1 00:00:02,440 --> 00:00:06,800 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:07,160 --> 00:00:08,960 Speaker 2: You just got out of speaking with the folks at 3 00:00:09,080 --> 00:00:11,719 Speaker 2: Y Combinator. Talk to us a little bit about who 4 00:00:11,800 --> 00:00:13,560 Speaker 2: you're speaking to and why you're here. 5 00:00:13,600 --> 00:00:14,440 Speaker 1: What's the message. 6 00:00:15,280 --> 00:00:17,720 Speaker 3: Well, thanks so much for having me, Emily, And an 7 00:00:17,720 --> 00:00:21,000 Speaker 3: important part of my job is going around the country 8 00:00:21,160 --> 00:00:25,880 Speaker 3: and hearing from Americans across markets, across sectors to understand 9 00:00:25,920 --> 00:00:28,400 Speaker 3: what are the pain points that they're seeing in the 10 00:00:28,440 --> 00:00:32,400 Speaker 3: markets that they're trying to work in, compete in, buy in. 11 00:00:32,920 --> 00:00:34,680 Speaker 3: And so I'm so glad to be here in San 12 00:00:34,680 --> 00:00:39,480 Speaker 3: Francisco meeting with folks across the tech community, including founders, 13 00:00:39,560 --> 00:00:43,839 Speaker 3: including vcs, including startups, and trying to understand, you know, 14 00:00:43,920 --> 00:00:46,680 Speaker 3: how do we make sure that our free and fair 15 00:00:47,040 --> 00:00:52,040 Speaker 3: enterprise system can remain robust and that innovation and competition 16 00:00:52,120 --> 00:00:56,080 Speaker 3: can thrive, especially at this moment of technological change and 17 00:00:56,200 --> 00:00:57,600 Speaker 3: a potential inflection point. 18 00:00:58,600 --> 00:01:01,120 Speaker 2: Obviously, how AI will play out is very much top 19 00:01:01,160 --> 00:01:04,160 Speaker 2: of mind here. I just spoke with Meta CEO Mark Zuckerberg, 20 00:01:04,160 --> 00:01:08,400 Speaker 2: who unveiled the largest open source AI model ever this week, 21 00:01:08,440 --> 00:01:10,920 Speaker 2: and really double down on what he thinks are the 22 00:01:10,959 --> 00:01:13,800 Speaker 2: benefits of the open source approach. Take a listen to 23 00:01:13,840 --> 00:01:14,600 Speaker 2: what he had to say. 24 00:01:15,440 --> 00:01:17,600 Speaker 1: The way that we can control our own destiny on 25 00:01:17,640 --> 00:01:19,440 Speaker 1: this and make sure that we have access to leading 26 00:01:19,480 --> 00:01:23,119 Speaker 1: AI is by building it and having it become an 27 00:01:23,120 --> 00:01:26,720 Speaker 1: industry's standard. But it actually gets stronger by being able 28 00:01:26,720 --> 00:01:29,080 Speaker 1: to share it and have the ecosystem around it. 29 00:01:31,000 --> 00:01:34,560 Speaker 2: Where do you stand cher con on Meta's open approach 30 00:01:34,720 --> 00:01:37,680 Speaker 2: versus closed source competitors like open AI and Google and 31 00:01:38,040 --> 00:01:42,240 Speaker 2: Zuckerberg's remark specifically, well, look, without. 32 00:01:42,400 --> 00:01:45,559 Speaker 3: Weighing in on any specific company. As a general matter, 33 00:01:45,800 --> 00:01:49,640 Speaker 3: historically we've seen that openness and open source can be 34 00:01:49,720 --> 00:01:52,920 Speaker 3: a critical vector of innovation, right. I mean, what happens 35 00:01:52,920 --> 00:01:56,559 Speaker 3: traditionally when you render some of these ecosystems more open 36 00:01:56,960 --> 00:01:59,720 Speaker 3: is that it can lower barriers to entry, It can 37 00:01:59,760 --> 00:02:04,560 Speaker 3: lower costs for entrepreneurs and startups and really enable them 38 00:02:04,600 --> 00:02:07,600 Speaker 3: to innovate much more freely. And so we want to 39 00:02:07,600 --> 00:02:12,440 Speaker 3: make sure that that tradition continues. We are watching very closely. 40 00:02:12,480 --> 00:02:15,679 Speaker 3: I think there's still an open question around what openness 41 00:02:15,720 --> 00:02:19,200 Speaker 3: really means in the AI context. Our team has been 42 00:02:19,200 --> 00:02:23,160 Speaker 3: focusing on this idea of open weight models, which we 43 00:02:23,280 --> 00:02:27,160 Speaker 3: think could similarly engender a lot of competition and innovation 44 00:02:27,360 --> 00:02:30,840 Speaker 3: and make it easier for startups and entrepreneurs to compete 45 00:02:30,919 --> 00:02:33,520 Speaker 3: on a level playing field. Of course, we need to 46 00:02:33,800 --> 00:02:38,800 Speaker 3: really closely understand what are any restrictions licensing restrictions that 47 00:02:38,840 --> 00:02:42,120 Speaker 3: are being included here and could those be fore closing competition. 48 00:02:42,560 --> 00:02:46,239 Speaker 3: More generally, we also need to be aware of how 49 00:02:46,280 --> 00:02:50,679 Speaker 3: there are significant incumbents that may have an outsized role 50 00:02:50,720 --> 00:02:54,160 Speaker 3: to be playing because they have key control over the 51 00:02:54,240 --> 00:02:57,280 Speaker 3: raw material and key inputs, and so we need to 52 00:02:57,280 --> 00:03:00,440 Speaker 3: be aware of the broader potential competition issue us or 53 00:03:00,440 --> 00:03:03,760 Speaker 3: bottlenecks or choke points that could emerge in ways that 54 00:03:03,800 --> 00:03:07,400 Speaker 3: could inhibit innovation and inhibit competition. And so that's what 55 00:03:07,440 --> 00:03:09,800 Speaker 3: we're going to be talking with founders and vcs and 56 00:03:09,840 --> 00:03:10,760 Speaker 3: others about today. 57 00:03:12,040 --> 00:03:14,799 Speaker 2: Something else you've been looking into more recently is surveillance pricing, 58 00:03:14,800 --> 00:03:18,520 Speaker 2: which is how AI is being used to rapidly change 59 00:03:18,520 --> 00:03:21,000 Speaker 2: pricing based on consumer behavior. And there are some really 60 00:03:21,040 --> 00:03:24,520 Speaker 2: dystopian concerns here about how this could lead to dangerous 61 00:03:24,840 --> 00:03:28,280 Speaker 2: financial targeting. What are some examples you've seen of this 62 00:03:28,400 --> 00:03:29,959 Speaker 2: and what are you hoping to find. 63 00:03:31,520 --> 00:03:34,880 Speaker 3: So as you know, for years now, Americans have had 64 00:03:34,960 --> 00:03:39,240 Speaker 3: their personal data and information closely tracked and surveilled by 65 00:03:39,280 --> 00:03:42,040 Speaker 3: a whole set of companies in ways that can really 66 00:03:42,080 --> 00:03:45,760 Speaker 3: threaten people's privacy. What we see now is that firms 67 00:03:45,800 --> 00:03:50,200 Speaker 3: could also be using this enormously personal data about people 68 00:03:50,360 --> 00:03:54,480 Speaker 3: to also set person specific prices based on what they 69 00:03:54,520 --> 00:03:57,560 Speaker 3: know about you, based on what you're feeling, who you're seeing, 70 00:03:57,760 --> 00:04:00,640 Speaker 3: what you're browsing, and so we want to make sure 71 00:04:00,760 --> 00:04:03,480 Speaker 3: that we are looking under the hood and understand what's 72 00:04:03,520 --> 00:04:06,760 Speaker 3: going on here. So, for example, you can imagine that 73 00:04:07,040 --> 00:04:11,040 Speaker 3: a hotel that knows you've already bought plane tickets may 74 00:04:11,120 --> 00:04:14,040 Speaker 3: show you a higher price than they show somebody who 75 00:04:14,080 --> 00:04:17,240 Speaker 3: hasn't really decided on where they're going to visit. You 76 00:04:17,279 --> 00:04:21,120 Speaker 3: can imagine a restaurant that knows you have a one 77 00:04:21,240 --> 00:04:26,359 Speaker 3: hour lunch break could hike prices for you during that hour. 78 00:04:26,440 --> 00:04:28,080 Speaker 3: And so these are just some of the types of 79 00:04:28,120 --> 00:04:31,400 Speaker 3: practices that we could see take hold if this type 80 00:04:31,440 --> 00:04:34,039 Speaker 3: of surveillance pricing is allowed to develop. 81 00:04:34,920 --> 00:04:38,359 Speaker 2: Interesting we're all still feeling the effects of this crowd 82 00:04:38,400 --> 00:04:41,159 Speaker 2: strike outage, and so many people are shocked about how 83 00:04:41,200 --> 00:04:43,760 Speaker 2: a company that is so small could just shake up 84 00:04:44,120 --> 00:04:47,080 Speaker 2: the world like this. What's your take on this and 85 00:04:47,160 --> 00:04:48,720 Speaker 2: is there something to investigate here. 86 00:04:50,920 --> 00:04:53,800 Speaker 3: So as a general matter, I think this really underscores 87 00:04:53,920 --> 00:04:58,120 Speaker 3: the trade offs between kind of fragility and resiliency, and 88 00:04:58,160 --> 00:05:01,000 Speaker 3: how when you have more centralization, or when you have 89 00:05:01,320 --> 00:05:04,640 Speaker 3: enormous dependence on just one firm or a very small 90 00:05:04,839 --> 00:05:07,599 Speaker 3: number of companies, that can make it so that a 91 00:05:07,720 --> 00:05:11,919 Speaker 3: single disruption can have cascading effects and really lead to 92 00:05:11,960 --> 00:05:14,760 Speaker 3: all sorts of breakdowns. And so as a result of 93 00:05:14,760 --> 00:05:18,279 Speaker 3: this one incident, for example, we saw over three thousand 94 00:05:18,320 --> 00:05:22,080 Speaker 3: flights grounded. We saw doctors that were no longer able 95 00:05:22,160 --> 00:05:27,200 Speaker 3: to prescribe medicines for their patients, We saw courthouses that 96 00:05:27,279 --> 00:05:30,680 Speaker 3: had to close off proceedings, and so the impact here 97 00:05:30,880 --> 00:05:34,400 Speaker 3: was significant, and it's really underscoring the importance of making 98 00:05:34,480 --> 00:05:38,200 Speaker 3: sure we have resilient markets and resilient systems so that 99 00:05:38,279 --> 00:05:41,440 Speaker 3: a single crash like this doesn't lead to so much 100 00:05:41,480 --> 00:05:42,560 Speaker 3: outsized disruption. 101 00:05:43,880 --> 00:05:45,400 Speaker 2: I do have to take a moment to talk about 102 00:05:45,400 --> 00:05:48,800 Speaker 2: the presidential election. A number of prominent tech folks have 103 00:05:48,920 --> 00:05:52,080 Speaker 2: endorsed President Trump for a variety of reasons, but I 104 00:05:52,120 --> 00:05:56,640 Speaker 2: have heard specifically multiple tech executives and investors complain about 105 00:05:56,640 --> 00:06:00,240 Speaker 2: how they can't do deals on your watch, you have 106 00:06:00,279 --> 00:06:04,599 Speaker 2: any concerns that your agenda has that all alienated the 107 00:06:04,680 --> 00:06:10,120 Speaker 2: tech community or could impact the impact of your agenda 108 00:06:10,240 --> 00:06:10,919 Speaker 2: going forward. 109 00:06:12,560 --> 00:06:14,359 Speaker 3: You know, it's been such an honor to serve and 110 00:06:14,400 --> 00:06:17,520 Speaker 3: then Biden Harris administration, and you know, we're just focused 111 00:06:17,520 --> 00:06:21,359 Speaker 3: on doing our work. What I oftentimes hear from the 112 00:06:21,360 --> 00:06:26,520 Speaker 3: business community, including small businesses, including entrepreneurs, is that they 113 00:06:26,600 --> 00:06:29,839 Speaker 3: want markets to be more open and more fair and 114 00:06:29,960 --> 00:06:34,240 Speaker 3: more competitive, rather than incumbents being able to squash out 115 00:06:34,400 --> 00:06:37,880 Speaker 3: maason competitive threats. I mean, our free enterprise system is 116 00:06:37,920 --> 00:06:40,840 Speaker 3: one where the best ideas are supposed to win, and 117 00:06:40,880 --> 00:06:44,560 Speaker 3: we've historically seen that it's the disruptors and entrepreneurs that 118 00:06:44,640 --> 00:06:47,320 Speaker 3: have been a key vector of innovation. And so our 119 00:06:47,440 --> 00:06:50,320 Speaker 3: job at the FTC when we enforce the antitrust laws 120 00:06:50,360 --> 00:06:53,000 Speaker 3: is to make sure that our markets stay open and 121 00:06:53,040 --> 00:06:56,719 Speaker 3: fair and competitive. And that's something that you know, most 122 00:06:56,760 --> 00:07:00,440 Speaker 3: businesses and most entrepreneurs should really be able to get behind. 123 00:07:02,000 --> 00:07:05,760 Speaker 2: Former President Trump's running mate jd Vance has actually praised 124 00:07:05,880 --> 00:07:08,920 Speaker 2: your work. In fact, I believe he said that you're 125 00:07:08,960 --> 00:07:11,120 Speaker 2: one of the few people in the Biden administration that's 126 00:07:11,160 --> 00:07:14,640 Speaker 2: doing a pretty good job. In his opinion, what do 127 00:07:14,680 --> 00:07:18,120 Speaker 2: you make of the irony there? And you know, how 128 00:07:18,200 --> 00:07:21,520 Speaker 2: do you see the FTC moving forward in the next administration. 129 00:07:23,160 --> 00:07:25,920 Speaker 3: So I will speculate about what's going to happen in November. 130 00:07:26,560 --> 00:07:30,520 Speaker 3: I do think we see enormous bipartisan agreement that we 131 00:07:30,600 --> 00:07:34,040 Speaker 3: need to reinvigorate and double down on anti trust enforcement. 132 00:07:34,560 --> 00:07:37,760 Speaker 3: We need to make sure that monopolies can't illegally use 133 00:07:37,800 --> 00:07:42,000 Speaker 3: their power to jack up prices for consumers, to really 134 00:07:42,120 --> 00:07:46,880 Speaker 3: undermine workers, or really stamp out entrepreneurs in small businesses. 135 00:07:46,920 --> 00:07:50,800 Speaker 3: And so that bipart is an agreement around the importance 136 00:07:50,880 --> 00:07:54,600 Speaker 3: of open, fair competition to protect our free and fair 137 00:07:54,760 --> 00:07:58,160 Speaker 3: enterprise system is absolutely critical. I mean, you know, just 138 00:07:58,240 --> 00:08:01,760 Speaker 3: the other week, the FTC release an interim staff report 139 00:08:02,080 --> 00:08:05,520 Speaker 3: looking at the practices of the pharmacy benefit managers and 140 00:08:05,560 --> 00:08:09,120 Speaker 3: some of our initial findings. And that's an area, for example, 141 00:08:09,120 --> 00:08:12,760 Speaker 3: where we see enormous bipartisan concern on both sides.