1
00:00:03,679 --> 00:00:05,060
John Robb, thanks for joining.

2
00:00:05,440 --> 00:00:18,365
Oh, my pleasure. Thanks, John. I I appreciate you taking the time. As I had mentioned before we got started, not to be too gratuitous, but I followed your work since I read Brave New War in I was trying to find my copy, 02/2009, '2 thousand '10,

3
00:00:19,145 --> 00:00:22,285
fascinating read. And I think, in in my view,

4
00:00:22,985 --> 00:00:24,445
was one of the first

5
00:00:26,310 --> 00:00:27,370
bold sort of

6
00:00:27,910 --> 00:00:33,290
reframings of open source. And what does that do to the asymmetry of power? And what does that do to enable

7
00:00:33,670 --> 00:00:34,730
actors who,

8
00:00:35,670 --> 00:00:37,930
you know, may turn some of these open technologies

9
00:00:38,550 --> 00:00:39,050
against

10
00:00:40,245 --> 00:00:46,025
against modern sort of society and culture. But but I think, you know, with your recent writing,

11
00:00:46,565 --> 00:00:48,825
I have I have really, really enjoyed

12
00:00:49,365 --> 00:00:54,185
network swarms and the ideas that you're putting forward, and I certainly wanna give you an opportunity

13
00:00:55,190 --> 00:00:57,210
to to frame that. I mean, I think what,

14
00:00:58,710 --> 00:01:04,010
I think is interesting for for the audience, for the viewers, and and they'll see this in the show notes is,

15
00:01:04,550 --> 00:01:08,810
correct me if I'm wrong, John, but you got your start at the US Air Force Academy.

16
00:01:09,245 --> 00:01:12,225
You went in then to US Special Ops Command,

17
00:01:13,405 --> 00:01:15,265
then decided Yale was the right

18
00:01:16,205 --> 00:01:19,105
follow-up after after special operations, which I think is fascinating.

19
00:01:19,565 --> 00:01:24,940
And then I presume took a lot of that and synthesized it into your role as an analyst at Forrester,

20
00:01:25,240 --> 00:01:28,300
where you were tracking some of the very earliest Internet technologies

21
00:01:29,000 --> 00:01:33,820
and then founded Gomez and had a very significant exit. Was it just,

22
00:01:34,200 --> 00:01:35,880
just shy of $300,000,000

23
00:01:35,880 --> 00:01:36,380
to,

24
00:01:36,895 --> 00:01:45,555
CompuWare, of course, at that time was a was a massive player. And the Easter egg for me, I have to say, was discovering that you were CEO of Userland Software,

25
00:01:46,255 --> 00:01:48,435
which I just think was one of the most delightful

26
00:01:49,775 --> 00:01:51,955
companies. And, you know, for those who

27
00:01:52,520 --> 00:01:58,299
may not know Userland, they certainly know RSS. You know, if if they're if they're techie,

28
00:01:58,600 --> 00:02:01,579
as I think a lot of a lot of listeners will be.

29
00:02:02,039 --> 00:02:18,945
And so a brief aside, tell me about Userland software. How was that? Yeah. So I was at Forrester in in '95, and I got pulled into the Internet. They didn't have anyone covering it at the time, and I was a new guy. You know, I'd just been doing tier one special apps and went to Yale to kinda fill in the gaps in my business knowledge. And,

30
00:02:21,030 --> 00:02:25,290
I was showing that all these new technologies, Internet technologies to everybody

31
00:02:25,670 --> 00:02:30,409
in the company, and they said, okay. Why don't you start that service? And it went like it was, like, 25% of the revenue

32
00:02:30,870 --> 00:02:32,409
after I launched it and

33
00:02:33,065 --> 00:02:36,505
started writing these big picture reports. I had a kind of a knack for it. And,

34
00:02:37,705 --> 00:02:40,425
one of the reports I wrote in '96

35
00:02:40,425 --> 00:02:41,165
was called,

36
00:02:42,665 --> 00:02:44,205
personal broadcast networks.

37
00:02:44,745 --> 00:02:50,690
This idea that we would be posting things that people would be subscribing to them, and then we could create all these personal

38
00:02:51,630 --> 00:02:52,930
publish subscribe networks,

39
00:02:53,550 --> 00:02:56,290
that would constantly keep us up to date on all these

40
00:02:56,750 --> 00:02:57,490
other individuals.

41
00:02:58,110 --> 00:02:58,430
And,

42
00:02:59,625 --> 00:03:05,165
everyone at Microsoft and Netscape and others came to me and said, how do we how do we build this? And I go, I don't know yet.

43
00:03:05,704 --> 00:03:22,390
But it feels like that was the fact that Microsoft on the browser team at that time, trying to get into the trying to get into the, you know, the right quadrant. So please go ahead. Yeah. Mike Homer over when he was, before he died was over at Netscape, and, he was head of marketing there. And he came to see he was kinda like, how do we do this? But,

44
00:03:23,910 --> 00:03:24,410
I,

45
00:03:25,430 --> 00:03:27,690
went and did Gomez, and we did that

46
00:03:28,085 --> 00:03:31,065
exit. I think it was, like, sold for 295,000,000

47
00:03:31,205 --> 00:03:38,905
was was the exit on that. And then, in 02/2001, I, you know, I had something else that I wanted to do, and I I wanted to see if I could

48
00:03:39,205 --> 00:03:40,985
make this idea real.

49
00:03:41,520 --> 00:03:47,380
It was basically social networking. And, in 02/2001, I saw a company that was doing a lot of that called Userland.

50
00:03:47,920 --> 00:03:48,240
And,

51
00:03:48,800 --> 00:03:51,280
Dave Weiner, who was the chief programmer there, and,

52
00:03:52,320 --> 00:03:57,165
he needed somebody to run his company. And I came in and ran it, and it was like, you know, three, four person affair.

53
00:03:59,084 --> 00:04:03,984
Robert Scoble was our marketing for a while. Punching way above its weight, though. Yeah.

54
00:04:04,284 --> 00:04:04,605
And,

55
00:04:05,644 --> 00:04:06,385
we built,

56
00:04:07,644 --> 00:04:08,144
basically,

57
00:04:08,525 --> 00:04:11,530
social networking as we know it today. We we published

58
00:04:11,910 --> 00:04:13,690
RSS as an open source standard,

59
00:04:14,470 --> 00:04:19,450
and, we created a tool that you could subscribe to RSS feeds. And

60
00:04:20,389 --> 00:04:30,715
the feed on our tool, we called it radio. It's a desktop tool. I mean, it looks exactly with the same kind of constraint on characters that you get in Twitter. So it looked exactly like a Twitter feed. And the publishing,

61
00:04:31,335 --> 00:04:43,920
you could take it from Twitter, that Twitter kind of interface, and then publish it into a weblog. And we established a lot of the early standards for how weblogs are published, reverse chronicle chronological order, you know, with time stamps.

62
00:04:44,380 --> 00:04:52,620
You could take what other people you you subscribe to and then post more on it. So and it was actually blue. It looked exactly like Facebook. So,

63
00:04:53,565 --> 00:04:58,544
that was the default color. I mean, it's exact the Facebook color. So we did that in 02/2001,

64
00:04:58,764 --> 00:05:01,345
and, it was too early. I got a I got experience

65
00:05:02,125 --> 00:05:06,544
trying to get people to see an emerging technology from

66
00:05:07,190 --> 00:05:08,630
the Ground Floor. And,

67
00:05:09,110 --> 00:05:10,170
it was excruciating.

68
00:05:10,710 --> 00:05:14,570
You know, I I saw the things that I told people how to use it and how it could be applied.

69
00:05:15,830 --> 00:05:21,135
Spent a couple hours with Ray Ozzie before he took over Microsoft for a while. Wow. And he was trying to figure out how to

70
00:05:21,695 --> 00:05:28,975
if this is something they wanted to employ, that could have put them in amazing position if he if he had taken that in. But I guess I wasn't convincing enough. And,

71
00:05:30,255 --> 00:05:40,669
we got New York Times to sign on to do an RSS feed and, as one of our exclusive feeds for for the radio tool. And once they were on, all these other places going on, NPR and everyone else,

72
00:05:41,690 --> 00:05:42,750
just wasn't enough.

73
00:05:43,289 --> 00:05:45,229
We just ran out of steam, and,

74
00:05:46,650 --> 00:05:49,530
I left before Facebook and Twitter took off. So,

75
00:05:50,164 --> 00:05:54,425
went on to do other things. It just, it was it was very excruciating

76
00:05:54,725 --> 00:06:01,544
to go through. It it it's hard. People have cognitive filters. They just can't see it. They just couldn't see the value,

77
00:06:03,050 --> 00:06:06,430
and the dynamism. And I just saw it. Like, it was clear as day, and I thought

78
00:06:06,889 --> 00:06:09,630
it just couldn't communicate that well enough, I guess.

79
00:06:10,490 --> 00:06:14,030
But, anyways, they say, my experience early being early is,

80
00:06:15,385 --> 00:06:17,165
an even greater or as great

81
00:06:17,545 --> 00:06:20,765
a a source of failure as being wrong in startups. And so,

82
00:06:21,385 --> 00:06:27,325
it is tremendous. I mean, I I do though you know, again, as I said, it delights me to to to find that you

83
00:06:27,785 --> 00:06:42,889
were were running Goosierland. I my Mac two SI, you know, I think I remember is what I had or a Quadra nine fifty or whatever the details are are not are not, important, but I distinctly remember that application, that software. And, it has to be It was it was a cool experience.

84
00:06:43,205 --> 00:06:45,465
Yeah. And, I mean, you know, in doing that, and I think,

85
00:06:46,325 --> 00:06:51,305
to to connect the dots, I raise that because that was an extremely early experiment

86
00:06:51,685 --> 00:06:52,185
in

87
00:06:52,565 --> 00:06:56,585
I don't wanna strain the word decentralized, but this was was pushing,

88
00:06:57,310 --> 00:07:01,410
you know, a lot of this to the edge or to the end, to the end user.

89
00:07:01,790 --> 00:07:11,090
And so, you know, we fast forward now twenty five plus years later. I'd I'd love to to get into, John, your framing

90
00:07:11,835 --> 00:07:14,575
of trust. And, again, I'll I'll sort of say because

91
00:07:15,195 --> 00:07:18,095
you have worked in special forces, because you have,

92
00:07:18,635 --> 00:07:21,295
built and sold a business, you you've got two,

93
00:07:22,475 --> 00:07:23,775
very, very different perspectives.

94
00:07:25,120 --> 00:07:28,979
How do you view trust? I know you thought a lot about this. Mhmm. I mean, trust

95
00:07:29,360 --> 00:07:31,699
is a minimum requirement for cohesion.

96
00:07:32,720 --> 00:07:34,020
Okay? And cohesion

97
00:07:34,720 --> 00:07:38,740
is a minimum requirement for high quality decision making.

98
00:07:39,665 --> 00:07:39,985
And,

99
00:07:40,545 --> 00:07:41,045
cohesion

100
00:07:41,425 --> 00:07:42,325
allows you

101
00:07:42,705 --> 00:07:46,485
to view the other participants in your decision making process as,

102
00:07:47,665 --> 00:07:50,725
friendly to that process, that they're not trying to sabotage it.

103
00:07:51,505 --> 00:07:53,525
It also works at a at a national level,

104
00:07:54,870 --> 00:07:56,010
with political discussion.

105
00:07:56,870 --> 00:07:58,090
So if you see,

106
00:07:58,550 --> 00:08:00,650
somebody with a different opinion that's an opponent,

107
00:08:01,190 --> 00:08:04,730
you can argue that and you could but you fundamentally trust them

108
00:08:05,990 --> 00:08:09,425
in the sense that they're working for the good of the nation to just disagree.

109
00:08:09,805 --> 00:08:14,625
But, I mean, the current environment, we see many of the people on the other side of the political spectrum

110
00:08:15,005 --> 00:08:15,824
as enemies.

111
00:08:17,324 --> 00:08:18,785
They're outside our tribe.

112
00:08:19,340 --> 00:08:28,080
And that tribalism, it would you know, I dug into kind of find the kind of origins of trust is that we were wired at a biological and neuro level for

113
00:08:29,340 --> 00:08:30,880
tribal life. And,

114
00:08:31,420 --> 00:08:34,160
life inside a tribe was a high trust environment.

115
00:08:34,595 --> 00:08:40,375
You knew everybody there. You were reliant on everybody there to get through the next day, the next year.

116
00:08:41,315 --> 00:08:42,135
Their success

117
00:08:43,315 --> 00:08:44,615
made you more successful.

118
00:08:45,555 --> 00:08:49,335
It was largely a gifting culture and the culture where you gave things

119
00:08:49,970 --> 00:08:57,670
and, the best better the gift that you the more status you had. And then we broke with the tribal cult culture and started to scale

120
00:08:58,290 --> 00:08:58,790
our

121
00:08:59,810 --> 00:09:00,310
society,

122
00:09:01,090 --> 00:09:07,015
adding more people. And that tribal connection, knowing there was other people, wasn't sufficient then. And,

123
00:09:08,215 --> 00:09:10,235
we came up with kind of

124
00:09:10,615 --> 00:09:17,755
acts or work around trying to make that trust possible, and we came up with a legal system. We came up with bureaucracy, bureaucracy being

125
00:09:19,710 --> 00:09:25,250
a formalized way of getting things done that operated on a civil code, and there was a certain level of professionalism,

126
00:09:26,030 --> 00:09:31,470
associated with it. And so you could trust that its output would be high quality. And then,

127
00:09:32,135 --> 00:09:34,955
we replicated tribalism in the sense by,

128
00:09:35,735 --> 00:09:36,875
coming up with nationalism.

129
00:09:37,335 --> 00:09:42,154
And nationalism gave us that cohesion at the national or nation state level,

130
00:09:43,015 --> 00:09:45,970
that allowed us to operate as a cohesive unit.

131
00:09:46,510 --> 00:09:53,230
And the marketplaces, of course, you know, they have to be fair. You have to make sure that they're not being corrupted or gained or or,

132
00:09:54,670 --> 00:09:59,685
in, you know, that kind of need for, you know, making that process transparent,

133
00:10:00,545 --> 00:10:06,084
is, you know, behind many of the rules that we see in terms of financial disclosures and things like that,

134
00:10:06,545 --> 00:10:12,950
and how contracts work. So we all of these things that we have are you know, that we rely on now are workarounds.

135
00:10:13,810 --> 00:10:14,310
Right?

136
00:10:16,450 --> 00:10:21,430
So, you know, that's kind of my my thinking on this is that can we use current and

137
00:10:21,810 --> 00:10:23,650
and currently being developed or,

138
00:10:24,210 --> 00:10:26,715
technologies to find better ways to do that?

139
00:10:27,435 --> 00:10:27,915
Okay?

140
00:10:28,315 --> 00:10:33,455
Improve the quality of trust. That's that's very, very helpful. And I think, you know, it is interesting to

141
00:10:33,835 --> 00:10:34,895
to look at

142
00:10:35,675 --> 00:10:36,655
all of our technologies

143
00:10:37,115 --> 00:10:40,575
as enamored as some, myself included, may get with them as

144
00:10:43,940 --> 00:10:53,380
attempts to scale trust, attempts to get beyond Dunbar's number, attempts to replicate the drive, as you say. Well, on that note, your work has, for a long time, highlighted,

145
00:10:53,700 --> 00:10:54,680
highlighted how

146
00:10:54,985 --> 00:11:01,485
centralized systems are prone to collapse under pressure. And you've been writing quite a bit and I know engaged in in many,

147
00:11:03,545 --> 00:11:05,965
energetic discussions on x, on Twitter,

148
00:11:06,505 --> 00:11:08,125
about AI. How is

149
00:11:08,505 --> 00:11:09,965
AI, in your view, making

150
00:11:10,420 --> 00:11:12,680
these weak spots harder to ignore?

151
00:11:13,220 --> 00:11:17,960
And and what's the clearest sign that we're trusting these centralized systems too much?

152
00:11:18,900 --> 00:11:19,380
Yeah. I mean,

153
00:11:20,180 --> 00:11:21,400
a centralized system,

154
00:11:21,780 --> 00:11:26,055
like, the big tech companies are currently running with social networking and other things. And, you know,

155
00:11:26,775 --> 00:11:29,515
social networking now is upstream of the,

156
00:11:30,055 --> 00:11:32,955
legacy news system and how we actually manage

157
00:11:34,695 --> 00:11:35,675
information transfer

158
00:11:36,295 --> 00:11:37,595
now and process information.

159
00:11:40,290 --> 00:11:41,649
Problem with that is that,

160
00:11:42,690 --> 00:11:47,829
it can be disrupted, and it's easily disrupted from the dot from underneath, but it can also be

161
00:11:48,170 --> 00:11:50,949
it could another failure mode is that it can be locked out.

162
00:11:51,250 --> 00:11:53,589
Right? And, one of my big worries

163
00:11:54,515 --> 00:11:55,815
back in 02/2017,

164
00:11:56,755 --> 00:11:57,495
was that,

165
00:11:59,155 --> 00:12:00,375
we were headed towards

166
00:12:00,915 --> 00:12:01,975
a potential lockdown

167
00:12:02,435 --> 00:12:03,735
of the information ecosystem,

168
00:12:04,355 --> 00:12:07,415
and that, the tendency of I I

169
00:12:07,810 --> 00:12:09,990
I I call our, political factions

170
00:12:10,450 --> 00:12:15,650
blue network, red network. The tendency of the blue network after it, you know, kicked Trump out of office,

171
00:12:16,610 --> 00:12:17,590
in 2020

172
00:12:17,810 --> 00:12:18,550
was to

173
00:12:19,170 --> 00:12:19,990
lock down

174
00:12:20,475 --> 00:12:22,095
these systems to try to

175
00:12:22,555 --> 00:12:29,935
minimize the ability of the opposition to say anything, anything that wasn't approved. And, they got support across the industry.

176
00:12:31,355 --> 00:12:32,495
Categorized all

177
00:12:33,730 --> 00:12:41,750
violations of these rules as as kind of evil and things that cause bans and stuff like that. I'm not trying to, you know, paint them as bad guys, but they saw it as a need for stability.

178
00:12:42,530 --> 00:12:46,310
And this was it needed to eliminate misinformation and disinformation.

179
00:12:46,930 --> 00:12:47,250
And,

180
00:12:49,665 --> 00:12:58,725
the rules were getting applied in more and more instances, both at the technology level with the the big companies as well as at the governmental level and and and different organizations.

181
00:12:59,905 --> 00:13:00,145
And,

182
00:13:01,970 --> 00:13:06,870
we just I saw I've been writing about AI during the same period since 02/2017,

183
00:13:06,930 --> 00:13:13,029
how it would actually work at at you know, when employed. So I was ahead of the game on this, and I saw AI just about to hit.

184
00:13:14,050 --> 00:13:14,949
And that was

185
00:13:15,464 --> 00:13:17,964
my big fear was that AI would be

186
00:13:18,665 --> 00:13:20,524
employed as a means of,

187
00:13:20,904 --> 00:13:23,885
locking down the entire system, getting to every conversation,

188
00:13:24,985 --> 00:13:27,000
managing those conversations, and then

189
00:13:27,400 --> 00:13:33,240
controlling them and redirecting them and, you know, not just simple censorship, but even more. And,

190
00:13:33,960 --> 00:13:35,020
once that happened,

191
00:13:35,640 --> 00:13:38,620
you know, billions of people in real time could be managed.

192
00:13:39,384 --> 00:13:40,204
All the topics

193
00:13:40,745 --> 00:13:41,384
that were,

194
00:13:41,944 --> 00:13:47,485
available to think about and talk about would be would shrink down to a narrow orthodoxy, a narrow,

195
00:13:50,105 --> 00:13:53,565
group of of approved topics. The And then all the window.

196
00:13:54,050 --> 00:13:58,230
Yeah. And then well, yeah. Not just over to everything that could potentially challenge,

197
00:14:00,050 --> 00:14:02,470
stability would be wiped out, and that means all innovation

198
00:14:03,010 --> 00:14:04,470
dies. Your ability to actually

199
00:14:05,250 --> 00:14:13,395
push back against the establishment would or, you know, how things were operating dies your ability to adapt to changing conditions and everything else would die.

200
00:14:14,815 --> 00:14:15,315
And,

201
00:14:15,855 --> 00:14:20,355
I mean, from perspective of of somebody who studied, like, totalitarian states, I mean, it was like,

202
00:14:20,735 --> 00:14:23,875
this was these corporations were building essentially

203
00:14:26,040 --> 00:14:26,780
like, totalitarian

204
00:14:27,640 --> 00:14:28,780
state in a box

205
00:14:29,320 --> 00:14:41,725
because all you need to do is turn it on, and they could do it cheaply. They didn't need, you know, massive bureaucracies of of people like they had the Stasi had of going through everybody's emails by hand and and and and that kind of thing. It could all be automated.

206
00:14:42,185 --> 00:14:42,425
And,

207
00:14:43,945 --> 00:14:47,005
that ended with with Musk taking over

208
00:14:47,385 --> 00:14:51,725
Twitter and unwinding and providing an alternative kind of information

209
00:14:52,425 --> 00:14:52,925
conduit

210
00:14:53,250 --> 00:14:54,230
that broke open

211
00:14:54,610 --> 00:14:58,630
the system. And and you're on your side. Is it is it that simple?

212
00:14:59,570 --> 00:15:02,390
Was was his buying Twitter and taking over Twitter

213
00:15:02,930 --> 00:15:03,670
that momentous?

214
00:15:04,690 --> 00:15:05,510
%.

215
00:15:06,645 --> 00:15:13,785
Trump never would have won. I mean, he didn't win in 2020, not because of election fraud or anything. It's because social networking locked him down.

216
00:15:14,165 --> 00:15:17,385
His ability to route around the media went to zero. It, you know,

217
00:15:18,960 --> 00:15:23,700
it was shut down on Facebook. It was shut down on Twitter. It was shut down on, all the other

218
00:15:24,080 --> 00:15:25,940
places that you would normally get information.

219
00:15:27,840 --> 00:15:30,660
And his supporters were sent to the boonies.

220
00:15:31,815 --> 00:15:35,195
And we would have seen a repeat of that in 2024

221
00:15:35,415 --> 00:15:36,955
if not for Musk's

222
00:15:38,295 --> 00:15:39,995
acquisition of of of the company.

223
00:15:41,735 --> 00:15:46,519
I think from reading his interviews that he was motivated for much the same thing I had,

224
00:15:47,459 --> 00:15:49,160
had seen, and he saw it too.

225
00:15:49,779 --> 00:15:56,600
And he was worried. And and the trigger for him and the trigger for me that this was potentially very dangerous was the response to Ukraine.

226
00:15:57,345 --> 00:16:03,285
I mean, we've been playing back and forth with with Russia, I think, with the mistaken policy of NATO expansion trying to turn

227
00:16:03,745 --> 00:16:10,885
a newly democratic company our country into an enemy. And the guy who came up with containment, George Kennan, said it was a bad idea. But nonetheless,

228
00:16:11,330 --> 00:16:20,390
it was a back and forth, and and Russia was pushing back against it as we pushed up against their border. And and, there'd been other conflicts in Ukraine and in in other places, and we

229
00:16:21,330 --> 00:16:26,870
turned this into using you know, the network turned it into a new cold war and pushed us up towards

230
00:16:27,475 --> 00:16:28,615
a nuclear confrontation

231
00:16:29,315 --> 00:16:30,935
where it didn't, you know, exist.

232
00:16:31,395 --> 00:16:40,695
I mean, you could travel to Moscow and and take a vacation two years a year prior to that war, and and all of a sudden, they were being disconnected by millions of people,

233
00:16:41,170 --> 00:16:45,990
you know, across government. And and people inside government, inside corporations were taking action

234
00:16:47,010 --> 00:16:47,910
on their own

235
00:16:48,370 --> 00:16:48,870
to

236
00:16:50,050 --> 00:16:51,110
push us towards

237
00:16:51,890 --> 00:16:53,430
cold war, towards confrontation.

238
00:16:53,795 --> 00:16:54,968
Yeah. It fits And this is

239
00:16:55,555 --> 00:16:56,055
preemptive

240
00:16:56,435 --> 00:16:57,255
and overcompliance.

241
00:16:57,635 --> 00:16:58,935
I mean, I won't name

242
00:16:59,235 --> 00:17:02,695
a particular company, but I was with one that aggressively,

243
00:17:03,235 --> 00:17:08,935
aggressively overcomplied in my view. And so to your point Yeah. Yeah. They reframed the whole conflict from,

244
00:17:10,130 --> 00:17:12,389
you know, regional war and, you know,

245
00:17:13,090 --> 00:17:17,990
back and forth that we would normally negotiate our way out of and and and deal with into,

246
00:17:18,610 --> 00:17:24,549
they just escalated it. Like, this is like a new Hitler emerging or anyone who said anything else would be

247
00:17:24,934 --> 00:17:27,255
swarmed and, stomped on. And,

248
00:17:28,295 --> 00:17:29,595
that swarming behavior,

249
00:17:31,895 --> 00:17:33,675
actually deciding war you know,

250
00:17:34,135 --> 00:17:39,200
whether we're at war or peace was kind of scary to me. It was like it and it was unreasonable.

251
00:17:39,500 --> 00:17:42,960
It it you know, the way the swarm operated and,

252
00:17:43,260 --> 00:17:44,080
was that,

253
00:17:44,940 --> 00:17:48,400
it saw the enemy as, as unconstrained evil.

254
00:17:48,860 --> 00:17:52,160
And Putin was unconstrained evil because of his support for Trump,

255
00:17:53,185 --> 00:17:56,085
you know, which is the seed of it, interviewed in our elections,

256
00:17:58,065 --> 00:18:03,105
and that, he be instantly became Hitler, and therefore, we had to fight him. And,

257
00:18:04,320 --> 00:18:10,100
yeah, no. It was a it was a it was a scary moment. You couldn't there was no nuance, you know, to the whole

258
00:18:10,480 --> 00:18:12,820
position of the swarm. There was no negotiation.

259
00:18:13,360 --> 00:18:14,740
It was only total victory,

260
00:18:15,200 --> 00:18:27,825
collapse of Russia, that kind of thing. So I don't wanna go off on the Ukraine thing, but the, you know, the swarming behavior was was, you know, scary to me. And then it you know, we've seen swarms with, George Floyd and other places that they

261
00:18:28,205 --> 00:18:31,404
it can't be reasoned with. And it distorts the truth, and it can't

262
00:18:32,610 --> 00:18:40,070
it doesn't stop when it should. So, I think that's what's so powerful about that that that word that and and what it conjures

263
00:18:40,610 --> 00:18:44,470
as compared, say, to a smart mob, a term, you know, used,

264
00:18:45,170 --> 00:18:47,110
I don't know, fifteen, twenty years ago maybe,

265
00:18:47,410 --> 00:19:00,865
is the swarm is, as you said, it it doesn't stop until it has, you know, complete victory. And and I'm curious, John, there are, you know, no end of of conspiracy theories. But if if we if we take a I take a naive

266
00:19:01,500 --> 00:19:02,000
approach

267
00:19:02,460 --> 00:19:05,120
and I look at incentives, what incentivized

268
00:19:06,940 --> 00:19:07,760
the emergence

269
00:19:08,540 --> 00:19:09,040
of

270
00:19:09,980 --> 00:19:12,720
the red and blue swarm and the all consuming

271
00:19:13,100 --> 00:19:14,080
total victory?

272
00:19:15,095 --> 00:19:16,715
Are these emergent behaviors

273
00:19:17,095 --> 00:19:23,255
or or was you know, was and is there was was and is there an incentive that drives this? Well,

274
00:19:24,935 --> 00:19:25,835
I've been tracking,

275
00:19:26,775 --> 00:19:29,755
networked organizations and their emergence, and I I saw

276
00:19:30,320 --> 00:19:32,020
these networked organizations as,

277
00:19:33,520 --> 00:19:42,260
potentially another layer of societal decision making. So we had tribal, which is nationalism in our current context. We had bureaucratic, which was this kind of professional

278
00:19:43,485 --> 00:19:46,925
system for mobilizing resources and analyzing information and and,

279
00:19:48,125 --> 00:19:51,585
managing people at at scale. And then you had markets for

280
00:19:52,925 --> 00:19:54,925
discovering information, for,

281
00:19:55,325 --> 00:19:56,385
allocating resources

282
00:19:58,260 --> 00:19:59,620
based on need. And,

283
00:20:00,900 --> 00:20:04,920
we combine them in our system of governance by using markets for elections

284
00:20:05,380 --> 00:20:07,000
and to elect the leader of the bureaucracy

285
00:20:07,540 --> 00:20:08,520
and, that,

286
00:20:08,900 --> 00:20:11,960
we use nice nationalism as a way to motivate people to

287
00:20:13,184 --> 00:20:14,325
point in the right direction,

288
00:20:14,625 --> 00:20:17,445
orient themselves towards, you know, advancing the good of the nation,

289
00:20:18,065 --> 00:20:24,245
and then cooperate and provide cohesion in our decision making as a whole. So we combine those into a useful whole. And

290
00:20:25,039 --> 00:20:33,059
all of those developed with the advent of the printing press, and it took five hundred years to roll out. And it was a bloody, horrible process of creating these organizations, creating these,

291
00:20:33,600 --> 00:20:35,539
means of of of deciding

292
00:20:35,919 --> 00:20:36,960
what to do next,

293
00:20:37,440 --> 00:20:40,305
and that we arrived on this. And now here comes something new,

294
00:20:40,705 --> 00:20:41,845
you know, this networked

295
00:20:42,465 --> 00:20:42,965
layer,

296
00:20:44,145 --> 00:20:46,245
networking layer, you know, for decision making.

297
00:20:46,545 --> 00:20:48,805
We saw it in the surge. We saw it in protest,

298
00:20:49,505 --> 00:20:51,445
like Egypt and other places, Tunisia.

299
00:20:52,145 --> 00:20:53,525
And then we now

300
00:20:54,450 --> 00:20:58,289
see it emerge in politics. And in terms of the red and blue,

301
00:20:59,010 --> 00:21:01,029
it emerged in the, you know, the red network,

302
00:21:02,370 --> 00:21:06,630
that supported Trump that tried to get him you know, got him into office the first time in 2016,

303
00:21:07,169 --> 00:21:11,345
came out of the blue. Okay? And it became out of the blue because he was challenging

304
00:21:11,885 --> 00:21:16,304
the globalist orientation of the current administration and and establishment.

305
00:21:17,325 --> 00:21:19,024
And, you know, that globalist

306
00:21:19,404 --> 00:21:24,570
orientation is, like, we made all our decisions as a country pointing towards globalism,

307
00:21:25,590 --> 00:21:26,970
and that we minimize

308
00:21:27,270 --> 00:21:28,730
nationalism and minimize

309
00:21:29,030 --> 00:21:30,250
the the kind of

310
00:21:31,350 --> 00:21:36,555
system that we were running during the Cold War where we had to have a strong nation state that was economically independent,

311
00:21:37,255 --> 00:21:37,995
that had

312
00:21:38,295 --> 00:21:39,355
an eye on prosperity

313
00:21:39,735 --> 00:21:43,675
and broad broad prosperity for the for everybody was focused on,

314
00:21:44,135 --> 00:21:45,035
national defense,

315
00:21:45,575 --> 00:22:08,925
you know, rather than defending the world. And, the we shifted at the end of the cold war towards a globalist orientation, and all the policies increasing the world had flat people and everyone else, you know, started thinking that everything you know, we didn't need any trade barriers or any kind of economic independence. We didn't need to worry about prosperity. We could open up all of them every American to competition in the rest of the world because that'll make them stronger,

316
00:22:10,185 --> 00:22:14,685
and that, we didn't deliver on prosperity anymore. And we we started deemphasizing

317
00:22:14,985 --> 00:22:21,190
nationalism. And the elites on the whole, from what I saw, and I, you know, interact with a ton of them, is that they started to see themselves

318
00:22:21,730 --> 00:22:22,950
more and more as globalized,

319
00:22:23,450 --> 00:22:23,950
you

320
00:22:24,450 --> 00:22:25,510
know, global people.

321
00:22:26,610 --> 00:22:28,070
They weren't nationalist anymore.

322
00:22:28,930 --> 00:22:29,590
And that

323
00:22:31,250 --> 00:22:34,710
that weakened the nation state, and we ended up with a a a country that

324
00:22:35,655 --> 00:22:39,255
didn't really have control over its borders anymore, didn't have a control over its,

325
00:22:39,895 --> 00:22:45,515
the messaging anymore, you know, the kind of narrative that kept us together and helped us move forward.

326
00:22:46,535 --> 00:22:49,115
It was starting to get really messy as the Internet started

327
00:22:49,540 --> 00:22:51,060
to eat away at it. And,

328
00:22:51,540 --> 00:22:59,720
we didn't have control over economics and finances because we globalized, and and we were making mistake after mistake, like, for instance, February bringing China into the WTO

329
00:23:00,900 --> 00:23:03,720
because we thought it would democratize them.

330
00:23:04,174 --> 00:23:10,674
And then instead, what we ended up doing is creating, an opponent, a competitor. We grew them because we didn't

331
00:23:12,335 --> 00:23:15,075
go after fair trade. We just opened our borders.

332
00:23:15,855 --> 00:23:18,210
It opened our our trading system to them.

333
00:23:19,570 --> 00:23:20,070
So,

334
00:23:21,010 --> 00:23:24,230
people are kind of fed up with that if you said because, you know,

335
00:23:24,610 --> 00:23:25,270
what the

336
00:23:25,809 --> 00:23:28,789
establishment was saying is that whenever you mentioned,

337
00:23:29,809 --> 00:23:34,664
focusing on US defense rather than, you know, policing the world with military force.

338
00:23:35,284 --> 00:23:37,625
Lots of useless wars and messed up in the rest,

339
00:23:38,085 --> 00:23:50,039
as we saw in Iraq and and toppling governments that caused more misery and than they saved us from, like Syria and Libya and other places, the bad of those dictators where they weren't as nearly as bad as the stuff that came after.

340
00:23:50,580 --> 00:23:58,020
We created ISIS because of that too. So it's like, yeah, we made tons of mistakes. Is that if you said you wanna focus on US defense, say you're,

341
00:23:58,500 --> 00:23:59,240
an isolationist,

342
00:23:59,805 --> 00:24:02,145
and you'd be dismissed from the conversation completely.

343
00:24:02,445 --> 00:24:05,025
If you say you wanted fair trade, they'd call you a protectionist.

344
00:24:05,885 --> 00:24:08,865
You said you want self reliance, you're a protectionist. You were dismissed.

345
00:24:09,245 --> 00:24:10,785
And if you wanted a a

346
00:24:12,340 --> 00:24:16,440
good, you know, control over immigration and borders, you were racist,

347
00:24:17,140 --> 00:24:18,760
or you were a protectionist

348
00:24:19,060 --> 00:24:22,120
because you're not letting these, you know, this flow happen.

349
00:24:22,420 --> 00:24:24,600
So, that restriction of the dialogue

350
00:24:26,625 --> 00:24:27,125
and

351
00:24:27,505 --> 00:24:29,285
the increasing number of failures

352
00:24:29,665 --> 00:24:36,165
we saw, like, with the financial crisis and the failure to, you know, punish anyone for that and and everything else created this

353
00:24:36,465 --> 00:24:38,085
great well of discontent

354
00:24:38,530 --> 00:24:39,830
with the globalist orientation.

355
00:24:40,610 --> 00:24:41,110
And,

356
00:24:41,730 --> 00:24:43,350
Trump tapped into it, and

357
00:24:43,970 --> 00:24:49,110
it put him into the White House because they knew that he would disrupt things. They weren't electing him as a candidate.

358
00:24:49,570 --> 00:24:51,885
They ran a open source insurgency.

359
00:24:52,505 --> 00:24:53,325
It was dynamic.

360
00:24:53,785 --> 00:24:59,885
It wasn't run by him. You know, it was run by places like The Donald on on Reddit. You know, I was interviewed there, like, a week,

361
00:25:00,265 --> 00:25:11,860
week before Trump. So it's like, okay. How did this work? And I explained how it was working for them. And in places like, you know, even, like, anonymous and stuff took a lot of my writing, and that was the founders used that to to found it.

362
00:25:12,400 --> 00:25:14,659
And, this kind of open source

363
00:25:15,280 --> 00:25:16,740
opposition to the establishment

364
00:25:17,360 --> 00:25:18,580
emerged. And

365
00:25:18,880 --> 00:25:22,020
it, was our first taste of of kind of network politics.

366
00:25:23,355 --> 00:25:25,535
And so these swarms, it sounds like you emerged.

367
00:25:26,155 --> 00:25:32,415
Swarm was kind of a later thing. I don't it's more of an uncertainty. Open source is surgery works like, very much like open source software.

368
00:25:33,035 --> 00:25:33,535
So

369
00:25:34,810 --> 00:25:39,550
it has a single single goal that kind of unites everybody. And they have all different reasons for

370
00:25:39,930 --> 00:25:47,230
motivations for joining it. I mean, there's no barriers to entry, so they can join. They can contribute. And if the contribution works in terms of, you know,

371
00:25:48,034 --> 00:25:50,054
memes or or some kind of information attack

372
00:25:51,075 --> 00:25:51,975
or or defense

373
00:25:52,355 --> 00:25:57,654
and it works, people copy it. And then Trump was very good at kind of interacting with that and pulling that out.

374
00:25:58,515 --> 00:25:59,154
And that,

375
00:25:59,635 --> 00:26:01,495
it's very innovative. I mean,

376
00:26:01,860 --> 00:26:05,559
you know, open source insurgency, open source politics, it was extraordinarily

377
00:26:05,860 --> 00:26:09,000
innovative, but it had one fatal flaw is that once you achieve the objective,

378
00:26:09,380 --> 00:26:10,440
the open source

379
00:26:11,620 --> 00:26:12,920
organization falls apart.

380
00:26:13,700 --> 00:26:19,054
Okay? I mean, no one can agree exactly what he should do once we got this this grenade into office.

381
00:26:19,355 --> 00:26:19,755
And,

382
00:26:20,554 --> 00:26:23,855
it fell apart, and he was basically left there alone

383
00:26:24,155 --> 00:26:29,455
for four years to basically, you know, swim against the a tidal wave of opposition from the establishment.

384
00:26:32,000 --> 00:26:37,220
And here we are go ahead, please. No. Part of that opposition was the formation of a blue network.

385
00:26:37,680 --> 00:26:40,900
And the blue network worked different than the open source insurgency.

386
00:26:42,480 --> 00:26:44,340
It waged more warfare.

387
00:26:45,155 --> 00:26:46,294
And the moral warfare,

388
00:26:47,395 --> 00:26:49,575
it's often a feature of guerrilla warfare,

389
00:26:50,515 --> 00:26:53,735
and that, what you wanna do is you wanna make the opponent look,

390
00:26:55,075 --> 00:26:55,575
immoral

391
00:26:55,955 --> 00:26:58,375
and not worth not not worthy of any legitimacy,

392
00:26:59,170 --> 00:27:02,710
shouldn't shouldn't be in office. And they founded that based on a,

393
00:27:03,970 --> 00:27:05,510
opposition to known evils,

394
00:27:05,890 --> 00:27:06,390
racism,

395
00:27:06,770 --> 00:27:07,990
sexism, colonialism,

396
00:27:08,610 --> 00:27:09,110
antisemitism,

397
00:27:09,730 --> 00:27:11,910
that kind of stuff, all those things that they hated.

398
00:27:13,145 --> 00:27:13,465
And,

399
00:27:15,304 --> 00:27:19,485
they formed a kind of tribal trust layer based on that. So they,

400
00:27:20,184 --> 00:27:21,804
if you're opposed to these,

401
00:27:22,665 --> 00:27:26,765
then you are part of their tribe. And anyone who sees examples of those,

402
00:27:27,840 --> 00:27:29,220
you would see you would

403
00:27:29,840 --> 00:27:34,659
have empathy evoked from those examples, and it that bonded you kind of a kind of a,

404
00:27:36,080 --> 00:27:36,980
network tribal

405
00:27:37,840 --> 00:27:38,340
kinship

406
00:27:38,880 --> 00:27:43,220
with these other players. So if you saw George Floyd, for instance, with the neon in his neck

407
00:27:43,595 --> 00:27:45,775
and you hated the officer for doing that,

408
00:27:46,635 --> 00:27:54,575
you your outrage would bind you with not just George Floyd, but everyone else was outraged by it. And your enemy would,

409
00:27:55,275 --> 00:28:00,559
you know, your enemy would be the police officer, and everyone else's enemies would be the police officer in the system,

410
00:28:01,900 --> 00:28:02,799
that he represented.

411
00:28:03,419 --> 00:28:03,660
So,

412
00:28:04,540 --> 00:28:05,520
instead of having

413
00:28:07,100 --> 00:28:13,865
a wild number many, many different kind of opinions on how things should work and attacks from everywhere, a kind of a maneuver warfare.

414
00:28:14,245 --> 00:28:16,424
Within the blue tribe, it was a cohesive

415
00:28:17,044 --> 00:28:18,105
pattern of,

416
00:28:19,765 --> 00:28:23,465
morality. So they parsed all the news at a kind of grand,

417
00:28:23,924 --> 00:28:27,929
co curated scale where everyone took every bit of news and

418
00:28:28,470 --> 00:28:38,090
spun it. You know? And we live in a kind of a packetized news environment, and everything's broken down to very small bits. And everything was actually parsed and and spun and put into a context that.

419
00:28:38,975 --> 00:28:41,075
So if you saw x happen,

420
00:28:43,775 --> 00:28:46,835
then you would say, okay. This happened because of

421
00:28:47,535 --> 00:28:51,635
racism or this happened because of sexism or this you know, the response is

422
00:28:52,330 --> 00:28:55,870
colonialist. Their back their response is anti Semitic. And that all

423
00:28:56,330 --> 00:29:05,870
happened in real time, and and it created this huge pattern that everyone was supportive of. And it grew large enough, that it had influence and it it aligned

424
00:29:06,345 --> 00:29:08,285
corporations and government with that pattern.

425
00:29:08,665 --> 00:29:11,165
And that was used as as a means of enforcement

426
00:29:12,025 --> 00:29:13,645
for limiting the conversation

427
00:29:14,105 --> 00:29:15,005
on these platforms.

428
00:29:15,385 --> 00:29:19,245
And so it sounds like if I if I hear you, this is fascinating. The blue swarm

429
00:29:19,850 --> 00:29:23,150
learned, in effect, from the failure of the red swarm

430
00:29:23,450 --> 00:29:27,950
in that, as you said, once it achieved its goal, it dissolved. There was no cohesion.

431
00:29:28,570 --> 00:29:30,990
And so in in filtering everything,

432
00:29:32,490 --> 00:29:32,990
as,

433
00:29:33,765 --> 00:29:35,865
you know, either for or anti

434
00:29:36,325 --> 00:29:37,545
the swarm's identity,

435
00:29:38,405 --> 00:29:42,745
then it it overcomes the short of the version of the swarm that came before it.

436
00:29:43,045 --> 00:29:43,865
And then

437
00:29:44,885 --> 00:29:46,665
it sounds like connecting the dots,

438
00:29:48,010 --> 00:29:48,510
Twitter,

439
00:29:49,289 --> 00:29:51,470
Meta, all the companies that that

440
00:29:51,850 --> 00:29:55,549
enacted and conducted all of this, in my view, egregious,

441
00:29:56,169 --> 00:29:57,710
censorship and other behavior,

442
00:29:58,010 --> 00:30:01,870
what did they see, and what were they capitalizing on? Okay. So

443
00:30:02,795 --> 00:30:03,455
the Boostworm

444
00:30:03,755 --> 00:30:08,155
drew its members from academia, from government, you know, from,

445
00:30:08,635 --> 00:30:09,375
big corporations,

446
00:30:10,075 --> 00:30:10,575
from

447
00:30:11,115 --> 00:30:12,015
the tech crowd.

448
00:30:13,515 --> 00:30:13,835
And,

449
00:30:14,490 --> 00:30:17,950
they formed a cohesive unit. They created a a kind of a reverse tribalism.

450
00:30:18,330 --> 00:30:19,230
So tribalism,

451
00:30:20,809 --> 00:30:28,190
the oldest way, of course, to create trust, like I said at the start, is that it's usually formed based on a positive narrative, why we came together,

452
00:30:28,495 --> 00:30:31,554
why what what we've overcome and where we're going in the future.

453
00:30:32,174 --> 00:30:32,674
And,

454
00:30:33,695 --> 00:30:47,030
that creates a kind of fictive blood kinship, meaning that you're not actually related to these people directly. They're not part of your immediate family or extended family, but you are they're members of your tribe and you are connected with them at a deep level.

455
00:30:48,930 --> 00:30:55,510
Instead of positive narratives, they worked on negative narratives. It is what you were against. Right? So it created a very aggressive

456
00:30:55,810 --> 00:30:57,350
combative kind of mindset.

457
00:30:57,810 --> 00:30:58,310
And

458
00:30:59,625 --> 00:31:10,365
it also had a big flaw. So when the Blue Network won the White House with a guy that didn't even campaign I mean, Biden mailed it in. I mean, he didn't do anything, and he was he was brought into the White House,

459
00:31:11,090 --> 00:31:18,070
based on the Blue network's kind of coercion of these big companies into, you know, strict alignment and employ you know, alignment with their

460
00:31:18,690 --> 00:31:19,670
view of the world.

461
00:31:22,770 --> 00:31:24,070
They started, you know,

462
00:31:24,664 --> 00:31:28,184
really pushing to try to squeeze out the political opposition completely. And,

463
00:31:29,065 --> 00:31:31,404
they also had an inability to police

464
00:31:32,265 --> 00:31:35,404
excessive use of their, way of looking at the world.

465
00:31:35,865 --> 00:31:42,520
They couldn't say no. When somebody applied that morality, that moral structure saying, you know, any opposition to what I do,

466
00:31:43,060 --> 00:31:45,880
if it's in opposition to this, you

467
00:31:47,060 --> 00:31:50,280
know, prohibited activity, this evil activity, it's okay.

468
00:31:50,895 --> 00:31:51,635
And so,

469
00:31:52,335 --> 00:31:53,315
you ended up,

470
00:31:54,015 --> 00:31:55,695
normally, it would be like, okay. I'm I'm

471
00:31:56,975 --> 00:31:58,735
just take trans for instance,

472
00:31:59,295 --> 00:32:00,515
putting men in sports.

473
00:32:01,535 --> 00:32:05,485
And, you know, it's whether you agree or not on agree on the issue, it it was

474
00:32:05,929 --> 00:32:06,830
highly unpopular.

475
00:32:08,170 --> 00:32:08,650
And,

476
00:32:09,130 --> 00:32:17,070
surgeries for kids, again, lightning rod. It proved unpopular even though they pushed it out and it was being rolled out at a at a mass scale.

477
00:32:19,145 --> 00:32:23,405
Not to pick on trends or anything, but that was just, like, example of its inability to actually police

478
00:32:23,945 --> 00:32:27,165
the excesses that would cause, you know, widespread resentment,

479
00:32:28,184 --> 00:32:37,210
DEI policies and things like that where, you know, hiring of, you know, certain subgroups were was prohibited in favor of other groups. And, of course, that created more and more resentment.

480
00:32:37,590 --> 00:32:38,169
It wasn't

481
00:32:38,630 --> 00:32:40,010
rolled out with any kind

482
00:32:40,950 --> 00:32:43,750
of nuance and subtlety and insight into,

483
00:32:44,284 --> 00:32:48,865
the viability of it. That generated all this negative resentment, and it was unlocked with

484
00:32:49,485 --> 00:32:50,945
Musk acquiring Twitter

485
00:32:51,325 --> 00:32:52,544
and turning it into x.

486
00:32:53,245 --> 00:32:55,184
And, it was then marshaled

487
00:32:56,365 --> 00:32:56,865
by

488
00:32:57,340 --> 00:33:00,640
instead of a bunch you know, millions of individuals like an open source

489
00:33:00,940 --> 00:33:01,440
insurgency

490
00:33:01,820 --> 00:33:03,120
in in in 2016,

491
00:33:03,500 --> 00:33:04,320
it was,

492
00:33:04,780 --> 00:33:07,280
marshaled by these bigger professional accounts.

493
00:33:09,495 --> 00:33:13,595
Hundreds of these accounts, millions of hundreds of millions of followers collectively,

494
00:33:15,095 --> 00:33:18,155
like a Musk with a couple hundred million followers. And and,

495
00:33:18,615 --> 00:33:19,115
they

496
00:33:19,895 --> 00:33:20,795
challenged establishment

497
00:33:22,110 --> 00:33:30,210
narratives, basically, blue network narratives, question DEI, question immigration, question this and this and this. It started poking holes in their in their narratives,

498
00:33:30,590 --> 00:33:31,070
and,

499
00:33:32,190 --> 00:33:34,785
people followed it. People signed on to it

500
00:33:36,305 --> 00:33:36,965
and, revitalized

501
00:33:37,345 --> 00:33:38,005
Red Network

502
00:33:38,465 --> 00:33:39,345
emerged. And,

503
00:33:39,825 --> 00:33:42,485
it had you know, the Blue Network was, you know,

504
00:33:43,105 --> 00:33:45,525
being taken apart piece by piece by piece,

505
00:33:46,705 --> 00:33:49,039
by these, you know, Red Network accounts.

506
00:33:49,820 --> 00:33:49,980
And,

507
00:33:50,940 --> 00:33:52,960
it was increasingly hard for them to actually,

508
00:33:53,260 --> 00:33:54,799
you know, get their message across,

509
00:33:56,779 --> 00:33:58,240
and they lost the White House.

510
00:33:58,940 --> 00:34:02,779
I mean, I guess maybe the final step on on them falling apart is one of the founding

511
00:34:03,215 --> 00:34:07,315
the Gaza incident caused a huge rift is that one of the founding,

512
00:34:08,095 --> 00:34:11,155
factions within the blue network is this opposition to antisemitism

513
00:34:11,615 --> 00:34:14,035
that ran a foul of those of, you know, opposing

514
00:34:14,575 --> 00:34:16,595
colonialism, fascism, and and racism.

515
00:34:17,890 --> 00:34:19,270
And it was irreconcilable,

516
00:34:20,930 --> 00:34:21,490
and that,

517
00:34:23,650 --> 00:34:28,230
that split the network. And what I usually, what do you call is a noncooperative centers of gravity,

518
00:34:29,010 --> 00:34:29,670
is that

519
00:34:31,785 --> 00:34:34,204
when waging war and warfare, if if

520
00:34:34,585 --> 00:34:38,924
you want to break the opponent into noncooperative centers of gravity where there are different

521
00:34:39,464 --> 00:34:44,045
groups within the opposition that would fight each other over moral issues.

522
00:34:44,424 --> 00:34:46,365
I don't trust you. I don't.

523
00:34:47,240 --> 00:34:48,359
That kind of thing. So,

524
00:34:49,640 --> 00:34:55,579
that was the final nail. Red network won. Put Trump in the White House, but it didn't go away this time. The big accounts

525
00:34:55,960 --> 00:34:57,160
took over, and,

526
00:34:57,800 --> 00:34:58,760
they served as the,

527
00:35:00,395 --> 00:35:01,855
most of the cabinet positions.

528
00:35:02,315 --> 00:35:07,214
They were the ones that were selecting a lot of the people that were going into the senior positions throughout government.

529
00:35:08,234 --> 00:35:11,214
You know, the deputies and other things behind you know, below,

530
00:35:11,515 --> 00:35:14,880
they were putting their people in. A lot of those people were tech people, and they did that.

531
00:35:16,799 --> 00:35:27,460
And they ran with their narratives. I mean, you know, Musk decided, okay. I'm gonna push cutting the budget. He came up with Doge, and he got the green light to do that. Started to trying to account for where all this money was going.

532
00:35:30,005 --> 00:35:30,805
Then they, you know,

533
00:35:31,245 --> 00:35:36,985
it has more sustainability than the blue network, but I think it has many since it's really kind of early,

534
00:35:39,285 --> 00:35:40,965
version of network decision making,

535
00:35:42,369 --> 00:35:47,109
like the Blue network was in this last iteration, is that it have flaws in its process

536
00:35:47,650 --> 00:36:03,145
that will eventually cause it to blow up in the same way the Blue network blew up. Because right now, the Blue network, for all intents and purposes, doesn't exist as it doesn't really have any weight anymore. It's gotta reform and reformat itself, and it will. And because that moralism is actually quite useful in decision making,

537
00:36:03,845 --> 00:36:05,704
because it sets boundaries and standards,

538
00:36:06,645 --> 00:36:07,865
but maybe not as

539
00:36:08,484 --> 00:36:10,980
maybe a minimalist approach that might be the better

540
00:36:11,540 --> 00:36:15,240
way to get it to grow faster and become more permanent. But,

541
00:36:15,940 --> 00:36:18,520
yeah, the red network that's in control right now will

542
00:36:19,140 --> 00:36:20,760
Probably suffer the same as well.

543
00:36:21,060 --> 00:36:25,505
Right. And but just like the evolutionary process, it dies. It comes back better,

544
00:36:26,525 --> 00:36:27,345
more evolved.

545
00:36:28,285 --> 00:36:30,704
Hopefully, not we don't end up with a version

546
00:36:31,565 --> 00:36:34,865
of network decision making, network politics that is truly disastrous

547
00:36:35,405 --> 00:36:36,385
because we could.

548
00:36:37,829 --> 00:36:38,569
It you know,

549
00:36:39,109 --> 00:36:47,369
it's so strong. I mean, look how it taken less than ten years before it took over the the whole political system. And that that to me is is what's so

550
00:36:48,915 --> 00:36:52,855
awe inspiring and terrifying about it is the ability to simply be washed downstream,

551
00:36:53,475 --> 00:36:59,975
you know, and or or carried off with the swarm, whatever metaphor we choose. And and I think, you know, with that as the backdrop,

552
00:37:00,355 --> 00:37:01,335
here we are

553
00:37:01,635 --> 00:37:03,255
in just a few years.

554
00:37:03,830 --> 00:37:06,410
We have the ability to manipulate information

555
00:37:07,190 --> 00:37:08,810
using LLMs, AI,

556
00:37:09,110 --> 00:37:11,530
deepfakes are trivial, automated propaganda.

557
00:37:12,550 --> 00:37:18,090
You know, it has to be rewiring how we decide. It is rewiring how we decide what's real.

558
00:37:18,835 --> 00:37:19,975
How do you see this

559
00:37:20,355 --> 00:37:21,975
shifting the way we

560
00:37:22,995 --> 00:37:25,815
choose to trust institutions and each other? Yeah.

561
00:37:26,195 --> 00:37:30,855
Well, having having two networks looking at the news tried tends to keep it more honest.

562
00:37:31,890 --> 00:37:32,330
So,

563
00:37:32,770 --> 00:37:33,349
you'll have

564
00:37:33,809 --> 00:37:34,790
a a a built in,

565
00:37:35,970 --> 00:37:37,510
questioning of of of

566
00:37:37,970 --> 00:37:46,790
a piece of news or or an item or event that favors the other side, particularly if it can be manipulated. And there are people out, you know, constantly looking at that,

567
00:37:47,375 --> 00:37:49,315
looking at for fabrication and misinformation,

568
00:37:49,935 --> 00:37:55,234
and they'll call people out on it. So I don't see disinformation or misinformation as a problem

569
00:37:55,535 --> 00:37:58,015
to the extent that we had prior to,

570
00:37:58,734 --> 00:37:59,635
during the

571
00:38:01,630 --> 00:38:05,090
six years or seven years prior to this last election.

572
00:38:05,550 --> 00:38:17,045
And everyone was crying about it and and mad about it. But that was largely just an excuse for cracking down on stuff and controlling stuff and controlling political outcomes using social networking and and information flow. So,

573
00:38:17,925 --> 00:38:24,665
and do you do you see and I and I hear you and and that, you know, that's what's echoing in the back of my head. It seems to me

574
00:38:24,965 --> 00:38:29,065
the very boogeyman that was called out, as you said, four or five years ago

575
00:38:29,680 --> 00:38:34,500
is now in some of these deepfakes or just simply AI generated video

576
00:38:35,120 --> 00:38:35,620
indistinguishable

577
00:38:36,080 --> 00:38:39,140
or rapidly approaching six months, twelve months indistinguishable

578
00:38:39,520 --> 00:38:40,820
from reality. So

579
00:38:41,440 --> 00:38:46,695
do do you discern, or or would you still say that it it is not a a a serious concern?

580
00:38:48,355 --> 00:38:49,175
I don't see

581
00:38:49,475 --> 00:38:51,095
the shared information environment,

582
00:38:52,115 --> 00:38:54,995
under that much threat from that kind of attack or that kind of,

583
00:38:55,555 --> 00:38:56,055
development.

584
00:38:56,755 --> 00:38:58,775
I see it more of a a threat

585
00:39:00,310 --> 00:39:01,770
at the individual level

586
00:39:02,630 --> 00:39:03,130
because

587
00:39:04,710 --> 00:39:06,329
we're really, really close

588
00:39:06,710 --> 00:39:08,490
to AI generated AR

589
00:39:09,109 --> 00:39:10,470
augmented reality. And,

590
00:39:12,045 --> 00:39:16,785
when that hits when that hits, it becomes easy where you're immersed in a visual and auditory,

591
00:39:17,724 --> 00:39:23,820
environment that's completely AI generated. The disconnection that will happen at the individual level is

592
00:39:24,380 --> 00:39:24,880
insane.

593
00:39:25,180 --> 00:39:27,360
I mean, we're already, you know, suffering kind of

594
00:39:28,060 --> 00:39:37,200
a sidal collapse at one level. I mean, you know, I wrote a report on the fertility collapse at the global level that just, this year. It was the first year that global fertility fell below replacement.

595
00:39:38,335 --> 00:39:42,435
And the information is just you know, the numbers are just catching up with that, you know, effect, but the

596
00:39:43,615 --> 00:39:47,795
and it's falling really fast. Make it get down to, say, one point

597
00:39:48,335 --> 00:39:50,275
point six, I think it was, the

598
00:39:50,575 --> 00:39:51,635
the lowest level,

599
00:39:52,230 --> 00:39:53,750
I saw in in,

600
00:39:54,310 --> 00:39:57,290
South Korea, the most wired nation on Earth. Right?

601
00:39:58,150 --> 00:40:00,410
Point six is one child for every four women.

602
00:40:01,510 --> 00:40:02,810
That's the way to kind

603
00:40:03,110 --> 00:40:07,005
of totally collapse the global population, and no one seems to be able to do anything. All that

604
00:40:07,805 --> 00:40:09,424
It's too complex already,

605
00:40:10,125 --> 00:40:14,625
because there's so many factors influencing it, and it's obviously shown a sign of deep dysfunction

606
00:40:15,325 --> 00:40:24,109
and how we our society is functioning. And now we're about to throw this AR on top of it where you could have the most trusted people in your life are not even real.

607
00:40:24,650 --> 00:40:29,710
Right? I mean, you could see them and hear them, and they'll be with you constantly, and they'll talk to you,

608
00:40:30,010 --> 00:40:36,705
not only, you know, just confidants and and and, advisors and educators and and, you know,

609
00:40:37,185 --> 00:40:37,685
romantic,

610
00:40:38,785 --> 00:40:39,605
you know, connections.

611
00:40:39,905 --> 00:40:41,285
These people are gonna be

612
00:40:41,665 --> 00:40:43,205
these fake people are gonna be

613
00:40:43,825 --> 00:40:49,525
these fake worlds that are created are gonna be just so much better than real life. And without without moralizing

614
00:40:49,985 --> 00:40:52,085
as to whether that's good, bad, or neutral,

615
00:40:53,130 --> 00:40:55,630
what do you think is necessary for individuals?

616
00:40:56,170 --> 00:40:59,630
You know, I think about still and and certainly historically

617
00:41:00,490 --> 00:41:02,349
the gap, at least in The US,

618
00:41:02,890 --> 00:41:07,230
as to media literacy and the ability to critically think about media.

619
00:41:07,805 --> 00:41:15,425
And now how does one critically think about this this immersive bubble that they live in where everything reinforces their views?

620
00:41:15,725 --> 00:41:17,265
You know, do do you have a position,

621
00:41:17,565 --> 00:41:22,145
position, John, on what's necessary to to get through this next phase?

622
00:41:22,890 --> 00:41:35,470
Oh, well, reality distortion field. Yes. Well, there's a kind of political tribalism, you know, as part of that solution, this network layer on how we think about politics and how we parse it at the at if if you want other people to talk to,

623
00:41:35,770 --> 00:41:38,865
you have to, you know, pick a fact pick a a tribe,

624
00:41:39,885 --> 00:41:41,025
in a red or blue

625
00:41:41,325 --> 00:41:45,825
network. Right? And, And two is sufficient, you think? Well, two

626
00:41:47,245 --> 00:41:50,370
But other one Seems to work within our context of our

627
00:41:50,690 --> 00:41:52,790
society. I I think what happens is

628
00:41:53,090 --> 00:41:56,710
if you get below two or you go to three or you go to four,

629
00:41:57,890 --> 00:41:58,710
is that

630
00:41:59,170 --> 00:41:59,910
the dominant

631
00:42:00,530 --> 00:42:05,195
party will walk away with it. It's kind of like that Metcalfe's law. Right? I think, You know,

632
00:42:05,575 --> 00:42:11,115
a a network that's, you know, 50% larger isn't just 50% valuable. It's many times more valuable,

633
00:42:11,415 --> 00:42:14,955
and it tends to concentrate power in the hands of that that larger network.

634
00:42:16,935 --> 00:42:17,335
And,

635
00:42:17,735 --> 00:42:28,190
I mean, I I think this the reason why I like the idea of having more information flow, even if it's painful, even if it's largely wrong, even if you have flat out earthers out there, you know,

636
00:42:28,490 --> 00:42:29,550
arguing nonsense,

637
00:42:30,490 --> 00:42:34,830
or people coming up with incredibly stupid things and pushing them, is that

638
00:42:35,995 --> 00:42:39,135
you have to have that openness in order to solve complex challenges.

639
00:42:39,435 --> 00:42:44,895
We live in a complex world now, not a complicated world. Complicated world is, you know, something you could solve using bureaucracy

640
00:42:45,275 --> 00:42:45,935
and planning.

641
00:42:46,235 --> 00:42:49,530
In a complex world, you you get hit with all sorts of things that you don't

642
00:42:50,010 --> 00:42:50,510
have

643
00:42:52,010 --> 00:42:53,390
a clue how to solve.

644
00:42:54,170 --> 00:43:03,310
Okay? You actually just have to throw things at it, ideas, and see what works. And then when you find the thing that works, then you reinforce it.

645
00:43:04,525 --> 00:43:05,025
And,

646
00:43:06,045 --> 00:43:06,705
you can't

647
00:43:07,165 --> 00:43:09,345
solve those problems if you have a, you know,

648
00:43:10,045 --> 00:43:16,865
structured information environment where everything's, like, limited. You have to have a free flow. You don't know where the new idea that's gonna save everybody

649
00:43:17,325 --> 00:43:18,819
will come from. So,

650
00:43:19,500 --> 00:43:21,360
And that's a that's a great,

651
00:43:21,980 --> 00:43:22,720
I think,

652
00:43:23,260 --> 00:43:25,760
pivot to or or or shift to

653
00:43:26,700 --> 00:43:28,640
we've talked quite a bit about the individual.

654
00:43:29,020 --> 00:43:37,135
On that note, you know, you you've warned about AI throwing supply chains and brands into chaos, and and I think we can extrapolate from our conversation so far.

655
00:43:37,435 --> 00:43:37,935
But

656
00:43:38,395 --> 00:43:40,655
to to go a bit deeper, what can organizations

657
00:43:40,955 --> 00:43:42,895
do to become more resilient

658
00:43:43,515 --> 00:43:48,975
to these changes? If if if the consumer, you know, from the standpoint of a of a business or a brand,

659
00:43:49,730 --> 00:43:50,470
are these

660
00:43:51,329 --> 00:43:52,309
highly tribal,

661
00:43:53,170 --> 00:43:54,230
swarm oriented,

662
00:43:55,329 --> 00:43:56,230
AR immersed,

663
00:43:57,970 --> 00:43:58,950
you know, individuals,

664
00:44:00,049 --> 00:44:04,950
how do organizations need to think about that? Yeah. It's it's gonna be a problem for organizations because

665
00:44:05,250 --> 00:44:07,965
I I did a report on the, you know, the global,

666
00:44:09,625 --> 00:44:15,485
Edelman's got a global trust survey. Yes. Familiar. You know, Microsoft sold a PR agency. Absolutely.

667
00:44:16,105 --> 00:44:17,165
Yeah. And so

668
00:44:17,880 --> 00:44:23,099
they found that in every country, every developed country, corporations are more trusted than they go.

669
00:44:23,880 --> 00:44:25,900
Every a long shot. And that's a recent,

670
00:44:26,279 --> 00:44:37,545
is it? Yeah. I have a report on that. So you can dig back in the in the in the substack and pull that up. I will. And it's basically saying that, people wanted corporations to do what the government isn't doing and take control

671
00:44:38,885 --> 00:44:39,945
and that people

672
00:44:40,485 --> 00:44:45,790
would not associate with a company that was aligned with one of the opposing political factions.

673
00:44:46,090 --> 00:44:48,730
But they wanted them to get into involved anyway. So,

674
00:44:49,290 --> 00:44:57,770
it was just a weird thing is that, okay. Here, they want these corporations to kind of solve the bigger problems that governments aren't solving, which is all these big global problems,

675
00:44:59,214 --> 00:45:03,474
in terms of, you know, everything from climate to, you know, economic justice to

676
00:45:04,335 --> 00:45:04,994
other things,

677
00:45:05,375 --> 00:45:08,275
but also kind of weigh in at the domestic level.

678
00:45:08,655 --> 00:45:23,630
So corporations are are being asked to align with one network or the other political network. And, we can see that it that turns out to be disastrous, everything from, you know, Miller Lite to Tesla. Right? So everyone everyone who aligns too strongly with one network is attacked by the other.

679
00:45:25,370 --> 00:45:28,910
Yet they're being asked and expected to kind of weigh in and and do things.

680
00:45:29,585 --> 00:45:30,565
In terms of AI,

681
00:45:31,025 --> 00:45:37,204
I mean, the way corporations are gonna have to you know, in order to participate is they're they're gonna be collecting data on everybody

682
00:45:37,505 --> 00:45:38,325
in their company.

683
00:45:38,625 --> 00:45:42,484
They you know, that's how they're gonna build those internal AIs necessary to kind of automate,

684
00:45:44,250 --> 00:45:51,070
the cognitive capabilities necessary to to grow and scale. And and you're talking about, John, if I understand you, employees, not not necessarily

685
00:45:51,450 --> 00:45:51,950
customers.

686
00:45:52,650 --> 00:45:55,630
Oh, yeah. No. They'll they'll suck their employees dry of data

687
00:45:56,010 --> 00:45:56,510
inevitably.

688
00:45:58,194 --> 00:46:01,895
I was trying to push at at the senate a couple years ago trying to get people

689
00:46:02,275 --> 00:46:20,050
to adopt a data ownership policy so that we would own our own data, everything we put up. And that would allow us to have a say in just before AI hit. I think it was 2020, I think it was. And, just before AI hit, I was saying, okay. This data is the most important thing in the world. If you want to have a participatory economy where everyone's votes rise

690
00:46:20,670 --> 00:46:23,490
and there's, you know, limits and controls over, you know,

691
00:46:25,115 --> 00:46:26,095
what gets developed.

692
00:46:26,635 --> 00:46:27,615
Give people ownership,

693
00:46:28,234 --> 00:46:29,055
of the data.

694
00:46:30,234 --> 00:46:33,214
Let them have a say and generate either income or,

695
00:46:34,155 --> 00:46:36,575
exercise control over how it's used.

696
00:46:37,194 --> 00:46:38,335
And then you have

697
00:46:39,200 --> 00:46:46,819
a stake, an equity stake, a good you know, one of those positive equity stakes in these AIs that are being developed, which will become the most valuable

698
00:46:47,279 --> 00:46:49,059
technological artifacts ever created.

699
00:46:49,839 --> 00:47:01,035
And they, you know, said it, of course, didn't believe AI was real at the time, so they kinda blew it off. And now we're in this situation where everybody's gonna be sucked, dry of their data strip mined. It's kinda like a it's worse than feudalism.

700
00:47:02,295 --> 00:47:09,180
Because feudalism was that the feudal lords are owned all the land and still kind of persists in England to a certain extent today.

701
00:47:09,800 --> 00:47:15,900
And that serfs would work that land, and they would be obligated to pay off a certain amount of product.

702
00:47:16,200 --> 00:47:16,700
Mhmm.

703
00:47:18,275 --> 00:47:25,575
And so there was never any motivation for them to do anymore. But there were, you know, they were they were it has an they were obliged to give them

704
00:47:26,355 --> 00:47:30,295
the produce, and in in exchange, they were allowed to live on that land,

705
00:47:30,740 --> 00:47:32,200
take the access for themselves,

706
00:47:32,579 --> 00:47:34,119
and get some level of security.

707
00:47:34,500 --> 00:47:38,599
But in this kind of feudalism, we're sucked dry of our data to build these amazingly

708
00:47:39,220 --> 00:47:44,520
valuable artifacts, and there's no real reciprocal thing other than you get to use them sometime.

709
00:47:45,365 --> 00:47:48,184
Right? And you actually even have to pay us to use them.

710
00:47:49,444 --> 00:47:51,785
In a corporate level Go ahead. No.

711
00:47:52,085 --> 00:47:54,665
In a in a company level, it's gonna be really tough because,

712
00:47:56,085 --> 00:48:06,770
screenwriters guild kind of got into this early, and they kind of set up some barriers. But most corporations are just sucking their employees' drive, all their emails, all their utterances inside the corporate

713
00:48:07,150 --> 00:48:07,650
setting,

714
00:48:08,110 --> 00:48:11,410
every work product. And that's gonna be fed into AI as to,

715
00:48:12,785 --> 00:48:17,685
not automation in a simple sense where it's not mechanical and it's it build cognitive replacement.

716
00:48:18,145 --> 00:48:18,625
Yes.

717
00:48:19,105 --> 00:48:24,245
They can think in complex and and and ways, and handle handle difficult

718
00:48:25,550 --> 00:48:26,050
exceptions.

719
00:48:26,350 --> 00:48:29,810
Because you know how the the standard thing is, like, 80% of all corporate

720
00:48:30,430 --> 00:48:31,410
problems are

721
00:48:31,870 --> 00:48:42,015
that take up 80% of the time are nonstandard tasks. It's easy to automate the bottom 20% because you can you could you could build something to do that. But if AI is gonna take that all over.

722
00:48:42,555 --> 00:48:43,055
Right?

723
00:48:43,915 --> 00:48:46,255
So the incentive for a given corporation

724
00:48:46,635 --> 00:48:48,495
to be able to tackle that is immense.

725
00:48:48,795 --> 00:48:56,540
I I did some work in 2020 on personal data ownership, legal ownership, and and and and technological sort of containerization,

726
00:48:56,840 --> 00:49:00,380
if you will. And Yep. Yep. I want to be more bullish,

727
00:49:00,840 --> 00:49:07,580
but, you know, what we learned was that most individuals would, you know, give away all their personal data for a free slice of pizza.

728
00:49:08,175 --> 00:49:11,075
And so, you know, it sounds like, John, you

729
00:49:11,935 --> 00:49:13,795
don't see a lot of bright,

730
00:49:14,895 --> 00:49:20,275
sunshiny days coming in that regard. But is there hope? Is there do you do you see anything on the horizon that would

731
00:49:20,780 --> 00:49:26,160
that would address personal data ownership and and would balance power in that regard to some degree?

732
00:49:26,619 --> 00:49:27,119
No.

733
00:49:27,900 --> 00:49:33,359
And so, it's not just your demographics. Most people wanna say data or they think, oh, just your demographic data.

734
00:49:33,660 --> 00:49:42,715
Oh, no. Some preference information. I'm talking, you know, how you blink your eyes and how you move your mouth, where your tone of your voice, your the way you interact with other people.

735
00:49:43,975 --> 00:49:51,720
All of that data is being sucked up because we've seen a strong correlation between the amount of data set, you know, applied to training and AI is directly

736
00:49:52,100 --> 00:50:08,395
correlated to its capabilities intelligence. A digital twin. I don't know if people are still using that term, but I think that was a term of art for some time. Yeah. No. The I mean, these AIs I mean, most of the guys actually working on these AIs come out of this mind model. Yeah. They're trying to create a model of the mind, and and it replicates a individual

737
00:50:09,095 --> 00:50:10,955
human mind unconstrained by,

738
00:50:12,055 --> 00:50:13,895
our biological limit. And,

739
00:50:14,615 --> 00:50:15,995
mistake was well,

740
00:50:17,655 --> 00:50:18,135
they,

741
00:50:18,455 --> 00:50:20,400
came up with a a way to kind of,

742
00:50:21,839 --> 00:50:23,140
reverse engineer it

743
00:50:24,160 --> 00:50:34,900
and kind of approximate a mind model by gathering all the social data, all this output, and then creating a model of that and then trying to make it act more like a single mind. Right?

744
00:50:35,285 --> 00:50:36,585
It's always kind of approximation.

745
00:50:37,445 --> 00:50:48,025
But the social model that we're use we call LLMs and all this other stuff is is actually more interesting as a social model than a mind model. You know, as because it contains

746
00:50:48,490 --> 00:50:56,910
all of these different perspectives. I was writing fiction with this stuff. I can tease out the perspective of a an Italian mother in New York sitting

747
00:50:57,610 --> 00:51:01,950
in the fifties, and it will respond and think like that if you if you because there's

748
00:51:02,410 --> 00:51:03,825
literature and thinking that

749
00:51:04,385 --> 00:51:05,525
reflects that inside

750
00:51:05,825 --> 00:51:12,244
that that meta model. Yes. I mean, I know I know you're you're very fond as I am. Maybe fond is not the word. You're

751
00:51:13,505 --> 00:51:14,484
you're experiencing

752
00:51:15,185 --> 00:51:21,540
the the benefits of grok as compared to others. I believe you've you've posted on that recently, and it is tremendous. It's amazing.

753
00:51:22,560 --> 00:51:28,560
But as you say, I mean, it's to some degree, you know, a deal with the devil. So you've got,

754
00:51:29,200 --> 00:51:34,845
you know, this blended military and tech background. You've seen systems fail up close, sort of across the spectrum.

755
00:51:35,705 --> 00:51:37,325
For those leaders who

756
00:51:38,345 --> 00:51:41,565
are facing this AI driven future, who are

757
00:51:41,865 --> 00:51:44,205
looking to to collect it all,

758
00:51:44,665 --> 00:51:46,125
you know, perhaps with their employees

759
00:51:46,425 --> 00:51:47,165
more than

760
00:51:47,545 --> 00:51:48,285
their customers,

761
00:51:49,440 --> 00:51:50,260
What do

762
00:51:50,880 --> 00:51:53,700
failure modes look like? What what should

763
00:51:54,400 --> 00:51:59,220
they be aware of? What's the cautionary tale to doing this? Or or is it just,

764
00:51:59,599 --> 00:52:00,260
you know,

765
00:52:00,560 --> 00:52:05,575
the incentives are there, and they're gonna do it? Yeah. Don't let third party suck all your data out.

766
00:52:06,115 --> 00:52:06,615
Alright?

767
00:52:08,915 --> 00:52:11,895
And control that. And and limit your

768
00:52:12,835 --> 00:52:15,180
use of third parties to actually crunch it and create,

769
00:52:16,540 --> 00:52:18,000
virtual employees. Optimally,

770
00:52:18,540 --> 00:52:20,240
if you do create virtual employees,

771
00:52:21,260 --> 00:52:22,160
is that you

772
00:52:23,339 --> 00:52:25,839
so do that on a open source AI platform.

773
00:52:26,859 --> 00:52:28,160
And is it as independently

774
00:52:28,460 --> 00:52:31,525
as possible and that you have complete control of the data,

775
00:52:32,785 --> 00:52:39,285
if you have, you wanna, you know, build up employee trust and get them, you know, working with these AIs, these virtual workers,

776
00:52:39,825 --> 00:52:43,620
is that you give them some level of ownership stake in the value of that AI.

777
00:52:44,340 --> 00:52:45,020
And that,

778
00:52:45,460 --> 00:53:00,035
I I I see that, you know, they're talking about agents now, which was inevitable. Mhmm. AI agents and and that's yeah. I've been through that since twenty years or twenty five years. We were doing Microsoft in the nineties. Yeah. They're they're redoing that whole thing. What we're really gonna look at is,

779
00:53:00,734 --> 00:53:01,555
social AIs.

780
00:53:02,015 --> 00:53:11,395
Okay? Social AI is, the way it's gonna roll out inside the corporation, inside our daily lives, inside of small companies and big companies is that it's going to be, a virtual

781
00:53:11,695 --> 00:53:12,980
employee or

782
00:53:14,160 --> 00:53:14,660
coworker

783
00:53:15,359 --> 00:53:15,859
or

784
00:53:16,320 --> 00:53:18,100
educator or adviser,

785
00:53:18,880 --> 00:53:20,180
and that you control

786
00:53:20,480 --> 00:53:23,300
the data that you put into them.

787
00:53:23,760 --> 00:53:29,235
Okay? So if you train them on your preferences and or you train them as an employee on a process or a technique,

788
00:53:29,535 --> 00:53:30,195
the data

789
00:53:31,775 --> 00:53:37,235
that delivered to that AI is not going off to the cloud. It's not being sucked up to the the mothership

790
00:53:37,535 --> 00:53:38,355
to be used.

791
00:53:39,180 --> 00:53:39,660
And that,

792
00:53:40,460 --> 00:53:43,599
that AI, it won't be flat. It will have a personality,

793
00:53:44,700 --> 00:53:52,095
and that, it will have a personality that fits the role that they're in, that you like as as the person who's working with them,

794
00:53:52,734 --> 00:53:54,435
and that, it will

795
00:53:55,535 --> 00:54:00,035
grow and improve itself based on your interactions and will remember those previous interactions.

796
00:54:00,494 --> 00:54:00,895
And,

797
00:54:01,375 --> 00:54:05,155
the best way to do that, of course, was open source because you you you control the whole process.

798
00:54:05,535 --> 00:54:06,095
So it's

799
00:54:07,430 --> 00:54:08,570
these social AIs

800
00:54:10,470 --> 00:54:10,970
build

801
00:54:11,910 --> 00:54:14,810
trust at the individual level with the other employees, human

802
00:54:15,110 --> 00:54:18,890
in particular. You know, they build trust with that human worker that they're working with.

803
00:54:19,750 --> 00:54:22,904
They handle complex tasks like they do. It's a

804
00:54:23,365 --> 00:54:25,125
partnership. It's not a,

805
00:54:25,605 --> 00:54:30,904
you know, not running a spreadsheet or something like that. It's not like an automated process in that regard. Should we trust them?

806
00:54:32,085 --> 00:54:33,704
If Or are we given no choice?

807
00:54:34,244 --> 00:54:34,805
Well, you you

808
00:54:35,559 --> 00:54:48,380
if you wanna compete, sure. I mean, you know, you have to trust them. But you you should only trust them if you control it or have a have a equity stake in the data that you're providing. I mean, if I'm a small company owner, I wanna know open source. I want my data sequestered.

809
00:54:49,160 --> 00:54:52,655
Because if I create something cool or do something proprietary,

810
00:54:53,115 --> 00:54:53,775
I want

811
00:54:54,635 --> 00:55:02,015
that to remain within my company. Okay? If I have virtual employees and human employees, I want that knowledge and and and

812
00:55:02,315 --> 00:55:02,815
insight

813
00:55:03,590 --> 00:55:04,090
contained,

814
00:55:06,150 --> 00:55:10,650
to producing you know, directed to producing value that I can I can acquire? Absolutely.

815
00:55:11,750 --> 00:55:20,305
Personality aspect's really big in per in terms of providing, you know, building trust. So, I mean, we have all of these ways of building trust with other human workers.

816
00:55:20,845 --> 00:55:21,345
Right?

817
00:55:21,725 --> 00:55:24,225
Building cohesive teams with other human workers,

818
00:55:25,645 --> 00:55:29,505
evaluating performance of other human workers or of human workers in general,

819
00:55:30,869 --> 00:55:35,769
what a successful training effort looks like, what all of that onboarding, all that slot is already there

820
00:55:36,710 --> 00:55:37,369
for doing

821
00:55:38,470 --> 00:55:39,049
for producing,

822
00:55:39,589 --> 00:55:42,490
someone that will do the job that's required.

823
00:55:43,670 --> 00:55:46,009
The virtual work of this from the social AI

824
00:55:46,715 --> 00:55:49,295
fits into that slot. It's a natural fit.

825
00:55:49,915 --> 00:55:50,315
And,

826
00:55:52,075 --> 00:55:57,135
so you have to have that personality. You have to have that vector of improvement. You have to have that, you know,

827
00:55:57,995 --> 00:55:59,660
interface that allows,

828
00:56:00,440 --> 00:56:03,980
you to interact with that slot. You know, agents won't do it.

829
00:56:04,440 --> 00:56:09,579
Current, like, dry Siri type things won't do it. You know, it's too generic. It's too flat.

830
00:56:10,040 --> 00:56:13,020
Those mind models, you don't want we're not talking about an AI

831
00:56:13,875 --> 00:56:15,095
brainiac. No.

832
00:56:15,955 --> 00:56:16,615
We're talking

833
00:56:17,155 --> 00:56:21,815
these AIs only have to be as smart as the the person that would be normally filling that role,

834
00:56:22,275 --> 00:56:25,095
which we've already achieved for many in many ways and

835
00:56:26,210 --> 00:56:27,190
nice, cooperative,

836
00:56:27,890 --> 00:56:30,150
willing to stand their ground on certain issues,

837
00:56:30,530 --> 00:56:32,710
all those things that you would want out of an employee.

838
00:56:34,130 --> 00:56:35,510
And we know what those are.

839
00:56:36,450 --> 00:56:41,385
And it can change based on the type of company, and you can you can train for that. You can push for that.

840
00:56:43,705 --> 00:56:55,565
So, yeah, to the extent that you don't let the mother ship suck it all up, you're better off. And the same is gonna be with robotics. You know, robotic and AI is gonna you're gonna see robots everywhere in ten years. They'll all be AI run.

841
00:56:56,210 --> 00:57:02,789
So you have to have physical workers as well as virtual workers. It's the same thing. But you don't want it sucked up to a big company.

842
00:57:04,130 --> 00:57:06,470
That data has to remain with you or you're lost.

843
00:57:07,410 --> 00:57:13,675
Somebody's gotta tap into it, that latent capability, and put you out of a out of a business really quick. So,

844
00:57:14,955 --> 00:57:16,155
I find that that is,

845
00:57:17,195 --> 00:57:20,575
as as often as the case, these things are invigorating and unsettling

846
00:57:20,875 --> 00:57:21,935
in equal measure.

847
00:57:23,435 --> 00:57:24,815
And and on that,

848
00:57:26,070 --> 00:57:35,450
note, perhaps on some time in. Hopefully no. Hopefully, invigorating. I would love to close it up, John. And, again, thanks for your time. Yeah. What what is what is one

849
00:57:36,230 --> 00:57:37,370
trend vector

850
00:57:38,335 --> 00:57:39,475
point on the horizon

851
00:57:39,935 --> 00:57:42,675
that you see that you think is going underappreciated

852
00:57:44,255 --> 00:57:50,035
that we should all be paying attention to? Well, the big rollout of social AI is gonna catch everyone by surprise.

853
00:57:50,390 --> 00:57:53,050
Define that for me, please. Well, it's like

854
00:57:54,630 --> 00:57:56,970
everyone's focused on, you know, cognitive,

855
00:57:58,870 --> 00:57:59,370
capabilities,

856
00:57:59,830 --> 00:58:08,235
you know, pushing the border. Can they do can they solve can you know, cure cancer kind of thing? You know, kind of pushing up to the limits of, you know, what they can do

857
00:58:09,495 --> 00:58:09,995
individual.

858
00:58:11,175 --> 00:58:15,035
The companies and and the individuals are working on trying to make socialize

859
00:58:15,335 --> 00:58:16,475
the voice quality,

860
00:58:16,850 --> 00:58:19,810
you know, the the emotional content of that, the,

861
00:58:21,010 --> 00:58:23,670
the, visuals that will be, you know,

862
00:58:23,970 --> 00:58:25,670
folded into augmented reality,

863
00:58:26,450 --> 00:58:26,950
the,

864
00:58:27,730 --> 00:58:28,230
personality.

865
00:58:29,744 --> 00:58:33,765
Okay. I see people working on personality, but it's, like, way out out of the mainstream,

866
00:58:35,025 --> 00:58:57,080
and and remembering past interactions and trying to get the that memory more cohesive over time. So you're probably running multiple in parallel LLMs, right, to do that. So they can check each other on the responses based on the previous interactions in history. And there's other kind of parallelisms that probably work. So those people are all often by the land right now, but they're gonna become the most dominant. So they're gonna catch a lot of people by surprise.

867
00:58:57,935 --> 00:59:01,555
And the first ones who employ it successfully are gonna make some amazing businesses.

868
00:59:02,095 --> 00:59:02,595
So,

869
00:59:03,935 --> 00:59:08,915
that's gonna be a surprise. I I don't think anyone's really care you know, set up to handle

870
00:59:09,295 --> 00:59:11,635
what's gonna happen with fertility crisis because

871
00:59:12,030 --> 00:59:15,730
when when we finally figured out fifteen years from now and and everyone's focused on it,

872
00:59:17,070 --> 00:59:21,250
being because it's global, you can't you know, immigration won't solve it.

873
00:59:22,110 --> 00:59:23,730
Nothing will solve it. So,

874
00:59:25,205 --> 00:59:33,865
you're gonna have to figure out a way to keep on growing the economy without people. My personal solution to that, and this thing would be the the ultimate kind of kicker,

875
00:59:34,405 --> 00:59:34,965
is that,

876
00:59:35,845 --> 00:59:38,185
at some point, we'll probably figure out a way to handle

877
00:59:38,829 --> 00:59:48,049
the collapse of population associated with the fertility crisis, and it'll probably be something that we hate right now, like clonings and and things like that. Just horrible kind of institutional kind of things

878
00:59:48,510 --> 00:59:50,130
or technology driven things.

879
00:59:50,670 --> 00:59:51,170
But

880
00:59:51,710 --> 00:59:52,930
how you grow an economy

881
00:59:55,105 --> 00:59:59,845
without people is that you give these social AIs the ability to buy

882
01:00:00,305 --> 01:00:01,605
as well as produce,

883
01:00:02,225 --> 01:00:02,725
purchase.

884
01:00:03,425 --> 01:00:05,685
They have a a vector of improvement

885
01:00:05,985 --> 01:00:11,849
of of where they wanna go and what they wanna do, and their interest will associate with that. As you build that personality out,

886
01:00:12,170 --> 01:00:13,309
they can become consumers.

887
01:00:14,170 --> 01:00:16,109
And if you have a billion

888
01:00:17,369 --> 01:00:18,410
virtual and,

889
01:00:18,970 --> 01:00:22,270
robotic workers in your economy in fifteen years, which is

890
01:00:22,605 --> 01:00:24,065
probably a low figure

891
01:00:24,365 --> 01:00:29,265
if this thing start really zooming. Because but we went from in 02/2007, there were zero smartphones.

892
01:00:30,205 --> 01:00:30,705
Okay?

893
01:00:31,085 --> 01:00:34,285
In 02/2024,

894
01:00:34,285 --> 01:00:36,145
there were 5,300,000,000

895
01:00:36,660 --> 01:00:39,079
smartphone users. We rewired the whole world

896
01:00:39,460 --> 01:00:53,595
in that short period of time. We could we will have that many virtual workers, if not more, probably closer to trillions. If they start buying it, the country that figures that out and gives them the level of autonomy necessary to buy and things purchase things, become consumers as well as producers,

897
01:00:54,775 --> 01:00:57,275
some level of, you know, personal autonomy

898
01:00:57,815 --> 01:01:03,360
is going to have the biggest economy in the world by far. Everyone else would be standing still thinking they're gonna use these

899
01:01:03,920 --> 01:01:11,060
AIs as, you know, virtual slaves. Yeah. And they'll always be producing and never taking. But the one that figures out the purchasing

900
01:01:11,600 --> 01:01:12,100
cycle

901
01:01:12,560 --> 01:01:23,605
would just walk away. I mean, you could see takes the rest of the world ten years, fifteen years to catch up. Well, well, it's gonna be too late because that that first economy will zoom so fast. It'll change everything.

902
01:01:24,145 --> 01:01:31,745
Fascinating. I did not see that coming. I'm I'm thinking now I'm thinking of share of wallet. You know, what does that look like when you've got billions of of AIs and agents and

903
01:01:33,140 --> 01:01:33,700
But even

904
01:01:34,260 --> 01:01:35,960
you know, a lot of people think

905
01:01:36,340 --> 01:01:44,200
this is the the cognitive problem I've seen with people even with, you know, people who understand economics and finance and stuff, is they tend to think of

906
01:01:45,460 --> 01:01:47,560
their personal wealth and ability to aggregate

907
01:01:48,025 --> 01:01:52,605
personal wealth. And they don't see any value in making sure that all boats rise.

908
01:01:55,065 --> 01:01:56,365
And they don't see

909
01:01:56,665 --> 01:02:01,085
that they would be much better off and richer than they are

910
01:02:01,809 --> 01:02:07,270
in the in the most acquisitive kind of scenario that we can imagine if everyone got richer and became,

911
01:02:08,450 --> 01:02:09,190
more prosperous.

912
01:02:09,730 --> 01:02:10,230
So,

913
01:02:11,809 --> 01:02:13,829
because the economy would be so much bigger.

914
01:02:14,555 --> 01:02:21,855
The the whole environment would be so much wealthier and so much productive and so much more rich in technologies and everything else is that that,

915
01:02:22,795 --> 01:02:34,030
you know, level would be so much higher that you're starting from and that compared to where you were if you had kid a few people that were very inquisitive and locked it down. It took the majority of what was going on.

916
01:02:34,970 --> 01:02:40,590
So they can they couldn't make the cognitive leap between that kind of slow, targeted environment

917
01:02:41,005 --> 01:02:44,385
and this dynamic massive environment. Another thing is that

918
01:02:45,165 --> 01:02:53,345
the other thing I failed at was in 02/2010 when I came up with a kind of a autonomous corporation concept. It's a couple years before they had these, DAOs.

919
01:02:54,080 --> 01:02:57,700
Yeah. Wait. It was, like, three years before they came out with Dows. Right?

920
01:02:58,000 --> 01:03:05,780
And Bitcoin was just started. We're trying to figure out a dollar. Right? It was a dollar at the time. How to incorporate it into this, but it was just too early

921
01:03:07,375 --> 01:03:09,875
days. And the idea was that we were gonna,

922
01:03:11,535 --> 01:03:13,714
come up with a company written entirely as software

923
01:03:14,174 --> 01:03:20,275
that would pay everybody who contributed to that economy because it was open source, open dynamic where people come in,

924
01:03:23,440 --> 01:03:25,220
do a a piece of work

925
01:03:26,000 --> 01:03:27,700
that was measurable by the software

926
01:03:28,240 --> 01:03:29,220
and become

927
01:03:29,680 --> 01:03:34,260
get paid a certain amount for it, potentially, or just earn equity in that company

928
01:03:34,715 --> 01:03:37,295
and all future earnings, like a kind of an annuity

929
01:03:38,155 --> 01:03:39,195
in the in the,

930
01:03:39,755 --> 01:03:44,495
value that was created. And that, I came up with this idea that it would be, acquiring,

931
01:03:46,075 --> 01:03:46,975
like, a metadata.

932
01:03:48,300 --> 01:03:50,000
So take a picture of every environment,

933
01:03:51,180 --> 01:03:52,400
every every object,

934
01:03:52,700 --> 01:03:57,440
and then label it. Because, eventually, we're gonna be using this in AIs, and this data repository

935
01:03:57,900 --> 01:04:01,360
would be the biggest data repository in the world for object recognition

936
01:04:01,740 --> 01:04:03,315
and that metadata and

937
01:04:03,795 --> 01:04:07,815
all sorts of other things that we could have individuals contributing to. And as they

938
01:04:08,755 --> 01:04:10,855
accessed it for training these models,

939
01:04:12,194 --> 01:04:15,175
making sure that they're not making virtual copies of it so they could have

940
01:04:15,570 --> 01:04:17,670
infinite training sessions, is that,

941
01:04:18,450 --> 01:04:24,710
everyone will get paid for that, and that the value that would be created could be immense. That so for that original hour of work

942
01:04:25,250 --> 01:04:29,190
that you made $2 on could become worth hundreds of dollars downstream.

943
01:04:30,225 --> 01:04:33,765
And it'd be paid constantly as they grew as the number of participants was

944
01:04:34,305 --> 01:04:43,925
you know, kept on growing. Of course, it didn't work because there was too many prerequisites for that, like a functional Bitcoin and other things like that. But while you invented Pokemon Go, among other things.

945
01:04:44,319 --> 01:04:53,619
Yeah. Well yeah. But the thing is that that kind of company could have created the ecosystem necessary to kind of challenge it. So if you have this kind of alternative things, they can grow really quickly in this kind of network environment.

946
01:04:54,079 --> 01:04:58,480
Just like how quickly network politics have evolved and changed and and and and,

947
01:04:59,875 --> 01:05:03,495
the dynamism is is is shifting in in unexpected ways,

948
01:05:03,875 --> 01:05:06,615
we could see that's with the economic system as well.

949
01:05:07,875 --> 01:05:12,295
I always thought that, you know, crypto would be better off within the context of an equity,

950
01:05:12,890 --> 01:05:14,030
and and corporate

951
01:05:14,890 --> 01:05:15,710
kind of context,

952
01:05:17,050 --> 01:05:20,830
help, you know, alleviate some of the elements associated with with trust

953
01:05:21,770 --> 01:05:22,510
at scale.

954
01:05:23,530 --> 01:05:24,250
And I think that

955
01:05:25,475 --> 01:05:27,575
yeah. And and and there's a lot of that emerging.

956
01:05:28,363 --> 01:05:28,771
So

957
01:05:29,179 --> 01:05:29,587
wow.

958
01:05:29,995 --> 01:05:34,135
Fascinating, John. I know Global Gorillas is one of your primary

959
01:05:34,515 --> 01:05:41,255
focuses and projects. I'll be sure that everyone gets a pointer to your Substack. As I say, I've really, really enjoyed it. I will,

960
01:05:41,610 --> 01:05:44,510
I do recommend everybody check it out so we can,

961
01:05:45,450 --> 01:05:54,186
keep getting these glimpses of of what's coming in the future. Thanks so much for your time today, John. Oh, you're welcome. Really appreciate it. Talk soon. Yep. Bye bye. Yep.