May 20, 2025 • 20 mins
Antitrust law has been unusually busy in recent years, with several high-profile cases, including in Big Tech. Steve Berman, Co-Founder and Managing Partner of plaintiff-side firm Hagens Berman Sobol and Shapiro LLP, joins Bloomberg Intelligence analyst Justin Teresi for a discussion of antitrust developments and trends, as seen from the plaintiffs’ bar. Topics include Berman’s recent litigation around the growth of artificial intelligence-based pricing algorithms in setting hotel rates, as well as work on alleged collusion in agriculture. Berman and Teresi also discuss how plaintiffs’ firms — and private aggregate litigation, like class actions — are working alongside government enforcement efforts.
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Speaker 1 (00:14):
Welcome to Votes and Verdicts. Hosted by the Litigation and
Policy team at Bloomberg Intelligence, the investment research arm of
Bloomberg LP. This podcast series examines the intersection of business
policy and the law. I'm Justin Terracey antitrust litigation and
policy analysts here at BI. Before we jump into today's episode,
just a quick word about Bloomberg Intelligence, where the investment
(00:36):
research platform on the Bloomberg Terminal, with five hundred analysts
and strategists working across the globe and focused on all
major markets. Our coverage includes over two thousand equities and credits,
and we have outlooks on more than ninety industries and
one hundred market indices, currencies and commodities. Steve, Welcome to
Votes and Verdicts.
Speaker 2 (00:55):
Welcome Justin.
Speaker 1 (00:57):
So Steve Berman is joining us today. He's the managing
part of the eponymous Hoggins Berman, which he co founded
in nineteen ninety three. And I can say from my
own time working as a plaintiff's lawyer that Steve and
the firm are truly top notch. Steve's firm has run
case leading cases on everything from big tobacco to widespread
automotive defects to just about every corner of antitrust, consumer protection,
(01:17):
and securities class actions you can think of. Truly, the
list of matters is endless, and the value of Hoggins
Berman settlements goes unmatched by most plaintiffs, most on the
plaintiffs side of the v partner. Today Today's chat, Steve
leads Hoggins Berman's work on anti trust, and cases in
this practice area alone have secured settlements valued at more
than twenty seven billion dollars. Steve's accolades are endless, with
(01:41):
the National Law Journal even proclaiming him as one of
the one hundred most powerful lawyers in the nation. So,
Steve's so glad to have you here with us today.
And just kind of a threshold question, we ask all
of our guests kind of brought what brought you to
where you are today? You know what got you started litigating,
and you know what made you kind of found the
firm when you did.
Speaker 3 (02:00):
And I went to law school, I decided right away
I wanted to be a trial lawyer.
Speaker 1 (02:04):
I don't know why, for better or worse, right, Yeah.
Speaker 3 (02:08):
And I remember I got into a big argument with
my academic advisor, Justice Scalia, because I turned down law
review because I wanted to go right away to the clinic,
because I wanted to get into the courtroom as soon
as I could.
Speaker 4 (02:24):
Interesting, why would you turn down law review.
Speaker 2 (02:26):
It's a path to a clerkship, for sure. It's like
I don't want a clerk.
Speaker 3 (02:29):
I want to get out and get into the court.
As to why, you know, I founded my firm. I
was at a firm that was mainly a defense firm,
but I was the little plaintiffs arm and I had
a case for a family who's young seven year old
had lost a kidney because of Ecoli contimidation, and it
(02:52):
was heartbreaking.
Speaker 2 (02:53):
My kids were the exact same age.
Speaker 3 (02:55):
So I went to take the case and my firm said, no,
we might get we might represent one of the insurance company.
Speaker 4 (03:02):
Got it, you got it, get it.
Speaker 3 (03:04):
I got to take this case, and so we went
out and started our firm.
Speaker 4 (03:10):
Interesting.
Speaker 1 (03:11):
Interesting, Yeah, I think that's why myself and many folks
who ended up on the plaintiff side kind of kind
of felt like doing that. You know, you kind of
kind of work on the defense side after a while,
and you kind of see some of the things you're
working on, and maybe rubs you.
Speaker 4 (03:23):
The wrong way.
Speaker 1 (03:24):
But you know, right now, specifically on anti trust, it's
an incredibly busy time, you know, I think, you know,
especially in enforcers, seem really focused on things like big tech.
There's been this revival of anti trust I think at
the government level. But what are you kind of seeing
as the largest issues are trends in the space for
antitrust right now.
Speaker 3 (03:43):
Well, certainly big tech. So I think I have five
anti trust cases against Amazon.
Speaker 1 (03:49):
Well, yeah, I mean I've been at the metatrial this
week myself. There's so much going on.
Speaker 3 (03:53):
Yeah, so Amazon is resisting one of my cases saying
it's too big to sort of if I remember the
old banks were too big to.
Speaker 1 (04:02):
Fail, Yeah, yeah, this is the Yeah, we're too.
Speaker 3 (04:05):
Big to certify because there'll be like two hundred and
thirty million Americans in this class because basically everyone who.
Speaker 2 (04:12):
Shopped on Amazon has been subject to their price.
Speaker 4 (04:14):
Fixing, right right, So we're very busy in.
Speaker 3 (04:20):
All kinds of high tech cases against Amazon and Apple.
And then I think we're the leading edge on these
cases involving using algorithms to set prices in either the
hotel industry, the leasing industry, or in the protein industry would.
Speaker 1 (04:41):
Call it definitely. Yeah, I know we'll get we'll get
into the Gibson case specifically, and you know, agricultural or
protein cases I think a little bit later on too,
But I guess you know those industries a lot of
any other industries you're kind of seeing anti trust issues
bubbling up in or those the primary ones you're you're
focused on at the moment.
Speaker 2 (04:59):
I think that's primary focus on the moment.
Speaker 1 (05:01):
Got it, got it? And kind of broader question with
regard to class actions, you know, more broadly. Right, So
even touching upon areas like labor or securities, are you
seeing any trends there? I know we've got this Lab
Corp Case coming up the Supreme Court relatively soon. Not
sure if you have any thoughts on that, but I'm
not seeing a lot of talk about it lately, and
it interests me that I'm not, because I feel like
it actually could be a really big deal for how
(05:22):
things progress.
Speaker 2 (05:24):
So the Plane's bar is very worried about the Lab
Court case.
Speaker 3 (05:27):
Sure, Sure, A small group of us have had calls
with the Larriors and help them, you know, work on
the briefs. We've been writing Amekas briefs but given them
conservative nature of the court, anytime a PLANEFFS case comes up,
no matter whether it's this class issue or right right,
any issue, you're more nervous than you used to be.
Speaker 1 (05:51):
Definitely, I feel like it's not a small statement to
say the court's been chipping away at Rule twenty three
anyway again over the last decade or two. So I
feel like you see the Davis case with this whole
concept of an uninjured plaintiff and whether you're consisting in
a class on that, and it definitely raises a little
bit of concern given the composition of the court being
what it is.
Speaker 3 (06:11):
But you never know, because when my inc Double eight
case was taken by the court, I was like, oh
my god, this is this is a disaster.
Speaker 2 (06:21):
And then I got a nine to zero opinion.
Speaker 1 (06:24):
Yeah, amazing, amazing.
Speaker 2 (06:25):
They're hard to predict.
Speaker 1 (06:27):
They are hard to predict. It. I think everything seems
hard to predict right now, and I think maybe that
rolls into the next question too. But you know, I
know the plaintiffs bar, you know, sometimes gets this negative
reception from Wall Street or you know, there's this view
of the plaintiff's bar in a negative way. But you know,
do you have any thoughts on how you kind of
see the plaintiffs bar carrying the labor or on anti
(06:47):
trust issues right now, and you know maybe what that
means in the context of political landscapes and how they've
changed recently from administration to administration.
Speaker 3 (06:56):
Well, I think the plaintiff's bar is always carried the
anti trust more and generally regulators have been slow and
behind us.
Speaker 2 (07:06):
Now it's a little.
Speaker 3 (07:07):
Different because you see a lot more anti trust cases
being brought by state ags, and some of the state
ags actually have fairly large staffs.
Speaker 4 (07:17):
Sure, sure, that's different, but I.
Speaker 3 (07:20):
Still think there's a large role for the plaintiffs bar
not only.
Speaker 2 (07:24):
An anti trust but in all kinds of areas to
be the regulator.
Speaker 1 (07:29):
Yep, that makes a lot of sense. And to your
point too, you know, I was reading somewhat recently about
the insulin cases you have brought you a few years back,
and we're just seeing the FTC now right trying to
go after pharmacy benefit managers. For I think a lot
of the very same subject matter that there was at
the heart of your your litigation around those issues. So
(07:49):
I think to your point, yeah, the plaintiff's bar really
does seem to be in many ways suggesting a direction
that regulators should or could go in with relation to
a wide range of different industry.
Speaker 3 (08:00):
If I recall in that case the President Trump his
first term.
Speaker 2 (08:06):
Sure was a fan of that case.
Speaker 4 (08:08):
Interesting.
Speaker 2 (08:09):
Interesting, Yes, we need to do something about this. And
here we are, like eight years later. Yeah, that litigation
is still going on.
Speaker 1 (08:18):
Still makes sense. And you know, really you know the
FTC case too, It's just there's a lot, a whole
lot of issues going on with that one too, and
who knows if that resolves, you know, anytime, anytime soon.
But I guess turning to to the Gibson case, and
you know, these AI rate algorithm cases a little bit
more more broadly, you know, I have to say it
was at the ABA Spring Anti Trust meeting a couple
(08:38):
of weeks ago, and the hot topic seemed to be
these AI price setting algorithms and you know what they
mean for antitrust and you know, can they even be
addressed by existing anti trust law? And I know your
firm has done a lot of work on this, I think, really,
you know, and very soon going to be leading one
of the first appellate arguments related to the issue itself,
(08:59):
But could you talk talk a little bit about the
Gibson case, and you know the oral arguments you have
slated for next month in the Ninth Circuit.
Speaker 3 (09:05):
Well, the Gibson case, like our other AI price mixing cases,
alleges that the hotel casinos hired the defendant to use
their rent maximizing services I think they call them. And
so the AI company collects non public information and public
(09:30):
information from the casinos or the landlords or.
Speaker 2 (09:34):
The protein you know, processors.
Speaker 3 (09:37):
They then take that information and they send it back
to the casino and they say, hey, here's what Steve's
casino is charging for that room, here's what Justin's casino
is charging, and here's what we think you should charge.
And we believe there's an agreement among the people subscribing
(09:58):
to this service that we will price where the AI
company suggests we should price. So you're taking away independent
decision making and there's a tacit understanding that you know,
we're all going to set the price recommended by someone else.
So it's just as I told Judge Lasnik when I
(10:21):
was arguing the Yardy motion.
Speaker 4 (10:23):
To dismiss sure Sure, It's like, hey, it used to be.
Speaker 3 (10:26):
You know, a bunch of old guys got in a room, right,
they smoked cigars, and they said, I said, look, imagine
if we were right before the Federal bar dinner, all
the leading CEOs of law firms got together and said, hey,
Microsoft is killing us on the rates.
Speaker 2 (10:43):
Man.
Speaker 3 (10:43):
You know, I don't want to charge four hundred. I
want to charge six hundred. But apparently some of you
are charging four hundred. You know, we should all charge
six hundred. And then everyone took that suggestion and they
all charged six Would anyone doubt that that was price fixing? No,
And that's what's going on with these AI things. He
got it, He got it that it was per se
(11:05):
price fixing, where the judge Tennessee said, oh no, it's
not per se. For a reason, Well, it's price fixing,
and price fixing is per se period.
Speaker 4 (11:14):
Right right.
Speaker 1 (11:15):
I mean, and to your point, I mean talk yeah, yeah, yeah,
I mean it's good, it's good.
Speaker 4 (11:20):
I mean, and I haven't read anything yet.
Speaker 1 (11:22):
Perfect, You're gonna do great, I have no doubt about that.
But I mean, to your point, this is really I
think something coming together and something that could be teed
up for a Supreme Court ruling at some point down
the road too, because the ruling so far has been
so disparate on this subject from place to place, right,
and in the Gibson case, the dismissal that you'll obviously
be arguing the appeal on next about the Lardy to
your point, the per se finding, you know, with the
(11:44):
use of these algorithms, and then in Tennessee kind of
this halfway step right with using the rule of reason.
Speaker 4 (11:49):
So yeah, just so so much going on there.
Speaker 1 (11:52):
And you know, I suppose you know you've already.
Speaker 4 (11:54):
Touched this one.
Speaker 2 (11:57):
I wouldn't mind going to the Supreme.
Speaker 4 (11:58):
Court with sure, sure, but they have been.
Speaker 2 (12:00):
Pretty good on anti trust matters.
Speaker 4 (12:04):
Yeah, Like if you read their.
Speaker 2 (12:05):
Opinion in my alstin case, they were right on sure.
Sure couldn't have written it better myself.
Speaker 1 (12:12):
Yeah, the court does, the core current composition of the
court does seem to get anti trust, which you can't
say for all judges. So it's definitely nice. Nice to
see that too. And I think you know you've probably
hit upon this too in what you said already, but
in terms of what the District Court got wrong in
Gibson or you might have gotten wrong, you know, I
think an important feature of these algorithms seems to be
(12:32):
that folks kind of auto accept them sometimes too, if
I'm not mistaken, right, you know, to your point about
there being in agreement, there isn't this independent decision making.
I think a lot of times when these folks use
an algorithm and you know, the price is then displayed
to the consumer. So if you have any thoughts about that,
you know, I think that probably is someone that really
points to an agreement being in place in terms of
(12:54):
how these cases look under an anti trust review as well, I.
Speaker 3 (12:57):
Would agree with you that you know it's either a
tacit understanding or express understanding. Got it, You're going to
accept the recommend the price, got it? Why would you
be paying the money to that to the AI company?
Speaker 1 (13:12):
Sure, they're given you something that's what it sounds like.
So definitely, so, you know, interesting and I certainly don't
know the answer to this, but you know, to your point,
we've seen these these algorithms that use in real estate
and with hotels, lodging, those kinds of those industries. But
you know, are you aware or you know kind of
think that maybe these algorithms are being used in a
more widespread way across different industries, and it was something
(13:34):
to kind of keep our eye on, you know, for
the future.
Speaker 3 (13:37):
Yes, I think it is more widespread than what's currently
targeted by litigation, and we're looking at some industries right now.
Speaker 1 (13:47):
So you know, I know you've been involved in a
large antitrust MDL for years now about beef prices and
a whole lot of other agricultural areas as well. You know,
I think just the other day we saw Tyson, you know,
agree to a settlement with relation to pork for example. Right,
you know, a lot of folks don't know about this,
but what's going on in agriculture, right, what's going on
with proteins?
Speaker 2 (14:07):
Why is this?
Speaker 1 (14:08):
Why is antitrust and price fixing such a pervasive allegation
proceeeding in these markets?
Speaker 3 (14:13):
So we have anti trust cases and we actually kind
of started these in the pork industry, the chicken industry,
the turkey and beef.
Speaker 2 (14:24):
You know, all these industries.
Speaker 3 (14:25):
Are you have a small group of processors do the same,
the Tysons and everyone.
Speaker 2 (14:30):
Cargills and everyone.
Speaker 3 (14:32):
And they can't control supply. So people supplied too many chickens,
too many pigs, and then the price goes down, the
allm you know, get hurt.
Speaker 2 (14:44):
So they came together and said, let's control our supply.
They we'll all do better.
Speaker 3 (14:48):
And they did that in every industry, and they did
it through one of these third parties.
Speaker 2 (14:53):
Now it's not a AI.
Speaker 4 (14:55):
It was kind of more old school, right, more traditional.
Speaker 3 (14:58):
Yeah, agristats would go meet with every processor and then
they would send the other processors pricing and supply information
back to you as a customer, and they wouldn't have
the name of the other processor on it, but these
people could figure it out. So they knew what Tyson
(15:19):
was charging, and they knew what you know, JD was charging,
and what the supply was and they were able to
control supply.
Speaker 1 (15:27):
Got it.
Speaker 4 (15:28):
Got it.
Speaker 1 (15:28):
And I'm assuming this is kind of similar to what
we're seeing around DOJ investigating eggs right now. And you know,
it seems like there's been litigation around that subject in
the past, but the same general idea I think with
regard to that particular corner of the market.
Speaker 3 (15:41):
I will tell you that half of my team, I
think has become vegetarians on those cases where we had
to see actually how they make all this.
Speaker 1 (15:50):
Yeah, yeah, I have a colleague who was involved in
an anti trust case. It's the same place, it's right, Yeah,
I think once you experience that, it's not something you
really want to want to adjust.
Speaker 3 (16:00):
Disgusting that in the case the judge granted their motion
eliminated that we couldn't show any pictures of processing their chickens.
Speaker 1 (16:09):
Wow wow, interesting Yeah, right, that speaks volumes then definitely, definitely.
Speaker 2 (16:14):
Sometimes there's fun facts in these cases.
Speaker 1 (16:17):
Yeah, yeah, no, definitely. You know, I feel like that's
the interesting thing about anti trust.
Speaker 2 (16:20):
I think that one of the big issues in anitrust cases. Yeah, that.
Speaker 3 (16:26):
I think judges are struggling with, and I've heard particularly
Judge Kenzalas.
Speaker 2 (16:30):
Rogers talking about yes, yeah, and that is the complexity.
Speaker 4 (16:35):
Sure.
Speaker 3 (16:35):
So, you know, I just got done with the deposition
of my expert in the Amazon price fixing case. This
reports like fifteen hundred pages with like two thousand footnotes.
Speaker 4 (16:47):
Sure, sure, both.
Speaker 3 (16:48):
Sides have done this right, and then the judge gets
all us and the judge is not an economist, right,
and you know, both sides say, well, the other expert
should be Dauber and he's full of beans.
Speaker 2 (17:02):
He doesn't know what he's doing.
Speaker 4 (17:03):
Sure. Sure, What are you supposed to do with all this?
Speaker 2 (17:06):
It's just too much?
Speaker 3 (17:08):
Yes, yes, I don't know that I have an answer
to it other than I keep telling my lawyers and
they're so tired of hearing it.
Speaker 2 (17:17):
Every time I get an ex report.
Speaker 3 (17:18):
I want to summary that is in plain English, that's
actually exciting that the judge will read, because I don't
believe any judge is going to read twelve hundred pages
or sure.
Speaker 1 (17:29):
Sure, I mean they might endeavor to do it, but
if you can stay away for it, that's a miracle
in and of itself.
Speaker 2 (17:35):
Get him interested in the summary, and then if they
want to read a little.
Speaker 4 (17:37):
Bit more they will, Sure, but please.
Speaker 2 (17:40):
Make it understandable. I think that's just a big challenge.
Speaker 1 (17:45):
Sure, I think you're right, Especially with the economics involved
with all these cases too, it could be really difficult
to follow sometimes and that makes a lot of sense
for sure.
Speaker 3 (17:54):
And another thing that I've seen because of the complexity
of the marketplace, So you know, in the protein cases,
we had to digest like every sale of chicken in
the nation at every single place, and same thing, and
so you're talking about mega bites of information that the
(18:14):
experts have to digest. In the Amazon case, imagine we've
examined I think eighty three billion transactions.
Speaker 2 (18:22):
Wow.
Speaker 3 (18:23):
Right the cost of all this, you know, it used
to be that as a plaintiff story, you might spend
a couple hundred grand on an expert.
Speaker 1 (18:30):
Oh yeah, it's incredible.
Speaker 2 (18:31):
Now we're talking.
Speaker 3 (18:32):
About spending five to ten million dollars. Sure, sure in
your economic experts.
Speaker 2 (18:37):
That is a huge change.
Speaker 1 (18:39):
Absolutely, And the government when it brings a case incurring
substantially the same cost too, right, So I mean it's
not even just the law firms, and you know if
they're if they're pursuing it as a plaintiff, is very
interesting stuff.
Speaker 4 (18:50):
Yeah.
Speaker 1 (18:51):
So, Steve, is there anything else you want to add
before we wrap up here? Outside of these cases, I
would say.
Speaker 3 (18:55):
Two things about it if you're thinking about plaintiff's law
and impact. So I've done two cases that I call
transformative cases in the last got it?
Speaker 2 (19:06):
And the first is the real estate.
Speaker 3 (19:08):
Case about commissions, and the New York Times and others
are suggesting that that might save somewhere between ten and
forty billion dollars to American consumers because of the change
and the rules that we implemented in the real estate.
So that's an anti trust case that actually is going
to transform into something that affects most Americans.
Speaker 2 (19:30):
We all buy homes. Of course, I'm highly.
Speaker 3 (19:34):
Confident that in the week Judge Wilkin will prove my
NCAA ANI trust case. But there's another anti trust case
that has been transformative because now going forward, all these
student athletes are going to share in the revenues that
come in from TV broadcasts to get sales. So you
can use the anti trust to be a powerful tool
(19:54):
for changing America. That's why I became a lawyer, So
I'm thrilled every day when I could come in and
work on stuff that makes a difference.
Speaker 1 (20:03):
Love that, love that super inspiring. Steve Berman, thanks again
for joining us a great conversation with that question. I
know I'll be seeing a lot more coming from Hoggins
Berman on the anti trust front and many others in
the months and years ahead. And as always, thank you
to you the listener for tuning in. As a reminder,
you can read all of our Bloomberg intelligence research on
the Bloomberg terminal at bi go. And with that, I'm
(20:25):
justin terresy and this with Boots and verdicts
Welcome to Votes and Verdicts. Hosted by the Litigation and
Policy team at Bloomberg Intelligence, the investment research arm of
Bloomberg LP. This podcast series examines the intersection of business
policy and the law. I'm Justin Terracey antitrust litigation and
policy analysts here at BI. Before we jump into today's episode,
just a quick word about Bloomberg Intelligence, where the investment
(00:36):
research platform on the Bloomberg Terminal, with five hundred analysts
and strategists working across the globe and focused on all
major markets. Our coverage includes over two thousand equities and credits,
and we have outlooks on more than ninety industries and
one hundred market indices, currencies and commodities. Steve, Welcome to
Votes and Verdicts.
Speaker 2 (00:55):
Welcome Justin.
Speaker 1 (00:57):
So Steve Berman is joining us today. He's the managing
part of the eponymous Hoggins Berman, which he co founded
in nineteen ninety three. And I can say from my
own time working as a plaintiff's lawyer that Steve and
the firm are truly top notch. Steve's firm has run
case leading cases on everything from big tobacco to widespread
automotive defects to just about every corner of antitrust, consumer protection,
(01:17):
and securities class actions you can think of. Truly, the
list of matters is endless, and the value of Hoggins
Berman settlements goes unmatched by most plaintiffs, most on the
plaintiffs side of the v partner. Today Today's chat, Steve
leads Hoggins Berman's work on anti trust, and cases in
this practice area alone have secured settlements valued at more
than twenty seven billion dollars. Steve's accolades are endless, with
(01:41):
the National Law Journal even proclaiming him as one of
the one hundred most powerful lawyers in the nation. So,
Steve's so glad to have you here with us today.
And just kind of a threshold question, we ask all
of our guests kind of brought what brought you to
where you are today? You know what got you started litigating,
and you know what made you kind of found the
firm when you did.
Speaker 3 (02:00):
And I went to law school, I decided right away
I wanted to be a trial lawyer.
Speaker 1 (02:04):
I don't know why, for better or worse, right, Yeah.
Speaker 3 (02:08):
And I remember I got into a big argument with
my academic advisor, Justice Scalia, because I turned down law
review because I wanted to go right away to the clinic,
because I wanted to get into the courtroom as soon
as I could.
Speaker 4 (02:24):
Interesting, why would you turn down law review.
Speaker 2 (02:26):
It's a path to a clerkship, for sure. It's like
I don't want a clerk.
Speaker 3 (02:29):
I want to get out and get into the court.
As to why, you know, I founded my firm. I
was at a firm that was mainly a defense firm,
but I was the little plaintiffs arm and I had
a case for a family who's young seven year old
had lost a kidney because of Ecoli contimidation, and it
(02:52):
was heartbreaking.
Speaker 2 (02:53):
My kids were the exact same age.
Speaker 3 (02:55):
So I went to take the case and my firm said, no,
we might get we might represent one of the insurance company.
Speaker 4 (03:02):
Got it, you got it, get it.
Speaker 3 (03:04):
I got to take this case, and so we went
out and started our firm.
Speaker 4 (03:10):
Interesting.
Speaker 1 (03:11):
Interesting, Yeah, I think that's why myself and many folks
who ended up on the plaintiff side kind of kind
of felt like doing that. You know, you kind of
kind of work on the defense side after a while,
and you kind of see some of the things you're
working on, and maybe rubs you.
Speaker 4 (03:23):
The wrong way.
Speaker 1 (03:24):
But you know, right now, specifically on anti trust, it's
an incredibly busy time, you know, I think, you know,
especially in enforcers, seem really focused on things like big tech.
There's been this revival of anti trust I think at
the government level. But what are you kind of seeing
as the largest issues are trends in the space for
antitrust right now.
Speaker 3 (03:43):
Well, certainly big tech. So I think I have five
anti trust cases against Amazon.
Speaker 1 (03:49):
Well, yeah, I mean I've been at the metatrial this
week myself. There's so much going on.
Speaker 3 (03:53):
Yeah, so Amazon is resisting one of my cases saying
it's too big to sort of if I remember the
old banks were too big to.
Speaker 1 (04:02):
Fail, Yeah, yeah, this is the Yeah, we're too.
Speaker 3 (04:05):
Big to certify because there'll be like two hundred and
thirty million Americans in this class because basically everyone who.
Speaker 2 (04:12):
Shopped on Amazon has been subject to their price.
Speaker 4 (04:14):
Fixing, right right, So we're very busy in.
Speaker 3 (04:20):
All kinds of high tech cases against Amazon and Apple.
And then I think we're the leading edge on these
cases involving using algorithms to set prices in either the
hotel industry, the leasing industry, or in the protein industry would.
Speaker 1 (04:41):
Call it definitely. Yeah, I know we'll get we'll get
into the Gibson case specifically, and you know, agricultural or
protein cases I think a little bit later on too,
But I guess you know those industries a lot of
any other industries you're kind of seeing anti trust issues
bubbling up in or those the primary ones you're you're
focused on at the moment.
Speaker 2 (04:59):
I think that's primary focus on the moment.
Speaker 1 (05:01):
Got it, got it? And kind of broader question with
regard to class actions, you know, more broadly. Right, So
even touching upon areas like labor or securities, are you
seeing any trends there? I know we've got this Lab
Corp Case coming up the Supreme Court relatively soon. Not
sure if you have any thoughts on that, but I'm
not seeing a lot of talk about it lately, and
it interests me that I'm not, because I feel like
it actually could be a really big deal for how
(05:22):
things progress.
Speaker 2 (05:24):
So the Plane's bar is very worried about the Lab
Court case.
Speaker 3 (05:27):
Sure, Sure, A small group of us have had calls
with the Larriors and help them, you know, work on
the briefs. We've been writing Amekas briefs but given them
conservative nature of the court, anytime a PLANEFFS case comes up,
no matter whether it's this class issue or right right,
any issue, you're more nervous than you used to be.
Speaker 1 (05:51):
Definitely, I feel like it's not a small statement to
say the court's been chipping away at Rule twenty three
anyway again over the last decade or two. So I
feel like you see the Davis case with this whole
concept of an uninjured plaintiff and whether you're consisting in
a class on that, and it definitely raises a little
bit of concern given the composition of the court being
what it is.
Speaker 3 (06:11):
But you never know, because when my inc Double eight
case was taken by the court, I was like, oh
my god, this is this is a disaster.
Speaker 2 (06:21):
And then I got a nine to zero opinion.
Speaker 1 (06:24):
Yeah, amazing, amazing.
Speaker 2 (06:25):
They're hard to predict.
Speaker 1 (06:27):
They are hard to predict. It. I think everything seems
hard to predict right now, and I think maybe that
rolls into the next question too. But you know, I
know the plaintiffs bar, you know, sometimes gets this negative
reception from Wall Street or you know, there's this view
of the plaintiff's bar in a negative way. But you know,
do you have any thoughts on how you kind of
see the plaintiffs bar carrying the labor or on anti
(06:47):
trust issues right now, and you know maybe what that
means in the context of political landscapes and how they've
changed recently from administration to administration.
Speaker 3 (06:56):
Well, I think the plaintiff's bar is always carried the
anti trust more and generally regulators have been slow and
behind us.
Speaker 2 (07:06):
Now it's a little.
Speaker 3 (07:07):
Different because you see a lot more anti trust cases
being brought by state ags, and some of the state
ags actually have fairly large staffs.
Speaker 4 (07:17):
Sure, sure, that's different, but I.
Speaker 3 (07:20):
Still think there's a large role for the plaintiffs bar
not only.
Speaker 2 (07:24):
An anti trust but in all kinds of areas to
be the regulator.
Speaker 1 (07:29):
Yep, that makes a lot of sense. And to your
point too, you know, I was reading somewhat recently about
the insulin cases you have brought you a few years back,
and we're just seeing the FTC now right trying to
go after pharmacy benefit managers. For I think a lot
of the very same subject matter that there was at
the heart of your your litigation around those issues. So
(07:49):
I think to your point, yeah, the plaintiff's bar really
does seem to be in many ways suggesting a direction
that regulators should or could go in with relation to
a wide range of different industry.
Speaker 3 (08:00):
If I recall in that case the President Trump his
first term.
Speaker 2 (08:06):
Sure was a fan of that case.
Speaker 4 (08:08):
Interesting.
Speaker 2 (08:09):
Interesting, Yes, we need to do something about this. And
here we are, like eight years later. Yeah, that litigation
is still going on.
Speaker 1 (08:18):
Still makes sense. And you know, really you know the
FTC case too, It's just there's a lot, a whole
lot of issues going on with that one too, and
who knows if that resolves, you know, anytime, anytime soon.
But I guess turning to to the Gibson case, and
you know, these AI rate algorithm cases a little bit
more more broadly, you know, I have to say it
was at the ABA Spring Anti Trust meeting a couple
(08:38):
of weeks ago, and the hot topic seemed to be
these AI price setting algorithms and you know what they
mean for antitrust and you know, can they even be
addressed by existing anti trust law? And I know your
firm has done a lot of work on this, I think, really,
you know, and very soon going to be leading one
of the first appellate arguments related to the issue itself,
(08:59):
But could you talk talk a little bit about the
Gibson case, and you know the oral arguments you have
slated for next month in the Ninth Circuit.
Speaker 3 (09:05):
Well, the Gibson case, like our other AI price mixing cases,
alleges that the hotel casinos hired the defendant to use
their rent maximizing services I think they call them. And
so the AI company collects non public information and public
(09:30):
information from the casinos or the landlords or.
Speaker 2 (09:34):
The protein you know, processors.
Speaker 3 (09:37):
They then take that information and they send it back
to the casino and they say, hey, here's what Steve's
casino is charging for that room, here's what Justin's casino
is charging, and here's what we think you should charge.
And we believe there's an agreement among the people subscribing
(09:58):
to this service that we will price where the AI
company suggests we should price. So you're taking away independent
decision making and there's a tacit understanding that you know,
we're all going to set the price recommended by someone else.
So it's just as I told Judge Lasnik when I
(10:21):
was arguing the Yardy motion.
Speaker 4 (10:23):
To dismiss sure Sure, It's like, hey, it used to be.
Speaker 3 (10:26):
You know, a bunch of old guys got in a room, right,
they smoked cigars, and they said, I said, look, imagine
if we were right before the Federal bar dinner, all
the leading CEOs of law firms got together and said, hey,
Microsoft is killing us on the rates.
Speaker 2 (10:43):
Man.
Speaker 3 (10:43):
You know, I don't want to charge four hundred. I
want to charge six hundred. But apparently some of you
are charging four hundred. You know, we should all charge
six hundred. And then everyone took that suggestion and they
all charged six Would anyone doubt that that was price fixing? No,
And that's what's going on with these AI things. He
got it, He got it that it was per se
(11:05):
price fixing, where the judge Tennessee said, oh no, it's
not per se. For a reason, Well, it's price fixing,
and price fixing is per se period.
Speaker 4 (11:14):
Right right.
Speaker 1 (11:15):
I mean, and to your point, I mean talk yeah, yeah, yeah,
I mean it's good, it's good.
Speaker 4 (11:20):
I mean, and I haven't read anything yet.
Speaker 1 (11:22):
Perfect, You're gonna do great, I have no doubt about that.
But I mean, to your point, this is really I
think something coming together and something that could be teed
up for a Supreme Court ruling at some point down
the road too, because the ruling so far has been
so disparate on this subject from place to place, right,
and in the Gibson case, the dismissal that you'll obviously
be arguing the appeal on next about the Lardy to
your point, the per se finding, you know, with the
(11:44):
use of these algorithms, and then in Tennessee kind of
this halfway step right with using the rule of reason.
Speaker 4 (11:49):
So yeah, just so so much going on there.
Speaker 1 (11:52):
And you know, I suppose you know you've already.
Speaker 4 (11:54):
Touched this one.
Speaker 2 (11:57):
I wouldn't mind going to the Supreme.
Speaker 4 (11:58):
Court with sure, sure, but they have been.
Speaker 2 (12:00):
Pretty good on anti trust matters.
Speaker 4 (12:04):
Yeah, Like if you read their.
Speaker 2 (12:05):
Opinion in my alstin case, they were right on sure.
Sure couldn't have written it better myself.
Speaker 1 (12:12):
Yeah, the court does, the core current composition of the
court does seem to get anti trust, which you can't
say for all judges. So it's definitely nice. Nice to
see that too. And I think you know you've probably
hit upon this too in what you said already, but
in terms of what the District Court got wrong in
Gibson or you might have gotten wrong, you know, I
think an important feature of these algorithms seems to be
(12:32):
that folks kind of auto accept them sometimes too, if
I'm not mistaken, right, you know, to your point about
there being in agreement, there isn't this independent decision making.
I think a lot of times when these folks use
an algorithm and you know, the price is then displayed
to the consumer. So if you have any thoughts about that,
you know, I think that probably is someone that really
points to an agreement being in place in terms of
(12:54):
how these cases look under an anti trust review as well, I.
Speaker 3 (12:57):
Would agree with you that you know it's either a
tacit understanding or express understanding. Got it, You're going to
accept the recommend the price, got it? Why would you
be paying the money to that to the AI company?
Speaker 1 (13:12):
Sure, they're given you something that's what it sounds like.
So definitely, so, you know, interesting and I certainly don't
know the answer to this, but you know, to your point,
we've seen these these algorithms that use in real estate
and with hotels, lodging, those kinds of those industries. But
you know, are you aware or you know kind of
think that maybe these algorithms are being used in a
more widespread way across different industries, and it was something
(13:34):
to kind of keep our eye on, you know, for
the future.
Speaker 3 (13:37):
Yes, I think it is more widespread than what's currently
targeted by litigation, and we're looking at some industries right now.
Speaker 1 (13:47):
So you know, I know you've been involved in a
large antitrust MDL for years now about beef prices and
a whole lot of other agricultural areas as well. You know,
I think just the other day we saw Tyson, you know,
agree to a settlement with relation to pork for example. Right,
you know, a lot of folks don't know about this,
but what's going on in agriculture, right, what's going on
with proteins?
Speaker 2 (14:07):
Why is this?
Speaker 1 (14:08):
Why is antitrust and price fixing such a pervasive allegation
proceeeding in these markets?
Speaker 3 (14:13):
So we have anti trust cases and we actually kind
of started these in the pork industry, the chicken industry,
the turkey and beef.
Speaker 2 (14:24):
You know, all these industries.
Speaker 3 (14:25):
Are you have a small group of processors do the same,
the Tysons and everyone.
Speaker 2 (14:30):
Cargills and everyone.
Speaker 3 (14:32):
And they can't control supply. So people supplied too many chickens,
too many pigs, and then the price goes down, the
allm you know, get hurt.
Speaker 2 (14:44):
So they came together and said, let's control our supply.
They we'll all do better.
Speaker 3 (14:48):
And they did that in every industry, and they did
it through one of these third parties.
Speaker 2 (14:53):
Now it's not a AI.
Speaker 4 (14:55):
It was kind of more old school, right, more traditional.
Speaker 3 (14:58):
Yeah, agristats would go meet with every processor and then
they would send the other processors pricing and supply information
back to you as a customer, and they wouldn't have
the name of the other processor on it, but these
people could figure it out. So they knew what Tyson
(15:19):
was charging, and they knew what you know, JD was charging,
and what the supply was and they were able to
control supply.
Speaker 1 (15:27):
Got it.
Speaker 4 (15:28):
Got it.
Speaker 1 (15:28):
And I'm assuming this is kind of similar to what
we're seeing around DOJ investigating eggs right now. And you know,
it seems like there's been litigation around that subject in
the past, but the same general idea I think with
regard to that particular corner of the market.
Speaker 3 (15:41):
I will tell you that half of my team, I
think has become vegetarians on those cases where we had
to see actually how they make all this.
Speaker 1 (15:50):
Yeah, yeah, I have a colleague who was involved in
an anti trust case. It's the same place, it's right, Yeah,
I think once you experience that, it's not something you
really want to want to adjust.
Speaker 3 (16:00):
Disgusting that in the case the judge granted their motion
eliminated that we couldn't show any pictures of processing their chickens.
Speaker 1 (16:09):
Wow wow, interesting Yeah, right, that speaks volumes then definitely, definitely.
Speaker 2 (16:14):
Sometimes there's fun facts in these cases.
Speaker 1 (16:17):
Yeah, yeah, no, definitely. You know, I feel like that's
the interesting thing about anti trust.
Speaker 2 (16:20):
I think that one of the big issues in anitrust cases. Yeah, that.
Speaker 3 (16:26):
I think judges are struggling with, and I've heard particularly
Judge Kenzalas.
Speaker 2 (16:30):
Rogers talking about yes, yeah, and that is the complexity.
Speaker 4 (16:35):
Sure.
Speaker 3 (16:35):
So, you know, I just got done with the deposition
of my expert in the Amazon price fixing case. This
reports like fifteen hundred pages with like two thousand footnotes.
Speaker 4 (16:47):
Sure, sure, both.
Speaker 3 (16:48):
Sides have done this right, and then the judge gets
all us and the judge is not an economist, right,
and you know, both sides say, well, the other expert
should be Dauber and he's full of beans.
Speaker 2 (17:02):
He doesn't know what he's doing.
Speaker 4 (17:03):
Sure. Sure, What are you supposed to do with all this?
Speaker 2 (17:06):
It's just too much?
Speaker 3 (17:08):
Yes, yes, I don't know that I have an answer
to it other than I keep telling my lawyers and
they're so tired of hearing it.
Speaker 2 (17:17):
Every time I get an ex report.
Speaker 3 (17:18):
I want to summary that is in plain English, that's
actually exciting that the judge will read, because I don't
believe any judge is going to read twelve hundred pages
or sure.
Speaker 1 (17:29):
Sure, I mean they might endeavor to do it, but
if you can stay away for it, that's a miracle
in and of itself.
Speaker 2 (17:35):
Get him interested in the summary, and then if they
want to read a little.
Speaker 4 (17:37):
Bit more they will, Sure, but please.
Speaker 2 (17:40):
Make it understandable. I think that's just a big challenge.
Speaker 1 (17:45):
Sure, I think you're right, Especially with the economics involved
with all these cases too, it could be really difficult
to follow sometimes and that makes a lot of sense
for sure.
Speaker 3 (17:54):
And another thing that I've seen because of the complexity
of the marketplace, So you know, in the protein cases,
we had to digest like every sale of chicken in
the nation at every single place, and same thing, and
so you're talking about mega bites of information that the
(18:14):
experts have to digest. In the Amazon case, imagine we've
examined I think eighty three billion transactions.
Speaker 2 (18:22):
Wow.
Speaker 3 (18:23):
Right the cost of all this, you know, it used
to be that as a plaintiff story, you might spend
a couple hundred grand on an expert.
Speaker 1 (18:30):
Oh yeah, it's incredible.
Speaker 2 (18:31):
Now we're talking.
Speaker 3 (18:32):
About spending five to ten million dollars. Sure, sure in
your economic experts.
Speaker 2 (18:37):
That is a huge change.
Speaker 1 (18:39):
Absolutely, And the government when it brings a case incurring
substantially the same cost too, right, So I mean it's
not even just the law firms, and you know if
they're if they're pursuing it as a plaintiff, is very
interesting stuff.
Speaker 4 (18:50):
Yeah.
Speaker 1 (18:51):
So, Steve, is there anything else you want to add
before we wrap up here? Outside of these cases, I
would say.
Speaker 3 (18:55):
Two things about it if you're thinking about plaintiff's law
and impact. So I've done two cases that I call
transformative cases in the last got it?
Speaker 2 (19:06):
And the first is the real estate.
Speaker 3 (19:08):
Case about commissions, and the New York Times and others
are suggesting that that might save somewhere between ten and
forty billion dollars to American consumers because of the change
and the rules that we implemented in the real estate.
So that's an anti trust case that actually is going
to transform into something that affects most Americans.
Speaker 2 (19:30):
We all buy homes. Of course, I'm highly.
Speaker 3 (19:34):
Confident that in the week Judge Wilkin will prove my
NCAA ANI trust case. But there's another anti trust case
that has been transformative because now going forward, all these
student athletes are going to share in the revenues that
come in from TV broadcasts to get sales. So you
can use the anti trust to be a powerful tool
(19:54):
for changing America. That's why I became a lawyer, So
I'm thrilled every day when I could come in and
work on stuff that makes a difference.
Speaker 1 (20:03):
Love that, love that super inspiring. Steve Berman, thanks again
for joining us a great conversation with that question. I
know I'll be seeing a lot more coming from Hoggins
Berman on the anti trust front and many others in
the months and years ahead. And as always, thank you
to you the listener for tuning in. As a reminder,
you can read all of our Bloomberg intelligence research on
the Bloomberg terminal at bi go. And with that, I'm
(20:25):
justin terresy and this with Boots and verdicts
Host
Elliott Stein
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