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