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Musk vs Altman & Prediction Markets · Bloomberg Law

0:02
Speaker 1: This is Bloomberg Law with June Grossel from Bloomberg Radio.
0:08
Speaker 2: Elon Musk and Sam Altman are facing off in a
0:12
Speaker 2: courtroom in California as their decades long fight over open
0:16
Speaker 2: Ai plays out before a jury. The high profile showdown
0:21
Speaker 2: between the billionaires is the culmination of years of animosity
0:26
Speaker 2: and public feuding over the startup that the pair founded
0:29
Speaker 2: together more than a decade ago, before their relationship soured
0:34
Speaker 2: and they became rivals. Musk alleges that Altman and others
0:39
Speaker 2: at open Ai enriched themselves by abandoning its altruistic principles
0:44
Speaker 2: and converting it to a for profit company with billions
0:48
Speaker 2: of dollars in support from Microsoft. Altman and open Ai
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Speaker 2: accused Musk of harassment and say the real goal of
0:56
Speaker 2: the lawsuit is to undercut competition with his own startup
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Speaker 2: that he co founded in twenty twenty three XAI. Joining
1:05
Speaker 2: me is Bloomberg Legal reporter Madlin Meckelberg, who's covering the trial.
1:10
Speaker 2: They started open Ai a decade ago, when their relationship
1:14
Speaker 2: was quite different.
1:15
Speaker 1: I mean, what happened that is the question. I think
1:20
Speaker 1: that's what we're going to find out over the course
1:22
Speaker 1: of the next three weeks at this trial. Certainly they
1:26
Speaker 1: were partners at the beginning of this enterprise, and obviously
1:30
Speaker 1: their relationship has soured since then. They've become very public
1:34
Speaker 1: bitter rivals, fighting with each other about Ai and specifically
1:39
Speaker 1: about open Ai, this company that they founded, and what
1:42
Speaker 1: should happen there. I think we heard from Elon Musk
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Speaker 1: when he initially left open Ai that he disagreed about
1:49
Speaker 1: the direction that they wanted to take things in. But
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Speaker 1: I don't think that we've gotten much more specifics from
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Speaker 1: them about what exactly happened there to prompt this falling out,
2:00
Speaker 1: and so I think that's something that eager watchers in
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Speaker 1: this space are going to be helping to hear more
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Speaker 1: about over the course of this trial.
2:06
Speaker 2: So Elon Musk brought the lawsuit, and he's looking for
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Speaker 2: one hundred and thirty four million dollars, an eye popping
2:13
Speaker 2: amount is the basic claim that open ai was converted
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Speaker 2: into a for profit company.
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Speaker 1: So, if you'll recall when this case was first filed,
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Speaker 1: it was massive. There were a lot of allegations, and
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Speaker 1: it's been seriously trimmed down since then by the judge
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Speaker 1: and also by Musk himself. Withdrawing some of the allegations.
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Speaker 1: But the crux of the argument here is that open ai,
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Speaker 1: Microsoft and its founders violated the founding mission of open
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Speaker 1: ai to pursue this AI for all mentality by converting
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Speaker 1: from a nonprofit to a for profit entity well through
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Speaker 1: the process they finished in October after quite an undertaking
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Speaker 1: that involved a lot of different parties. So that's the
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Speaker 1: central allegation here. But technically, the two claims that are
3:01
Speaker 1: going to be up before this jury are breach of
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Speaker 1: charitable trust and unjust enrichment.
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Speaker 2: And how do Altman and open ai respond to those allegations.
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Speaker 1: So open ai and Sam Altman stay first of all,
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Speaker 1: deny these allegations, and they say that Elon Musk is
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Speaker 1: harassing them through litigate in this is not the only
3:22
Speaker 1: lawsuit he has involving one of these entities. And they
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Speaker 1: say that it's a clear attempt by him to undercut
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Speaker 1: a competitor in the AI space, because, as you and
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Speaker 1: your listeners know, Elon Musk started his own AI company
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Speaker 1: in twenty twenty three Xai, And so they say that
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Speaker 1: this is clearly a competitive beef between the two. The
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Speaker 1: charges are unfounded and there are plenty to fight them
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Speaker 1: to the noil.
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Speaker 2: And Microsoft is also a defendant.
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Speaker 1: Here, right. Microsoft is a defendant here, and that's because
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Speaker 1: of their significant investments that they made in open Ai,
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Speaker 1: and that funding was part of what made it possible
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Speaker 1: for open Ai to pursue this for profit conversion, because
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Speaker 1: that's what we heard from Sam Altman when all this
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Speaker 1: was happening that in order for them to sustain and
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Speaker 1: continue to meet this mission of providing this tool and
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Speaker 1: service in the way that it's accessible now is because
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Speaker 1: they need private funding. They need to convert to this
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Speaker 1: kind of entity. So, yes, Microsoft is a party as well.
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Speaker 1: We're expecting to hear In addition to hearing from witnesses
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Speaker 1: from open Ai and from Musk Camp, we're also going
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Speaker 1: to hear from executives from Microsoft.
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Speaker 2: Musk and Altman will both be testifying. Musk is very
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Speaker 2: practiced at testifying and he's been called teflon Elon for
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Speaker 2: his success at trial. What about Altman?
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Speaker 1: I think this is going to be the first time
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Speaker 1: that Altman will be testifying in any kind of trial
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Speaker 1: like this. We've heard him speak in committee hearings on
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Speaker 1: Capitol Hill, which you know can have some of the
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Speaker 1: same characteristics of sitting in a jury box, but obviously
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Speaker 1: the stakes here are really different because he defending his
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Speaker 1: business practices as a CEO and decisions that he made
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Speaker 1: in leading this company. So definitely, I think a lot
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Speaker 1: of attention, rightfully so, is being paid to the just
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Speaker 1: huge characters and personalities that these guys are. I mean,
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Speaker 1: when they're coming into the courtroom, they're bringing with them
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Speaker 1: billions of dollars and huge public personas and reputations.
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Speaker 2: Besides testimony, what other evidence do you expect.
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Speaker 1: My understanding is that the evidence that we're going to
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Speaker 1: be able to see at trial is going to include
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Speaker 1: a lot of internal documents about the mission of Open AI.
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Speaker 1: We're going to see emails and messages from executives at
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Speaker 1: these companies talking about what they want the mission to be.
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Speaker 1: We're going to see text messages between Elon Musk and
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Speaker 1: some of his close allies talking about frustrations about the
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Speaker 1: direction that things are heading in. I think we're going
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Speaker 1: to see a lot of internal We've seen quite a
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Speaker 1: few come out already through the course of discovery, but
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Speaker 1: I think we're expecting quite a bit more. Hard to
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Speaker 1: say at this point what that will entail.
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Speaker 2: So we've seen Mosk called Altman quote scam, Altman accusing
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Speaker 2: him of betrayal of Shakespearean proportions, and Altman claiming Musk
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Speaker 2: is insecure and not a happy person. Are we likely
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Speaker 2: to see some of these personal attacks at trial.
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Speaker 1: I think that's kind of what people are expecting, just
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Speaker 1: based on what we've seen from these two guys in
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Speaker 1: the public sphere. You know, they've been even leading up
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Speaker 1: to this trial, they've been posting on social media about
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Speaker 1: it about each other. They're not strangers to talking about
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Speaker 1: their very strong feelings about the other in a public way.
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Speaker 1: But I think one thing that's going to be different
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Speaker 1: here is that we have a judge who has said
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Speaker 1: previously that she doesn't want this case to be about
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Speaker 1: billionaire versus billionaire. She really wants it to be about
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Speaker 1: the issues, and so I think we're going to see
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Speaker 1: her trying to limit some of that. I know that
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Speaker 1: she's restricted what some of the questions that can be
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Speaker 1: asked are specifically open. Aye was hoping to ask must
7:00
Speaker 1: about his Ketemie news. She said that's going to be
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Speaker 1: a no go. But they are going to be allowed
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Speaker 1: to ask him about his attendance at Burning Man, which
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Speaker 1: was apparently during some of the years of some negotiations
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Speaker 1: with open AI. So I think we're going to get
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Speaker 1: a little bit a little taste of that. It's hard
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Speaker 1: to say exactly right now how into the weeds this
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Speaker 1: is going to get on the personal level.
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Speaker 2: So I know, let's talk about the stakes of this
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Speaker 2: trial for open AI. It goes beyond the one hundred
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Speaker 2: and thirty four billion dollars in damages that Musk is
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Speaker 2: asking for.
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Speaker 1: The steaks are huge for open AI. The judges divided
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Speaker 1: this case into two separate sections. One is going to
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Speaker 1: be the liability section, where they're going to decide whether
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Speaker 1: or not the claims are legitimate. But the judge is
7:45
Speaker 1: going to have a whole separate set of arguments about
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Speaker 1: what the remedies should be should she and the jury
7:52
Speaker 1: find in musks favor. And as you said, he's seeking
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Speaker 1: as much as one hundred and thirty four billion dollars
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Speaker 1: that he has said that he would like to give
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Speaker 1: to Verity. He's not intending to keep that money for himself.
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Speaker 1: He wants to give it back to the open AI's
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Speaker 1: charitable arm. At the conclusion of this, should he be
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Speaker 1: awarded that, but you're right, there are other stakes here
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Speaker 1: besides the dollar amount, and that includes a request from
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Speaker 1: Musk that Altman and the president of open AI, Greg Brockman,
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Speaker 1: be removed from their leadership positions. And he's also seeking
8:22
Speaker 1: to restore the startup status as a full nonprofit research organization,
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Speaker 1: so unwinding this for profit conversion that we saw them
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Speaker 1: spend the past year trying to achieve, and so there's
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Speaker 1: definite concern that that could destabilize the company, especially during
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Speaker 1: kind of this critical moment when there's this kind of
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Speaker 1: public offering maybe in the future, So the stakes are huge.
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Speaker 1: It's hard to say right now whether any of those remedies,
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Speaker 1: of course, are actually going to be awarded. They are
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Speaker 1: huge asks that can't be overstated. But yeah, if they
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Speaker 1: were to come to pass, I think open AI would
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Speaker 1: definitely be facing a big question mark about what the
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Speaker 1: future holds.
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Speaker 2: The jury verdict is only going to be advisory. Do
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Speaker 2: you know why the judge chose an advisory opinion.
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Speaker 1: It's quite unusual to have an advisory opinion for the
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Speaker 1: liabilities phase of a trial. Sometimes you'll see that where
9:12
Speaker 1: a jury can offer suggestions to the judge when it
9:15
Speaker 1: comes to damages how much money they think should be awarded,
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Speaker 1: and the judge will come in and say, actually, no,
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Speaker 1: we're going to cut this down or it should be higher.
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Speaker 1: I'm not exactly sure why the judge decided to do
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Speaker 1: that in this case, but what we do know is
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Speaker 1: that once the jury hands in its verdict, once they've
9:31
Speaker 1: made these arguments about remedies, the judge is going to
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Speaker 1: take all of that back. She's going to be sitting
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Speaker 1: there through all the arguments and she's going to be
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Speaker 1: weighing her own view of the arguments and the legal
9:41
Speaker 1: arguments being presented, but also taking into consideration this suggestion
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Speaker 1: from the jury about what should be done and how
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Speaker 1: to resolve this very complicated case that involves so many
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Speaker 1: huge public figures and huge companies and this hot button
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Speaker 1: issue of artificial intelligence.
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Speaker 2: There'll be nine people on the jury. What are some
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Speaker 2: of the concerns about jury selection when you have two
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Speaker 2: such well known billionaires opposing each other.
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Speaker 1: That's a great question. I mean, when you're talking about
10:12
Speaker 1: these huge companies and these huge names, a lot of
10:15
Speaker 1: people are going to come in with reconceived notions about them.
10:18
Speaker 1: They're going to have strong opinions about them. Least if
10:21
Speaker 1: they don't have strong opinions about them, they're going to
10:23
Speaker 1: know who they are. And I think it's always a
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Speaker 1: complicating factor when one of your parties is incredibly wealthy
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Speaker 1: and known for being incredibly wealthy, and in this case,
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Speaker 1: there is more than one person in that room that's
10:35
Speaker 1: got applied a lot of money to their name, and
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Speaker 1: so I think that's definitely a factor for jurors. There's
10:40
Speaker 1: also going to be like a technological element of this
10:43
Speaker 1: and their familiarity with artificial intelligence and whether that's you know,
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Speaker 1: do they use CHATGPT, do they use XAI, do they
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Speaker 1: use rock any of these tools, because that could certainly
10:54
Speaker 1: factor into how they view this case. So those are
10:56
Speaker 1: all kind of thorny issues that lawyers are going to
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Speaker 1: be navigating. They're trying to nail down who's going to
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Speaker 1: sit in the jury box during jury selection. Sam Altman
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Speaker 1: and Greg Brockman actually were there in the room as
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Speaker 1: jurors were being questioned, which is I think quite unusual
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Speaker 1: for someone of that high profile to attend jury selection.
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Speaker 2: That looks like a good strategic move to me, letting
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Speaker 2: the jurorsye your concerned and involved in the case. Thanks
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Speaker 2: so much, Madlin. We'll check back with you as the
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Speaker 2: trial goes on. That's Bloomberg. Legal reporter Madelein Mecklberg. Coming
11:29
Speaker 2: up next. A soldier will be arraigned on charges of
11:33
Speaker 2: using classified information to make four hundred thousand dollars trading
11:37
Speaker 2: on the timing of the capture of Nicolas Maduro. This
11:41
Speaker 2: is Bloomberg. A US Army soldier has been charged with
11:48
Speaker 2: using classified information about the timing of the capture of
11:53
Speaker 2: then Venezuelan President Nicolas Maduro to make more than four
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Speaker 2: hundred thousand dollars on polymarkets prediction market.
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Speaker 3: It's a little like Peter Rose. Peter Rose, he kept
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Speaker 3: him out of the Hall of Fame because he bet
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Speaker 3: on his own team.
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Speaker 2: Federal prosecutors say Master Sergeant Gannon Ken van Dyke, a
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Speaker 2: Special Forces soldier who was involved in the planning and
12:15
Speaker 2: execution of Operation Absolute Resolve, the military effort to capture Maduro,
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Speaker 2: placed a total of about thirteen bets from December twenty
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Speaker 2: seventh through the evening of January second, all taking yes
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Speaker 2: positions on various Maduro related questions posed by the trading platform.
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Speaker 2: President Trump said last week that he has issues with
12:40
Speaker 2: the concept of event betting platforms.
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Speaker 3: The whole world unfortunately, has become somewhat of a casino,
12:48
Speaker 3: and you look at what's going on all over the world,
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Speaker 3: in Europe and every place, they're doing these betting things.
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Speaker 3: I was never much in favor of that. I don't
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Speaker 3: like it conceptually, but it is what it is. No
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Speaker 3: I think that I'm not happy with any of those.
13:03
Speaker 2: However, His son, Donald Trump Junior, is an advisor to
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Speaker 2: both Calshi and Polymarket, and an investor in Polymarket through
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Speaker 2: the venture fund where he's a partner. My guest is
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Speaker 2: Joshua Mitt's, a professor at Columbia Law School and an
13:17
Speaker 2: authority on insider trading, securities law, and corporate law. Explain
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Speaker 2: what the sergeant's accused of?
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Speaker 4: Sure, So, these websites known as betting markets sometimes prediction markets.
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Speaker 4: They are platforms which allow individuals to essentially purchase a
13:39
Speaker 4: contract that pays off if in a future event happens,
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Speaker 4: and if the event does not happen, then you lose
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Speaker 4: all the money you paid. So is there like any
13:49
Speaker 4: other markets where you might pay you twenty cents then
13:51
Speaker 4: you can make a dollar or lose all of your
13:53
Speaker 4: twenty cents, and these markets on a website known as
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Speaker 4: polymarket have I've sort of sprung into existence for all
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Speaker 4: sorts of future events. And in this case, the sergeant
14:06
Speaker 4: purchased contracts which paid off one dollar if Maduro was
14:13
Speaker 4: I think it was deposed as leader of Venezuelers, might
14:15
Speaker 4: have been madurou out by a certain date, something of
14:18
Speaker 4: that effect. And the sergeant purchased these contracts when they
14:23
Speaker 4: were relatively inexpensive, so I think in the order of
14:27
Speaker 4: single digit sense, maybe around seven cents or so of contract.
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Speaker 4: And of course he knew, very few people knew at
14:34
Speaker 4: the time he purchased the contract that the operation was underway.
14:38
Speaker 4: And so when the operation occurred and the contracts value
14:45
Speaker 4: went from whatever it was seven cents eight cents to
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Speaker 4: one dollar per contract, and he had purchased a large
14:52
Speaker 4: number of contracts, he made just short of half a
14:56
Speaker 4: million dollars or so in profit.
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Speaker 2: And is he being charged because he used classified information
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Speaker 2: to make the bets?
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Speaker 4: That's exactly right. I mean, the operation itself was classified information,
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Speaker 4: so the capture of rendition of Maduro was non public
15:18
Speaker 4: information that it was going to happen. When it happened,
15:20
Speaker 4: and so the way that prosecutors have set forth the
15:24
Speaker 4: theory of criminal liability here is that he was essentially
15:28
Speaker 4: misappropriating information that belonged to the federal government and information
15:33
Speaker 4: that was non public information that was classified for personal gain.
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Speaker 2: He placed a total of thirteen bets from December twenty
15:41
Speaker 2: seventh through January tewod All yes on various Maduro related questions.
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Speaker 2: Is that an any defense for him that he was
15:51
Speaker 2: placing thirteen and making different predictions.
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Speaker 4: So there's two questions here. I mean, they're on polymarket,
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Speaker 4: you'll often see minor vary and variations of the same
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Speaker 4: underlying contract or. It could be that an event happens
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Speaker 4: by a particular date, but there might be slight variations
16:09
Speaker 4: in the date. It could be a day before, a
16:11
Speaker 4: day after. So an individual who is in possession of
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Speaker 4: material non public information about one of these future events
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Speaker 4: may decide to trade in connection with that information without
16:24
Speaker 4: necessarily pinning themselves down to one specific date. It could
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Speaker 4: be that you are highly highly confident that an event
16:30
Speaker 4: is going to happen by a particular point in time,
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Speaker 4: but you're not sure exactly when, so you hedge your
16:36
Speaker 4: bets a little bit on the specific contract. I think
16:39
Speaker 4: your question, though, is getting at a broader question, which
16:41
Speaker 4: is that there isn't a lot of case law, or
16:44
Speaker 4: it's not very clear, and this is such a new
16:47
Speaker 4: and emerging area what it means for information to be
16:51
Speaker 4: material in this context and for the misappropriation of information
16:55
Speaker 4: to be more than the sort of garden variety, you know,
16:59
Speaker 4: general in tuitions that people have from their exposure to
17:04
Speaker 4: ordinary speculation about the future. And I would imagine that
17:08
Speaker 4: the sergeant will try to make the argument that he
17:13
Speaker 4: did not necessarily have this level of specificity which would
17:17
Speaker 4: be required to render this an actual misappropriation of information,
17:22
Speaker 4: but simply that he had a general sense that something
17:25
Speaker 4: was going to happen, and that general sense was not
17:28
Speaker 4: any sort of information that had been misappropriated, but rather
17:33
Speaker 4: his own impression or analysis of what he had been
17:37
Speaker 4: exposed to.
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Speaker 2: And it was poly Market that turned him in, that
17:40
Speaker 2: alerted the authorities.
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Speaker 4: Poly Market did, and one of the facts from the
17:45
Speaker 4: indictment we see is that he used a virtual private network.
17:49
Speaker 4: Because poly market is actually not accessible under essentially an
17:54
Speaker 4: agreement with the CFTC. They do have a small US
17:58
Speaker 4: market that they've been working with, but the poly markets
18:01
Speaker 4: primary markets are not accessible to US residents, so he
18:07
Speaker 4: had to use a VPN to use poly Market. That
18:09
Speaker 4: wasn't the problem, but it did explain why it was
18:12
Speaker 4: a little difficult for poly Market. Polymarket, you know, they
18:15
Speaker 4: didn't have an obvious indication based on his IP address
18:19
Speaker 4: that he was coming from the United States. He did. However,
18:23
Speaker 4: my understanding from the indictment is that he had shared
18:26
Speaker 4: his actual email address with poly market and that is
18:29
Speaker 4: what gave them a trail, if you will, back to
18:32
Speaker 4: this individual.
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Speaker 2: So last week Calsha, another predictions platform, said it had
18:38
Speaker 2: fined and banned three political candidates who had bet on
18:41
Speaker 2: their own elections. So is it up to the prediction
18:45
Speaker 2: platforms themselves to police themselves.
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Speaker 4: Well, we are seeing increased regulatory and enforcement attention on this.
18:53
Speaker 4: Jake Clayton gave a speech a couple months ago, this
18:57
Speaker 4: was back in February, that this was going to be
18:58
Speaker 4: an area of priority the most recent indictment, so all
19:02
Speaker 4: this suggests that this is growing in importance and focus
19:06
Speaker 4: for federal prosecutors. The reality is that most cases are
19:11
Speaker 4: unlikely to be as simple as this one. And you
19:15
Speaker 4: mentioned these three congressional candidates who had placed bets essentially
19:19
Speaker 4: on their own markets and markets concerning their own campaigns.
19:25
Speaker 4: That's a form of manipulation or a form of influencing
19:29
Speaker 4: the outcome of a contract, which is also prohibited. But
19:33
Speaker 4: these are again the exception. I have a new paper
19:35
Speaker 4: which looked systematically at polymarket, and we think that there's
19:41
Speaker 4: quite a bit of informed trading. Not all of this
19:44
Speaker 4: will be illegal misappropriation of information, but anomalous or suspicious trading,
19:50
Speaker 4: which suggests that perhaps there could be much more widespread
19:54
Speaker 4: exploitation of this sort of information than these individual idiosyncratic
19:59
Speaker 4: cases might suggest.
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Speaker 2: Yeah, what about there was apparently there was also trading
20:06
Speaker 2: on the Iran war, and then the White House put
20:10
Speaker 2: out a statement warning against insider trading. Yeah.
20:16
Speaker 4: Well, as we explain in the paper, I mean this
20:18
Speaker 4: happened in a number of cases, both before the February
20:23
Speaker 4: Iran War, the Second Ran War, as well as the
20:27
Speaker 4: June twenty twenty five Iran War. There were other events,
20:32
Speaker 4: So we do see anomalist trading, large purchases. Again, unless
20:37
Speaker 4: someone is going to put their email address in, it's
20:39
Speaker 4: going to be quite hard for poly Market in particular
20:42
Speaker 4: poly market runs on the blockchain. The blockchain is much
20:46
Speaker 4: more anonymous in its structure than a traditional market, so
20:51
Speaker 4: there's very little know your customer or similar regulatory disclosures
20:56
Speaker 4: which are required. So it's going to be more difficult
20:59
Speaker 4: formarket and regulators to chase down whoever might have been
21:04
Speaker 4: trading in advance of these events. And the other thing
21:07
Speaker 4: is it's important to recognize that not all lucky trading
21:11
Speaker 4: is on the basis of inside information. Some of it
21:14
Speaker 4: may be on the basis of putting lots of pieces
21:16
Speaker 4: of information together, but it's not necessarily using some misappropriated
21:21
Speaker 4: facts that only you possess. And so we don't know
21:24
Speaker 4: in any of these cases whether the traders might have
21:27
Speaker 4: just connected some dots that the rest of us had
21:29
Speaker 4: not yet connected, in which case, under the law, they're
21:33
Speaker 4: entirely entitled to benefit from the profits of that work.
21:37
Speaker 2: What concerns do you have about the prediction markets.
21:42
Speaker 4: Well, if in fact there are episodes even episodically even
21:47
Speaker 4: here there where government officials or those like the sergeant
21:52
Speaker 4: and possession of this sort of information are rushing out
21:54
Speaker 4: to these markets to profit off of that information, there
21:58
Speaker 4: can be a number of concerning collateral consequences. So one
22:02
Speaker 4: could be that our adversaries learn from this sort of trading.
22:06
Speaker 4: So if there's any exploitation of information that takes the
22:09
Speaker 4: form of large transactions prior to national security or military actions,
22:15
Speaker 4: that information is broadcast immediately globally, and so it could
22:19
Speaker 4: in fact put our soldiers in harms way. And I
22:22
Speaker 4: believe the prosecution referred to this as betrayal of his
22:26
Speaker 4: fellows servicemen, and I think there's definitely truth to that.
22:30
Speaker 4: There's also a question around whether the profits that could
22:34
Speaker 4: be made from these sorts of contracts may have a
22:37
Speaker 4: first order of factor, may skew the way that individuals
22:41
Speaker 4: behave So if I know that if I take a
22:43
Speaker 4: certain action, I'm going to profit personally or my friends
22:47
Speaker 4: are going to profit personally, that might introduce a form
22:50
Speaker 4: of corruption to my decisions. We see certain forms of
22:54
Speaker 4: this in the extreme, so called mention markets, where contracts
22:58
Speaker 4: that pay out if a public says something. And you
23:01
Speaker 4: can start to imagine how this can create incentives to
23:04
Speaker 4: say certain things and essentially, you know, redirect and redistribute
23:09
Speaker 4: who's winning from these mentioned market bets. So this sort
23:13
Speaker 4: of activity, if it continues to grow and aggregate, and
23:16
Speaker 4: it's not just widespread gambling or widespread betting. It can
23:20
Speaker 4: actually change potentially the way people behave.
23:24
Speaker 2: Coming up next on the Bloomberg Law Show, I'll continue
23:27
Speaker 2: this conversation with Professor Mitz. The Commodity Futures Trading Commission
23:32
Speaker 2: lodged a parallel civil complaint against the soldier, the first
23:36
Speaker 2: time the regulator filed a prediction markets insider trading case.
23:40
Speaker 2: Also the first time the agency used what's known as
23:43
Speaker 2: the Eddie Murphy rule in an insider trading case. I'm
23:47
Speaker 2: June Grosso and you're listening to Bloomberg. A US Army
23:51
Speaker 2: soldier will be arranged tomorrow in New York for using
23:55
Speaker 2: classified information about the timing of the capture of then
23:58
Speaker 2: Venezuela and pressident Nicolas Maduro to make more than four
24:03
Speaker 2: hundred thousand dollars trading on polymarkets prediction market. I've been
24:08
Speaker 2: talking to Columbia Law School professor Joshua Mittz. I mean
24:12
Speaker 2: it sounds like gambling, you place a bet on something.
24:15
Speaker 2: Yet there is this battle between some states and the
24:19
Speaker 2: commadi's Future Trading Commission about who will regulate the markets
24:25
Speaker 2: and the States say it's gambling and they should regulate it.
24:30
Speaker 2: The CFTC says, no, it's not, and they've sued three states.
24:34
Speaker 2: I mean, what do you think.
24:37
Speaker 4: Well, these contracts in many ways very similar to the
24:42
Speaker 4: sort of if you look at the definition of a
24:45
Speaker 4: swap or of a future that you know, they seem
24:47
Speaker 4: to satisfy these definitions that the CFTC has statutorily. In part,
24:53
Speaker 4: they lend themselves very naturally to the CFTC framework because
24:56
Speaker 4: they are traded on markets with trading price. Whereas traditionally
25:02
Speaker 4: betting was against some house accounts, so you would you
25:05
Speaker 4: would open a bet against let's say the dealer, and
25:09
Speaker 4: the dealer would take a particular position, whereas these platforms
25:13
Speaker 4: look more like financial markets and that they match buyers
25:15
Speaker 4: and sellers. The reality is that this is this is
25:19
Speaker 4: an area of ongoing litigation, and I would expect to
25:22
Speaker 4: see potentially this reached the Supreme Court. I believe CALCI
25:25
Speaker 4: just won in the Third Circuit against an attempt by
25:28
Speaker 4: States New Jersey to regulate its activities. So I think
25:32
Speaker 4: we will see increasing litigation around the scope of the
25:37
Speaker 4: CFTC statutory authority. If I had to place a bet
25:40
Speaker 4: on it no pun intended. I would say that perhaps
25:43
Speaker 4: the CFTC is likely to win this in the end.
25:46
Speaker 2: I mean, the chairman of the CFTC, Mike Zellig, seems
25:51
Speaker 2: very supportive of the prediction markets. He called them exciting products,
25:57
Speaker 2: and he scrapped a Biden rule that would have restricted
26:01
Speaker 2: them like everything else. I guess, and life does it
26:04
Speaker 2: depend on who's in charge of the CFTC.
26:07
Speaker 4: I think that's right. I also think that there's regulators
26:11
Speaker 4: prefer to establish a sort of area of the market
26:15
Speaker 4: that they consider legitimate and then an area of the
26:17
Speaker 4: market that they consider illegitimate. This is also true for
26:20
Speaker 4: industry participants. Industry participants and regulators in any industry would
26:25
Speaker 4: like to have sort of the accepted safe activity and
26:28
Speaker 4: then the unacceptable dangerous activity, and the latter is what
26:32
Speaker 4: the regulators cracked down on. It creates a need both
26:35
Speaker 4: for the regulation and it legitimizes the industry. If you
26:39
Speaker 4: had no industry, you would have no regulators. So they
26:41
Speaker 4: both have an interest in this outcome, whether it's good
26:45
Speaker 4: or not for society. There is an economic argument that
26:48
Speaker 4: it is beneficial for society to have this information, particularly
26:52
Speaker 4: in the context of macroeconomic or geopolitical events because there's
26:56
Speaker 4: an aggregation of information that happens, So every participant has
26:59
Speaker 4: a particular view, and in the end, the one who's
27:02
Speaker 4: willing to put the most money behind their view determines
27:04
Speaker 4: the price, and we all can look and learn. It's
27:06
Speaker 4: kind of like a live poll, and this gives some
27:10
Speaker 4: information about the likelihood of future events and we can
27:12
Speaker 4: organize our activity accordingly. That's a little bit of an
27:16
Speaker 4: idealistic notion, but it may bear out in some cases
27:20
Speaker 4: that there's value in having this sort of this sort
27:23
Speaker 4: of market. At the end of the day, the question
27:25
Speaker 4: is are there steps that can be taken that make
27:27
Speaker 4: these markets safer, that make them less dangerous for ordinary
27:32
Speaker 4: participants who may not have this sort of non public
27:35
Speaker 4: information that we're talking about, And are there potentially, you know,
27:39
Speaker 4: external effects like leaking information out or changing the way
27:44
Speaker 4: people make decisions which weren't particular regulatory scrutiny.
27:48
Speaker 2: The CFTC has filed a civil complaint against the soldier.
27:53
Speaker 2: It's the first time it filed a complaint in connection
27:56
Speaker 2: with the prediction markets. It's also the first time the
27:59
Speaker 2: agency has used what's known as the Eddie Murphy rule
28:03
Speaker 2: in an insider trading case tell us about that.
28:06
Speaker 4: This is a rule which basically prohibits for Synthon Dot
28:09
Speaker 4: Frankact prohibits the misappropriation of information that is held by
28:14
Speaker 4: the government. And there's some technical history here in the
28:18
Speaker 4: context of insider trading law that I won't get into
28:21
Speaker 4: all the details right now, but basically, traditionally there was
28:25
Speaker 4: some question around whether information held by the government could
28:29
Speaker 4: satisfy these fraud statutes which are used for insider trading law.
28:34
Speaker 4: The classical sort of view of insider trading was that
28:38
Speaker 4: it involved information that belonged to a company, and trading
28:42
Speaker 4: on the basis of that information was a kind of
28:45
Speaker 4: deception of the shareholders of the company or a deception
28:49
Speaker 4: of the source of the information, and it had a
28:53
Speaker 4: very commercial context in which it arose. Now, these cases,
28:58
Speaker 4: like the case of the Urgent, are cases involving the
29:02
Speaker 4: misappropriation of information received from the government or received pursu
29:06
Speaker 4: into a governmental role, and the Eddie Murphy rule clarifies
29:11
Speaker 4: that that information can also be misappropriated. So what we're
29:17
Speaker 4: seeing now are new ways to exploit information. I mean,
29:20
Speaker 4: you might say from the standpoint of what's good for society.
29:23
Speaker 4: It's better to have these misappropriation rules because the risk
29:28
Speaker 4: to society of stealing information that belongs to the public
29:31
Speaker 4: is greater. But it is a different context than we
29:35
Speaker 4: initially thought traditionally of insider trading as applying to individual companies.
29:39
Speaker 2: And the rule is nicknamed the Eddie Murphy rule after
29:43
Speaker 2: the nineteen eighty three movie Trading Places, where the characters
29:47
Speaker 2: use a stolen Department of Agriculture report to manipulate the
29:52
Speaker 2: orange juice market that was part of the Dodd Frank law.
29:56
Speaker 2: Do you think we need a federal law to handle
29:58
Speaker 2: the prediction markets.
30:00
Speaker 4: Well, we definitely need to see more work on the
30:04
Speaker 4: prediction markets more generally, and there are some proposals. The CFTC,
30:08
Speaker 4: for example, has a Notice of Proposed Rulemaking comment period
30:11
Speaker 4: that's ending in a few days on April thirtieth, and
30:15
Speaker 4: the CFTC has invited commentary on the question of whether
30:18
Speaker 4: the prediction markets should be regulated more that could take
30:22
Speaker 4: the form of rulemaking. There are some legislative proposals to
30:25
Speaker 4: clarify other settings, such as congressional settings. For example, congressional
30:30
Speaker 4: staffers and others who may want to rush out and
30:32
Speaker 4: trade on prediction markets on the basis of information, and
30:36
Speaker 4: this legislation would clarify that that that's not permitted. Beyond that,
30:41
Speaker 4: I think there's a broader challenge here that's really more
30:44
Speaker 4: of an enforcement challenge than a legislative challenge. If you
30:48
Speaker 4: look globally at the activity here and you think, well,
30:52
Speaker 4: it could be originating anywhere around the world. The challenge
30:56
Speaker 4: I see it is more of a cooperation and coordination challenge.
31:01
Speaker 4: How do you get different components of the regulatory and
31:05
Speaker 4: enforcement apparatus around the world to work together, whether that's
31:08
Speaker 4: financial institutions, whether that's prosecutors, whether that's market regulators. And
31:13
Speaker 4: that's more of an institutional challenge than it is a
31:16
Speaker 4: legislative challenge. How you need to get national governments to
31:19
Speaker 4: cooperate and root out essentially this sort of transnational exploitation
31:24
Speaker 4: of information, because in many cases it's not going to
31:27
Speaker 4: be only in the United States. It's going to be
31:29
Speaker 4: especially on poly market on the blockchain, could be anywhere
31:32
Speaker 4: around the world.
31:33
Speaker 2: Why do you think these prediction markets have become so
31:36
Speaker 2: popular so fast?
31:38
Speaker 4: Well, just say, I think what's important for you know,
31:41
Speaker 4: someone who's never thought about this, I think to understand
31:44
Speaker 4: is the context that you know, this is not the
31:47
Speaker 4: first iteration of sort of gambling that we've seen in
31:51
Speaker 4: the financial world in recent years. I would say traditionally
31:56
Speaker 4: speculation was viewed as almost a necessary by product of investing.
32:01
Speaker 4: So you might buy or sell stocks, but you kind
32:03
Speaker 4: of knew that what you at the end of the
32:05
Speaker 4: day needed to do was to buy and invest in companies.
32:08
Speaker 4: Then we started to see more gambling and gamification of
32:13
Speaker 4: the financial markets in the last five or six years.
32:16
Speaker 4: It started with Game Stop, we saw with meme stocks,
32:19
Speaker 4: We saw with crypto, a sort of increasing acceptance of
32:22
Speaker 4: this sort of gambling and risk taking that had very
32:26
Speaker 4: little connection with any kind of underlying investment thesis. And
32:30
Speaker 4: so it probably should not surprise us that the prediction
32:34
Speaker 4: markets emerged on the backdrop of this societal trend. And
32:37
Speaker 4: so I think the broader question here really to think
32:39
Speaker 4: about is why is it that these prediction markets have
32:42
Speaker 4: in fact become as popular as they have the insider
32:46
Speaker 4: trading opportunities that we document in our research, and that
32:49
Speaker 4: the basis of this indictment, they wouldn't exist if you
32:52
Speaker 4: did not have an active, frothy market for people to
32:56
Speaker 4: trade in and out of four hundred and fifty five
32:58
Speaker 4: hundred thousand dollars that a particular trader made, where four
33:02
Speaker 4: and fifty five hundred thousand dollars of losses suffered by
33:05
Speaker 4: others in the market. So that means that there's a
33:07
Speaker 4: lot of activity out there that can be exploited. And
33:11
Speaker 4: there's a broader question as to why these markets have
33:14
Speaker 4: exploded in popularity and the increasing acceptance perhaps societally, of
33:19
Speaker 4: this sort of activity may have something to do with it.
33:21
Speaker 2: This is a topic I'm sure we'll hear more and
33:24
Speaker 2: more about in the coming days. Thanks so much for
33:27
Speaker 2: joining me. That's Columbia Law School professor Joshua Mitts, and
33:31
Speaker 2: that's it for this edition of The Bloomberg Law Show.
33:34
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33:36
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33:41
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33:49
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33:53
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