Speaker 1: Welcome to Votes and Verdicts. Hosted by the Litigation and
Speaker 1: Policy team at Bloomberg Intelligence, the investment research arm of
Speaker 1: Bloomberg LP. This podcast series examines the intersection of business
Speaker 1: policy and the law. I'm Justin Terracey antitrust litigation and
Speaker 1: policy analysts here at BI. Before we jump into today's episode,
Speaker 1: just a quick word about Bloomberg Intelligence, where the investment
Speaker 1: research platform on the Bloomberg Terminal, with five hundred analysts
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Speaker 1: and we have outlooks on more than ninety industries and
Speaker 1: one hundred market indices, currencies and commodities. Steve, Welcome to
Speaker 1: Votes and Verdicts.
Speaker 2: Welcome Justin.
Speaker 1: So Steve Berman is joining us today. He's the managing
Speaker 1: part of the eponymous Hoggins Berman, which he co founded
Speaker 1: in nineteen ninety three. And I can say from my
Speaker 1: own time working as a plaintiff's lawyer that Steve and
Speaker 1: the firm are truly top notch. Steve's firm has run
Speaker 1: case leading cases on everything from big tobacco to widespread
Speaker 1: automotive defects to just about every corner of antitrust, consumer protection,
Speaker 1: and securities class actions you can think of. Truly, the
Speaker 1: list of matters is endless, and the value of Hoggins
Speaker 1: Berman settlements goes unmatched by most plaintiffs, most on the
Speaker 1: plaintiffs side of the v partner. Today Today's chat, Steve
Speaker 1: leads Hoggins Berman's work on anti trust, and cases in
Speaker 1: this practice area alone have secured settlements valued at more
Speaker 1: than twenty seven billion dollars. Steve's accolades are endless, with
Speaker 1: the National Law Journal even proclaiming him as one of
Speaker 1: the one hundred most powerful lawyers in the nation. So,
Speaker 1: Steve's so glad to have you here with us today.
Speaker 1: And just kind of a threshold question, we ask all
Speaker 1: of our guests kind of brought what brought you to
Speaker 1: where you are today? You know what got you started litigating,
Speaker 1: and you know what made you kind of found the
Speaker 1: firm when you did.
Speaker 3: And I went to law school, I decided right away
Speaker 3: I wanted to be a trial lawyer.
Speaker 1: I don't know why, for better or worse, right, Yeah.
Speaker 3: And I remember I got into a big argument with
Speaker 3: my academic advisor, Justice Scalia, because I turned down law
Speaker 3: review because I wanted to go right away to the clinic,
Speaker 3: because I wanted to get into the courtroom as soon
Speaker 3: as I could.
Speaker 4: Interesting, why would you turn down law review.
Speaker 2: It's a path to a clerkship, for sure. It's like
Speaker 2: I don't want a clerk.
Speaker 3: I want to get out and get into the court.
Speaker 3: As to why, you know, I founded my firm. I
Speaker 3: was at a firm that was mainly a defense firm,
Speaker 3: but I was the little plaintiffs arm and I had
Speaker 3: a case for a family who's young seven year old
Speaker 3: had lost a kidney because of Ecoli contimidation, and it
Speaker 3: was heartbreaking.
Speaker 2: My kids were the exact same age.
Speaker 3: So I went to take the case and my firm said, no,
Speaker 3: we might get we might represent one of the insurance company.
Speaker 4: Got it, you got it, get it.
Speaker 3: I got to take this case, and so we went
Speaker 3: out and started our firm.
Speaker 4: Interesting.
Speaker 1: Interesting, Yeah, I think that's why myself and many folks
Speaker 1: who ended up on the plaintiff side kind of kind
Speaker 1: of felt like doing that. You know, you kind of
Speaker 1: kind of work on the defense side after a while,
Speaker 1: and you kind of see some of the things you're
Speaker 1: working on, and maybe rubs you.
Speaker 4: The wrong way.
Speaker 1: But you know, right now, specifically on anti trust, it's
Speaker 1: an incredibly busy time, you know, I think, you know,
Speaker 1: especially in enforcers, seem really focused on things like big tech.
Speaker 1: There's been this revival of anti trust I think at
Speaker 1: the government level. But what are you kind of seeing
Speaker 1: as the largest issues are trends in the space for
Speaker 1: antitrust right now.
Speaker 3: Well, certainly big tech. So I think I have five
Speaker 3: anti trust cases against Amazon.
Speaker 1: Well, yeah, I mean I've been at the metatrial this
Speaker 1: week myself. There's so much going on.
Speaker 3: Yeah, so Amazon is resisting one of my cases saying
Speaker 3: it's too big to sort of if I remember the
Speaker 3: old banks were too big to.
Speaker 1: Fail, Yeah, yeah, this is the Yeah, we're too.
Speaker 3: Big to certify because there'll be like two hundred and
Speaker 3: thirty million Americans in this class because basically everyone who.
Speaker 2: Shopped on Amazon has been subject to their price.
Speaker 4: Fixing, right right, So we're very busy in.
Speaker 3: All kinds of high tech cases against Amazon and Apple.
Speaker 3: And then I think we're the leading edge on these
Speaker 3: cases involving using algorithms to set prices in either the
Speaker 3: hotel industry, the leasing industry, or in the protein industry would.
Speaker 1: Call it definitely. Yeah, I know we'll get we'll get
Speaker 1: into the Gibson case specifically, and you know, agricultural or
Speaker 1: protein cases I think a little bit later on too,
Speaker 1: But I guess you know those industries a lot of
Speaker 1: any other industries you're kind of seeing anti trust issues
Speaker 1: bubbling up in or those the primary ones you're you're
Speaker 1: focused on at the moment.
Speaker 2: I think that's primary focus on the moment.
Speaker 1: Got it, got it? And kind of broader question with
Speaker 1: regard to class actions, you know, more broadly. Right, So
Speaker 1: even touching upon areas like labor or securities, are you
Speaker 1: seeing any trends there? I know we've got this Lab
Speaker 1: Corp Case coming up the Supreme Court relatively soon. Not
Speaker 1: sure if you have any thoughts on that, but I'm
Speaker 1: not seeing a lot of talk about it lately, and
Speaker 1: it interests me that I'm not, because I feel like
Speaker 1: it actually could be a really big deal for how
Speaker 1: things progress.
Speaker 2: So the Plane's bar is very worried about the Lab
Speaker 2: Court case.
Speaker 3: Sure, Sure, A small group of us have had calls
Speaker 3: with the Larriors and help them, you know, work on
Speaker 3: the briefs. We've been writing Amekas briefs but given them
Speaker 3: conservative nature of the court, anytime a PLANEFFS case comes up,
Speaker 3: no matter whether it's this class issue or right right,
Speaker 3: any issue, you're more nervous than you used to be.
Speaker 1: Definitely, I feel like it's not a small statement to
Speaker 1: say the court's been chipping away at Rule twenty three
Speaker 1: anyway again over the last decade or two. So I
Speaker 1: feel like you see the Davis case with this whole
Speaker 1: concept of an uninjured plaintiff and whether you're consisting in
Speaker 1: a class on that, and it definitely raises a little
Speaker 1: bit of concern given the composition of the court being
Speaker 1: what it is.
Speaker 3: But you never know, because when my inc Double eight
Speaker 3: case was taken by the court, I was like, oh
Speaker 3: my god, this is this is a disaster.
Speaker 2: And then I got a nine to zero opinion.
Speaker 1: Yeah, amazing, amazing.
Speaker 2: They're hard to predict.
Speaker 1: They are hard to predict. It. I think everything seems
Speaker 1: hard to predict right now, and I think maybe that
Speaker 1: rolls into the next question too. But you know, I
Speaker 1: know the plaintiffs bar, you know, sometimes gets this negative
Speaker 1: reception from Wall Street or you know, there's this view
Speaker 1: of the plaintiff's bar in a negative way. But you know,
Speaker 1: do you have any thoughts on how you kind of
Speaker 1: see the plaintiffs bar carrying the labor or on anti
Speaker 1: trust issues right now, and you know maybe what that
Speaker 1: means in the context of political landscapes and how they've
Speaker 1: changed recently from administration to administration.
Speaker 3: Well, I think the plaintiff's bar is always carried the
Speaker 3: anti trust more and generally regulators have been slow and
Speaker 3: behind us.
Speaker 2: Now it's a little.
Speaker 3: Different because you see a lot more anti trust cases
Speaker 3: being brought by state ags, and some of the state
Speaker 3: ags actually have fairly large staffs.
Speaker 4: Sure, sure, that's different, but I.
Speaker 3: Still think there's a large role for the plaintiffs bar
Speaker 3: not only.
Speaker 2: An anti trust but in all kinds of areas to
Speaker 2: be the regulator.
Speaker 1: Yep, that makes a lot of sense. And to your
Speaker 1: point too, you know, I was reading somewhat recently about
Speaker 1: the insulin cases you have brought you a few years back,
Speaker 1: and we're just seeing the FTC now right trying to
Speaker 1: go after pharmacy benefit managers. For I think a lot
Speaker 1: of the very same subject matter that there was at
Speaker 1: the heart of your your litigation around those issues. So
Speaker 1: I think to your point, yeah, the plaintiff's bar really
Speaker 1: does seem to be in many ways suggesting a direction
Speaker 1: that regulators should or could go in with relation to
Speaker 1: a wide range of different industry.
Speaker 3: If I recall in that case the President Trump his
Speaker 3: first term.
Speaker 2: Sure was a fan of that case.
Speaker 4: Interesting.
Speaker 2: Interesting, Yes, we need to do something about this. And
Speaker 2: here we are, like eight years later. Yeah, that litigation
Speaker 2: is still going on.
Speaker 1: Still makes sense. And you know, really you know the
Speaker 1: FTC case too, It's just there's a lot, a whole
Speaker 1: lot of issues going on with that one too, and
Speaker 1: who knows if that resolves, you know, anytime, anytime soon.
Speaker 1: But I guess turning to to the Gibson case, and
Speaker 1: you know, these AI rate algorithm cases a little bit
Speaker 1: more more broadly, you know, I have to say it
Speaker 1: was at the ABA Spring Anti Trust meeting a couple
Speaker 1: of weeks ago, and the hot topic seemed to be
Speaker 1: these AI price setting algorithms and you know what they
Speaker 1: mean for antitrust and you know, can they even be
Speaker 1: addressed by existing anti trust law? And I know your
Speaker 1: firm has done a lot of work on this, I think, really,
Speaker 1: you know, and very soon going to be leading one
Speaker 1: of the first appellate arguments related to the issue itself,
Speaker 1: But could you talk talk a little bit about the
Speaker 1: Gibson case, and you know the oral arguments you have
Speaker 1: slated for next month in the Ninth Circuit.
Speaker 3: Well, the Gibson case, like our other AI price mixing cases,
Speaker 3: alleges that the hotel casinos hired the defendant to use
Speaker 3: their rent maximizing services I think they call them. And
Speaker 3: so the AI company collects non public information and public
Speaker 3: information from the casinos or the landlords or.
Speaker 2: The protein you know, processors.
Speaker 3: They then take that information and they send it back
Speaker 3: to the casino and they say, hey, here's what Steve's
Speaker 3: casino is charging for that room, here's what Justin's casino
Speaker 3: is charging, and here's what we think you should charge.
Speaker 3: And we believe there's an agreement among the people subscribing
Speaker 3: to this service that we will price where the AI
Speaker 3: company suggests we should price. So you're taking away independent
Speaker 3: decision making and there's a tacit understanding that you know,
Speaker 3: we're all going to set the price recommended by someone else.
Speaker 3: So it's just as I told Judge Lasnik when I
Speaker 3: was arguing the Yardy motion.
Speaker 4: To dismiss sure Sure, It's like, hey, it used to be.
Speaker 3: You know, a bunch of old guys got in a room, right,
Speaker 3: they smoked cigars, and they said, I said, look, imagine
Speaker 3: if we were right before the Federal bar dinner, all
Speaker 3: the leading CEOs of law firms got together and said, hey,
Speaker 3: Microsoft is killing us on the rates.
Speaker 2: Man.
Speaker 3: You know, I don't want to charge four hundred. I
Speaker 3: want to charge six hundred. But apparently some of you
Speaker 3: are charging four hundred. You know, we should all charge
Speaker 3: six hundred. And then everyone took that suggestion and they
Speaker 3: all charged six Would anyone doubt that that was price fixing? No,
Speaker 3: And that's what's going on with these AI things. He
Speaker 3: got it, He got it that it was per se
Speaker 3: price fixing, where the judge Tennessee said, oh no, it's
Speaker 3: not per se. For a reason, Well, it's price fixing,
Speaker 3: and price fixing is per se period.
Speaker 4: Right right.
Speaker 1: I mean, and to your point, I mean talk yeah, yeah, yeah,
Speaker 1: I mean it's good, it's good.
Speaker 4: I mean, and I haven't read anything yet.
Speaker 1: Perfect, You're gonna do great, I have no doubt about that.
Speaker 1: But I mean, to your point, this is really I
Speaker 1: think something coming together and something that could be teed
Speaker 1: up for a Supreme Court ruling at some point down
Speaker 1: the road too, because the ruling so far has been
Speaker 1: so disparate on this subject from place to place, right,
Speaker 1: and in the Gibson case, the dismissal that you'll obviously
Speaker 1: be arguing the appeal on next about the Lardy to
Speaker 1: your point, the per se finding, you know, with the
Speaker 1: use of these algorithms, and then in Tennessee kind of
Speaker 1: this halfway step right with using the rule of reason.
Speaker 4: So yeah, just so so much going on there.
Speaker 1: And you know, I suppose you know you've already.
Speaker 4: Touched this one.
Speaker 2: I wouldn't mind going to the Supreme.
Speaker 4: Court with sure, sure, but they have been.
Speaker 2: Pretty good on anti trust matters.
Speaker 4: Yeah, Like if you read their.
Speaker 2: Opinion in my alstin case, they were right on sure.
Speaker 2: Sure couldn't have written it better myself.
Speaker 1: Yeah, the court does, the core current composition of the
Speaker 1: court does seem to get anti trust, which you can't
Speaker 1: say for all judges. So it's definitely nice. Nice to
Speaker 1: see that too. And I think you know you've probably
Speaker 1: hit upon this too in what you said already, but
Speaker 1: in terms of what the District Court got wrong in
Speaker 1: Gibson or you might have gotten wrong, you know, I
Speaker 1: think an important feature of these algorithms seems to be
Speaker 1: that folks kind of auto accept them sometimes too, if
Speaker 1: I'm not mistaken, right, you know, to your point about
Speaker 1: there being in agreement, there isn't this independent decision making.
Speaker 1: I think a lot of times when these folks use
Speaker 1: an algorithm and you know, the price is then displayed
Speaker 1: to the consumer. So if you have any thoughts about that,
Speaker 1: you know, I think that probably is someone that really
Speaker 1: points to an agreement being in place in terms of
Speaker 1: how these cases look under an anti trust review as well, I.
Speaker 3: Would agree with you that you know it's either a
Speaker 3: tacit understanding or express understanding. Got it, You're going to
Speaker 3: accept the recommend the price, got it? Why would you
Speaker 3: be paying the money to that to the AI company?
Speaker 1: Sure, they're given you something that's what it sounds like.
Speaker 1: So definitely, so, you know, interesting and I certainly don't
Speaker 1: know the answer to this, but you know, to your point,
Speaker 1: we've seen these these algorithms that use in real estate
Speaker 1: and with hotels, lodging, those kinds of those industries. But
Speaker 1: you know, are you aware or you know kind of
Speaker 1: think that maybe these algorithms are being used in a
Speaker 1: more widespread way across different industries, and it was something
Speaker 1: to kind of keep our eye on, you know, for
Speaker 1: the future.
Speaker 3: Yes, I think it is more widespread than what's currently
Speaker 3: targeted by litigation, and we're looking at some industries right now.
Speaker 1: So you know, I know you've been involved in a
Speaker 1: large antitrust MDL for years now about beef prices and
Speaker 1: a whole lot of other agricultural areas as well. You know,
Speaker 1: I think just the other day we saw Tyson, you know,
Speaker 1: agree to a settlement with relation to pork for example. Right,
Speaker 1: you know, a lot of folks don't know about this,
Speaker 1: but what's going on in agriculture, right, what's going on
Speaker 1: with proteins?
Speaker 2: Why is this?
Speaker 1: Why is antitrust and price fixing such a pervasive allegation
Speaker 1: proceeeding in these markets?
Speaker 3: So we have anti trust cases and we actually kind
Speaker 3: of started these in the pork industry, the chicken industry,
Speaker 3: the turkey and beef.
Speaker 2: You know, all these industries.
Speaker 3: Are you have a small group of processors do the same,
Speaker 3: the Tysons and everyone.
Speaker 2: Cargills and everyone.
Speaker 3: And they can't control supply. So people supplied too many chickens,
Speaker 3: too many pigs, and then the price goes down, the
Speaker 3: allm you know, get hurt.
Speaker 2: So they came together and said, let's control our supply.
Speaker 2: They we'll all do better.
Speaker 3: And they did that in every industry, and they did
Speaker 3: it through one of these third parties.
Speaker 2: Now it's not a AI.
Speaker 4: It was kind of more old school, right, more traditional.
Speaker 3: Yeah, agristats would go meet with every processor and then
Speaker 3: they would send the other processors pricing and supply information
Speaker 3: back to you as a customer, and they wouldn't have
Speaker 3: the name of the other processor on it, but these
Speaker 3: people could figure it out. So they knew what Tyson
Speaker 3: was charging, and they knew what you know, JD was charging,
Speaker 3: and what the supply was and they were able to
Speaker 3: control supply.
Speaker 1: Got it.
Speaker 4: Got it.
Speaker 1: And I'm assuming this is kind of similar to what
Speaker 1: we're seeing around DOJ investigating eggs right now. And you know,
Speaker 1: it seems like there's been litigation around that subject in
Speaker 1: the past, but the same general idea I think with
Speaker 1: regard to that particular corner of the market.
Speaker 3: I will tell you that half of my team, I
Speaker 3: think has become vegetarians on those cases where we had
Speaker 3: to see actually how they make all this.
Speaker 1: Yeah, yeah, I have a colleague who was involved in
Speaker 1: an anti trust case. It's the same place, it's right, Yeah,
Speaker 1: I think once you experience that, it's not something you
Speaker 1: really want to want to adjust.
Speaker 3: Disgusting that in the case the judge granted their motion
Speaker 3: eliminated that we couldn't show any pictures of processing their chickens.
Speaker 1: Wow wow, interesting Yeah, right, that speaks volumes then definitely, definitely.
Speaker 2: Sometimes there's fun facts in these cases.
Speaker 1: Yeah, yeah, no, definitely. You know, I feel like that's
Speaker 1: the interesting thing about anti trust.
Speaker 2: I think that one of the big issues in anitrust cases. Yeah, that.
Speaker 3: I think judges are struggling with, and I've heard particularly
Speaker 3: Judge Kenzalas.
Speaker 2: Rogers talking about yes, yeah, and that is the complexity.
Speaker 4: Sure.
Speaker 3: So, you know, I just got done with the deposition
Speaker 3: of my expert in the Amazon price fixing case. This
Speaker 3: reports like fifteen hundred pages with like two thousand footnotes.
Speaker 4: Sure, sure, both.
Speaker 3: Sides have done this right, and then the judge gets
Speaker 3: all us and the judge is not an economist, right,
Speaker 3: and you know, both sides say, well, the other expert
Speaker 3: should be Dauber and he's full of beans.
Speaker 2: He doesn't know what he's doing.
Speaker 4: Sure. Sure, What are you supposed to do with all this?
Speaker 2: It's just too much?
Speaker 3: Yes, yes, I don't know that I have an answer
Speaker 3: to it other than I keep telling my lawyers and
Speaker 3: they're so tired of hearing it.
Speaker 2: Every time I get an ex report.
Speaker 3: I want to summary that is in plain English, that's
Speaker 3: actually exciting that the judge will read, because I don't
Speaker 3: believe any judge is going to read twelve hundred pages
Speaker 3: or sure.
Speaker 1: Sure, I mean they might endeavor to do it, but
Speaker 1: if you can stay away for it, that's a miracle
Speaker 1: in and of itself.
Speaker 2: Get him interested in the summary, and then if they
Speaker 2: want to read a little.
Speaker 4: Bit more they will, Sure, but please.
Speaker 2: Make it understandable. I think that's just a big challenge.
Speaker 1: Sure, I think you're right, Especially with the economics involved
Speaker 1: with all these cases too, it could be really difficult
Speaker 1: to follow sometimes and that makes a lot of sense
Speaker 1: for sure.
Speaker 3: And another thing that I've seen because of the complexity
Speaker 3: of the marketplace, So you know, in the protein cases,
Speaker 3: we had to digest like every sale of chicken in
Speaker 3: the nation at every single place, and same thing, and
Speaker 3: so you're talking about mega bites of information that the
Speaker 3: experts have to digest. In the Amazon case, imagine we've
Speaker 3: examined I think eighty three billion transactions.
Speaker 2: Wow.
Speaker 3: Right the cost of all this, you know, it used
Speaker 3: to be that as a plaintiff story, you might spend
Speaker 3: a couple hundred grand on an expert.
Speaker 1: Oh yeah, it's incredible.
Speaker 2: Now we're talking.
Speaker 3: About spending five to ten million dollars. Sure, sure in
Speaker 3: your economic experts.
Speaker 2: That is a huge change.
Speaker 1: Absolutely, And the government when it brings a case incurring
Speaker 1: substantially the same cost too, right, So I mean it's
Speaker 1: not even just the law firms, and you know if
Speaker 1: they're if they're pursuing it as a plaintiff, is very
Speaker 1: interesting stuff.
Speaker 4: Yeah.
Speaker 1: So, Steve, is there anything else you want to add
Speaker 1: before we wrap up here? Outside of these cases, I
Speaker 1: would say.
Speaker 3: Two things about it if you're thinking about plaintiff's law
Speaker 3: and impact. So I've done two cases that I call
Speaker 3: transformative cases in the last got it?
Speaker 2: And the first is the real estate.
Speaker 3: Case about commissions, and the New York Times and others
Speaker 3: are suggesting that that might save somewhere between ten and
Speaker 3: forty billion dollars to American consumers because of the change
Speaker 3: and the rules that we implemented in the real estate.
Speaker 3: So that's an anti trust case that actually is going
Speaker 3: to transform into something that affects most Americans.
Speaker 2: We all buy homes. Of course, I'm highly.
Speaker 3: Confident that in the week Judge Wilkin will prove my
Speaker 3: NCAA ANI trust case. But there's another anti trust case
Speaker 3: that has been transformative because now going forward, all these
Speaker 3: student athletes are going to share in the revenues that
Speaker 3: come in from TV broadcasts to get sales. So you
Speaker 3: can use the anti trust to be a powerful tool
Speaker 3: for changing America. That's why I became a lawyer, So
Speaker 3: I'm thrilled every day when I could come in and
Speaker 3: work on stuff that makes a difference.
Speaker 1: Love that, love that super inspiring. Steve Berman, thanks again
Speaker 1: for joining us a great conversation with that question. I
Speaker 1: know I'll be seeing a lot more coming from Hoggins
Speaker 1: Berman on the anti trust front and many others in
Speaker 1: the months and years ahead. And as always, thank you
Speaker 1: to you the listener for tuning in. As a reminder,
Speaker 1: you can read all of our Bloomberg intelligence research on
Speaker 1: the Bloomberg terminal at bi go. And with that, I'm
Speaker 1: justin terresy and this with Boots and verdicts