Speaker 1: This is Bloomberg Law with June Brusso from Bloomberg Radio.
Speaker 2: The prosecution and defense have rested their cases in the
Speaker 2: trial of Sam bankman Fried, who's accused of masterminding a
Speaker 2: multi billion dollar fraud at FTX. Bankman Fried spent two
Speaker 2: and a half days on the witness stand, testimony that's
Speaker 2: crucial to his hopes of avoiding a conviction in decades
Speaker 2: behind bars. But during his last hours on the stand,
Speaker 2: he struggled through a withering cross examination by the prosecutor
Speaker 2: joining me is Bloomberg Legal reporter Bob van Vories, who
Speaker 2: was in the courtroom for his testimony, was SBF able
Speaker 2: to establish any part of his case for the jury.
Speaker 3: Well, he did get up on the stand. I think
Speaker 3: he was able to humanize himself in front of the jury.
Speaker 3: I think he was able to give his perspective on
Speaker 3: a lot of transacts that prosecutors had tried to make
Speaker 3: look very sinister. And I think he was successful in
Speaker 3: giving his own perspective to some of the things that
Speaker 3: went on at FTX and now need a research. But
Speaker 3: I do think that on cross examination today yesterday, he
Speaker 3: gave back some of the games he had made on
Speaker 3: the direct testimony just inevitably, the prosecution asked him the
Speaker 3: difficult questions and the questions where they had evidence that
Speaker 3: maybe countered or undercut some of the points that he
Speaker 3: was trying to make out direct. It's difficult to know
Speaker 3: whether the decision to go on the stand and submit
Speaker 3: himself to the host of questioning was a good one,
Speaker 3: whether he benefited more than that he suffered. But the
Speaker 3: question of whether he provided enough testimony to get over
Speaker 3: the hump of countering the story that was told by
Speaker 3: the three cooperating witnesses, the former executive at FTX and Alameda,
Speaker 3: it seems like he probably wasn't able to do that.
Speaker 2: So there was this picture of him in the opening
Speaker 2: statements where the prosecution painted him as a criminal mastermind
Speaker 2: and the defense painted him as a hapless executive. Which
Speaker 2: picture do you think fits him better at the end
Speaker 2: of the.
Speaker 3: Day, It's difficult to say, because there was a balance
Speaker 3: between the two. Certainly, he presented himself as somebody who
Speaker 3: was too busy running FTX to be able to pay
Speaker 3: attention to what was going on at Alamede Research. Prosecutors
Speaker 3: claimed that Alameda Research were billions of dollars of FTX
Speaker 3: customer money and used it for all kinds of things,
Speaker 3: including for expensive real estate for venture capital investments. However,
Speaker 3: that counter with is very sort of precise style of speaking,
Speaker 3: his understanding of many many aspects in great detail of
Speaker 3: his business, and so he had to sort of walk
Speaker 3: a tightrope of on the one hand, not knowing what
Speaker 3: was going on, but on the other hand seeming like
Speaker 3: somebody who generally did know everything that was going on.
Speaker 2: Did he make any really damaging admissions during cross He.
Speaker 3: Did admit to elements that the prosecutors already knew that
Speaker 3: the prosecutors were already able to prove with documents and
Speaker 3: through previous testimony. There were some things that would have
Speaker 3: been very hard for him to deny, and so he
Speaker 3: did it in those nights. But I think perhaps one
Speaker 3: of the most damaging aspects of his testimony was when
Speaker 3: he was asked the very difficult question, he would become evasive,
Speaker 3: he would become he would quarrel with the questioning. He
Speaker 3: I don't think was able to credibly answer questions that
Speaker 3: were directed towards the most damaging evidence against him in
Speaker 3: other people's testimonies.
Speaker 2: And when he testified about the people who flipped. Did
Speaker 2: he appear antagonistic, No, not at all.
Speaker 3: He testified fairly gently about his former friends and co
Speaker 3: executives at FTX and Alameda, particularly Caroline Ellison, his former
Speaker 3: girlfriend who he put in her job as CEO of Alameda.
Speaker 3: He was very understanding complementary in his direct testimony, but
Speaker 3: he certainly had to come around to blaming her for
Speaker 3: not heading Alameda's risk at the time when he wanted
Speaker 3: her to do that. Also for not being able to
Speaker 3: sort of keep tabs on the amount of money that
Speaker 3: Alameda was borrowing from FTX. So again, for him, it
Speaker 3: was kind of a type book. He needed to blame her.
Speaker 3: But she was somebody who I think presented a very
Speaker 3: sympathetic face to the jury, and I think they believed
Speaker 3: her testimony. So it was very difficult, I think, for
Speaker 3: as SBF to do both of those things at the
Speaker 3: same time.
Speaker 2: Were the jurors paying close attention to him at all times?
Speaker 2: Did they get lost in this cross examination that at
Speaker 2: times seemed painstaking?
Speaker 3: There were certainly times in the testimony when he was
Speaker 3: covering technical aspects and when he was talking about financial
Speaker 3: transactions that were maybe not quite as accessible to the
Speaker 3: jury that they seemed a little more disengaged, But when
Speaker 3: he was talking about the most important parts of his testimony,
Speaker 3: and particularly on cross examination by Assistant US Attorney Danielle Sassoon,
Speaker 3: she was very focused in her questions. She was just
Speaker 3: relentless in coming back at him and asking questions, following
Speaker 3: up on logical implications of what his testimony was. She
Speaker 3: had him, particularly this morning, really kind of had him
Speaker 3: on the ropes with her, you know, questioning over and over,
Speaker 3: and the jury was paying attention to that.
Speaker 2: Did he come across as sympathetic or friendly that one
Speaker 2: juror or two might think, I don't want to send
Speaker 2: this guy to jail.
Speaker 3: I think for sure he made sense for him to
Speaker 3: take the stand, you know, being able to connect to
Speaker 3: the jury at least on some level. Before he took
Speaker 3: the stand on Friday, they had not heard a word
Speaker 3: from him. They'd just seen him sitting at the defense table,
Speaker 3: watching just like they were watching everything that was going on.
Speaker 3: So I think he was able to sort of present
Speaker 3: himself sympathetically to some extent, But I'm not sure he
Speaker 3: was able to break through and counter the prosecution case,
Speaker 3: which is what he needs to do to be able
Speaker 3: to be acquitted here.
Speaker 2: That question will be in the hands of the jury
Speaker 2: probably by Thursday, with closing arguments tomorrow. Thanks so much,
Speaker 2: Bob for that look from inside the courtroom. That's Bloomberg
Speaker 2: Legal reporter Bob van Voris. It's the biggest US anti
Speaker 2: trust case since the Justice Department went after Microsoft twenty
Speaker 2: five years ago. The government has spent six weeks presenting
Speaker 2: evidence in its case, contending that Google pays off tech
Speaker 2: companies to lock out rival search engines to smother competition
Speaker 2: and innovation. But now it's Google's turn, and the defense
Speaker 2: put on its star witness on Monday, Google CEO Sundhor Pichai,
Speaker 2: who defended his company's practice of paying Apple and other
Speaker 2: tech companies to make Google the default search engine on
Speaker 2: their devices, saying the intent was to make the user
Speaker 2: experience seamless and easy. Joining me is anti trust expert
Speaker 2: Harry First, a professor at NYU Law School. The government
Speaker 2: spent so much time zetting its case, do you think
Speaker 2: they drew a strong enough line between Google's actions and
Speaker 2: measurable harm to consumers?
Speaker 4: Well, that's a great question, because it isn't clear as
Speaker 4: you are saying it. What that's through line is to consumers.
Speaker 4: And one of the problems in the tech cases are,
Speaker 4: by and large, a lot of consumers, like these companies,
Speaker 4: you know, become reliant on Google for searches and you know,
Speaker 4: just use it all the time. It's become a verb.
Speaker 4: So that's a hard task and legally not necessarily one
Speaker 4: the government has to carry. So what the government has
Speaker 4: to carry is that Google has improperly excluded competition, that
Speaker 4: it has a monopoly and has excluded competition and thereby
Speaker 4: maintained it and excluded it by improper means rather than
Speaker 4: by competition on the merits. So that's really the task.
Speaker 4: The task isn't to show that we get bad searches
Speaker 4: or that our search results are litered with ads or
Speaker 4: any of those things. It's really to show that Google
Speaker 4: has made a strong effort to sort of cement itself
Speaker 4: in as the leader. You know, all paths are going
Speaker 4: to lead to Google, and that it's done that through
Speaker 4: any competitive means, rather than by competing with having just
Speaker 4: simply the best product.
Speaker 2: Do you think the government has gotten close to that?
Speaker 4: Well, Looming large in all of this is the amount
Speaker 4: of money that Google paid for these defaults, and you know,
Speaker 4: sort of the easy argument, or the direct argument is,
Speaker 4: if you're so good, why did you pay twenty six
Speaker 4: billion dollars to ensure that consumers use your product?
Speaker 2: Why?
Speaker 4: I just put it in front of them and consumers
Speaker 4: will say, hey, yeah, I like that one. And you know,
Speaker 4: what are you getting for your twenty six billion dollars?
Speaker 4: And I think that's that's a big h for Google
Speaker 4: and big plus I think for the government. You know,
Speaker 4: companies do rational things. They don't throw money away for nothing.
Speaker 4: So what do they think they're getting, Well, something they
Speaker 4: can't get through competition on the merits, which is cementing
Speaker 4: in that loyalty. Because defaults are really important in consumer behavior.
Speaker 2: Does it seem as if Google has learned from the
Speaker 2: lessons of the Microsoft case.
Speaker 4: That is a question tinged with irony. So Google started
Speaker 4: out by saying, you know, we're going to be the
Speaker 4: good company, We're not going to be Microsoft. And in fact,
Speaker 4: they took advantage of the remedy decree in the Microsoft
Speaker 4: case to make sure that as Windows was being updated
Speaker 4: and new versions were in that Microsoft Search engine, which
Speaker 4: was not called being at the time, would not be
Speaker 4: cement in is the default in Windows that consumers would
Speaker 4: be able to get to Google and choose it. So
Speaker 4: they were concerned to be sure, and one point there
Speaker 4: was some interaction with District Court that was, you know,
Speaker 4: supervising to create to make sure that Microsoft didn't use
Speaker 4: or build in a default that would exclude Google. So
Speaker 4: they understand the value, and they understand competition, and they
Speaker 4: wanted to get their product in front of consumers to use.
Speaker 4: But as time went on, as happens, you know, monopolies
Speaker 4: a heady thing. So having cemented their position, they wanted
Speaker 4: to keep it and keep it by whatever means.
Speaker 2: So here we are something that they might have learned
Speaker 2: from the Microsoft case. People are pointing to the importance
Speaker 2: of not having a paper trail. The Justice Department has
Speaker 2: implied that Google automatically deleted messages for that reason. How
Speaker 2: important do you think that is to the judge who's
Speaker 2: going to design this case.
Speaker 4: You know, I think in the end this isn't going
Speaker 4: to sway the judge particularly one way or the other.
Speaker 4: I think, you know, the governments tried to say that,
Speaker 4: you know, particularly early on, Google was very concerned about
Speaker 4: the language used in emails and you know, not saying
Speaker 4: things like we have to cut off their air supply,
Speaker 4: like one of the Microsoft people allegedly did you know
Speaker 4: with regard to Netscape, it's nascent competitor at the time,
Speaker 4: so they were aware, and you know, maybe this was
Speaker 4: done intentionally, maybe it wasn't. Who knows that this doesn't
Speaker 4: look great. I think in the end this is not
Speaker 4: going to be determinative. I think there are important legal
Speaker 4: issues that are going to be more important for this judge.
Speaker 2: One disagreement in the case has been over a search
Speaker 2: engine's quote scale, the amount of data collects from websites
Speaker 2: and users. So explain explain the scale argument.
Speaker 4: Well, this is a very interesting argument, I think is
Speaker 4: one of the important arguments in the case. And in
Speaker 4: some ways it cuts two ways. So the government says,
Speaker 4: you know, so why is it important for Google to
Speaker 4: keep it as a default and to you know, have
Speaker 4: all paths lead to Google. Well, obviously it's important for
Speaker 4: revenue and you know, for their advertising revenue. But more important,
Speaker 4: the more searches they get, the more they build up
Speaker 4: their base of searches of information about people, about things,
Speaker 4: about all sorts of things, and that this enables them
Speaker 4: to constantly update the search function and makes the search
Speaker 4: engine in some ways better and better. And what they're
Speaker 4: trying to do basically is make sure that other search
Speaker 4: engines never get that scale, never get to be of
Speaker 4: a size where where they can have the base of
Speaker 4: data that will enable them to provide searches of equality
Speaker 4: that equal Google. So it explains Google's motivation for wanting
Speaker 4: to keep being small or other competitors small. On the
Speaker 4: other hand, it does play into the notion that bigger
Speaker 4: maybe better. And you know, how far does the scale go?
Speaker 4: Would Google be even better if it had all the
Speaker 4: data in the world and there were no other search engines.
Speaker 4: So the government doesn't want to quite say that. Now. Google,
Speaker 4: on the other hand, doesn't want to quite say that
Speaker 4: scale is the reason why they're so good, So they
Speaker 4: want to downplay the scale argument a little bit and
Speaker 4: say no, no, no, no, we're not trying to deprive them
Speaker 4: of scale. The reason why we're so good is what
Speaker 4: we do with the data. It's not just having it.
Speaker 4: It's all the money we put into the engineering of
Speaker 4: figuring out the best algorithms, the best way to use
Speaker 4: the data. So it isn't just a question of scale,
Speaker 4: that's not just this thing that keeps us better. So
Speaker 4: it's sort of an argument that's fun in a way.
Speaker 4: Google could use the scale argument to say, Aha, we're
Speaker 4: better off with monopoly. But that's a hard legal argument
Speaker 4: to make. There's room in the law for saying that,
Speaker 4: by the way, but it's not the best argument to
Speaker 4: put in front of a judge. And the government doesn't
Speaker 4: want to say scale is so important that we're better
Speaker 4: off with a monopoly. So it's an argument. And here's
Speaker 4: where I'm not quite sure the testimony shows us what's true.
Speaker 4: It's not clear where the scale economies, and so I'm
Speaker 4: not sure. Maybe Google doesn't know. And this has been
Speaker 4: true in other cases Facebook, for example, you know how
Speaker 4: big does Facebook have to be? Amazon? Any of these
Speaker 4: companies that rely on data are where points where you know,
Speaker 4: economies of scale just diminished and getting bigger doesn't necessarily
Speaker 4: make you better. In manufacturing, there are you know, that's
Speaker 4: a commonplace in manufacturing, But for data not so clear.
Speaker 2: Some internal Google emails show that executives were mindful of
Speaker 2: avoiding keywords like market share in their records. Is this
Speaker 2: case about market share or does scale take the place
Speaker 2: of market share.
Speaker 4: Well, the answer is not either.
Speaker 2: Or so I'm wrong on both counts.
Speaker 4: No, you're right on both camps. It is about market share.
Speaker 4: So for the law, you have to show two things
Speaker 4: to violate Section two of the Shermanac, which is the monopoly.
Speaker 4: Section one is that you are a monopoly, that you
Speaker 4: have monopoly power in a relevant market. That's the language.
Speaker 4: So that's market share, not only market share, but that's
Speaker 4: a key determinant of whether you're a monopolist. So government
Speaker 4: exhibits show Google with eighty nine to ninety some percent
Speaker 4: of the market, being with three percent, So market share
Speaker 4: is the first indication that you have monopoly power. You
Speaker 4: have most of the market. So market share is important.
Speaker 4: And I can understand if you were counseling you know, Google,
Speaker 4: you would say, look, don't say great, we have our
Speaker 4: share is as high as it can get. You know,
Speaker 4: it's just doesn't sound good. But of course, in the end,
Speaker 4: this doesn't depend on you know, some emails claiming it.
Speaker 4: It depends on the data. And you can find you know,
Speaker 4: the exhibits that the government has put together they're online,
Speaker 4: which show very high market shairs based on data put
Speaker 4: together by you know, other companies like stat Counter. So
Speaker 4: that is the first thing. Market share scale goes to
Speaker 4: this strategy question of you know, why they're trying to
Speaker 4: what they're going to gain by keeping others small, you know,
Speaker 4: other than a lot of money, which is important, but
Speaker 4: you know this competitive edge that is going to be
Speaker 4: hard to overcome.
Speaker 2: Interesting is the focus on artificial intelligence. The Department of
Speaker 2: Justice says that Google was way ahead in generative AI
Speaker 2: and chose not to release the technology sooner because of
Speaker 2: fear of losing its monopoly on search.
Speaker 4: I haven't seen that as dominant in argument. That's an
Speaker 4: interesting argument, hard to you know, it is an argument
Speaker 4: about monopolist that they control the pace of innovation and
Speaker 4: they don't want their current products cannibalized by new products
Speaker 4: that will only you know, take away market share and
Speaker 4: not help them. So in one sense, that could very
Speaker 4: well be AI. And you know, major economists have argued
Speaker 4: this point in terms of the ability and willingness of
Speaker 4: monopolis to innovate. Now at this point, you know, there
Speaker 4: may be other explanations for why they would be cautious
Speaker 4: with AI. And everybody seems to be jumping into the
Speaker 4: AI race, and they may want to turn it the
Speaker 4: other way. You know, don't worry so much about Google
Speaker 4: because you know, Being is featuring chat, GPT, and they've
Speaker 4: made this big investment in artificial intelligence, and you know
Speaker 4: they're going to have searches are going to be fantastic.
Speaker 4: You know that competition is just coming tomorrow.
Speaker 2: A contrast between this trial and the Microsoft trial seems
Speaker 2: to be the testimony of the CEOs. Apparently, Sundar Prashai
Speaker 2: took the stand and was cool, calm and collected, unlike
Speaker 2: what we saw from Bill Gates so many years ago.
Speaker 2: He talked about that search deal with Apple and said
Speaker 2: we fiercely compete on so many products, and that the
Speaker 2: meta when they decided that was tense. At times, we
Speaker 2: continue to have moments of tension between the companies. Is
Speaker 2: that enough? I don't know.
Speaker 4: Well, nice try, Yeah, I'm tempted to. You know, the
Speaker 4: old point when the elephants danced, the fleas get crushed.
Speaker 4: So I don't know. Yeah, I'm sure that they are
Speaker 4: in some way frenemies, as the word might be. These platforms,
Speaker 4: major platforms have points of competition and points of cooperation,
Speaker 4: But in some sense that doesn't matter all that much.
Speaker 4: What matters is this point of cooperation on search and
Speaker 4: the payments, which you know also acted to dissuade Apple
Speaker 4: from developing its own search engine. So you know, they
Speaker 4: could cooperate a lot of things, which isn't necessarily the
Speaker 4: greatest thing in the world or competing a lot of things,
Speaker 4: but the focus here is on search.
Speaker 2: I saw this analysis and I want to pass it
Speaker 2: by you that much of the Justice Department's case is
Speaker 2: based on documents, emails, and other records from Google itself,
Speaker 2: while Google's case so far seems to be executives testifying
Speaker 2: and contesting the conclusions from those records.
Speaker 4: So they'll have their experts. You know, they're economists. They've
Speaker 4: got a computer scientist on now, you know, they'll have that.
Speaker 4: But sort of a standard way these trials seem to
Speaker 4: be going in recent years is the government has experts
Speaker 4: talking about the industry, how persuasive or not. They're experts
Speaker 4: talking about the industry, and sometimes industry experts, but that's
Speaker 4: often counterweighted by people from the companies themselves. And this
Speaker 4: is often the case in mergers. For example, you know,
Speaker 4: high level executives who are very persuasive and come in
Speaker 4: and do often convince judges that what they've done is
Speaker 4: you know, rational business behavior, you know, done not to
Speaker 4: exclude compet but to advance competition. And the people who
Speaker 4: rise in these companies are often very skilled, you know, communicators.
Speaker 4: So in the Microsoft activision case, that merger case, you know,
Speaker 4: there were high level Microsoft executives testifying. Now they're also
Speaker 4: executives testifying for the government here, so it makes an
Speaker 4: bit of an interesting contrast to most merger cases. So
Speaker 4: you did have Microsoft testifying on behalf of the government.
Speaker 2: And but Shaw seemed to be one of those good communicators.
Speaker 2: He started his testimony talking about his childhood in India,
Speaker 2: then studying at Stanford University and joining Google in two
Speaker 2: thousand and four as a product manager for Google Toolbar.
Speaker 4: Yeah, well, it would have been better for the government
Speaker 4: if they had a good villain. You know, these stories
Speaker 4: are always better with villains. So Bill Gates was a
Speaker 4: great villain, and Mark Zuckerberg would be a great villain.
Speaker 4: But you know, for Google, no villains really of that sense.
Speaker 4: So yeah, the government doesn't have that part of the narrative.
Speaker 2: Is it too soon to tell which side has the
Speaker 2: better case? So far?
Speaker 4: Hard to say. I think there were issues that the
Speaker 4: judge wrote about. There was a motion made by Google
Speaker 4: and I think by the government to end the case
Speaker 4: before trial, motion for summary judgment, and the judge addressed
Speaker 4: some of the issues that he felt were in contention
Speaker 4: at trial. And these are legal issues, so, you know,
Speaker 4: I think it remains to be seen how the judge
Speaker 4: is going to decide that, and he's pushed as I
Speaker 4: read the reports of the trial, you know, push some
Speaker 4: of the witnesses on these issues, particularly whether it really
Speaker 4: makes a difference. Would have made a difference in market shares,
Speaker 4: in Google's position in the market, or in beings if
Speaker 4: these defaults weren't there, And depending on the legal standard
Speaker 4: that he applies, this could be a very important issue.
Speaker 4: And it's not a behavioral issue so much as a
Speaker 4: well but for these defaults, what would the world look like?
Speaker 2: I believe the judge is going to make his decision
Speaker 2: in December, so we'll find out all this soon enough.
Speaker 2: Thanks so much, Harry. That's Professor Harry First of NYU
Speaker 2: Law School. Coming up next, the Executive Order on artificial intelligence.
Speaker 2: This is Bloomberg.
Speaker 5: We're going to see more technological change in the next
Speaker 5: ten maybe next five years, and we've seen in the
Speaker 5: last fifty years, and that's a fact. As the most
Speaker 5: consequential technology are our time, artificial intelligence is accelerating that change.
Speaker 5: It's going to accelerate at warp speed.
Speaker 2: On Monday, President Joe Biden signed an executive Order on
Speaker 2: artificial Intelligence that he says will make the development of
Speaker 2: AI safer for Americans. Among other things, it establishes standards
Speaker 2: for secure in privacy protections and requires developers to safety
Speaker 2: test new models. Joining me is Reggie Babin, Senior counsel
Speaker 2: at Ach and Gump. How important is this executive order
Speaker 2: in light of the skyrocketing use of AI in recent months.
Speaker 1: That's a good opening question. I would say it is
Speaker 1: significant for two reasons. At a minimum, it serves as
Speaker 1: a clear signal to the world of what the President
Speaker 1: and this administration's priorities are as it relates to artificial intelligence.
Speaker 1: There's been a bit of a vacuum of sorts on
Speaker 1: substantive US leadership on the issue as it relates to
Speaker 1: AI governance, and now there is a clear, digestible set
Speaker 1: of principles and set of mandates that reflect where this
Speaker 1: administration would like to see the technology go. And then
Speaker 1: beyond that, there are those aforementioned mandates, particularly as it
Speaker 1: relates to companies training foundational models and cloud service companies
Speaker 1: that are providing services for foreign customers. There are new,
Speaker 1: previously unreported requirements in THEEO that are likely going to
Speaker 1: have some impact on particularly those companies advancing the most
Speaker 1: advanced AI models and how they go about training and
Speaker 1: reporting on the development of that technology. So it's both
Speaker 1: a huge political signal and will likely shape the global
Speaker 1: AI governance conversation, but also has some fairly significant implications
Speaker 1: for the domestic AI development process and the US's desire
Speaker 1: to maintain its global lead in that space.
Speaker 2: Is it difficult to make rules or you know, suggestions,
Speaker 2: even in an area that's still developing, Yeah, it is.
Speaker 1: It's difficult, though not impossible. The challenge is one how
Speaker 1: do you balance concerns about safety and reducing the risk
Speaker 1: of whatever harms may be perceived or feared, while maintaining
Speaker 1: the flexibility and the dynamic space needed to lead to
Speaker 1: the types of innovations that we all want to see.
Speaker 1: And then on the second piece, if you take as
Speaker 1: a given that the federal government by design moves much
Speaker 1: more slowly than industry normally, and certainly much more slowly
Speaker 1: than this exponentially advancing technology. How do you write rules
Speaker 1: that are both effective but also flexible enough that they
Speaker 1: are still relevant in eighteen months when the technology is
Speaker 1: advanced beyond where it is now. So it's a constant
Speaker 1: challenge trying to regulate in a way that allows for
Speaker 1: continued innovation without undue risk, but also trying to do
Speaker 1: so in a way that takes into account the rapidly
Speaker 1: changing nature of this particular space, which is unique in
Speaker 1: so far as we're moving at an exponential pace while
Speaker 1: trying to regulate through a system that's designed to move
Speaker 1: at something closer to guatial So.
Speaker 2: Let's go through a couple of areas of concern and
Speaker 2: you tell me in how the Executive Order addresses it.
Speaker 2: So a big concern has been privacy, So.
Speaker 1: This is one of the areas where it's a bit
Speaker 1: more limited. There are calls for more stringent practices as
Speaker 1: it relates to the federal government's handling of data of
Speaker 1: American citizens. But there's also the EOS, accompanied by a
Speaker 1: call from the President for Congress to pass comprehensive privacy legislation,
Speaker 1: which I think is indicative of how much more Congressional
Speaker 1: action is needed to see the type of significant movement
Speaker 1: in this space that some have called for. And so
Speaker 1: they're attempting to balance the ability to move forward with
Speaker 1: existing powers with the acknowledgement that more authority is needed
Speaker 1: from Congress if we're actually going to see comprehensive privacy
Speaker 1: movement in a way that has not necessarily been experienced
Speaker 1: to the state.
Speaker 2: Something that I think people can relate to because they've
Speaker 2: seen it. As Biden said that he'd watch deep fakes
Speaker 2: of himself speaking and marveled at it, saying, when the
Speaker 2: hell did I say that? They're asking the Commerce Department
Speaker 2: to develop standards here?
Speaker 1: Yeah, and then content providence is one of the big
Speaker 1: areas that is being hotly debated in Washington. Now. It's
Speaker 1: how do we allow for the type of creative freedom
Speaker 1: that these technologies are going to provide while also acknowledging
Speaker 1: that the potential for widespread dissemination of potentially misleading information,
Speaker 1: whether it be images, voice, or text, has the power
Speaker 1: to be significantly disorienting in a democracy that relies on
Speaker 1: the transfer of reliable information from person to person. So
Speaker 1: there's a request for the Department of Commerce to come
Speaker 1: up with standards or guidance on how to develop standards
Speaker 1: as it relates to managing quote unquote defakes our AI
Speaker 1: produced content. But this is an area where we're probably
Speaker 1: at the beginning stages of getting the federal government's arms
Speaker 1: around how to address the concerns that have been expressed
Speaker 1: in some that are anticipated.
Speaker 2: Yeah, guidance on guidance sounds like. So now there are
Speaker 2: also concerns about workers. I don't know how many workers
Speaker 2: have been displaced by AI already. They directed the Department
Speaker 2: of Labor to try to do something with that.
Speaker 1: Yeah, and your point about not knowing how many have
Speaker 1: been displaced already, this is an area where I think
Speaker 1: there's anticipated displacement and an attempt to get out ahead
Speaker 1: of it to avoid the kind of disorientation you can
Speaker 1: see in the market and as a result society with
Speaker 1: people potentially being pushed out of jobs that are automated
Speaker 1: very quickly. There's also a need to ensure that we
Speaker 1: have the type of skilled labor force in America that
Speaker 1: we need to actually maximize our ability to lead on
Speaker 1: these technologies. So there's both a request for the Department
Speaker 1: of labor to work with the private sector who publish
Speaker 1: best practices on how to mitigate AI's harms to employees,
Speaker 1: but also to solicit information on how and where we
Speaker 1: can increase the flow of immigrants with advanced skills to
Speaker 1: ensure that we have the workforce on hand to continue
Speaker 1: to innovate. So it's a bit of a double edged
Speaker 1: sword where we need more workers to advance technology, but
Speaker 1: we also need protections in place to protect from undoed
Speaker 1: harm to the existing workforce that we have.
Speaker 2: Tell me about how discrimination occurs in hiring systems driven
Speaker 2: by AI. That seems to be a concern.
Speaker 1: Yeah, it's a concern essentially rooted in the nature of
Speaker 1: the data we have, right like, AI systems operate on
Speaker 1: repositories of existing data, and to the extent that data
Speaker 1: flows from systems wherein discrimination has occurred previously, there is
Speaker 1: a risk that by automating on that arguably discriminatory data,
Speaker 1: we increase the risk of future discrimination by basically training
Speaker 1: the systems to act in the way that whether it
Speaker 1: be previous human actors or previous automated systems have And
Speaker 1: so there's a challenge wherein you're trying to train on
Speaker 1: the best available data, but also trying to acknowledge where
Speaker 1: that data may have built in biases, and then trying
Speaker 1: to figure out technologically how you can innovate around those
Speaker 1: existing potentially discriminatory outcomes. And it's a challenge in lending,
Speaker 1: it's a challenge in law enforcement of criminal justice. It's
Speaker 1: one of the bigger I would say social challenges that
Speaker 1: particularly this administration, both through its a I Build Rights
Speaker 1: and now to the order, is trying to get its
Speaker 1: hands around.
Speaker 2: Tell me about concerns about national security and I don't know,
Speaker 2: do national security and cybersecurity go hand in hand or not?
Speaker 1: Yeah, I would say national security in cybersecurity and national
Speaker 1: security and economic security go hand in hand. This is
Speaker 1: an issue, like Mini and Washington at the moment, that
Speaker 1: is colored in large part by questions and concerns around
Speaker 1: the US's relationship, particularly with China, and the desire to
Speaker 1: ensure we maintain and edge and innovation development and deployment
Speaker 1: of AI technology as it could relate to numerous uses,
Speaker 1: including national security specific uses both in terms of offensive
Speaker 1: capacity but also the ability to defend against potential malicious
Speaker 1: cyberactivity that could be supercharged using automated systems, and so
Speaker 1: there's a cybersecurity component and the need to ensure that
Speaker 1: we have technological capacity to defend against beefed up cyber attacks.
Speaker 1: And there's also the need to stay out ahead as
Speaker 1: the global leader in this technology to ensure that we're
Speaker 1: able to incorporate it in whatever ways are deemed necessary
Speaker 1: to maintain advantages across a number of fields related to security.
Speaker 2: Is there anything else in this order that I know
Speaker 2: is pretty long for an executive orders?
Speaker 1: Yeah, No, I would say as far as executive orders go,
Speaker 1: ex massive, there's a lot in there. It reads both
Speaker 1: parts as a document principles, but again a document of mandates.
Speaker 1: And I think there's particularly two important mandates that are
Speaker 1: included that are going to be discussed and deliberated at
Speaker 1: nauseum over the next few months as the Commerce Department
Speaker 1: gets its stated rules in place. And so one is
Speaker 1: the requirement for companies training foundational models are frontier models
Speaker 1: rather to report to the Commerce Department on the development
Speaker 1: of those models. And then the second would be know
Speaker 1: your customer style requirement for cloud service providers who are
Speaker 1: providing services for foreign customers training similarly powerful frontier models
Speaker 1: and it's not exactly clear what the contours of those
Speaker 1: rules and requirements are going to be. There's a pretty
Speaker 1: tight turnaround that's required by the EO. There are standards
Speaker 1: that still have to be developed in order to give
Speaker 1: those requirements the kind of clarity and anteeth frankly that
Speaker 1: they're going to need to be effective. And there's the
Speaker 1: ongoing conversation as to whether and to what extent that
Speaker 1: information will be used to dictate the development and deployment
Speaker 1: of these types of systems. And so I think those
Speaker 1: two are particularly interesting components, given that they are requirements
Speaker 1: and mandates rather than asked for reporting and potentially collecting
Speaker 1: information for future actions.
Speaker 2: Is congressional action really needed in this area and how
Speaker 2: close are we to that?
Speaker 1: Well? Yeah, I think at a minimum, you've seen the
Speaker 1: President say yesterday that congressional action would be needed on
Speaker 1: privacy as the administration sees fit. But there's also federal
Speaker 1: mandates typically require federal funding, and Congress still has the
Speaker 1: power of the purse, and so at a minimum you
Speaker 1: would expect the need for some type of congressional appropriations
Speaker 1: in order to ensure that some where all of these
Speaker 1: policies are able to be achieved successfully. There's also the
Speaker 1: need for potentially federal investment to ensure that we are
Speaker 1: able to lead the world in cutting edge R and D.
Speaker 1: There have been some calls for as much as thirty
Speaker 1: two billion dollars in annual federal investment by twenty twenty six.
Speaker 1: I believe it is from the National AI Security Council.
Speaker 1: So the President, as I understand it, is meeting with
Speaker 1: Majority Leader Schumer and the bipartisan group of Senators who
Speaker 1: are working on this issue today to discuss their continued
Speaker 1: to push for legislation and all of its messaging. Yesterday,
Speaker 1: the administration signaled that it wants to continue working with
Speaker 1: Congress to try to move legislation, and so I think again,
Speaker 1: this is an important document insofar as includes some critical mandates,
Speaker 1: It leverages the federal government's purchasing power to try to
Speaker 1: shape the domestic market. But also it necessarily signals that
Speaker 1: there are some limitations and existing authorities and the need
Speaker 1: for additional Congressional action in order to continue to move
Speaker 1: the American AI governance infrastructure forward.
Speaker 2: So I read that the US has set aside I
Speaker 2: at one point six billion in fiscal twenty twenty three
Speaker 2: for AI, what does that go toward?
Speaker 1: Mostly R and D through DoD and NSF, as I
Speaker 1: understand it. There are probably other pots, but those are
Speaker 1: the two at the top of my mind. Most of
Speaker 1: what we do at the federal level is research and development,
Speaker 1: is advancing standards and basically setting the stage for private
Speaker 1: sector innovation. But again, there are experts who believe that
Speaker 1: considerably more investment is needed at the federal level to
Speaker 1: augment what the private sector is able to do and
Speaker 1: to invest in. Also, the types of public resources are
Speaker 1: going to be necessary to make sure that a wide
Speaker 1: swath of researchers, academics, and others are able to access
Speaker 1: the best technology, which now is very capital intensive and
Speaker 1: certainly not widely available to all who would want to
Speaker 1: conduct research or pursue different types of innovation.
Speaker 2: And is this iss You're gaining a lot of traction
Speaker 2: in DC.
Speaker 1: Yeah, I think it's important to stay explicitly how significantly
Speaker 1: this issue has taken over Washington in my time here.
Speaker 1: The only thing that I could frankly think of as
Speaker 1: even close to it is the COVID response, and that was, yeah,
Speaker 1: it's really I mean, you've had I think over two
Speaker 1: dozen hearings in Congress at this point across the number
Speaker 1: of committees that do not typically share jurisdiction. You have
Speaker 1: this executive order that was released yesterday. You have the
Speaker 1: Senate efforts that's ongoing. It's captured the imagination in a
Speaker 1: way again absent a significant, potentially world historic emergency that
Speaker 1: is ongoing. It is not normal for Congress, Congress in particular,
Speaker 1: but the federal government in general, to spend this much
Speaker 1: time and this much attention and to dive this deep
Speaker 1: on a specific policy issue. And I think it just
Speaker 1: speaks to one the breath of the issue and the
Speaker 1: fact that frankly, advances in AI have the power to
Speaker 1: impact nearly every aspect of our lives and our work,
Speaker 1: but also the rapid expansion and the rapid deployment of
Speaker 1: the technology, at least the perceived rapid expansion and deployment,
Speaker 1: and how that has the ability to the system in
Speaker 1: a way that can trigger political action in a way
Speaker 1: that's steady or progress may not. So it's just I
Speaker 1: don't want folks to take for granted that there was
Speaker 1: a signing ceremony at the White House yesterday and its
Speaker 1: business as usual. This is a wholly unique issue, and
Speaker 1: I have a very difficult time coming up with a
Speaker 1: proper historical analogy because it's not just rushing to try
Speaker 1: to avert disaster, it's also rushing to try to ensure
Speaker 1: we're able to maximize the upside effect. And that's a really,
Speaker 1: really interesting dichotomy that you don't often see with something,
Speaker 1: again that covers nearly every sector of the economy and
Speaker 1: every aspect of American life.
Speaker 2: You think the lawmakers are afraid they'll be replaced by bots.
Speaker 1: No, No, it's something so human about our system of democracy.
Speaker 1: And frankly, I think that the AI systems may be
Speaker 1: smart enough to not want to subject themselves to the
Speaker 1: rigors of public service. It takes a special kind of
Speaker 1: person in particular, but I'm sure they are trying to
Speaker 1: figure out how to best use the bots to ensure
Speaker 1: they're able to better serve their constituents and frankly, to
Speaker 1: maintain office, which is the way that it's going to
Speaker 1: design to work.
Speaker 2: Thanks so much for coming on the show, Reggie. That's
Speaker 2: Reggie Babin, senior counsel at Ach and Gump. And that's
Speaker 2: it for this edition of The Bloomberg Law Show. Remember
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