3: a systematic measurement gap. And so that's where you've got

285
00:14:15,240 --> 00:14:16,200
Speaker 3: under You've got I call it.

286
00:14:16,200 --> 00:14:18,719
Speaker 4: A three lens system, and one lens is.

287
00:14:18,720 --> 00:14:23,200
Speaker 3: Polling, and that can be valuable for measuring opinions towards

288
00:14:23,200 --> 00:14:25,920
Speaker 3: specific messaging, it's kind of tough to test the messaging

289
00:14:25,960 --> 00:14:28,440
Speaker 3: and centiment be ing less you're pushing it out. Then

290
00:14:28,440 --> 00:14:30,400
Speaker 3: you've got the sentiment, which is the ongoing measurement of

291
00:14:30,480 --> 00:14:33,400
Speaker 3: what is occurring in opinions. And then predictive analytics, which

292
00:14:33,400 --> 00:14:36,160
Speaker 3: are the is the third lens and all those three.

293
00:14:36,360 --> 00:14:38,640
Speaker 3: So the future, I would say is not anti polling

294
00:14:39,200 --> 00:14:41,040
Speaker 3: campaign but campaigns that rely only.

295
00:14:40,880 --> 00:14:42,520
Speaker 4: On polling or flying partially blind.

296
00:14:42,840 --> 00:14:47,040
Speaker 3: And the future is layered intelligence surveys plus narrative at

297
00:14:47,120 --> 00:14:50,000
Speaker 3: tracking plus predictive analytics. And those are the three things

298
00:14:50,000 --> 00:14:55,040
Speaker 3: that I think any any strong solid campaign has to

299
00:14:55,080 --> 00:14:57,640
Speaker 3: have each of the three, or they're leaving one part

300
00:14:57,640 --> 00:15:00,000
Speaker 3: of they've got a blind spot in one aspect of it.

301
00:15:00,640 --> 00:15:06,440
Speaker 2: Well, I'll never forget watching the watching the polls come

302
00:15:06,480 --> 00:15:11,440
Speaker 2: back on election Day. They're at the polling locations on

303
00:15:11,640 --> 00:15:14,400
Speaker 2: in twenty sixteen, and I knew they were not going

304
00:15:14,480 --> 00:15:18,200
Speaker 2: to accurately reflect what was going to happen. You know,

305
00:15:18,320 --> 00:15:21,120
Speaker 2: you have those exit polls as people are leaving, they've

306
00:15:21,160 --> 00:15:24,280
Speaker 2: already gone to vote, Chris, and they're being asked by

307
00:15:24,320 --> 00:15:27,680
Speaker 2: some reporter generally, you know, who'd you vote for, And

308
00:15:27,760 --> 00:15:29,560
Speaker 2: a lot of those people I knew we're not going

309
00:15:29,640 --> 00:15:31,880
Speaker 2: to say Donald Trump, even if they had gone in

310
00:15:31,920 --> 00:15:34,200
Speaker 2: and voted for him. So I knew those polls were

311
00:15:34,240 --> 00:15:36,720
Speaker 2: going to be inaccurate. Turns out they really were, because

312
00:15:36,800 --> 00:15:39,680
Speaker 2: those polls predicted Hillary Clinton was going to be the

313
00:15:39,680 --> 00:15:42,720
Speaker 2: forty fifth president of the United States. Obviously we know

314
00:15:42,800 --> 00:15:45,800
Speaker 2: how that all worked out, but look still a valuable

315
00:15:46,040 --> 00:15:49,280
Speaker 2: thing for all of us to understand and something that

316
00:15:49,320 --> 00:15:51,840
Speaker 2: we're going to continue to hear a lot about polls

317
00:15:51,880 --> 00:15:55,320
Speaker 2: as we head towards this November. So Chris Wilson, thank

318
00:15:55,360 --> 00:15:57,160
Speaker 2: you so much for breaking it all down for us,

319
00:15:57,240 --> 00:15:59,440
Speaker 2: Thanks for giving us a little insight into this space,

320
00:15:59,640 --> 00:16:01,720
Speaker 2: and hope fully for making us all feel a little

321
00:16:01,760 --> 00:16:04,200
Speaker 2: more confident that going forward, we should be looking at

322
00:16:04,200 --> 00:16:07,120
Speaker 2: a lot of different things, not solely the polls as

323
00:16:07,120 --> 00:16:09,320
Speaker 2: we head towards the midterm. So Chris Wilson, thanks so

324
00:16:09,400 --> 00:16:12,600
Speaker 2: much for joining us. We appreciate it all right. I

325
00:16:12,640 --> 00:16:15,080
Speaker 2: need to share how to get two free tickets to

326
00:16:15,120 --> 00:16:20,600
Speaker 2: see Angel Studio's newest film, Solomeo, in theaters this Valentine's Day.

327
00:16:20,640 --> 00:16:24,600
Speaker 2: If you're looking for a funny, heartwarming, romantic comedy for

328
00:16:24,720 --> 00:16:28,880
Speaker 2: Valentine's this is the one. Angel Studios has truly done

329
00:16:28,880 --> 00:16:33,440
Speaker 2: it again. Solomeo's light, joyful, and funny. It's exactly the

330
00:16:33,520 --> 00:16:36,640
Speaker 2: kind of movie we need right now. Set in Italy,

331
00:16:36,880 --> 00:16:41,840
Speaker 2: gorgeous villas, sunsets and a dreamy backdrop, the film is

332
00:16:42,000 --> 00:16:46,240
Speaker 2: pure escapism. Kevin James is absolutely at his best, so

333
00:16:46,400 --> 00:16:49,440
Speaker 2: funny and so heartfelt, and Jonathan Roumy shows a side

334
00:16:49,440 --> 00:16:52,920
Speaker 2: of himself that will completely surprise you. Trust me, you

335
00:16:53,080 --> 00:16:55,600
Speaker 2: are going to love it. I love supporting movies that

336
00:16:55,640 --> 00:16:59,000
Speaker 2: make you feel good without compromising your values, and this

337
00:16:59,080 --> 00:17:02,760
Speaker 2: one is whole. I'm charming and genuinely funny right now,

338
00:17:02,760 --> 00:17:05,359
Speaker 2: when you become a Premium member of the Angel Guild,

339
00:17:05,440 --> 00:17:08,280
Speaker 2: you'll get two free tickets to see Solo Meo in

340
00:17:08,400 --> 00:17:13,840
Speaker 2: theaters February six. Let's fill theaters with stories that inspire humor, hope,

341
00:17:13,960 --> 00:17:17,960
Speaker 2: beauty and love. Go to angel dot com slash Laura

342
00:17:18,240 --> 00:17:21,439
Speaker 2: to join today and get your free tickets. I am

343
00:17:21,480 --> 00:17:25,000
Speaker 2: so excited to share something that has changed my daily life.

344
00:17:25,000 --> 00:17:28,240
Speaker 2: If you find yourself struggling with low energy, brain fog,

345
00:17:28,440 --> 00:17:31,800
Speaker 2: pesky colds, or waking up feeling just stiff and achy,

346
00:17:32,440 --> 00:17:35,000
Speaker 2: maybe you need to look into strong Cell. For me,

347
00:17:35,560 --> 00:17:38,439
Speaker 2: focus is essential, and strong cell keeps me sharp and

348
00:17:38,560 --> 00:17:42,359
Speaker 2: laser focused. Plus it provides me with clean natural energy,

349
00:17:42,520 --> 00:17:47,360
Speaker 2: no jitters, no weird spikes, and definitely no afternoon crash.

350
00:17:47,520 --> 00:17:50,640
Speaker 2: I just feel alive and like me. What really makes

351
00:17:50,680 --> 00:17:56,199
Speaker 2: strong cells stand out is its star ingredient na DH.

352
00:17:56,359 --> 00:17:59,800
Speaker 2: This powerful compound fuels every single cell in our bodies.

353
00:18:00,160 --> 00:18:04,600
Speaker 2: Think of it as the spark plug for cellular energy. Unfortunately,

354
00:18:04,840 --> 00:18:08,240
Speaker 2: as we age, our levels of NADH start to decline,

355
00:18:08,400 --> 00:18:11,560
Speaker 2: and with over thirty trillion cells in our bodies, it's

356
00:18:11,640 --> 00:18:16,240
Speaker 2: clear that healthier cells translate to a healthier, more vibrant me.

357
00:18:16,800 --> 00:18:21,240
Speaker 2: Strong cell doesn't just throw random ingredients together for results.

358
00:18:21,280 --> 00:18:24,920
Speaker 2: They're going to hope for They use its proprietary delivery

359
00:18:24,960 --> 00:18:28,919
Speaker 2: system designed to ensure that those ingredients actually reach your

360
00:18:28,960 --> 00:18:31,960
Speaker 2: cells where they need to work their magic. This is

361
00:18:32,000 --> 00:18:35,720
Speaker 2: important because so many supplements are just expensive powders without

362
00:18:35,760 --> 00:18:39,720
Speaker 2: effective delivery. The best part you can try strong cell

363
00:18:39,840 --> 00:18:42,800
Speaker 2: completely risk free. If it doesn't work for you, there's

364
00:18:42,840 --> 00:18:46,400
Speaker 2: a guarantee, so you have nothing to lose. If you're

365
00:18:46,440 --> 00:18:49,280
Speaker 2: tired of feeling drained, struggling with brain fog, or simply

366
00:18:49,320 --> 00:18:52,439
Speaker 2: not feeling like your best self, I strongly encourage you

367
00:18:52,480 --> 00:18:55,760
Speaker 2: to check out strong Cell. Visit strongsell dot com and

368
00:18:55,840 --> 00:18:59,359
Speaker 2: use discount code Lara to snag twenty percent off your order.

369
00:18:59,400 --> 00:19:03,639
Speaker 2: Remember you can try it completely risk free that strongsell

370
00:19:03,840 --> 00:19:07,160
Speaker 2: dot com discount code Laura. Don't just take my word

371
00:19:07,200 --> 00:19:09,439
Speaker 2: for it, do your research. I did, and that's why

372
00:19:09,520 --> 00:19:13,320
Speaker 2: I chose strong Sell. We're joined by the Director of

373
00:19:13,440 --> 00:19:18,160
Speaker 2: Economics at the American Institute of Economic Research, Peter Earl. Peter,

374
00:19:18,280 --> 00:19:21,320
Speaker 2: Welcome to the show. You know people talk a lot

375
00:19:21,359 --> 00:19:24,040
Speaker 2: about gold, they talk a lot about silver. I want

376
00:19:24,080 --> 00:19:26,280
Speaker 2: to get your expert opinion on this. Why are we

377
00:19:26,359 --> 00:19:30,440
Speaker 2: seeing such unprecedented growth in that space gold and silver?

378
00:19:30,760 --> 00:19:34,800
Speaker 2: Right now, gold is passed five thousand dollars an ounce,

379
00:19:34,840 --> 00:19:37,639
Speaker 2: and silver was recently over one hundred dollars an ounce.

380
00:19:38,000 --> 00:19:39,639
Speaker 2: What's going on with the gold and silver? What do

381
00:19:39,680 --> 00:19:40,440
Speaker 2: people need to know?

382
00:19:41,600 --> 00:19:44,080
Speaker 5: Well, great to be here and thank you. There's a

383
00:19:44,080 --> 00:19:46,880
Speaker 5: few forces that are converging at once. You know, it's

384
00:19:46,880 --> 00:19:49,639
Speaker 5: only four years ago that our nations saw the highest

385
00:19:49,640 --> 00:19:54,200
Speaker 5: inflation since the seventies, and that increased uncertainty about monetary

386
00:19:54,280 --> 00:19:57,560
Speaker 5: value and federal reserve policies has pushed a lot of

387
00:19:57,560 --> 00:20:01,840
Speaker 5: Americans towards more neutral stores of value. Right. In addition

388
00:20:01,920 --> 00:20:04,560
Speaker 5: to that, central banks have been really heavy buyers of

389
00:20:04,640 --> 00:20:08,479
Speaker 5: gold in recent years, which adds what we call structural demand.

390
00:20:08,560 --> 00:20:11,280
Speaker 5: So there's a lot of forces pushing up on gold.

391
00:20:11,880 --> 00:20:14,240
Speaker 5: There's also the fact that for the first time in decades,

392
00:20:14,560 --> 00:20:16,600
Speaker 5: you know, the US government is actually paying attention to

393
00:20:16,640 --> 00:20:20,119
Speaker 5: our gold deserves, something that was ignored for decades, and

394
00:20:20,160 --> 00:20:22,480
Speaker 5: it's now part of a broader conversation about the dollars,

395
00:20:22,560 --> 00:20:26,080
Speaker 5: credibility and our national wealth. So, you know, that has

396
00:20:26,119 --> 00:20:30,000
Speaker 5: to do with growing or changing situations. But the surgeon

397
00:20:30,119 --> 00:20:33,280
Speaker 5: silver is both many of those monetary issues and also

398
00:20:33,800 --> 00:20:37,679
Speaker 5: it's growing role in electrification in AI infrastructure and all that.

399
00:20:37,720 --> 00:20:40,080
Speaker 5: So there's a lot of factors right now pushing up

400
00:20:40,119 --> 00:20:40,879
Speaker 5: on gold and silver.

401
00:20:41,520 --> 00:20:43,359
Speaker 2: Well, a lot of people look to gold and silver

402
00:20:43,520 --> 00:20:45,600
Speaker 2: as kind of an indicator as to what's going on

403
00:20:45,640 --> 00:20:48,040
Speaker 2: in the economy, what they need to be aware of,

404
00:20:48,119 --> 00:20:50,800
Speaker 2: maybe a predictor of sorts. I think a lot of

405
00:20:50,800 --> 00:20:54,760
Speaker 2: people remember the two thousand and eight financial crisis, obviously

406
00:20:54,760 --> 00:20:57,640
Speaker 2: a very scary time for a lot of people. What

407
00:20:57,680 --> 00:21:00,000
Speaker 2: can you tell us about how gold and silver performed

408
00:21:00,760 --> 00:21:02,480
Speaker 2: when that crisis was unfolding.

409
00:21:02,960 --> 00:21:04,959
Speaker 5: I remember that time period. Well, I was working in

410
00:21:04,960 --> 00:21:08,240
Speaker 5: financial markets. It was scary for all of us. During

411
00:21:08,240 --> 00:21:11,040
Speaker 5: the initial panic in two thousand and eight, gold and

412
00:21:11,080 --> 00:21:15,320
Speaker 5: silver actually fell alongside other assets when we had investors

413
00:21:15,320 --> 00:21:19,120
Speaker 5: and bludge investment banks go scrambling for liquidity and for cash.

414
00:21:19,480 --> 00:21:22,639
Speaker 5: But once the central banks, including the FED, began a

415
00:21:22,760 --> 00:21:25,400
Speaker 5: very aggressive monetary easing, there was a lot of worry

416
00:21:25,440 --> 00:21:28,200
Speaker 5: about inflation. And so both medals, both gold and silver,

417
00:21:28,680 --> 00:21:31,720
Speaker 5: and did a pretty powerful multi year rally, with gold

418
00:21:31,960 --> 00:21:35,560
Speaker 5: eventually reaching new highs and silver dramatically utperforming even other

419
00:21:35,560 --> 00:21:38,359
Speaker 5: assets for a while. And so that's an important pattern

420
00:21:38,400 --> 00:21:41,600
Speaker 5: to notice, and that's that precious metals don't always rise

421
00:21:42,000 --> 00:21:45,000
Speaker 5: at in the moment of crisis, but they often respond

422
00:21:45,320 --> 00:21:49,399
Speaker 5: pretty strongly afterwards, usually to the policies right, especially in

423
00:21:49,440 --> 00:21:52,240
Speaker 5: a period of rapidly expanding money supply such as we

424
00:21:52,240 --> 00:21:55,879
Speaker 5: saw in twenty twenty one and twenty twenty two. In

425
00:21:55,920 --> 00:21:59,080
Speaker 5: two thousand and two thousand and nine, investors came to

426
00:21:59,160 --> 00:22:03,200
Speaker 5: view gold as a hedge against monetary debasement and systemic risk,

427
00:22:03,480 --> 00:22:07,000
Speaker 5: and that episode reinforce the idea that metals can serve

428
00:22:07,000 --> 00:22:09,840
Speaker 5: as a counterbalance to financial system issues, even if the

429
00:22:09,880 --> 00:22:12,080
Speaker 5: timing isn't perfect or directly linear.

430
00:22:12,920 --> 00:22:16,199
Speaker 2: So is that why precious metals tend to kind of

431
00:22:16,240 --> 00:22:21,800
Speaker 2: get more attention during these periods of uncertainty or economic challenges? That?

432
00:22:22,320 --> 00:22:24,520
Speaker 2: You know? I feel like for a lot of people,

433
00:22:24,640 --> 00:22:26,480
Speaker 2: they look at something like gold, and they look at

434
00:22:26,480 --> 00:22:29,399
Speaker 2: something like silver, and they say, look for since the

435
00:22:29,400 --> 00:22:33,640
Speaker 2: beginning of time, these have been solid items to hold

436
00:22:33,680 --> 00:22:36,880
Speaker 2: in our hand, a commodity we can physically have and

437
00:22:36,920 --> 00:22:39,359
Speaker 2: no one can take away from us. Is that why

438
00:22:39,440 --> 00:22:41,359
Speaker 2: people tend to pay more attention to it?

439
00:22:41,720 --> 00:22:45,359
Speaker 5: You're absolutely right. Yeah, Precious metals sit outside the credit system,

440
00:22:45,359 --> 00:22:47,800
Speaker 5: which means when you own them, you own them outright.

441
00:22:47,800 --> 00:22:51,160
Speaker 5: They're not someone else's liability, which makes them both psychologically

442
00:22:51,200 --> 00:22:54,680
Speaker 5: and financially appealing. When uncertainty is high or conditions are changing,

443
00:22:54,920 --> 00:22:58,240
Speaker 5: it's not for better or worse. Right, So during during

444
00:22:58,280 --> 00:23:02,040
Speaker 5: certain periods, people want assets that don't depend on corporate earnings,

445
00:23:02,200 --> 00:23:04,520
Speaker 5: they don't depend on central bank balance sheets, and so

446
00:23:04,680 --> 00:23:07,520
Speaker 5: gold functions as a sort of a macro hedge against that,

447
00:23:07,880 --> 00:23:11,639
Speaker 5: whether it's creery volatility or even just transitions in the

448
00:23:11,640 --> 00:23:14,600
Speaker 5: international order. So you know, the moves we've seen are

449
00:23:14,600 --> 00:23:19,040
Speaker 5: not about panic. It's about diversification, and portfolios tend to

450
00:23:19,040 --> 00:23:22,560
Speaker 5: shift towards resilience in times of change, and precious metals

451
00:23:22,640 --> 00:23:24,879
Speaker 5: naturally benefit from that sort of rebalancing.

452
00:23:25,480 --> 00:23:29,399
Speaker 2: Yeah, and I assume that you know inflation plays into

453
00:23:29,440 --> 00:23:31,040
Speaker 2: all of this. I mean, my gosh, it wasn't that

454
00:23:31,119 --> 00:23:36,000
Speaker 2: long ago inflation was around eight percent. That must have

455
00:23:36,040 --> 00:23:38,440
Speaker 2: been a time where people were saying, hey, if I

456
00:23:38,480 --> 00:23:42,000
Speaker 2: can't count on the economy here in the United States,

457
00:23:42,040 --> 00:23:44,919
Speaker 2: because nobody knows what's going on, I can count on

458
00:23:45,000 --> 00:23:47,199
Speaker 2: gold and silver. Is that is do people use it

459
00:23:47,240 --> 00:23:49,959
Speaker 2: as a bit of a protection for themselves and their investments.

460
00:23:50,320 --> 00:23:52,760
Speaker 5: Yep, that's absolutely right. Inflation is a big part of

461
00:23:52,800 --> 00:23:56,159
Speaker 5: the recent story. Historically, you know, we've seen gold perform

462
00:23:56,200 --> 00:23:58,760
Speaker 5: best during periods where we have what it's called negative

463
00:23:58,800 --> 00:24:02,040
Speaker 5: real interest rates. That means inflation is outrunning yields on

464
00:24:02,080 --> 00:24:05,359
Speaker 5: financial assets, so holding cash becomes a little less attractive.

465
00:24:05,720 --> 00:24:08,520
Speaker 5: You know, we had headline inflation at nine percent in

466
00:24:08,560 --> 00:24:11,760
Speaker 5: the summer of twenty twenty two, and many investors had

467
00:24:11,760 --> 00:24:15,120
Speaker 5: to reassess how vulnerable their purchasing power was when policy

468
00:24:15,480 --> 00:24:18,320
Speaker 5: falls behind price pressure. So, you know, golden sower. They

469
00:24:18,359 --> 00:24:20,840
Speaker 5: don't generate income, they don't pay dividends like a stock

470
00:24:20,920 --> 00:24:22,920
Speaker 5: or have a yield like a bond, but they do

471
00:24:22,960 --> 00:24:25,840
Speaker 5: act as long term stores of value. They're not tied

472
00:24:25,880 --> 00:24:29,159
Speaker 5: to any particular currency regime or central bank policy, So

473
00:24:29,640 --> 00:24:32,439
Speaker 5: I tend to think of them less as insurance against

474
00:24:32,440 --> 00:24:35,960
Speaker 5: every inflation bit, but more like protection against sustained monetary

475
00:24:35,960 --> 00:24:38,159
Speaker 5: stability and central bank mistakes.

476
00:24:39,320 --> 00:24:41,600
Speaker 2: Well, I'll tell you it's a good time to start

477
00:24:41,640 --> 00:24:44,199
Speaker 2: paying attention. I feel like we're in we're entering a

478
00:24:44,200 --> 00:24:46,960
Speaker 2: new era in terms of our economy. Obviously, we have

479
00:24:47,000 --> 00:24:49,480
Speaker 2: a different president in the White House right now who's

480
00:24:49,520 --> 00:24:52,000
Speaker 2: doing what he can to kind of write the ship.

481
00:24:52,119 --> 00:24:54,600
Speaker 2: Things have gone in the wrong direction for four years.

482
00:24:54,640 --> 00:24:57,120
Speaker 2: He's trying to bring it back around. But that said,

483
00:24:57,119 --> 00:24:58,680
Speaker 2: I think there are a lot of people who are

484
00:24:58,720 --> 00:25:03,680
Speaker 2: always looking for ways to protect themselves, to manage their

485
00:25:03,720 --> 00:25:06,600
Speaker 2: money in a smart way. If someone is watching this

486
00:25:06,800 --> 00:25:09,080
Speaker 2: right now and they're saying, you know, I don't know.

487
00:25:09,119 --> 00:25:12,040
Speaker 2: I've heard about gold and silver, I've heard about precious metals,

488
00:25:12,480 --> 00:25:14,480
Speaker 2: I'm not sure that this is a space for me.

489
00:25:15,000 --> 00:25:17,080
Speaker 2: What would you tell them? This is a space I

490
00:25:17,119 --> 00:25:19,919
Speaker 2: think kind of anyone should be able to investigate and

491
00:25:19,920 --> 00:25:23,000
Speaker 2: probably should do some sort of research into. It's just,

492
00:25:23,440 --> 00:25:25,040
Speaker 2: you know, a good business practice for them.

493
00:25:25,760 --> 00:25:28,960
Speaker 5: Sure, I would tell someone in that position that diversification

494
00:25:29,680 --> 00:25:34,360
Speaker 5: is really about combining assets that respond differently to economic shocks,

495
00:25:34,720 --> 00:25:38,320
Speaker 5: and herd assets can provide that sort of non correlated exposure.

496
00:25:38,640 --> 00:25:42,200
Speaker 5: You know, stocks depend on growth and earnings, bonds depend

497
00:25:42,320 --> 00:25:44,639
Speaker 5: on interest rates and credit conditions, but gold and silver

498
00:25:45,080 --> 00:25:48,880
Speaker 5: often respond to macro questions or currency concerns and sometimes

499
00:25:48,920 --> 00:25:52,920
Speaker 5: just change. So including some assets and heart assets in

500
00:25:52,920 --> 00:25:57,320
Speaker 5: a portfolio can usually help smooth overall volatility because they

501
00:25:57,320 --> 00:26:02,120
Speaker 5: don't always move in the same direction as traditional financial assets. Economically,

502
00:26:02,680 --> 00:26:05,680
Speaker 5: it's about reducing dependence on any single narrative, whether that's

503
00:26:06,000 --> 00:26:10,480
Speaker 5: perpetual growth, you know, geopolitics, the direction of inflation. You know.

504
00:26:10,560 --> 00:26:14,399
Speaker 5: Heart assets are not meant to replace productive investments, but

505
00:26:14,440 --> 00:26:17,320
Speaker 5: the act as a stabilizer when conditions get more ambiguous,

506
00:26:17,520 --> 00:26:19,760
Speaker 5: and in times of change, things are always ambiguous for

507
00:26:19,760 --> 00:26:21,119
Speaker 5: a little or at least a little while.

508
00:26:21,760 --> 00:26:25,080
Speaker 2: Well, we're in an interesting time right now because you know,

509
00:26:25,280 --> 00:26:29,320
Speaker 2: there's things like crypto that are kind of becoming more mainstream.

510
00:26:29,359 --> 00:26:32,760
Speaker 2: More people are feeling very comfortable with that. That's very volatile,

511
00:26:32,880 --> 00:26:36,000
Speaker 2: right that The highs and lows of crypto are crazy,

512
00:26:36,040 --> 00:26:38,960
Speaker 2: and I mean from our perspective in my family, I

513
00:26:39,000 --> 00:26:40,840
Speaker 2: think we want to do a little bit of everything,

514
00:26:40,920 --> 00:26:43,640
Speaker 2: because you don't want all your eggs in one basket.

515
00:26:43,640 --> 00:26:46,359
Speaker 2: You don't want to put everything you have into one thing,

516
00:26:46,359 --> 00:26:49,960
Speaker 2: because that's that's not smart, right. So to me, if

517
00:26:50,000 --> 00:26:52,359
Speaker 2: you want to dabble in the crypto space, maybe on

518
00:26:52,400 --> 00:26:54,320
Speaker 2: the other side of that you have you have something

519
00:26:54,359 --> 00:26:56,280
Speaker 2: hard like gold and silver you can fall back on

520
00:26:56,320 --> 00:26:58,880
Speaker 2: and say, like, I know, that's always there, because man,

521
00:26:59,200 --> 00:27:01,520
Speaker 2: maybe it's a good time be buying crypto, but it's

522
00:27:01,520 --> 00:27:04,240
Speaker 2: always I think a good time to be buying gold

523
00:27:04,240 --> 00:27:07,680
Speaker 2: and silver for twenty twenty six. What are you predicting?

524
00:27:07,760 --> 00:27:09,840
Speaker 2: What can you see maybe that some of us can't

525
00:27:09,880 --> 00:27:13,440
Speaker 2: see in terms of gold and silver, you know anything

526
00:27:13,440 --> 00:27:16,200
Speaker 2: people should looking out, be looking out for maybe new

527
00:27:16,240 --> 00:27:19,399
Speaker 2: economic challenges that could be on the horizon. What are

528
00:27:19,400 --> 00:27:19,840
Speaker 2: you thinking?

529
00:27:20,800 --> 00:27:24,120
Speaker 5: Sure, So I have to start by saying forecasting price

530
00:27:24,200 --> 00:27:28,160
Speaker 5: levels is always risky, but the structural backdrop, to be honest,

531
00:27:28,160 --> 00:27:30,560
Speaker 5: still appears to be very supportive. You know, we have

532
00:27:31,440 --> 00:27:34,600
Speaker 5: debt all around the world is rising, we have geopolitical shifts,

533
00:27:35,000 --> 00:27:37,440
Speaker 5: and we still have global central banks around the world

534
00:27:37,480 --> 00:27:40,840
Speaker 5: buying gold and that all those conditions tend to favor

535
00:27:41,080 --> 00:27:45,280
Speaker 5: precious metals. But there's another potential driver, and that's industrial demand.

536
00:27:45,280 --> 00:27:47,800
Speaker 5: And that's in particular in the case of silver, silver

537
00:27:47,920 --> 00:27:51,560
Speaker 5: is now tied to booming AI infrastructure spending, and that

538
00:27:51,640 --> 00:27:55,000
Speaker 5: adds another industrial dimension beyond its monetary role. So you know,

539
00:27:55,119 --> 00:27:58,480
Speaker 5: even if or when gold and silver prices consolidate after

540
00:27:58,520 --> 00:28:02,880
Speaker 5: a big run, the macro narrative around diversification, around resilience

541
00:28:02,920 --> 00:28:06,000
Speaker 5: and alternative stores of value isn't going anywhere anytime soon.

542
00:28:06,800 --> 00:28:09,560
Speaker 5: As you said, gold and silver have played a central

543
00:28:09,640 --> 00:28:12,760
Speaker 5: role in human civilization for over five thousand years and

544
00:28:12,800 --> 00:28:16,200
Speaker 5: they are continuing to and that's the story, all right.

545
00:28:16,280 --> 00:28:19,800
Speaker 2: Well, it's always good to make sure that we take

546
00:28:19,840 --> 00:28:23,120
Speaker 2: a moment and look at kind of the future, look

547
00:28:23,119 --> 00:28:25,320
Speaker 2: at the economy, look at our own economic standing. I

548
00:28:25,320 --> 00:28:27,480
Speaker 2: feel like for so many of us, days tend to

549
00:28:27,520 --> 00:28:29,400
Speaker 2: go by very quickly and we say, oh, I'll get

550
00:28:29,400 --> 00:28:32,160
Speaker 2: to that another day. There's no better day than right

551
00:28:32,200 --> 00:28:35,200
Speaker 2: now to kind of secure your money and ensure that

552
00:28:36,119 --> 00:28:38,480
Speaker 2: you know prosperity in the future is something that is

553
00:28:38,880 --> 00:28:42,080
Speaker 2: real for you. So, Peter Earle, thank you so much

554
00:28:42,120 --> 00:28:44,719
Speaker 2: for giving us all the great tips the info. You

555
00:28:44,800 --> 00:28:46,800
Speaker 2: are the guy and we appreciate you breaking it down

556
00:28:46,800 --> 00:28:48,200
Speaker 2: for us today. Thank you so much.

557
00:28:48,400 --> 00:28:50,600
Speaker 4: Thanks so much for having me take care And if.

558
00:28:50,440 --> 00:28:52,760
Speaker 2: You want to learn more about investing in gold for

559
00:28:52,880 --> 00:28:55,520
Speaker 2: all the reasons we discussed today about the benefits of

560
00:28:55,600 --> 00:28:59,200
Speaker 2: buying precious metals, you should go to Laura likes goold

561
00:28:59,440 --> 00:29:02,520
Speaker 2: dot com. I'm an advocate for owning gold and silver

562
00:29:02,600 --> 00:29:05,200
Speaker 2: as part of your portfolio, and that's why I partnered

563
00:29:05,200 --> 00:29:08,719
Speaker 2: with gold Co, the number one rated precious metals company.

564
00:29:08,800 --> 00:29:11,680
Speaker 2: Right now, they have a great offer to honor America's

565
00:29:11,680 --> 00:29:14,479
Speaker 2: two hundred and fiftieth birthday. Get up to ten percent

566
00:29:14,600 --> 00:29:18,120
Speaker 2: in free gold or silver, a free home safe, or

567
00:29:18,160 --> 00:29:20,920
Speaker 2: if you buy medals with cash, you can get your

568
00:29:20,960 --> 00:29:24,080
Speaker 2: metal stored for free. Go to Laura likes goold dot

569
00:29:24,120 --> 00:29:28,680
Speaker 2: com to learn more and Oh Mom, back down.

570
00:29:32,320 --> 00:29:32,640
Speaker 1: Baby.

571
00:29:32,840 --> 00:29:35,480
Speaker 5: May Therey No