1
00:00:02,360 --> 00:00:03,520
Speaker 1: Cool Media.

2
00:00:05,160 --> 00:00:08,360
Speaker 2: Hello, and welcome's a Better offline. I'm your host ed zietron.

3
00:00:16,640 --> 00:00:16,880
Speaker 1: As.

4
00:00:19,760 --> 00:00:21,799
Speaker 2: I am joined by the Chair of the Federal Trade Commission,

5
00:00:21,840 --> 00:00:23,919
Speaker 2: Lena Cohn. Lena, thank you so much for joining me.

6
00:00:24,600 --> 00:00:25,319
Speaker 1: Great to be here.

7
00:00:25,960 --> 00:00:29,480
Speaker 2: So on a simple level, what does the FTC actually do?

8
00:00:30,120 --> 00:00:34,720
Speaker 1: So, the FTC enforces America's anti trust and consumer protection laws,

9
00:00:35,000 --> 00:00:37,000
Speaker 1: and so these are the laws that try to ensure

10
00:00:37,040 --> 00:00:40,839
Speaker 1: that our markets are fair and honest and competitive, and

11
00:00:40,880 --> 00:00:44,479
Speaker 1: so that means we're looking to protect people from illegal monopolies.

12
00:00:44,800 --> 00:00:47,360
Speaker 1: We're trying to protect people from all sorts of frauds

13
00:00:47,440 --> 00:00:50,640
Speaker 1: and scams. We're trying to protect people's privacy and wanting

14
00:00:50,680 --> 00:00:52,720
Speaker 1: to make sure that they're not subjected to all sorts

15
00:00:52,720 --> 00:00:56,280
Speaker 1: of unfair practices. We were created one hundred and ten

16
00:00:56,360 --> 00:01:00,880
Speaker 1: years ago, and so it's a pretty big mandate. We

17
00:01:00,920 --> 00:01:04,720
Speaker 1: have oversight across markets across the entire economy for the

18
00:01:04,720 --> 00:01:08,039
Speaker 1: most part, with some exceptions like in areas such as

19
00:01:08,080 --> 00:01:11,840
Speaker 1: banks and airlines. So it's a really big job that

20
00:01:11,880 --> 00:01:14,640
Speaker 1: this agency does and it's been thrilling to get to

21
00:01:14,640 --> 00:01:14,920
Speaker 1: do it.

22
00:01:15,760 --> 00:01:18,960
Speaker 2: And it feels like you're a lot more aggressive than

23
00:01:19,160 --> 00:01:22,240
Speaker 2: perhaps anti monopoly and anti consolidation has been in the past,

24
00:01:22,280 --> 00:01:23,000
Speaker 2: what led to them.

25
00:01:24,040 --> 00:01:26,720
Speaker 1: So I came into this job wanting to make sure

26
00:01:26,840 --> 00:01:30,640
Speaker 1: that we were a fully using the tools that Congress

27
00:01:30,680 --> 00:01:33,360
Speaker 1: gave us. As I noted, this agency has been around

28
00:01:33,440 --> 00:01:37,080
Speaker 1: for o first century. Our agency was given some pretty

29
00:01:37,120 --> 00:01:41,319
Speaker 1: important authorities and tools, but over the decades there had

30
00:01:41,360 --> 00:01:44,880
Speaker 1: been a drift away from fully using all of the

31
00:01:44,880 --> 00:01:48,920
Speaker 1: tools that we have, from fully embracing the law on

32
00:01:49,040 --> 00:01:51,400
Speaker 1: the books. And so the first thing we did was

33
00:01:51,480 --> 00:01:53,840
Speaker 1: kind of come in and just make sure that we

34
00:01:53,880 --> 00:01:56,600
Speaker 1: are mapping out what are all the tools we actually

35
00:01:56,600 --> 00:01:59,320
Speaker 1: have and how do we make sure we're faithfully using those.

36
00:02:00,480 --> 00:02:03,280
Speaker 1: The second thing that's been important is wanting to make

37
00:02:03,320 --> 00:02:07,120
Speaker 1: sure that we're enforcing the law and taking action in

38
00:02:07,200 --> 00:02:12,200
Speaker 1: response to how markets actually work today, and that meant

39
00:02:12,400 --> 00:02:16,600
Speaker 1: making sure we were having top expertise Internally. We started

40
00:02:16,600 --> 00:02:20,680
Speaker 1: a new Bureau of Technologists that you know, brought data scientists,

41
00:02:20,760 --> 00:02:24,119
Speaker 1: data engineers, people who fully understand the ins and outs

42
00:02:24,160 --> 00:02:29,240
Speaker 1: of how algorithms work. Previously, companies would view lawsuits as

43
00:02:29,360 --> 00:02:32,640
Speaker 1: just a cost of doing business, and especially in digital

44
00:02:32,680 --> 00:02:35,760
Speaker 1: markets where there's such a focus on chasing scale and

45
00:02:35,840 --> 00:02:38,880
Speaker 1: chasing growth, you know, there was a bit of a

46
00:02:38,880 --> 00:02:43,240
Speaker 1: ask for forgiveness later mentality, rather than everybody abiding by

47
00:02:43,240 --> 00:02:45,880
Speaker 1: the law and making sure Americans were getting their rights

48
00:02:45,919 --> 00:02:46,560
Speaker 1: on the front end.

49
00:02:47,440 --> 00:02:50,400
Speaker 2: So how do you curtail that instinct where they have

50
00:02:50,520 --> 00:02:53,160
Speaker 2: so much money that they can just kind of absorb

51
00:02:53,240 --> 00:02:54,840
Speaker 2: the fee, sorry, the fine.

52
00:02:54,880 --> 00:02:58,840
Speaker 1: I mean, yeah, it's a good question, and it's especially

53
00:02:58,880 --> 00:03:02,680
Speaker 1: important because a few months before I came into this role,

54
00:03:03,280 --> 00:03:07,240
Speaker 1: the courts had actually further limited the FTC's ability to

55
00:03:07,280 --> 00:03:11,240
Speaker 1: get money. We mitigated that in a couple of ways. First,

56
00:03:11,320 --> 00:03:13,600
Speaker 1: we used the tools we did have to their full

57
00:03:13,639 --> 00:03:18,079
Speaker 1: extent to still get record breaking sums. We also made

58
00:03:18,120 --> 00:03:22,240
Speaker 1: sure we were looking at things like individual accountability, and

59
00:03:22,320 --> 00:03:27,800
Speaker 1: so if a specific individual executive was involved in directing

60
00:03:28,639 --> 00:03:32,000
Speaker 1: or participating in the law breaking, the lawsuit can be

61
00:03:32,040 --> 00:03:35,080
Speaker 1: brought not just against the company but also against the

62
00:03:35,120 --> 00:03:39,600
Speaker 1: individual executive. And so we've done that in several instances

63
00:03:40,280 --> 00:03:43,600
Speaker 1: where we had evidence that high level execs knew what

64
00:03:43,680 --> 00:03:46,440
Speaker 1: was going on, had the ability to stop it, and didn't.

65
00:03:46,960 --> 00:03:49,480
Speaker 1: And there's been a lot of empirical work that shows

66
00:03:49,480 --> 00:03:55,800
Speaker 1: that actually holding individual executives accountable is really important for

67
00:03:56,040 --> 00:03:59,800
Speaker 1: deterring law breaking in the first instance. So we've done that.

68
00:04:00,080 --> 00:04:04,200
Speaker 1: We've also made sure that when companies, for example, have

69
00:04:04,360 --> 00:04:09,440
Speaker 1: used illegal practices to hoard people's data, that they're having

70
00:04:09,480 --> 00:04:12,120
Speaker 1: to actually get rid of that data or get rid

71
00:04:12,200 --> 00:04:14,880
Speaker 1: of the models that we're trained on the data. So

72
00:04:14,920 --> 00:04:18,560
Speaker 1: we're actually getting remedies that make sense for today's markets.

73
00:04:19,440 --> 00:04:22,159
Speaker 2: So you file the case against Amazon? What is the case?

74
00:04:22,200 --> 00:04:23,680
Speaker 2: What's going on over there? Because I know you have

75
00:04:23,720 --> 00:04:26,440
Speaker 2: some history when at Yale Law School you wrote that

76
00:04:26,720 --> 00:04:29,840
Speaker 2: the antitrust paradox. I believe it, like, what's the case

77
00:04:29,839 --> 00:04:30,560
Speaker 2: against Amazon?

78
00:04:32,440 --> 00:04:35,839
Speaker 1: So just to step back, what we see with digital

79
00:04:35,880 --> 00:04:39,760
Speaker 1: platforms in particular is that there can be a life cycle.

80
00:04:40,320 --> 00:04:44,000
Speaker 1: Right initially, when a digital platform is entering the market,

81
00:04:44,400 --> 00:04:48,840
Speaker 1: they're really focused on chasing scale and building up a

82
00:04:48,960 --> 00:04:51,680
Speaker 1: large customer base on one side of the market, so

83
00:04:51,760 --> 00:04:54,159
Speaker 1: then they can also attract a big customer base on

84
00:04:54,200 --> 00:04:57,280
Speaker 1: the other end, and they want to basically achieve, you know,

85
00:04:57,360 --> 00:05:01,719
Speaker 1: the flywheel of accelerated growth in them. Mentum that, especially

86
00:05:01,760 --> 00:05:04,719
Speaker 1: in digital markets, once you've kind of hit that sweet

87
00:05:04,720 --> 00:05:09,800
Speaker 1: spot of sufficient scale, there can be enormous acceleration. But

88
00:05:09,880 --> 00:05:14,440
Speaker 1: what we've seen is that once firms achieve that accelerated growth,

89
00:05:14,680 --> 00:05:18,440
Speaker 1: and if they're successful at knocking out their arrivals, we

90
00:05:18,480 --> 00:05:22,480
Speaker 1: can see a different phase kick in where the platform

91
00:05:22,600 --> 00:05:26,440
Speaker 1: starts looking to milk the monopoly right, and we can

92
00:05:26,480 --> 00:05:29,640
Speaker 1: see that in a few ways, the company can start

93
00:05:29,839 --> 00:05:34,839
Speaker 1: charging higher prices. Sometimes they can make service worse. Corey

94
00:05:34,880 --> 00:05:37,920
Speaker 1: doctor Rowe has coined this term and shoitification around just

95
00:05:38,040 --> 00:05:41,479
Speaker 1: the degradation of the services that you see. And so

96
00:05:41,600 --> 00:05:45,200
Speaker 1: the lawsuit that we've brought is about Amazon as it

97
00:05:45,279 --> 00:05:50,440
Speaker 1: is in this second phase, where basically we alleged they

98
00:05:50,480 --> 00:05:55,640
Speaker 1: have height prices for both buyers on Amazon's platform as

99
00:05:55,680 --> 00:05:59,320
Speaker 1: well as the small businesses that sell through its platform,

100
00:05:59,440 --> 00:06:02,200
Speaker 1: where Amazon now collects one out of every two dollars.

101
00:06:02,800 --> 00:06:06,240
Speaker 1: We also note that Amazon has kind of cluttered its

102
00:06:06,320 --> 00:06:10,960
Speaker 1: search results page with irrelevant ads as a very deliberate

103
00:06:10,960 --> 00:06:14,080
Speaker 1: strategy to be able to basically milk more ad revenue

104
00:06:14,120 --> 00:06:17,760
Speaker 1: from the platform even when it's not serving shoppers and

105
00:06:17,839 --> 00:06:22,280
Speaker 1: serving consumers. And so we allege that Amazon's only been

106
00:06:22,320 --> 00:06:25,960
Speaker 1: able to make things worse in this way for people

107
00:06:26,120 --> 00:06:30,400
Speaker 1: because they've architected this anti competitive scheme to block out

108
00:06:30,520 --> 00:06:34,560
Speaker 1: rivals through illegal tactics. And so that's what the lawsuit

109
00:06:34,680 --> 00:06:36,920
Speaker 1: is about. It's going to go to trial in a

110
00:06:36,960 --> 00:06:39,760
Speaker 1: couple of years, and we brought it with a whole

111
00:06:39,760 --> 00:06:41,520
Speaker 1: bunch of state attorneys general as well.

112
00:06:42,200 --> 00:06:46,040
Speaker 2: Lovely So some one of the core thrusts you made

113
00:06:46,040 --> 00:06:49,960
Speaker 2: in your paper. Amazon's antitrust paradox is that they prioritized

114
00:06:50,720 --> 00:06:54,359
Speaker 2: growth over being a profitable company. This feels like a

115
00:06:54,440 --> 00:06:57,520
Speaker 2: problem across the tech firms, all of them, they all

116
00:06:57,600 --> 00:07:00,960
Speaker 2: seem to be growth hungry. I feel do you feel

117
00:07:00,960 --> 00:07:03,400
Speaker 2: that this is anti competitive at its core because growth

118
00:07:03,400 --> 00:07:06,080
Speaker 2: doesn't seem to be about better, just seems like more.

119
00:07:07,640 --> 00:07:10,800
Speaker 1: Yeah, it's a really good question. And the antitrust laws

120
00:07:10,880 --> 00:07:15,280
Speaker 1: in no way say that chasing scale or chasing growth

121
00:07:15,640 --> 00:07:19,360
Speaker 1: is illegal, or even that being big is illegal. It

122
00:07:19,480 --> 00:07:23,640
Speaker 1: really comes down to what are the mechanisms of chasing

123
00:07:23,680 --> 00:07:27,320
Speaker 1: that growth or the mechanisms of becoming big? Right, and

124
00:07:27,360 --> 00:07:30,720
Speaker 1: so in the same ways that we would recognize, hey,

125
00:07:31,080 --> 00:07:33,480
Speaker 1: like going across You know, if you have a pizza

126
00:07:33,480 --> 00:07:35,760
Speaker 1: shop that goes across the street and sets fire to

127
00:07:35,840 --> 00:07:38,800
Speaker 1: its rival pizza shop, you know that's not fair competition.

128
00:07:39,360 --> 00:07:41,520
Speaker 1: That's an extreme example, but there are all sorts of

129
00:07:41,560 --> 00:07:45,400
Speaker 1: other mechanisms that the law say are not fair means

130
00:07:45,400 --> 00:07:48,760
Speaker 1: of competing, and so that's what the law does. It

131
00:07:48,800 --> 00:07:53,120
Speaker 1: tries to distinguish what is fair play versus not when

132
00:07:53,160 --> 00:07:56,320
Speaker 1: you're looking to, you know, compete and grow and get big.

133
00:07:57,800 --> 00:08:01,560
Speaker 1: And so chasing scale and growth is not in any

134
00:08:01,600 --> 00:08:04,320
Speaker 1: way by itself illegal and instead is a really kind

135
00:08:04,320 --> 00:08:08,640
Speaker 1: of core part of what incentivizes business. Is What we

136
00:08:08,800 --> 00:08:13,600
Speaker 1: have seen though, is if law enforcers are not effective

137
00:08:13,640 --> 00:08:19,160
Speaker 1: and are not timely, chasing growth can happen through playing

138
00:08:19,160 --> 00:08:23,560
Speaker 1: fast and loose with the rules, especially if companies know that, Okay,

139
00:08:23,560 --> 00:08:26,080
Speaker 1: sure I might get hit with a lawsuit in five years,

140
00:08:26,120 --> 00:08:28,840
Speaker 1: but guess what, I will have hit my targets by then,

141
00:08:29,080 --> 00:08:32,160
Speaker 1: I'll be the biggest firm. I'll have achieved dominance, and

142
00:08:32,240 --> 00:08:35,839
Speaker 1: so I can worry about that later. From a business perspective,

143
00:08:35,880 --> 00:08:39,160
Speaker 1: it's actually better for the company to play fast and

144
00:08:39,160 --> 00:08:42,120
Speaker 1: loose with the rules so that they gain that dominance

145
00:08:42,120 --> 00:08:44,640
Speaker 1: and then deal with it later. That's really problematic as

146
00:08:44,679 --> 00:08:47,080
Speaker 1: a mindset for law enforcement, and so that's something that

147
00:08:47,120 --> 00:08:49,160
Speaker 1: we've been trying to figure out. How do we devise

148
00:08:49,200 --> 00:08:52,680
Speaker 1: strategies to be much more assertive, be much more forward leaning,

149
00:08:52,840 --> 00:08:55,720
Speaker 1: be much more timely, So that we're not having to

150
00:08:55,760 --> 00:08:58,679
Speaker 1: do that clean up five years, ten years after.

151
00:08:58,440 --> 00:09:02,079
Speaker 2: The fact, How does the FTC have to actually tackle

152
00:09:02,200 --> 00:09:06,320
Speaker 2: anti trust violators? And indeed within those shortened time scales.

153
00:09:06,559 --> 00:09:13,520
Speaker 1: So we oversee various facets of firms behavior. One is

154
00:09:13,600 --> 00:09:17,000
Speaker 1: if they are looking to merge or pursue an acquisition,

155
00:09:17,600 --> 00:09:20,400
Speaker 1: if it's above you know, one hundred and nineteen million dollars,

156
00:09:20,440 --> 00:09:22,760
Speaker 1: it gets reported both to the FTC and to the

157
00:09:22,800 --> 00:09:25,280
Speaker 1: Anti Trust Division, and we can figure out is this

158
00:09:25,320 --> 00:09:29,079
Speaker 1: an anti competitive transaction? Is this basically going to reduce competition?

159
00:09:30,200 --> 00:09:32,960
Speaker 1: And then we can also look at companies business tactics,

160
00:09:33,080 --> 00:09:36,800
Speaker 1: especially you know, if they've become monopolies or are kind

161
00:09:36,840 --> 00:09:40,520
Speaker 1: of using their dominance in illegal ways, and so we

162
00:09:40,520 --> 00:09:44,600
Speaker 1: can bring lawsuits. We can also issue rules, and we've

163
00:09:44,640 --> 00:09:47,840
Speaker 1: been very active in issuing rules, including in areas like

164
00:09:48,559 --> 00:09:54,560
Speaker 1: fake reviews, you know, taking on things like government impostors.

165
00:09:55,360 --> 00:09:58,200
Speaker 1: We just finalized a rule taking on junk fees in

166
00:09:58,240 --> 00:10:02,240
Speaker 1: the economy. These you know, hidden fees that companies just

167
00:10:02,320 --> 00:10:04,920
Speaker 1: show at the very end that you don't know what

168
00:10:04,960 --> 00:10:08,440
Speaker 1: you're exactly paying for, but suddenly the price of the

169
00:10:08,480 --> 00:10:11,520
Speaker 1: ticket is almost doubled and you have no choice, and

170
00:10:11,600 --> 00:10:14,280
Speaker 1: so we've issued a series of rules, we've brought a

171
00:10:14,320 --> 00:10:18,040
Speaker 1: series of lawsuits. We can also do various studies of

172
00:10:18,160 --> 00:10:21,360
Speaker 1: the market, including in areas where things are moving very quickly.

173
00:10:21,920 --> 00:10:25,160
Speaker 1: So we a few months ago launched a study into

174
00:10:25,160 --> 00:10:29,040
Speaker 1: surveillance pricing, this idea that firms could be charging every

175
00:10:29,080 --> 00:10:33,160
Speaker 1: single individual a standalone price based on the data they

176
00:10:33,200 --> 00:10:35,200
Speaker 1: have on you. So these are just some of the

177
00:10:35,200 --> 00:10:36,560
Speaker 1: tools and authorities we have.

178
00:10:47,400 --> 00:10:50,640
Speaker 2: So let's still call official intelligence. From a regulatory perspective,

179
00:10:51,040 --> 00:10:52,439
Speaker 2: what are your major concerns.

180
00:10:53,679 --> 00:10:56,040
Speaker 1: So the biggest concern for me, just right at the

181
00:10:56,040 --> 00:10:59,520
Speaker 1: beginning was making sure we were making very very clear

182
00:11:00,160 --> 00:11:03,800
Speaker 1: to the market that there was no AI exemption from

183
00:11:03,800 --> 00:11:06,280
Speaker 1: the laws on the books. And this can sound like

184
00:11:06,320 --> 00:11:09,440
Speaker 1: a basic point, but it seemed incredibly important because we

185
00:11:09,559 --> 00:11:13,760
Speaker 1: have seen, especially when new technologies come onto the market,

186
00:11:14,120 --> 00:11:17,000
Speaker 1: we can see an effort by firms to say, Okay,

187
00:11:17,000 --> 00:11:19,679
Speaker 1: sure you have these age old laws on the books,

188
00:11:20,160 --> 00:11:24,079
Speaker 1: but this new technology is different, and that means these

189
00:11:24,160 --> 00:11:27,600
Speaker 1: laws don't apply or they have to apply in dramatically

190
00:11:27,640 --> 00:11:31,120
Speaker 1: different ways. And it's really important for enforcers to hear

191
00:11:31,160 --> 00:11:33,880
Speaker 1: out those arguments, you know, make sure we understand how

192
00:11:33,880 --> 00:11:37,520
Speaker 1: the technologies are working, but not get so dazzled by

193
00:11:37,559 --> 00:11:40,559
Speaker 1: the novelty to say, okay, well, I guess we can

194
00:11:40,600 --> 00:11:46,120
Speaker 1: totally abandon our core laws and suddenly we're saying, okay,

195
00:11:46,720 --> 00:11:49,920
Speaker 1: fraud is illegal, but if you do fraud with AI

196
00:11:50,200 --> 00:11:53,720
Speaker 1: sometimes somehow that's okay. Right, That's not a position we

197
00:11:53,760 --> 00:11:54,320
Speaker 1: want to be in.

198
00:11:54,480 --> 00:11:57,840
Speaker 2: Companies are making like that kind of argument. They were

199
00:11:57,840 --> 00:12:01,000
Speaker 2: attempted to sites that, not that specifically, but they trying

200
00:12:01,040 --> 00:12:01,400
Speaker 2: to dodge.

201
00:12:03,200 --> 00:12:05,760
Speaker 1: Yeah, we do see arguments that, you know, the traditional

202
00:12:05,880 --> 00:12:11,280
Speaker 1: laws around unfair practices or deceptive practices applied differently. The

203
00:12:11,360 --> 00:12:14,200
Speaker 1: other big thing is, you know, America has been so

204
00:12:14,320 --> 00:12:20,239
Speaker 1: fortunate to be such a key home of breakthrough innovations historically,

205
00:12:20,840 --> 00:12:23,640
Speaker 1: and to my mind, a key ingredient of that has

206
00:12:23,720 --> 00:12:28,400
Speaker 1: been making sure we have fair competitive markets where you

207
00:12:28,480 --> 00:12:32,160
Speaker 1: actually do have somebody with a great new idea, an

208
00:12:32,280 --> 00:12:35,120
Speaker 1: upstart that's able to come in, that's able to fairly

209
00:12:35,200 --> 00:12:39,440
Speaker 1: compete and knock out the incumbents. That's how historically we

210
00:12:39,520 --> 00:12:44,000
Speaker 1: have gotten real major technological progress in our country. And

211
00:12:44,280 --> 00:12:46,280
Speaker 1: what I wanted to make sure we were being very

212
00:12:46,280 --> 00:12:50,679
Speaker 1: clear eyed about is the risk of a few large

213
00:12:50,760 --> 00:12:54,960
Speaker 1: dominant incumbents locking in the market in a way that

214
00:12:55,160 --> 00:12:58,080
Speaker 1: shuts out a lot of that innovation and a lot

215
00:12:58,120 --> 00:13:03,080
Speaker 1: of that next generation breakthrough that historically we've seen come

216
00:13:03,280 --> 00:13:07,480
Speaker 1: purely from fair competition and open markets. So it was

217
00:13:07,520 --> 00:13:10,680
Speaker 1: about wanting to make sure that companies are not using

218
00:13:10,679 --> 00:13:15,000
Speaker 1: their existing heft to immediately lock up the market and

219
00:13:15,640 --> 00:13:18,560
Speaker 1: shut out the innovation that we should be able to see.

220
00:13:19,960 --> 00:13:22,719
Speaker 2: So, with that in mind, are you worried about the

221
00:13:22,760 --> 00:13:25,800
Speaker 2: consolidation we're seeing right now in the generative AI market?

222
00:13:25,840 --> 00:13:29,520
Speaker 2: Because to build these models, the foundation models like Claude

223
00:13:29,559 --> 00:13:32,400
Speaker 2: three or GPT or LAMA or what have you, it

224
00:13:32,440 --> 00:13:36,600
Speaker 2: requires financial heft. How do you avoid the monopoly that

225
00:13:36,679 --> 00:13:38,760
Speaker 2: naturally comes out of the fact that you need billions

226
00:13:38,760 --> 00:13:40,920
Speaker 2: and billions of dollars to even make one of these.

227
00:13:42,520 --> 00:13:45,680
Speaker 1: Yeah, it's a key question, and one approach that we've

228
00:13:45,720 --> 00:13:50,560
Speaker 1: taken is making sure that we are actually going layer

229
00:13:50,679 --> 00:13:53,880
Speaker 1: by layer in the market. Right, And so you want

230
00:13:53,880 --> 00:13:58,080
Speaker 1: to understand, Okay, what's happening with chips, what's happening with

231
00:13:58,240 --> 00:14:02,320
Speaker 1: cloud and compute, what's happening with the models. You want

232
00:14:02,320 --> 00:14:06,320
Speaker 1: to understand what are the key economic properties of each

233
00:14:06,720 --> 00:14:10,720
Speaker 1: point in the stack and then understand, Okay, do we

234
00:14:10,800 --> 00:14:16,000
Speaker 1: see this consolidation purely because they're such high fixed costs

235
00:14:16,160 --> 00:14:20,240
Speaker 1: and you know, that's just going to be the state

236
00:14:20,280 --> 00:14:23,200
Speaker 1: of the market. And how do we make sure that

237
00:14:23,280 --> 00:14:26,320
Speaker 1: the degree you do have dominant players in some of

238
00:14:26,320 --> 00:14:30,440
Speaker 1: these layers, they're not using that dominance to then squelch

239
00:14:30,560 --> 00:14:33,760
Speaker 1: out competition in a layer where you should actually be

240
00:14:33,840 --> 00:14:38,080
Speaker 1: able to see more innovation, more competition. And so we're

241
00:14:38,120 --> 00:14:42,600
Speaker 1: looking at, for example, some of the partnerships and investments

242
00:14:43,000 --> 00:14:49,160
Speaker 1: between the big cloud providers and some of the newer firms. Famously,

243
00:14:49,240 --> 00:14:53,000
Speaker 1: you know, the Microsoft Open Ai partnership. Amazon and Google

244
00:14:53,080 --> 00:14:56,160
Speaker 1: have also made some investments, and we want to understand,

245
00:14:56,160 --> 00:15:00,280
Speaker 1: you know, are these truly kind of independent companies. Are

246
00:15:00,280 --> 00:15:03,320
Speaker 1: these able to be independent firms in terms of the

247
00:15:03,360 --> 00:15:07,520
Speaker 1: competitive decision making some of the key strategic calls when

248
00:15:07,640 --> 00:15:11,200
Speaker 1: so much investment is being made. What is the structure

249
00:15:11,240 --> 00:15:14,040
Speaker 1: of the contracts, What are some of the key requirements?

250
00:15:15,000 --> 00:15:18,120
Speaker 1: Are there kind of interlocking director it's here in ways

251
00:15:18,160 --> 00:15:22,960
Speaker 1: that create conflicts that are problematic? Are there contractual you know,

252
00:15:23,120 --> 00:15:26,600
Speaker 1: tying provisions here? So that's just the universe of what

253
00:15:26,640 --> 00:15:29,080
Speaker 1: we're looking at, But of course, it's a fast moving

254
00:15:29,720 --> 00:15:32,920
Speaker 1: market and we're very fortunate to have just top tier

255
00:15:33,160 --> 00:15:36,800
Speaker 1: technological talent in house to be letting us push forward here.

256
00:15:37,280 --> 00:15:42,280
Speaker 2: So consolidation is a concern though in general of AI, it's.

257
00:15:42,120 --> 00:15:44,640
Speaker 1: Certainly something we have to be vigilant about to make

258
00:15:44,720 --> 00:15:47,920
Speaker 1: sure that to the degree we do see you know,

259
00:15:48,160 --> 00:15:52,520
Speaker 1: monopolies or firms with enormous market power, we want to

260
00:15:52,560 --> 00:15:56,960
Speaker 1: make sure a that that's not being achieved through illegal tactics,

261
00:15:57,800 --> 00:16:00,920
Speaker 1: or that it's not being used illegal to snuff out

262
00:16:00,920 --> 00:16:04,000
Speaker 1: competition somewhere else. So that's incredibly important.

263
00:16:04,840 --> 00:16:07,920
Speaker 2: How about the training data situation, because that feels like

264
00:16:07,960 --> 00:16:10,120
Speaker 2: a mixture of different parts of the government be involved,

265
00:16:10,120 --> 00:16:14,240
Speaker 2: but that also feels like a massive anti competitive issue.

266
00:16:14,320 --> 00:16:16,840
Speaker 2: Is this something the FTC is looking into or would

267
00:16:16,880 --> 00:16:20,720
Speaker 2: have to partner with other parts of the government potentially, So.

268
00:16:20,640 --> 00:16:23,720
Speaker 1: We are looking into it. Actually, last year we convened

269
00:16:23,720 --> 00:16:27,760
Speaker 1: a roundtable with creators from all sorts of different sectors.

270
00:16:27,760 --> 00:16:34,000
Speaker 1: So we had you know, artists, authors, graphic designers, even

271
00:16:34,160 --> 00:16:40,320
Speaker 1: people who work in fashion sharing how their core creations

272
00:16:40,400 --> 00:16:44,200
Speaker 1: had actually already been scraped in many instances and suddenly

273
00:16:44,240 --> 00:16:47,480
Speaker 1: they were waking up where their life's creation having been

274
00:16:47,680 --> 00:16:50,800
Speaker 1: ingested by this machine and spitting out outcomes that they

275
00:16:50,840 --> 00:16:53,840
Speaker 1: had never consented to and suddenly felt like they had

276
00:16:53,840 --> 00:16:56,600
Speaker 1: no control over. And so that's something we've heard a

277
00:16:56,600 --> 00:17:00,680
Speaker 1: lot about. Interestingly, these creators, many of them were acknowledging

278
00:17:00,720 --> 00:17:04,480
Speaker 1: that these technologies could be quite fruitful for them as well.

279
00:17:04,640 --> 00:17:08,720
Speaker 1: They're not kind of reflexively and viscerally anti AI. It's

280
00:17:08,760 --> 00:17:11,919
Speaker 1: really about wanting to make sure that the terms on

281
00:17:12,000 --> 00:17:16,440
Speaker 1: which their creations are being used, that those are actually

282
00:17:16,480 --> 00:17:20,000
Speaker 1: fairly negotiated and it's not some type of opt out

283
00:17:20,080 --> 00:17:23,280
Speaker 1: model after the fact that they actually should be able

284
00:17:23,359 --> 00:17:27,200
Speaker 1: to consent, that they should actually be getting compensation that's

285
00:17:27,320 --> 00:17:29,480
Speaker 1: you know, can measure it with the value of what

286
00:17:29,520 --> 00:17:32,800
Speaker 1: they're getting. So that's a lot of concerns we've heard.

287
00:17:34,040 --> 00:17:37,720
Speaker 1: The FTC submitted a comment to the Copyright Office, which

288
00:17:37,720 --> 00:17:40,639
Speaker 1: is considering some of these issues, kind of relaying what

289
00:17:40,640 --> 00:17:44,240
Speaker 1: we had heard, and so it's certainly a live issue,

290
00:17:44,280 --> 00:17:47,080
Speaker 1: and to the extent the FTC can share expertise on it,

291
00:17:47,119 --> 00:17:48,199
Speaker 1: we've been looking to do that.

292
00:17:49,040 --> 00:17:52,439
Speaker 2: So Generati is being crammed into every tech product. Do

293
00:17:52,480 --> 00:17:55,120
Speaker 2: you see any potential for consumer homes from this happening.

294
00:17:57,680 --> 00:18:01,680
Speaker 1: Well, generally, we've brought a set of lawsuits that fall

295
00:18:01,720 --> 00:18:05,080
Speaker 1: into a few categories. One of the big categories is

296
00:18:05,280 --> 00:18:09,520
Speaker 1: around this idea of AI hype. So as more and

297
00:18:09,560 --> 00:18:14,840
Speaker 1: more products are adopting generative AI services, they're making oftentimes

298
00:18:15,280 --> 00:18:19,840
Speaker 1: commitments or promises about what these services can actually deliver,

299
00:18:20,520 --> 00:18:26,040
Speaker 1: and sometimes we see that those claims are inflated. And

300
00:18:26,119 --> 00:18:29,240
Speaker 1: so you know, for example, the FTC a few months

301
00:18:29,280 --> 00:18:34,240
Speaker 1: ago brought a whole sweep of enforcement actions against for example,

302
00:18:34,280 --> 00:18:37,359
Speaker 1: a company that was claiming to be the world's first

303
00:18:37,440 --> 00:18:41,240
Speaker 1: robot lawyer. Do not pay, but the product fail to

304
00:18:41,280 --> 00:18:44,200
Speaker 1: live up to its claims that the service could substitute

305
00:18:44,240 --> 00:18:47,200
Speaker 1: for the expertise of a human lawyer. Now, don't get

306
00:18:47,200 --> 00:18:49,919
Speaker 1: me wrong. To the extent that these types of services

307
00:18:49,960 --> 00:18:54,600
Speaker 1: and advances can bring things like way low cost legal

308
00:18:54,640 --> 00:18:57,679
Speaker 1: services to people, that's a great thing. But just we

309
00:18:57,800 --> 00:19:01,680
Speaker 1: want to make sure companies are not inflating or hyping

310
00:19:02,000 --> 00:19:06,840
Speaker 1: or falsely overstating what those services can actually do. So

311
00:19:06,920 --> 00:19:09,480
Speaker 1: that's been a big strain of the cases that we've

312
00:19:09,520 --> 00:19:10,760
Speaker 1: brought so far in this area.

313
00:19:12,119 --> 00:19:15,280
Speaker 2: So do you see any anti competitive issues in the

314
00:19:15,280 --> 00:19:18,480
Speaker 2: cloud in the compute industry in general, even outside of AI,

315
00:19:18,920 --> 00:19:21,120
Speaker 2: because it really is just a few big players.

316
00:19:23,480 --> 00:19:26,960
Speaker 1: It is. Yeah, it is a relatively small number of firms.

317
00:19:27,720 --> 00:19:31,359
Speaker 1: The FTC did do a inquiry here. We got a

318
00:19:31,400 --> 00:19:35,000
Speaker 1: lot of comments and some of the complaints that we

319
00:19:35,080 --> 00:19:39,120
Speaker 1: heard about focused on things like how easy is it

320
00:19:39,240 --> 00:19:45,960
Speaker 1: to exit the cloud service and transfer your data elsewhere?

321
00:19:46,440 --> 00:19:50,359
Speaker 1: And are you having to play pay these egress fees

322
00:19:51,520 --> 00:19:55,960
Speaker 1: to the cloud providers in ways that inhibits, you know, switching.

323
00:19:57,280 --> 00:20:00,679
Speaker 1: We also heard just more generally about some of the

324
00:20:00,760 --> 00:20:05,520
Speaker 1: software licensing practices, where some people suggested that some of

325
00:20:05,520 --> 00:20:10,200
Speaker 1: the cloud providers limit their ability to use certain software

326
00:20:10,240 --> 00:20:14,080
Speaker 1: in other cloud infrastructure provider environments, so that you can

327
00:20:14,119 --> 00:20:16,800
Speaker 1: imagine could lead to lock in, or if one cloud

328
00:20:16,800 --> 00:20:21,720
Speaker 1: provider is effectively degrading the ability to use other third

329
00:20:21,760 --> 00:20:25,320
Speaker 1: party softwares on that cloud, you could see some issues there.

330
00:20:26,359 --> 00:20:29,399
Speaker 1: And then we also heard some concerns that some provisions

331
00:20:29,400 --> 00:20:34,040
Speaker 1: in cloud computing contracts could be incentivizing customers to consolidate

332
00:20:34,119 --> 00:20:37,479
Speaker 1: their use of cloud services to just one provider that

333
00:20:37,520 --> 00:20:42,399
Speaker 1: could further hasten consolidation. More generally, we looked at this

334
00:20:42,640 --> 00:20:45,119
Speaker 1: not just from the competition lens, but also from a

335
00:20:45,200 --> 00:20:48,919
Speaker 1: resiliency lens. I think we've all seen how when you

336
00:20:49,040 --> 00:20:53,119
Speaker 1: have extreme centralization that can also create a lot of

337
00:20:53,119 --> 00:20:56,480
Speaker 1: fragility where you have a single point of failure, right,

338
00:20:56,520 --> 00:21:00,240
Speaker 1: And we've seen how if a single data of a

339
00:21:00,640 --> 00:21:04,000
Speaker 1: center somewhere goes out, sometimes a corner of the Internet

340
00:21:04,080 --> 00:21:06,480
Speaker 1: also goes out. And so how do we make sure

341
00:21:06,480 --> 00:21:10,600
Speaker 1: we're also thinking about the resiliency element here. And then

342
00:21:10,600 --> 00:21:13,639
Speaker 1: they're kind of similar data security concerns as well that

343
00:21:13,680 --> 00:21:14,320
Speaker 1: we heard about.

344
00:21:29,000 --> 00:21:33,120
Speaker 2: So you've been a nonmeditorializing here attacked I would describe

345
00:21:33,119 --> 00:21:34,960
Speaker 2: some of the clammiest men alive. A lot of people

346
00:21:35,000 --> 00:21:37,919
Speaker 2: in bench capital and within tech have come for you.

347
00:21:38,000 --> 00:21:40,720
Speaker 2: How do you deal with that? How's that affected you?

348
00:21:44,240 --> 00:21:47,320
Speaker 1: So as a general matter, you know, I focus on

349
00:21:48,280 --> 00:21:52,160
Speaker 1: making sure we're hearing from Americans across the country. And

350
00:21:52,359 --> 00:21:55,760
Speaker 1: sometimes it's very easy in these jobs to actually become

351
00:21:55,880 --> 00:21:59,520
Speaker 1: very insulated and only hear from the people who have

352
00:21:59,640 --> 00:22:02,360
Speaker 1: access us to power or kind of know you know,

353
00:22:03,200 --> 00:22:05,399
Speaker 1: where to be ranting in a way that it gets

354
00:22:05,480 --> 00:22:09,679
Speaker 1: to public enforcers very easily. So it's really about just

355
00:22:09,720 --> 00:22:14,679
Speaker 1: making sure that you're keeping good perspective, keeping a broad

356
00:22:14,760 --> 00:22:18,160
Speaker 1: purview of who it is that we serve. So we've

357
00:22:18,160 --> 00:22:21,080
Speaker 1: done listening sessions across the country, for example, going to

358
00:22:21,160 --> 00:22:26,879
Speaker 1: places like Baraboo, Wisconsin or Aimes, Iowa, hearing from you know,

359
00:22:27,080 --> 00:22:29,679
Speaker 1: the gig drivers that use some of these ride sharing

360
00:22:29,720 --> 00:22:33,879
Speaker 1: platforms to understand what are they seeing, what is their experience.

361
00:22:34,760 --> 00:22:37,000
Speaker 1: We talk to a lot of farmers who are concerned

362
00:22:37,000 --> 00:22:40,560
Speaker 1: about the ability to repair their own tractors and why

363
00:22:40,600 --> 00:22:44,680
Speaker 1: there's been you know, increasing friction there and so keeping

364
00:22:44,840 --> 00:22:48,480
Speaker 1: just a broader set of voices in mind as we're

365
00:22:48,520 --> 00:22:52,600
Speaker 1: making our decisions, I think has been incredibly important to

366
00:22:52,800 --> 00:22:56,399
Speaker 1: just keep a north star that's properly focused on, you know,

367
00:22:56,480 --> 00:23:00,040
Speaker 1: the public as a whole, rather than a handful of

368
00:23:00,040 --> 00:23:04,640
Speaker 1: of well resourced, well connected individuals that can sometimes have

369
00:23:04,680 --> 00:23:07,680
Speaker 1: an outsized role in policy decisions.

370
00:23:09,080 --> 00:23:11,399
Speaker 2: So what do you think, what are some of the

371
00:23:11,440 --> 00:23:14,000
Speaker 2: big wins? What the ones you're most proud of in

372
00:23:14,040 --> 00:23:14,440
Speaker 2: your time?

373
00:23:15,480 --> 00:23:20,280
Speaker 1: Well, because of the FTC's work, Americans saw the cost

374
00:23:20,320 --> 00:23:23,320
Speaker 1: of inhalers go down from hundreds of dollars just just

375
00:23:23,440 --> 00:23:27,639
Speaker 1: thirty five dollars. In the digital space, you know, we've

376
00:23:27,840 --> 00:23:30,760
Speaker 1: really helped set new rules of the road. I mean,

377
00:23:30,800 --> 00:23:33,840
Speaker 1: one trend that we've seen is as more companies have

378
00:23:34,960 --> 00:23:40,439
Speaker 1: become reliant on service based revenues, they've introduced subscriptions and

379
00:23:40,480 --> 00:23:43,679
Speaker 1: become much more reliant on subscription revenue, and so we

380
00:23:44,160 --> 00:23:46,639
Speaker 1: see firms make it very easy to sign up for

381
00:23:46,680 --> 00:23:51,440
Speaker 1: a subscription, but then extraordinarily difficult to cancel. We brought

382
00:23:51,440 --> 00:23:54,840
Speaker 1: a whole bunch of lawsuits, including against Amazon, including against

383
00:23:54,920 --> 00:24:01,000
Speaker 1: Adobe for their illegal subscription practices that were awarding Americans

384
00:24:01,000 --> 00:24:04,560
Speaker 1: from being able to cancel in ways that resulted in people,

385
00:24:04,760 --> 00:24:08,320
Speaker 1: you know, overpaying for months and months. We had people

386
00:24:08,359 --> 00:24:11,000
Speaker 1: tell us the only way I could cancel my subscription

387
00:24:11,160 --> 00:24:13,639
Speaker 1: was to cancel my credit card, right, I mean, just

388
00:24:13,760 --> 00:24:18,320
Speaker 1: deeply anti anti consumer practices. We also finalized a rule

389
00:24:18,560 --> 00:24:21,840
Speaker 1: that will go into effect next year such that all

390
00:24:21,840 --> 00:24:24,199
Speaker 1: companies would have to make it as easy to cancel

391
00:24:24,240 --> 00:24:26,520
Speaker 1: a subscription as it is to sign up for one.

392
00:24:26,920 --> 00:24:29,760
Speaker 1: We've also been very active in taking on data brokers.

393
00:24:30,480 --> 00:24:32,400
Speaker 1: You know, there's been a wild wild West out there

394
00:24:32,440 --> 00:24:36,880
Speaker 1: and how people's personal information is bought and sold, and

395
00:24:37,000 --> 00:24:39,480
Speaker 1: we've brought a whole set of law enforcement actions when

396
00:24:39,640 --> 00:24:44,200
Speaker 1: data brokers are illegally using or collecting people's health data.

397
00:24:45,119 --> 00:24:51,280
Speaker 1: People's precise geolocation data, sensitive data like browsing data. Just

398
00:24:51,320 --> 00:24:54,520
Speaker 1: to make clear that the default assumption is not that

399
00:24:55,000 --> 00:24:57,720
Speaker 1: all of this sensitive data can be bought and sold

400
00:24:58,200 --> 00:25:02,480
Speaker 1: even if people have not affirmative given permission. We just

401
00:25:02,560 --> 00:25:06,320
Speaker 1: brought the other week two cases against significant data brokers

402
00:25:06,600 --> 00:25:09,480
Speaker 1: Mobile Walla and Gravy Analytics for some of their illegal

403
00:25:09,520 --> 00:25:13,920
Speaker 1: practices involving geolocation data. The Mobile Walla case was especially

404
00:25:13,960 --> 00:25:18,520
Speaker 1: interesting to my mind because it involved account about real

405
00:25:18,560 --> 00:25:21,720
Speaker 1: time bidding data, and there's been all this research suggesting

406
00:25:21,760 --> 00:25:25,320
Speaker 1: that the online auctions of real time bidding end up

407
00:25:25,359 --> 00:25:30,080
Speaker 1: exposing people sensitive data, and we brought a case noting

408
00:25:30,160 --> 00:25:34,520
Speaker 1: that that exposure could be you know, and companies using

409
00:25:34,520 --> 00:25:39,040
Speaker 1: the real time bidding data unlawfully is problematic. And so

410
00:25:39,400 --> 00:25:41,359
Speaker 1: those have been, you know, some of the advances that

411
00:25:41,359 --> 00:25:42,919
Speaker 1: we've made.

412
00:25:43,240 --> 00:25:47,320
Speaker 2: So you were confirmed with broad bipartisan support. Jadie Vance

413
00:25:47,320 --> 00:25:50,200
Speaker 2: spoke fondly of you. Do you have hope that your

414
00:25:50,280 --> 00:25:52,200
Speaker 2: kind of your legacy continues in some level?

415
00:25:54,119 --> 00:25:56,720
Speaker 1: Well, I can't predict what the future holds. I do

416
00:25:56,880 --> 00:26:01,280
Speaker 1: know that there has been strong bipartisan support for taking

417
00:26:01,280 --> 00:26:06,440
Speaker 1: on unchecked private power. That's true in technology markets. That's

418
00:26:06,480 --> 00:26:10,520
Speaker 1: been especially true when it involves people's privacy, when it

419
00:26:10,600 --> 00:26:14,760
Speaker 1: involves kids privacy. I think we've seen, you know, people

420
00:26:14,840 --> 00:26:19,520
Speaker 1: recognize that if you're freaked out by unlawful surveillance when

421
00:26:19,520 --> 00:26:22,200
Speaker 1: the government does it, you should also be freaked out

422
00:26:22,280 --> 00:26:26,159
Speaker 1: by surveillance when private companies do it, because the the

423
00:26:26,280 --> 00:26:28,840
Speaker 1: you know, the line there can be quite porous. And

424
00:26:28,920 --> 00:26:30,800
Speaker 1: so I do think there are a set of areas

425
00:26:30,840 --> 00:26:34,879
Speaker 1: where there is strong bipartisan concern and commitment to taking

426
00:26:34,920 --> 00:26:39,240
Speaker 1: on corporate law breaking, and so I hope that will continue.

427
00:26:39,400 --> 00:26:42,360
Speaker 2: All right, One last question, So right now, I would

428
00:26:42,440 --> 00:26:44,960
Speaker 2: describe the mood is not great out. I think the

429
00:26:44,960 --> 00:26:47,040
Speaker 2: people are feeling a little dark. Feels like the ultra

430
00:26:47,080 --> 00:26:49,800
Speaker 2: wealthy are kind of gating speed and seeping into the government.

431
00:26:50,400 --> 00:26:52,040
Speaker 2: What would you tell people to give them hope?

432
00:26:53,000 --> 00:26:56,199
Speaker 1: Ooof's a that's a tough one. I mean, you know,

433
00:26:57,280 --> 00:27:00,359
Speaker 1: I'm a patriot, you know, I really believe in America.

434
00:27:00,600 --> 00:27:04,840
Speaker 1: I think there have been moments before where the path

435
00:27:04,880 --> 00:27:08,240
Speaker 1: ahead was not clear. And one approach that I've taken

436
00:27:08,320 --> 00:27:12,320
Speaker 1: to this job is there are no inevitable outcomes, right,

437
00:27:12,480 --> 00:27:15,080
Speaker 1: be it in terms of how our markets evolve, be

438
00:27:15,160 --> 00:27:17,520
Speaker 1: it in terms of what our government does or doesn't do,

439
00:27:18,320 --> 00:27:23,000
Speaker 1: and how people in positions like at the FTC at

440
00:27:23,520 --> 00:27:27,920
Speaker 1: have huge consequences for you know, whether you have markets

441
00:27:27,960 --> 00:27:30,399
Speaker 1: that are premised on on check surveillance or whether you

442
00:27:30,440 --> 00:27:34,479
Speaker 1: can imagine people's data and privacy being protected right. There

443
00:27:34,520 --> 00:27:37,080
Speaker 1: can sometimes be an effort to say, well, there's just

444
00:27:37,160 --> 00:27:41,960
Speaker 1: this inevitable march of technological progress where outcomes are sort

445
00:27:41,960 --> 00:27:44,639
Speaker 1: of already baked, and I don't believe that. I think

446
00:27:45,040 --> 00:27:47,560
Speaker 1: how we use our laws, how we use our policies,

447
00:27:47,640 --> 00:27:51,480
Speaker 1: is incredibly important. A priority for me at the FTC

448
00:27:51,600 --> 00:27:55,360
Speaker 1: has been to engage with the public and that's partly

449
00:27:55,440 --> 00:27:57,359
Speaker 1: so that we hear from them, partly so that we

450
00:27:57,400 --> 00:27:59,800
Speaker 1: share with them what we're doing, but it's also to

451
00:27:59,840 --> 00:28:02,840
Speaker 1: me make sure that people know that they can hold

452
00:28:02,960 --> 00:28:06,359
Speaker 1: future people at the FTC accountable as well for what

453
00:28:06,480 --> 00:28:09,760
Speaker 1: decisions are not being made. So I think we've seen

454
00:28:10,760 --> 00:28:13,760
Speaker 1: you know that having a strong government that's focused on

455
00:28:13,840 --> 00:28:17,240
Speaker 1: protecting people is important and people should be expecting that.

456
00:28:18,320 --> 00:28:20,720
Speaker 2: Lena, thank you so much for joining me. It's been

457
00:28:20,760 --> 00:28:23,679
Speaker 2: such a pleasure to have you. Thank you for doing this.

458
00:28:24,960 --> 00:28:25,600
Speaker 1: Thanks so much.

459
00:28:26,359 --> 00:28:28,879
Speaker 2: You've been listening to better Offline, Neil, You've got to

460
00:28:28,920 --> 00:28:31,679
Speaker 2: name my own podcast day. Lena Khan, Chair of the FTC,

461
00:28:31,880 --> 00:28:42,240
Speaker 2: thank you so much for listening. Everyone, Thank you for

462
00:28:42,280 --> 00:28:44,960
Speaker 2: listening to Better Offline. The editor and composer of the

463
00:28:44,960 --> 00:28:48,080
Speaker 2: Better Offline theme song is Matasowski. You can check out

464
00:28:48,080 --> 00:28:51,560
Speaker 2: more of his music and audio projects at Matasowski dot com,

465
00:28:51,920 --> 00:28:55,240
Speaker 2: M A T T O S O W s ki

466
00:28:55,640 --> 00:28:58,520
Speaker 2: dot com. You can email me at easy at Better

467
00:28:58,520 --> 00:29:01,280
Speaker 2: Offline dot com or visit offline dot com to find

468
00:29:01,280 --> 00:29:04,200
Speaker 2: more podcast links and of course, my newsletter. I also

469
00:29:04,600 --> 00:29:07,160
Speaker 2: really recommend you go to chat dot where'soead dot at

470
00:29:07,160 --> 00:29:09,600
Speaker 2: to visit the discord, and go to our slash Better

471
00:29:09,640 --> 00:29:12,800
Speaker 2: Offline to check out I'll Reddit. Thank you so much

472
00:29:12,840 --> 00:29:13,360
Speaker 2: for listening.

473
00:29:14,200 --> 00:29:16,880
Speaker 1: Better Offline is a production of cool Zone Media. For

474
00:29:17,000 --> 00:29:20,160
Speaker 1: more from cool Zone Media, visit our website cool Zonemedia

475
00:29:20,240 --> 00:29:23,040
Speaker 1: dot com, or check us out on the iHeartRadio app,

476
00:29:23,120 --> 00:29:25,800
Speaker 1: Apple Podcasts, or wherever you get your podcasts.