Speaker 1: Welcome to Votes and Verdicts, hosted by the Litigation and
Speaker 1: Policy team at Bloomberg Intelligence, the investment research arm of
Speaker 1: Bloomberg LP. This podcast series examines the intersection of business
Speaker 1: policy and the law. I'm JUSTINTERREESI and to trust litigation
Speaker 1: and policy analysts here at BI. Just a quick word
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Speaker 1: Our coverage includes over two thousand equities and credits, and
Speaker 1: we have outlooks on more than ninety industries and one
Speaker 1: hundred market indices, currencies and commodities. Today's topic Artificial intelligence AI.
Speaker 1: It seems to be everywhere, from simple use of chat
Speaker 1: GPT to grow prevalence of AI across business platforms. It's
Speaker 1: hard to sit through a single news show, much less
Speaker 1: a whole day without hearing something about AI. Some say
Speaker 1: it's the next big thing. Some say it's the next
Speaker 1: version of the space race where the US and other
Speaker 1: Western nations need to show their dominance. But one thing
Speaker 1: seems to be certain. AI and all of its surrounding
Speaker 1: issues have become ubiquitous as of recent news reports regarding
Speaker 1: antitrust implications and investigations around the technology by enforcement agencies
Speaker 1: across the globe, and all of that begs the question
Speaker 1: who's controlling the development of AI and what exactly does
Speaker 1: that mean From the perspective of competition in this developing sector,
Speaker 1: are smaller AI actors really able to get off the ground.
Speaker 1: With all of that, I'd like to welcome my guest,
Speaker 1: Sarah Myers West, Co executive director of the AI Now Institute,
Speaker 1: the leading policy research and advocacy organization on the subject
Speaker 1: of AI. HI. Sarah, thanks so much for joining me today.
Speaker 1: Thank you for having me absolutely so. I could spend
Speaker 1: a half hour just telling you all about Sarah's skill set,
Speaker 1: but what I'll say is Sarah spent the last fifteen
Speaker 1: years or so focused on the role of technology companies
Speaker 1: and the growth of their political influence, and her current
Speaker 1: role is as co executive director. Sarah focuses on addressing
Speaker 1: the market issues and infrastructure that guides the role of
Speaker 1: tech in society and holds a sector to task in
Speaker 1: serving the needs of the public, including a relevant to
Speaker 1: our chat today antitrust issues. Her research is featured in
Speaker 1: leading academic journals and a wide range of media outlets,
Speaker 1: and she's a go to for governments on questions surrounding
Speaker 1: tech and AI, having testified before Congress and advised the
Speaker 1: White House, European Commissioned CFPB, and other agencies. Also incredibly
Speaker 1: important for today's discussion. Sarah recently completed a term at
Speaker 1: the FTC as a senior advisor on AI. She worked
Speaker 1: on competition and consumer protection issues, and last, but certainly
Speaker 1: not least, Sarah's also working on a book, Tracing Code,
Speaker 1: which we'll examine the origins of data capitalism and commercial
Speaker 1: commercial surveillance. Sarah, There's so much more I could say
Speaker 1: about you, but there's obviously a lot to talk about
Speaker 1: in this space, so let's get to it. We're recording
Speaker 1: this on July nineteenth, twenty twenty four. Obviously some really
Speaker 1: big news today considering the Microsoft out it just wondering
Speaker 1: if you have anything you'd like to lead off with
Speaker 1: on that subject.
Speaker 2: Yeah, So, as we speak, there are airlines and hospital
Speaker 2: systems and banks all around the world trying to bring
Speaker 2: themselves back online after a bug in the systems that
Speaker 2: have brought everything to a sudden halt, and I think
Speaker 2: what that really shows is the fragility of our infrastructure,
Speaker 2: particularly given the very heavy reliance on one or a
Speaker 2: small handful of players. In this instance, it was Microsoft
Speaker 2: and CrowdStrike, where the two companies kind of behind this,
Speaker 2: you know, massive technological outage that uh, you know we're
Speaker 2: all experiencing today.
Speaker 1: Yeah. Absolutely, I think I think that point is super
Speaker 1: well taken, and you know, I think it really leads
Speaker 1: us into our conversation about about AI too, where we
Speaker 1: might see that similar kind of issue of consolidation and
Speaker 1: you know, a few a few players, if you will,
Speaker 1: kind of running the space. But if you could talk
Speaker 1: a little bit about the role of big tech and
Speaker 1: AI and that, I think that'd be really grateious as
Speaker 1: a foundation to lead things off.
Speaker 2: Yeah, so I think it might be helpful to sort
Speaker 2: of step back and look at the broader history behind
Speaker 2: the field of artificial intelligence. Over an almost seventy year history,
Speaker 2: AI has been used to mean a whole range of
Speaker 2: different things, from robotics to the generative AI systems that
Speaker 2: I think have really captured everybody's in genations today. And
Speaker 2: you know, the definition of what AI is in the
Speaker 2: present moment, is in many ways constituted by it's defined
Speaker 2: by an existing concentration of power within the tech industry.
Speaker 2: So if you wind back the clock maybe twenty years,
Speaker 2: you see these tech giants Google, Amazon emerging on the
Speaker 2: scene and developing out business models that involve the collection
Speaker 2: of massive amounts of data and the development of huge
Speaker 2: computational infrastructures needed to process that data. And once you
Speaker 2: had those two big pieces in place, these companies began
Speaker 2: to develop new techniques of trying to process that data
Speaker 2: to make sense through analysis. Often it's you know, sort
Speaker 2: of basic statistics, but sort of combining massive data sets
Speaker 2: massive computational infrastructures. And those are two of the core
Speaker 2: elements that you know, make up what we call AI today.
Speaker 2: The third is the field of research and the the
Speaker 2: big tech firms also began to dominate the leading conferences
Speaker 2: in artificial intelligence. The latter their corporate labs became the
Speaker 2: place that computer science graduates wanted to go get hired.
Speaker 2: They were offering the highest paying salaries. There became the
Speaker 2: most prestigious places to go and work. And so between
Speaker 2: the sort of business elements of what kind of AI
Speaker 2: was being developed within these firms as well as defining
Speaker 2: what constitutes the cutting edge in the research space. Big
Speaker 2: tech firms I think have really significantly shaped our understanding
Speaker 2: of AI, what it can be used for or what
Speaker 2: is most of interest over the span of at least
Speaker 2: a decade and probably more. And so getting back to
Speaker 2: our subject today of thinking about antitrust, it really brings
Speaker 2: to question, you know, if we were to intervene in
Speaker 2: the AI market in a more structural way, not only
Speaker 2: sort of like tackling the the you know, concentration in
Speaker 2: big tech, but they're shaping hand in shaping research and
Speaker 2: development as well. I really wonder how that changes what
Speaker 2: kind of AI we're building and what vision it serves,
Speaker 2: because to my thinking right now, it seems somewhat stale
Speaker 2: compared to what you know, we were being sold a
Speaker 2: year ago from companies like open Ai. Like I find
Speaker 2: it kind of hard to get all that excited about
Speaker 2: a chatbot and more excited about the vision of what
Speaker 2: could be possible if we were to to break up
Speaker 2: big tech.
Speaker 1: Yeah, I think that's super fascinating, and you know, just
Speaker 1: even looking back at AI now's most recent kind of
Speaker 1: large scale report on the subject. I saw the twenty
Speaker 1: twenty three Landscape report that was put out. You know,
Speaker 1: I think you make some really there's some really important
Speaker 1: points that come from that. I kind of guide, you know,
Speaker 1: where we're head to hear this discussion too, And I
Speaker 1: think those are that, you know, big data really is
Speaker 1: big AI or has the potential to kind of you know,
Speaker 1: influence where AI goes. It just so is so dependent
Speaker 1: on the data that it's taking in, if you will,
Speaker 1: And that really nothing nothing regarding AI is inevitable or
Speaker 1: has to be inevitable. And I think with those two
Speaker 1: kind of points in mind, you know, what do you
Speaker 1: really see at the most pressing antitrust considerations right now
Speaker 1: from maybe a company standpoint or problems that have really
Speaker 1: emerged recently that you think really are right for a challenge.
Speaker 2: Yeah, great question. I think. So what I think is
Speaker 2: most pressing right now is the ecosystem dominance of that
Speaker 2: small handful of firms. So a year ago, when we
Speaker 2: published that report, we were really calling it into the
Speaker 2: infrastructural dominance of big tech firms. And at that moment
Speaker 2: in time, it was a really unpopular thing to say
Speaker 2: that these cloud monopolies were shaping a race to the
Speaker 2: bottom in AI development. Most people were saying, let's wait
Speaker 2: and see. Maybe we're going to see startups starting to
Speaker 2: bubble up, and you know, we'll have new entrants that
Speaker 2: are going to be competitive with Google and Microsoft. But
Speaker 2: now I think we're seeing a recognition that this heavy
Speaker 2: concentration in these firms and their control over the data,
Speaker 2: their control over the infrastructures are presenting real barriers to
Speaker 2: innovation and competition in the market. Now there's a long
Speaker 2: way to go on actually meaningfully tackling that issue. You know,
Speaker 2: the DOJ just I think maybe three weeks ago, announced
Speaker 2: that it's going to be looking into in Nvidia, which
Speaker 2: is the maker of the chips that are powering a
Speaker 2: lot of AI development. The French authorities are a little
Speaker 2: bit further along. They conducted a ra aid on in
Speaker 2: videos headquarters last year. But I think that infrastructure is
Speaker 2: only one part of the problem. These firms also control
Speaker 2: crucial paths to market, and that I think is still
Speaker 2: an undercovered antitrust issue. It's why we see promising startups
Speaker 2: like Mistral striking deals with dominant firms like Microsoft, because
Speaker 2: these new entrants need help connecting to their customers. There
Speaker 2: just isn't really a clear business proposition for a lot
Speaker 2: of new startups. And we've seen firms like Goldman Sachs
Speaker 2: and Sequoia, firms that have themselves made big investments in
Speaker 2: this market issue increasingly skeptical reports about the potential of
Speaker 2: new players to compete. So I think addressing those two pieces,
Speaker 2: the role of the big firms in dominating the resources
Speaker 2: that you need to build AI, the infrastructure that you
Speaker 2: need to build AI, as well as their role in
Speaker 2: shaping the market it through their dominance of the ecosystem
Speaker 2: of the path to you know, to profit is key.
Speaker 1: Sure, sure, And I think from a really basic standpoint too,
Speaker 1: you know, it's really fascinating. I think, you know, from
Speaker 1: a standpoint of what the FTC or DOJ can do
Speaker 1: in the context of traditional anti trust enforcement, right, you
Speaker 1: see these situations where perhaps making a large investment in
Speaker 1: a smaller AI startup, if you will, or hiring most
Speaker 1: of that that startups you know, labor folks or skilled
Speaker 1: labor who you know has the brain power behind AI
Speaker 1: as a way to kind of get around that traditional
Speaker 1: concept of a heart Scott Redina review or something like that.
Speaker 1: You know, where it would be a traditional full skill
Speaker 1: out acquisition. It raises a lot of questions about what
Speaker 1: can be done from an enforcement perspective, and you know,
Speaker 1: we'll get to that a little bit later on, you know,
Speaker 1: in terms of legislation and you know what what might
Speaker 1: reshape the way things are proceeding right now. But you know,
Speaker 1: I think another issue that you know, I'm hearing a
Speaker 1: lot about from my side here too, is you know
Speaker 1: this concept of this AI you know space race, you will, right,
Speaker 1: the US has to compete with other global entities that
Speaker 1: are also developing AI. And you know, no surprise, I
Speaker 1: think in political rhetoric we hear you know, China comes
Speaker 1: up a lot, and this purported need for the US
Speaker 1: to compete with China on the subject of AI. How
Speaker 1: do you view that And do you kind of think
Speaker 1: it's this red herring if you will, in some ways,
Speaker 1: as you know, you know, as a reason not to
Speaker 1: really reiin in AI from an anti trust perspective.
Speaker 2: Yeah, So the discourse around this AI arms race isn't
Speaker 2: just an invention of this past year. It really goes
Speaker 2: back a lot further. If you look back at some
Speaker 2: of the discussions about the anti trust package that Congress
Speaker 2: was considering a couple of years ago. That China arms
Speaker 2: race discourse was very much utilized by industry in its
Speaker 2: lobbying to push back on the notion that we needed
Speaker 2: a new anti trust rules for the industry. And you
Speaker 2: saw prominent people in the Defense establishment, any of whom
Speaker 2: we're also on the payroll of Eric Schmid adjacent firms
Speaker 2: out there saying that if you do anything to restrain
Speaker 2: big tech firms, it's going to diminish our competitiveness with China.
Speaker 2: And I think the Biden administration, to its credit, clap
Speaker 2: back by issuing this Executive Order on Competition that said so, actually,
Speaker 2: national monopolies are not in the national interests. What we
Speaker 2: want is a really vibrant and competitive sector, and that's
Speaker 2: what's going to set us up for a success. But
Speaker 2: I don't think that other parts of the government have
Speaker 2: fully lived up to that vision. I mean, certainly, as
Speaker 2: you know, Congress hasn't really meaningfully moved, and in part
Speaker 2: that's due to fears about the US falling behind on
Speaker 2: innovation if it regulates the market. But I think that's misguided,
Speaker 2: if anything, regulation of a sector that's gotten this bloated
Speaker 2: would really foster more innovation and would benefit a wider public.
Speaker 1: Sure, thanks definitely seeming a bit stagnant right now on
Speaker 1: the hill. There's there's no question out that. And you know,
Speaker 1: I think, you know, building upon the rhetoric around you know,
Speaker 1: China and this just this idea of an arms race,
Speaker 1: you know, I think there's this other ick factor, if
Speaker 1: you will, sometimes AI where people think about how that
Speaker 1: might implicate things like biometrics, surveillance, right, how does that
Speaker 1: roll out in the future, and what industries is that
Speaker 1: does that become an issue and if you have any
Speaker 1: thoughts on about that aspect of AI too. I think
Speaker 1: that's something folks are super interested in right now as well.
Speaker 2: Yeah, absolutely. I mean biometrics I think haven't gotten as
Speaker 2: much attention as they should over the last year because
Speaker 2: of this you know, surge and attention to generate AVEAI,
Speaker 2: But there has been a really quiet and significant expansion
Speaker 2: in their use places like in cars. For example. You know,
Speaker 2: there are if you're a delivery driver, one of the
Speaker 2: ways that drivers are being monitored by their employers is
Speaker 2: through the use of biometrics in car can that purport
Speaker 2: to be able to evaluate you know, whether they're falling
Speaker 2: asleep or whether they're you know, they're signaling aggression. And
Speaker 2: that use case of what we call emotion recognition is
Speaker 2: one of the areas that I'm especially worried about. Emotion
Speaker 2: recognition systems have largely been disregarded by the scientific community
Speaker 2: as pseudoscientific. You can't sort of with any statistical validity
Speaker 2: take you know, the measurement of somebody's facial expression and
Speaker 2: be able to evaluate what their interstate looks like. But
Speaker 2: that certainly doesn't stop a company from selling a system
Speaker 2: that claims to be able to make those kinds of assessments.
Speaker 2: And we're seeing the rollout of emotion recognition in a
Speaker 2: lot of workplace surveillance contacts. You know, mentioned drivers, call
Speaker 2: center workers are having their voice print measured and they're
Speaker 2: getting feedback about, you know, whether or not they're sounding
Speaker 2: pleasant enough to their customers, and all of these other
Speaker 2: places where often they're used in ways that have quite
Speaker 2: significant consequences for the people that it's used on. So
Speaker 2: I think that biometrics are we remain an undercovered area
Speaker 2: and one that we really need much more policy scrutiny of.
Speaker 1: Sure. I mean, so many privacy issues there obviously, you know,
Speaker 1: and so many privacy issues. I think we're obviously a
Speaker 1: bit behind other global counterparts in our privacy development here
Speaker 1: from a legal standpoint too in the US. But yeah,
Speaker 1: just so many issues there, and again you know, kind
Speaker 1: of robing adgit trust into that situation too with biometric surveillance,
Speaker 1: you know, beyond the privacy issues itself, it's all of
Speaker 1: that information the hands of a select few foot people too.
Speaker 1: If it continues to roll out the way it does.
Speaker 1: Sounds like so many, so many flags I think on
Speaker 1: the play with that one. But you know, kind of
Speaker 1: turning back a bit to actual enforcement or the regulatory
Speaker 1: oversight here with anti trust. You know, so we see
Speaker 1: all these these reports of investigations going on. I feel
Speaker 1: like several times a week I'm seeing something about investigation
Speaker 1: happening either in the US or abroad, you know. I
Speaker 1: know you mentioned the French investigation of Navidia, for example.
Speaker 1: But what do you see as that kind of problems
Speaker 1: right now with the available methods for oversight, you know,
Speaker 1: and the way that regulators are going about employing their
Speaker 1: oversight or investigations of these entities.
Speaker 2: Yeah, So, I mean the in the current environment. You know,
Speaker 2: one enforcement agencies are certainly doing the most. They're taking
Speaker 2: a very assertive and muscular stance to enforcing the laws
Speaker 2: on the books, and they deserve all all credit for that.
Speaker 2: They're also in an unenviable position of trying to play
Speaker 2: whack a mole after the fact with companies that are
Speaker 2: so big that they're very comfortable sort of experimenting out
Speaker 2: in the wild and just seeing, you know, how these
Speaker 2: technologies are going to work, and you know, have people
Speaker 2: give them feedback on where they fail. And so like
Speaker 2: the the enforcement agencies and investigative journalists and independent researchers
Speaker 2: are all like playing whack a mole, trying to find
Speaker 2: and surface harms long after they've occurred, and then you know,
Speaker 2: attempting to use the law to remediate harm. But in
Speaker 2: some cases it's it's way too late. So I think
Speaker 2: that that's you know, far from an ideal mode of
Speaker 2: regulating a sector that has such significant consequences for the public.
Speaker 2: And there's you know, limited incentives for companies that have
Speaker 2: grown this large to really comply. You know, for a
Speaker 2: lot of these firms, they just allocate a budget line
Speaker 2: for the finds that they're going to get hit, sure, sure,
Speaker 2: and so we need stronger incentives for compliance and stronger
Speaker 2: incentives for firms to be you know, engaging in basic
Speaker 2: levels of you know, testing and validation of their systems
Speaker 2: even to make sure that they work as intended before
Speaker 2: they roll them out, let alone, make sure that they're
Speaker 2: not causing harm.
Speaker 1: Right, right, And I guess also from from the standpoint
Speaker 1: of you know, they have TC you know, d O
Speaker 1: J you know do I'm wondering if you have any
Speaker 1: thoughts on just you know, what they should be looking
Speaker 1: out for from the from the perspective of merger activity
Speaker 1: or something that looks like a merger, right, you know,
Speaker 1: I'm thinking about the kind of classic brick and mortar
Speaker 1: merger context right where you know, to Let's say two
Speaker 1: retailers are merging and I look at a map and
Speaker 1: I draw a circle and say, hey, you've got you know,
Speaker 1: five stores, and that's really concentrated relevant market here. The
Speaker 1: merger is not good for this particular reason, right, But
Speaker 1: obviously AI, you know, it's a different scenario. What kind
Speaker 1: of thing should folks be looking looking at around merger activity?
Speaker 1: Around AI? Should we actually start seeing you know, real
Speaker 1: acquisitions in that space.
Speaker 2: Yeah, so a couple things stand out. One is mergers
Speaker 2: that are conducted for the purpose of acquiring data. And
Speaker 2: we saw examples of this back in the day. Facebook
Speaker 2: acquired a company and the name of the company I'm
Speaker 2: blanking on right now.
Speaker 1: But it was too many companies.
Speaker 2: That's why many companies, too many acquisitions too. So they
Speaker 2: acquired a company that was a VPN provider and once
Speaker 2: they acquired that company, they pushed out a new research
Speaker 2: tool on Facebook that users could sign up for that
Speaker 2: would allow them to monitor those users traffic using the
Speaker 2: VPN and they were able to see, well, what kinds
Speaker 2: of apps and services were those users using, and from
Speaker 2: that they determined that everybody was using WhatsApp and that
Speaker 2: was one of the factors that led to you know,
Speaker 2: while at the time was one of the largest acquisitions
Speaker 2: in tech history, the Facebook's acquisition of WhatsApp. So, you know,
Speaker 2: the use of data obtained through acquisition can lead to
Speaker 2: competitive harms. It can also lead to privacy harms. I mean,
Speaker 2: certainly for the users whose activity was being monitored. There
Speaker 2: were similar concerns raised.
Speaker 1: Uh.
Speaker 2: For example, Amazon was considering acquiring one Medical and the
Speaker 2: FTC was evaluating that acquisition. Uh FTC commissioners Bedoya and
Speaker 2: Slaughter issued an opinion saying, you know this, this merger
Speaker 2: is going to go through, but we do want to
Speaker 2: raise some concerns about the new pools of data that
Speaker 2: Amazon's now going to have access to, because they're now
Speaker 2: going to have access to sensitive health data that may
Speaker 2: not you know, violate privacy rules, but nevertheless, could let
Speaker 2: Amazon make inferences about people in ways that will will
Speaker 2: be highly consequential. So that kind of activity, I think
Speaker 2: is one thing that deserves scrutiny. And also what you
Speaker 2: raised earlier around you know, these sort of non traditional
Speaker 2: paths to not acquiring companies but making these unusual business
Speaker 2: arrangements through provision of compute credits or things that don't
Speaker 2: reach a Heartscott Regina threshold sort of and runs around
Speaker 2: traditional acquisition are the other that we're seeing a lot
Speaker 2: of in the sector.
Speaker 1: God, I got it so much to consider it there,
Speaker 1: And you know, I think we've also been seeing so
Speaker 1: much activity recently in the way of kind of private
Speaker 1: lawsuits or class actions if you will, you know, and
Speaker 1: really what stood out to me recently is these class
Speaker 1: actions we've seen regarding that you of AI pricing algorithms
Speaker 1: and setting residential rental rates, hotel rates, things like that.
Speaker 1: Where where what's happening, or what's alleged to be happening,
Speaker 1: is that you know, competitors are acting in kind of
Speaker 1: this hub and spoke you know, conspiracy where they're sharing
Speaker 1: their private information with a third party but also getting
Speaker 1: access to their competitor competitors information when they by virtue
Speaker 1: of them doing that. But you could talk a little
Speaker 1: bit more about those lawsuits and you know what, what
Speaker 1: other kinds of suits maybe do you expect that we
Speaker 1: might see coming up regarding you know, AI and its
Speaker 1: uses in those contexts.
Speaker 2: Yeah, So there's this quiet but endemic problem of algorithmic pricing.
Speaker 2: It's it's gone everywhere from hotels to realtors to UH groceries, insurance,
Speaker 2: even some companies are using algorithmic systems to set the
Speaker 2: wages that they'll pay to workers. Viena Duball has really
Speaker 2: documented really well the use of algorithmic wage discrimination in
Speaker 2: the gigwork sector, and what that means is that a
Speaker 2: lot of people are being squeezed on both sides that
Speaker 2: that the firms, you know, on the one hand, are
Speaker 2: pushing prices as high as they can get people to
Speaker 2: pay and trying to target them to pay as much
Speaker 2: as possible, and then on the other side, paying them
Speaker 2: as little as they possibly can, trying to you know,
Speaker 2: utilize consumer surveillance data on both ends, and the firms
Speaker 2: that have the ability to take advantage of information asymmetries
Speaker 2: are the ones that benefit. So, like you've said that,
Speaker 2: we've seen these cases focusing specifically on the use of
Speaker 2: algorithmic methods to set rents, and this is problematic for
Speaker 2: many reasons. You know, we already have a real affordable
Speaker 2: housing problem in this country that's exacerbated by the existence
Speaker 2: of monopolies in housing markets and cities around the country.
Speaker 2: And what this what this does is it essentially extends
Speaker 2: cartel like behavior into markets where it otherwise couldn't extend.
Speaker 2: It would be really difficult for rental companies in Houston
Speaker 2: and Chicago to coordinate with one another on setting prices,
Speaker 2: but through systems like you know, those provided by real Page,
Speaker 2: it creates sort of this hub and scope, hub and
Speaker 2: spoke model across all of the firms that are relying
Speaker 2: on this one company. There are a couple of bills
Speaker 2: that also try and tackle this issue. Senator Klobuchar has one.
Speaker 2: Senator wide, it has one, but like you've mentioned, nothing's
Speaker 2: really moving through Congress right now. So what that means
Speaker 2: is these lawsuits are really the front lines of trying
Speaker 2: to tackle these problems in the absence of regulatory movement,
Speaker 2: just doing the best that they can with the law
Speaker 2: we already have on the books right right.
Speaker 1: You know what I know, both in the real page
Speaker 1: suit and you know the some larger hotel class actions
Speaker 1: that are also penning. DJ certainly has filed statements of
Speaker 1: interest and you know, sharing its view that you know,
Speaker 1: it does believe that use of these pricing algorithms can
Speaker 1: in fact be a violation of the Sherman Act. So
Speaker 1: you know DJ is out there, DJ is I think,
Speaker 1: you know, commenting on the issue as best as it
Speaker 1: can with existing law. But you know, to your point
Speaker 1: about this legislation pending in Congress, you know there's no
Speaker 1: shortage of anti trust legislation that that seems to be
Speaker 1: pending on the Hill right now. I know you testified
Speaker 1: regarding these bills before Senator Klobashar's subcommittee last December, but
Speaker 1: you know, beyond just those those bills you just mentioned,
Speaker 1: what do you view as the most pressing legislation that
Speaker 1: kind of needs to get over the finish line right
Speaker 1: now in DC?
Speaker 2: Yeah, I mean there's there's very little hope of much
Speaker 2: moving within election.
Speaker 1: Yeah, very very true. Maybe even after Unfortunately, we'll see,
Speaker 1: we'll see what happens.
Speaker 2: But yeah, I mean so like my my real but
Speaker 2: a little and avasive answer is, you know, our enforcement
Speaker 2: agencies are trying to do the work, and the interims
Speaker 2: of making sure that they're adequately resourced is probably the
Speaker 2: most likely thing that we will hopefully see. But you know,
Speaker 2: beyond that, it is striking that we still don't have
Speaker 2: a federal privacy law in the US, and data privacy
Speaker 2: law is AI policy. What we saw in the EU
Speaker 2: after chat GPT was released is the swiftest action that
Speaker 2: regulators took took place under the GDPR, the EU's privacy law.
Speaker 2: We saw, you know, the EU be able to clap
Speaker 2: back on Uber and Lift's use of algorithmic pricing methods
Speaker 2: and algorithmic wage setting also under the GDPR. So I
Speaker 2: think that's a really good place to start. The other place, also,
Speaker 2: non conventional but I think reforming our labor law and
Speaker 2: whistleblower protections because so much of what we know about AI,
Speaker 2: which is often a very opaque sector, and many of
Speaker 2: the early policy wines that we've seen have come from
Speaker 2: movement by workers, whether that's organizing or whistle blowing, or
Speaker 2: you know, codifying restrictions on how AI can be used
Speaker 2: through collective bargaining. So I think protecting workers is the
Speaker 2: other place where I think we can do a lot more.
Speaker 1: Got it? Got it? And I think, you know, maybe
Speaker 1: not so much on the labor pieces you just mentioned,
Speaker 1: but you know, I know that some of the legislation,
Speaker 1: at least some of the legislation that might be a
Speaker 1: bit more tailored or narrowed to a particular antitrust concern
Speaker 1: in a specific industry, like you know, the rental market
Speaker 1: or the residential rental market, or you know, things along
Speaker 1: those lines. You know, some of that legislation does seem
Speaker 1: to have some bipartisan support, you know, And I think
Speaker 1: you might have alluded to this a little bit earlier,
Speaker 1: you know, when we first started speaking too. But you know,
Speaker 1: what are your view? What's your view? I'm perhaps withstalling
Speaker 1: this legislation and if you could talk a little bit about,
Speaker 1: you know, just the influence of tech and D see today.
Speaker 1: I think that's also something that you know a lot
Speaker 1: of folks might not be considering as part of what's
Speaker 1: happening with the legislative angle as well.
Speaker 2: Yeah, tech's influence in DC has really grown and it's transformed.
Speaker 2: Big tech lobbying now outspends the lobbying giants of yesterday,
Speaker 2: like big oil and big tobacco.
Speaker 1: Oh wow. And I think that's always what people think
Speaker 1: of when they're thinking about the classic lobbyists.
Speaker 2: And it's like, if anything, there's been a huge uptick
Speaker 2: in lobbying over the last year in the EU over
Speaker 2: the AI Act. In the US through things like you know,
Speaker 2: Senator Schumer's Insight Forums, which you know, really prominently foregrounded
Speaker 2: industry voices. We're also seeing the re emergence of you know,
Speaker 2: purported self regulation through things like the voluntary commitments the
Speaker 2: big firms made around AI through this Frontier AI Forum.
Speaker 2: So big tech lobbying is very prominent and it's gaining
Speaker 2: traction as you know, the industry tries to push the
Speaker 2: narrative that AI is too complicated for a government to
Speaker 2: regulate and that we need to trust them to determine
Speaker 2: next steps instead.
Speaker 1: Got it, got it? Honestly, Sarah, I feel like we
Speaker 1: could take any one of these topics or questions and
Speaker 1: make a separate and complete podcast episode about just that
Speaker 1: question itself. There's just so much going on in the
Speaker 1: space right now. I think, you know, as we even
Speaker 1: said getting started, but kind of the closing, do you
Speaker 1: have anything else you might just want to add, or
Speaker 1: any considerations that you want to touch upon before we
Speaker 1: wrap up? Yeah?
Speaker 2: Yeah, I mean, so one other quick thing that I'd
Speaker 2: add to, like the last point about how lobbying is transformed.
Speaker 2: We're also seeing new constituencies emerge, and I think that
Speaker 2: we've seen this particularly come to the four with the
Speaker 2: elections that there's you know, on the one hand, this
Speaker 2: existential risk lobby, which was very effective in shaping a
Speaker 2: tech agenda focused on like this sort of doom and
Speaker 2: gloom vision for AI, and then on the other hand,
Speaker 2: this effective accelerationism lobby, which is, you know, promoting unrestrained development.
Speaker 2: That's the Andres and Horowitz and y Combinator and sort
Speaker 2: of they've established their their presence in shaping sure Trump's
Speaker 2: AI agenda, and you know, with those two camps, I
Speaker 2: think it's it's really important to make sure that the
Speaker 2: scope of the agenda, like the vision for what we
Speaker 2: hope to see with this technology, doesn't just get narrowed
Speaker 2: to that range of interest from Silicon Valley, because I
Speaker 2: think that there's a lot more that we could build
Speaker 2: and see, but that the industry's version has sort of
Speaker 2: benefited only that narrow set of actors. And that's where
Speaker 2: I hope that stronger anti trust enforcement will give us
Speaker 2: fresh perspectives that we can really sort of like revitalize
Speaker 2: this industry and make sure it's serving all of us.
Speaker 1: Got it, Got it? Sarah Myers Wes, thank you so
Speaker 1: much for joining us today, and hopefully we'll have you
Speaker 1: back again again sometime soon. There's just so much to
Speaker 1: talk about here, and obviously I think we're going to
Speaker 1: continue seeing all of this roll out, you know, quite
Speaker 1: a bit more in the coming months and years ahead.
Speaker 1: So thank you so much for joining us today. Really
Speaker 1: appreciate it.
Speaker 2: Thank you for having me.
Speaker 1: Absolutely so a fascinating topic here, so many moving parts
Speaker 1: from a litigation and policy perspective, and as we just said,
Speaker 1: only going to grow busier with the passage of time.
Speaker 1: I really appreciate you taking the time to discuss it
Speaker 1: here today. Sarah. Also thank you to the listener for
Speaker 1: tuning in. As a reminder, you can read all of
Speaker 1: our Bloomberg intelligence research on the Bloomberg terminal at bi GO.
Speaker 1: And with that, I'm JUSTINTERREESI signing off. This was folks
Speaker 1: and Vernex