July 17, 2025 • 48 mins
If there's one thing that lawyers do a lot of, it's spending a prodigious number of hours going through documents. And they're often very well compensated for this work. So if there's one area where AI can obviously be highly disruptive, it's law. Documents that used to take hours to scan or format might be dealt with instantly. Finding relevant prior case law is becoming much faster, thanks to today's most advanced models. On this episode, we speak with Joel Wertheimer of Wertheimer Fleder LLP, a civil rights law firm in New York. We discuss the actual economics of being a lawyer, how it's changing, the effect that the technology will have on the distribution of income going forward, and what the entire profession could look like years into the future.
Only Bloomberg.com subscribers can get the Odd Lots newsletter in their inbox — now delivered every weekday — plus unlimited access to the site and app. Subscribe at bloomberg.com/subscriptions/oddlots
See omnystudio.com/listener for privacy information.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, radio News.
Speaker 2 (00:18):
Hello and welcome to another episode of The Odd Lots podcast.
Speaker 3 (00:22):
I'm Joe Wisenthal and I'm Tracy Alloway.
Speaker 2 (00:24):
Tracy, I was at my cousin's wedding this weekend, and
I have a lot of lawyers in my family, and
every time I know that, yeah, yeah, and my extended
family a lot of lawyers in there, and I'm always
asking them, like what they do and stuff. Within like
five seconds of any conversation, I'm like, tell me about
trials and techniques like swathe the jury, etc. The stuff
(00:45):
I see on TV. I am aware though that that
is actually not that big of a part of many
lawyers like day to day.
Speaker 3 (00:52):
Well, I have a lawyer in my family too, an
ex lawyer, my husband, who did big law, big corporate law,
absolutely hated it and got out of it luckily. And
so I have a feeling in this particular episode, I'm
just going to ask a lot of work life balance
questions based on my own experience of my husband's experience. Yeah,
(01:15):
but it is a huge industry, and it's one of
those industries that I think all financial journalism actually doesn't
do a good job of covering along with accounting. So
we should talk about it.
Speaker 2 (01:27):
We definitely should talk about it. We should talk about
it way more than we do. Within the AI conversation, specifically,
you hear a lot about the prospects of this being
either like a force multiplier or a labor reducer, because
my understanding is that a lot of like, especially like
junior lawyers, they're up all night. What are they like
(01:47):
looking for misplaced commas because those could be a big
deal in contracts, right, and so in theory, and again, Tracy,
I'm sure you know way more about this than I do.
But in theory that sort of seems like something a
I might be good at, Like, oh no, if the
is not here and it's there, then that totally changes
the definition of this clause or whatever.
Speaker 3 (02:04):
There's a famous case involving a commo that did exactly that.
So many points to make here. First of all, I
am vastly in favor of anything that makes corporate lawyers
lives slightly more efficient and happier, so AI could be
useful here. But I also wonder, you know, the lawyer profession,
they have things like templates and standard forms and stuff
(02:26):
like that. So I also wonder how much of an
improvement AI will be here. So I'm excited to talk
about it.
Speaker 2 (02:32):
You know that, Tracy, when they get the AI tools
really in place, they're just going to give them more work.
Speaker 3 (02:36):
Yeah, well that's what I suspect.
Speaker 1 (02:38):
Yeah, yeah, no, one's.
Speaker 3 (02:39):
Actually by the way, I have a lot of stories
of like partners calling from their fishing boats on the
weekend demanding that junior lawyers go into the office and
like fix a comma and things like that.
Speaker 2 (02:51):
All Right, Well, I'm really excited to say we do
have the perfect get. Someone that I've known for a
very long time, someone who just knows about a lot
of stuff. Someone who is lawyer. We're going to be
speaking with Joel Worthheimer. He's currently at Worthheimer Fleet LLP
of civil rights firm here in New York City. He's
previously at the White House. He's done big law in
(03:12):
the past. He knows a lot about a lot of stuff.
He knows a lot about poker, he knows a lot
about AI. Someone I think we had just talked to
about anything. He knows a lot about elections. He just
sort of knows everything. Joel, Thank you so much for
coming on Odd Laws thrilled to have you here.
Speaker 4 (03:27):
Thank you for having me.
Speaker 2 (03:28):
Why do you real? Quickly tell us, like who you are,
what do you do? Why are we talking to you.
Speaker 5 (03:32):
I run my own civil rights law firm. I just
partnered up, and we sue the government mostly for violations
of civil rights. Sometimes that's false arrests or wrongful convictions.
Sometimes that's wrongful removals of kids and let's say child
services for a shaken baby that was a false accusation,
that sort of thing, And we try to get people
(03:53):
compensation for the wrongs of their constitutional rights. That's about
eighty percent of what we do.
Speaker 3 (04:00):
Question. Are civil slash criminal lawyers? Are they happier than
corporate lawyers?
Speaker 5 (04:04):
I would say on average, sure, but the distribution is
probably pretty wide for each you know. Look, I do
think on the nice thing on the plaintiff side, and
it's like I'm my own boss. I get to, you know,
determine how much I work, and each extra case it's
just more money or less money if I if I
decide not to take it, and so I can sort
of set my own work life balance when I do that,
(04:28):
you know, and it's it's constantly a decision of sort
of what's the expected value of a case and is
it worth it to me in terms of the hours
I have to put in.
Speaker 2 (04:35):
So let's talk about when you were at a big
law and you know, I joked that you know people
they're up at one am and they're looking at commas.
I know that's a little bit of an exaggeration, but no,
it's not, and it really isn't.
Speaker 1 (04:46):
Yeah, I guess it's not.
Speaker 2 (04:48):
And I know that lawyers are really obsessed with billbile
hours and I think they even like measure things in
ten minute increments, like so six minutes, six minute increments.
If you're a junior associated or enter a law firm, whatever,
what is the modal use of your time? What are
you mostly doing when you're clocking those six minute increments?
Speaker 4 (05:06):
Right?
Speaker 5 (05:06):
So it's gonna I can only really speak to litigation
because of corporate you're I think we're just reviewing contracts
and deal points constantly. For litigator, A lot of your
your time is in discovery, and that's true small law,
big law, but you are reviewing documents, uh, synthesizing what
they say. Maybe you're trying to do a privileged check
(05:27):
and say, okay, this document we can't turn over. You know,
that's changed some actually with machine learning, the predictive coding
has shrunk the amount of time that you know, junior
associates are spent doing that legal research, fights with opposing counsel.
You need to give us these documents you're saying they're privileged,
they're not privileged, that sort of thing. And then there's
(05:49):
the smaller section on taking depositions, you know, briefing things
to court. So that's very broad overview of those six
minute increments, and yes, editing and reviewing, looking for hanging commas,
you know, hanging headers. That was always the ban of
my existence, was forgetting that there was a hanging header.
Speaker 4 (06:07):
Yeah, and getting ye all that for it.
Speaker 2 (06:09):
That sounds bad, you know, the economics of a big
law firm. It feels like this very big pyramid structure,
which I think is replicated in many industries around the world,
probably in finance to some extent, and then I think
even academia to some extent. But talk to us a
little bit about like how that value accruise to the
(06:29):
entire firm and the partners and the distribution of the
fees that the clients are paying.
Speaker 5 (06:35):
Right, so you have what they call leverage in a
law firm, So you have equity partners. Some firms have
equity partners and income partners who don't actually own a
chair of the firm, but the partners are trying to
get leverage on the associates. So one partner to say
four associate ratio, all of the big law firms basically
(06:55):
pay the exact same amount to their associates.
Speaker 4 (06:58):
This is called the Cravat scale.
Speaker 5 (07:00):
You can look it up and it'll say a third
year associate makes two hundred and fifty thousand dollars and
gets this bonus each year.
Speaker 4 (07:08):
Let's just say for.
Speaker 5 (07:11):
The average associate bills seven hundred dollars an hour and
is expected to bill about two thousand hours a year.
So they're generating one point four million for the firm
in revenue in terms of build out, and they're getting
paid i'd say with taxes and everything, five hundred thousand.
(07:31):
So the partners are making nine hundred thousand dollars for
every extra associate. So if you have a four to
one leverage, nine hundred thousand profits per partner three point
six million. And that's how they're trying to think of it,
and the big partners, the rain makers are the ones
who can generate enough work to support those associates. And
if you can't support those associates, your leverage goes down,
(07:53):
your profits go down.
Speaker 4 (07:54):
You might have to let people off that sort of thing.
Speaker 3 (07:57):
It's nice to be a partner at big law. But
on that note, so my understanding, at least in corporate
law is that it is harder to make partner nowadays
than it used to be. And this is part of
the reason why it's a miserable experience, because it used
to be in the past. You know, you work really
really hard, basically give up your life for like two
decades or whatever, and then you get rewarded with a
(08:18):
huge salary and you don't have to do as much
of the grunt work. Your job is basically sourcing deals
and making the intros and stuff like that. Do you
get that impression as well on your side?
Speaker 5 (08:30):
I definitely see from the outside that it seems harder
to make partner. I think that's led to people more
people leaving earlier to do their own firms. I think
it's easier than ever to start.
Speaker 4 (08:41):
Your own firm.
Speaker 3 (08:42):
And why is that.
Speaker 5 (08:43):
I mean, for one, I mean for me, for example,
I didn't need an office when I started. I started
in January of twenty twenty one. I had a desk
at a you know, at another law firm that collected mail.
I think the number of services are just easier to access,
even things like you know now if you really wanted to,
like cut, you could start with a cheaper legal research
(09:04):
service than West Law. Things like that, I think, and
you've seen it in the in the business creation numbers.
I think you see a lot of professional services, you know,
splitting off from firms. But I definitely think it's harder
to make partner.
Speaker 4 (09:16):
They have had that.
Speaker 5 (09:17):
They've added this income partner level, so you make partner,
but you're not an equity member of the firm. I
think consolation prize, that's right, and you get to shop
the title.
Speaker 4 (09:27):
I think it's the other reason. You know.
Speaker 5 (09:29):
So let's say you want to go in house somewhere.
Now you're a partner at this firm and you can
say you're a partner at the firm even if you
haven't bought in.
Speaker 4 (09:36):
But I think that structure has been around longer.
Speaker 5 (09:38):
Honestly, it feels like the same thing it's in academy
it's harder to get ten here now, it's just the
latter's getting pulled up.
Speaker 4 (09:44):
I guess in the sort of.
Speaker 2 (09:45):
Industry, would anyone go into a big law firm if
they knew in advance that they wouldn't make partner? Like
there's some like the angel of the future comes to
them in a dream and says, you know what, you're
not going to make partner? Would that still be worthwhile?
Or is the prospect even if it's declining of making
(10:08):
partner like? Is that crucial towards that decision? If you
knew in advance you weren't going to make it? Would
anyone make that decision?
Speaker 5 (10:15):
So they do have staff attorneys at big law firms
that are people who are not on partner track.
Speaker 1 (10:20):
Okay, and those are fine careers.
Speaker 5 (10:23):
And they're fine careers I think people you know, but
they also have less expectation of how much they're going
to work.
Speaker 4 (10:30):
You typically wouldn't do it.
Speaker 5 (10:31):
And the reason they have this up or out sort
of system at the big law firms is because the
prospect of being partner drives you to sell you twenty
twenty five hundred hours, how many it is you're showing.
Speaker 3 (10:44):
How well the light at the end of the tunnel, right.
Speaker 1 (10:46):
That's right?
Speaker 5 (10:47):
So you know, I think, Look, the training is really good,
the cases are really interesting, Like I actually quite enjoyed
some of it, But that pressure to bill and work is.
Speaker 4 (10:59):
You probably wouldn't I want that.
Speaker 1 (11:01):
When you say training, like, you know, I don't, like
what's the deal? Like in law school you don't even
learn about any of the things you actually do as
a lawyer.
Speaker 5 (11:09):
You certainly learn, you know how to think about the law,
but you're not learning in the city and you have
a leader.
Speaker 1 (11:15):
Because I think this is.
Speaker 2 (11:16):
Actually important for the AI component of like, Okay, what
is how do you actually learn to be a lawyer
if you don't really do it in law school? And
then you know AI is going to take over more
and more of these functions like the prospect where do
you learn?
Speaker 3 (11:30):
Right?
Speaker 5 (11:31):
So what is So here's an example. You don't learn
how to have a dispute about discovery in law school. Okay,
you know I sent out discovery demands you owe me documents.
Right under in the American system of law, somebody you get,
you end up in a lawsuit, and each side is
obligated to exchange documents with each other. And you you
(11:51):
send out demands and you ask for a certain category
of documents and they come back and say we're not
going to give them to that request was overly burdensome
or they're not really or they say they lost them,
or they say they lost them, and you have to
have a fight about getting the documents. What keywords did
you search, who did you collect documents from? All of
those sorts of things, and how to have that dispute,
(12:14):
how to make the request so you don't get the
denial those sorts of things, and what the writing looks
like and feels like you just don't get. In law school,
you just the and even writing a brief, and what's
a persuasive brief? The edits those sorts of things. You
learn how to do legal writing, but it's just you
can't do it until you're doing it.
Speaker 1 (12:35):
Got it okay?
Speaker 3 (12:37):
So on that note, I mean, AI seems possibly most
at home replicating the work done by say a mildly competent,
maybe not too tired, junior associate. And historically you do
that work for many years and you build foundational skills
of being a lawyer, like attention to detail and issue
(12:59):
spot and I guess, risk triage, and that sort of thing.
If those tasks, those formational tasks are now outsourced to AI,
what do you see as the impact on junior lawyers.
Speaker 5 (13:11):
It's a great question. I think it's going to be
hard for junior lawyers at big law firms to get
their sort of that training. On the other hand, it
may just be that they are doing more work and
so on the same things, but more efficiently. Maybe they're
now going to have more fights about documents and less
(13:35):
time spending reviewing the documents. Maybe they can increase the
volume of things they demand, that sort of thing. I
certainly think that the leverage model and the build our
model is going to run into some difficulty. It'll also
make their lives easier, just in terms of you know,
as an example, you.
Speaker 4 (13:55):
Get discovery requests.
Speaker 5 (13:56):
I talk about discovery a lot because it's truly like
a lot of the work of being a lawyer. But
they come, you know, the other side will send you
a PDF with a bunch of demands, and then you've
got to respond to the demands, and even just the
moment where you have to convert the PDF into a
word document and start editing the work word document it's
like the true bane of my existence. And I've actually
(14:17):
started using this AI program which it's called brief Point AI,
and and they are it's also very templated, right, so
you're constantly trying to find templates. Hey, other associated in
this law firm, can you send me, you know, a
previous document?
Speaker 4 (14:34):
Now I can?
Speaker 5 (14:35):
They have you know, eighty different objections that you're used
to making, and they convert them and it's a lot
more pointing click And of course you have to know
what you're doing when you're you know that these objections
are valid. But just the document formatting and getting it through,
you know, and it looked to look good and and
(14:57):
not have to fight with Microsoft Word for three hours
is really valuable.
Speaker 3 (15:02):
I realized I should have asked this earlier. But when
we say AI, what does that actually entail in the
legal field, Because, as you point out, I mean template
standard forms, those sort of things have been around forever
and a lot of law firms already use template software
to quickly duplicate ork or make document packages or whatever.
So when we talk about AI in law, what exactly
(15:25):
would that be?
Speaker 4 (15:26):
I think it can be a lot of things.
Speaker 5 (15:28):
One, it can be making that template process a lot faster,
and uh, you know that will free up labor time
for sure. The you know Chatgypts three pro is doing
legal research now that is quite excellent.
Speaker 2 (15:43):
This is really important. People who think that this that
three is dumb or is a hallucination machine are not
or that chagpts have not used oh three.
Speaker 4 (15:53):
That's that's my view.
Speaker 5 (15:54):
And you know, there's this professor at Georgetown I think
its name is Danny Wels Townsend who's just sort of
every time a new model has been coming out, has
been running sort of exam questions that he gives to
his students. I think it's in his Federal Courts class
about you know, how they do on each of these questions.
(16:14):
And when O three came out, not even O three PRO.
When O three came out, it was it answered them all,
some of them excellently, and even got what he was
called an issue spotter question. So it wasn't on the
face of the question it was an appellate jurisdiction question.
If you really were thinking hard about it as a student,
(16:34):
you would have noticed this issue that he wasn't asking
about explicitly. But there might not have been jurisdiction to
even bring the appeal that he prompted you about. And
O three caught that. And when I've used it, you know,
you hear a lot of these cases lawyers getting sanctioned
because they're, you know, submitting things with hallucinated cases.
Speaker 3 (16:53):
And there's some funny examples of that.
Speaker 4 (16:55):
They're they're amazing.
Speaker 5 (16:56):
And the thing I think to myself is you would
never admit as a as a partner at a law firm,
you'd never submit whatever the junior associate just turned over
to you. Sometimes they didn't understand the case exactly right.
And so that's the job is checking the cases. Shepherdizing
is the I think the Lexus term for it, and
making sure the cases stand for what they say, that
(17:18):
they're still valid precedent.
Speaker 4 (17:19):
That's the job of being a lawyer.
Speaker 5 (17:22):
And now I can rely on three to start some
of the research for me, point me even just to
point me to the cases and exciting to the cases.
And this is without access to Bloomberg Law or Thompson
Reuters or anything like that. I assume it's coming and
once it's going to be integrated with those databases of cases.
(17:42):
Right now, it's just trawling the Internet. I think it's
going to do a fantastic job. And you spend so
much time as a lawyer, as a litigator thinking of
the Boollyan search terms for lexus, the and or these
sorts of things, and you don't know the exact term
that's going to come up in case, you know what
the all of the precedent use this term, and not
(18:05):
having to think about that, I can run it in
the background as I'm doing another task and for twenty
minutes and something comes back from three It's got the
five cases that I need to to dig in and
find the right you know, language to then go on
Lexus and then to chase it down.
Speaker 2 (18:20):
I've been using three more for just sort of my
own like intellectual questions from time lawsuits. No, I haven't
done any I haven't started any lawsuits yet. But this
is really the way that I've been using it, which
is that it's a fantastic tool for just like discovering
the existing research that's out there. I was looking at
(18:42):
something I was curious about, like trade barriers within China
between provinces, you know, something like that. There is a
lot of research that's been done on the question of
like Okay, if each of these provinces has some motivation
to promote their champions, is there any tension?
Speaker 1 (18:56):
There is something?
Speaker 2 (18:56):
I would have it found all of this all. It
had the links to the academic research that's been about it.
It had summaries of them. The summaries may have been wrong,
but I'm not in the I'm not going to like
copy and past summaries and present it as my work.
I could click on it most of the time, it is,
they are pretty correct. It's so what you say in
(19:18):
terms of like just even like being able to find
the relevant case law, et cetera, seems extremely powerful and
time saving.
Speaker 5 (19:25):
It's truly been life changing for me. Well, and I
like doing legal research. I like getting into the cases,
but just you know, if there's a new issue and
you just don't know where to start, you know, that's
that It was always I think for a juniors, where
do I start? And I think it will make their
life easier in that regard, even if it might also
make their.
Speaker 1 (19:46):
Lives you know hard.
Speaker 3 (19:55):
Okay, time saving making associates lives easier, that sounds great
from a personal perspective, but what does that actually mean
for billable hours? Because of course, the whole business model
seems to rely on eking out as much work as
many billable hours as possible, right, and that includes grunt work,
which theoretically could be done by AI. Now, and I'm
(20:17):
not sure Big law or any law is going to
be necessarily incentivized to use AI if it means a
reduction in billable hours. I suppose they could make it
up in volume. Maybe that's that's the idea they can
take on more cases. But is that the expectation they
might be able to make it up in volume. I
(20:38):
do think things like they call them alternate fee arrangements
are going to become more popular. We get a flat
fee of let's say five million dollars to do this
deal for you or something like.
Speaker 1 (20:50):
That, then you're incentivized to do it in the fewest
hours possible. That's right, keep going.
Speaker 5 (20:54):
So that's one possibility that the model just changes the
billable hour, it stops being the model. The other thing is,
you know the way it works right now is it's
been a while for me, so you know, the big partners,
let's say they're building out at two thousand dollars an
hour or fifteen hundred dollars an hour and the associates
are seven hundred dollars an hour. I think in a
lot of ways, what the client is paying for is
(21:16):
the is really like five thousand dollars an hour for
the partner and four hundred or three hundred for the associate.
But it just gets built out sept differently. And I
think one thing is that partners might just accrue a
lot more of the value with fewer associates. They still
have the billd hours, they're just a lot more efficient.
(21:37):
And you know, in particular, I think for general counsels
who are hiring at the big law firms, they're hiring
for safety. You know, nobody ever got fired for hiring Cravat.
It's sort of like a way to think about this
or a big law firm, if something goes wrong, you
want to have hired the best lawyer you could and
(21:57):
say to your board or your CEO, look I hired
a great law firm, and they just they just missed it.
But look this is everybody agrees this is a great
law firm. Which is all to just say that. I
think one possibility here is the bill hour remains, but
all the value accruise to the top top lawyer.
Speaker 2 (22:15):
Yeah, I mean that seems like it'll have implications. We
should talk about that further. Something I have done is
I'll take episodes transcripts of odd lats, and afterwards I'll
do a little self criticism session. Well, I'll like say, like,
where could we have pressed this? Where were the weaknesses
in the guests?
Speaker 1 (22:35):
Answer?
Speaker 2 (22:36):
Where should we have pressed further and harder? What were
some of the logical flaws? What would you have done differently? Etcetera?
And sometimes I've found that to be useful. Have you
been able to use AI for essentially like building better
arguments or finding weaknesses in an argument or anything like
that yet.
Speaker 5 (22:53):
I haven't done that yet. I'm sure I will. I
have used it for taking audio and making it into
oh transcripts. I mean that's just like a foundational thing
for me. Prison will produce an audio of a hearing
or something like that, and I need the transcript and
I need to like just read it instead of listening
to it for forty minutes.
Speaker 2 (23:11):
But self criticism, Yeah, but it also it does sound
like you mentioned the issue spotter question, like actually being
able to identify real legal questions.
Speaker 3 (23:22):
Not just an identify precedent.
Speaker 2 (23:23):
Yeah, not just identify president, but actually logical sequences or
where like it sounds like if you're getting.
Speaker 4 (23:29):
That, I'm sure it is coming.
Speaker 5 (23:31):
And I think as I, you know, get as the
models get better, and I have to produce a brief
and maybe I can start running it through. Of course,
lawyers all have huge confidentiality concerns so everything they do,
so I'm very careful about what I'm putting into GPT. Yeah,
you know, and I can run your own deep sea instance.
(23:53):
I think that that's right. And I think the big
law firms are having sort of servers on site with
their own models, but those models aren't as good as
three yet, and so I think as you can start
to have great models in house on your own servers,
that's going to really be the thing that launches it.
I can't do that because it's just me and I'm
(24:14):
not going to host a server farm, but I do know,
right the new Apple chips on these very nice the
news they can run you know, things like Lama very well,
and so it's coming. But I think for the top models,
I'm sort of reluctant to put everything up there that
makes sense.
Speaker 3 (24:30):
This is exactly what I was going to ask next,
which is how do clients feel about AI in the
legal industry, because I imagine, you know, nobody ever got
fired for hiring Kravath as you mentioned, or some other
magic circle law firm. But on the other hand, if
Kravath is now using AI, I imagine on the client side,
(24:50):
maybe there's some concern over having their material contracts or
employee data or financing documents or whatever getting uploads to
off site servers. And then there's also the question of
what if AI just makes a mistake, although, as you
pointed out, no partner would ever submit something done by
(25:11):
a junior associate without actually reviewing it first, so maybe
that's not as much of an issue. But are there
any qualms I guess coming from the client side that
you see.
Speaker 5 (25:21):
So I can't speak to the big law as much
any sure, And it's very different I think on my side,
and I think, you know, my clients are their qualms
are much sort of bigger in terms of privacy and
much more you know, focused on the government and are
wanting to get just the best representation they can. So
(25:42):
but for example, I'm getting medical records from my clients
a lot. That's a lot of the job of a
plaintiff side lawyer is documenting injuries things like that, and
they're certainly concerned about their medical privacy, and so I can't,
you know, use AI yet to take the medical recD
and condense them into you know, the quick summaries. But
(26:05):
those programs I'm sure are coming where you know you
have there's there's privacy and security and all of the things.
They probably exist already. I'm just not using them yet
to make that part feasible. I am sure that you know,
if you are Goldman Sachs and you hire a big
law firm and they've been doing your your deals or
your IPOs such as they exist right now, and you
(26:27):
don't want the law firm training on your documents to
go use them in other deals. I'm sure this is
an issue. On the other hand, you know it might
reduce your legal costs by by half, and you can
fight about that, and so you know what they're willing
to do.
Speaker 4 (26:42):
I don't. I don't know.
Speaker 2 (26:43):
Let's extend forth some of these economic questions, because allowing
the senior partners to accrue more value by not needing
to allocate as many hours to the junior lawyers, that
makes total sense for this specific generation, right, because Okay,
some people are lucky enough to have made partner before AI,
and then other people are going to be in this
(27:04):
situation which their value may be could be done more
cheaply or for a few hours, but ten years from
now whatever, a lot of those partners are gonna be retired, etc.
Like what is the downstream consequence of your view in
your view of some of these shifts that happen right now,
because you know, eventually all the partners you know, ventually
Evere's get die and there's gonna be new, Like where
(27:25):
does this go?
Speaker 1 (27:26):
Like what's the next? What are the consequences?
Speaker 5 (27:28):
So I think that the skills that will be valued
in lawyers are just going to change a lot. The
interpersonal skills of client management, walking your client through the
risks that they have, their nervous they're getting sued. These
are bet the company litigations. The lawyers who can make
them feel safe and let them understand what's happening to
(27:51):
them and what their odds are. Those sorts of things.
The lawyers who are great at taking depositions and the
lawyers who are great at oral argument, those skills are
going to go up and up. I think in skill
in value and the skill of legal research or just
being great at writing a brief, I do think that
that's going to get maybe not the ninety ninth percentile
(28:13):
brief writing the people who are going to the Supreme
Court and who are just truly excellent.
Speaker 4 (28:17):
Maybe that will take time.
Speaker 5 (28:18):
But the sort of gruntwork, you know, solid junior associate,
mid level associate, senior associate who are writing the brief,
that I question whether that skill will have the same value.
But there's a lot of interpersonal skill that matters a
lot for being a lawyer, and that's going to go
up in value.
Speaker 2 (28:37):
Now. Question with any new technology is does it because
one argument is clearly, okay, there's an x amount of
demand for legal services and there's an x amount of
people who supply them, and maybe you save some money.
Could the market for legal services grow such that if
capacity to do legal research and some of this other
(28:58):
stuff gets cheaper, that there are more areas it's like, oh,
you know what, maybe this is worth filing the laws.
Speaker 3 (29:05):
This was actually going to be my question as well,
but particularly for poorer plaintiffs who normally can't afford a lawyer,
what did they call them.
Speaker 5 (29:14):
In indigent and they sometimes will file pro se and
their on behalf.
Speaker 1 (29:18):
Or maybe more.
Speaker 2 (29:19):
Lawyers like you take on cases, take other cases that
five years ago the economics wouldn't have made sense, but
today the economics made sense.
Speaker 1 (29:27):
Like could it just be you know, Jevin's paradox?
Speaker 5 (29:30):
But for law I think that's absolutely going to happen.
You know, I can just sort of walk through the
economics in one of my cases. You know, somebody comes
in and they say they had a false arrest case
against the NYPD and they spent let's say five hours
in custody. We sort of know what the expected value
of that case is. You know, you're doing what chance
are you do you have to win? And what are
(29:51):
the damages you are going to get when you win?
And I can sort of and then I I a
contingency fee, typically a third in New York, and you
can sort of do that math of the expected value
of the case and then think about how many hours
it's going to take to win that case or get
to a settlement. And if I'm using AI to make
myself more productive in my research, the number of hours
(30:13):
that I'm expecting to put into that case goes down.
Suddenly my hurdle rate for you know, what it takes
to take on that case has gone down, and I
can take on more cases for the same number of hours.
And so that I definitely think is coming. It's also
the case that right and because of that, because lawyers
have to think in that term of you know, how
much is it going to cost me to do this
(30:34):
case in terms of labor, there are a lot of
cases brought pro sae in the court system right now.
I think it's like twenty twenty five percent of cases
are from pro se litigants. These are other people represent
the who represent themselves because they can't afford a lawyer
or you know, my cases are contingency. People aren't paying
out of pocket, but so I can't afford to take
on the case because the damages aren't potentially high enough.
Speaker 4 (30:56):
That's how I have to sort.
Speaker 5 (30:57):
Of think about it. And so I think there's going
to be a lot more representation.
Speaker 4 (31:02):
Of those people.
Speaker 5 (31:02):
It's also the case probably that pro say it lawyers
are going to start getting better that you know, you
said you were doing research on your own, you know,
with three it's possible that you know, if it was
just a little dispute with somebody over some amount of money.
You might think I can do this myself rather than
trying to go find a lawyer. And so, you know,
(31:23):
but for legal aid, for people who are criminal defense
attorneys at legal aid, those attorneys that I think are
about to go on because of how overworked they are
and underpaid they are, they they might get a lot
more efficient and be able to represent a lot more people.
Speaker 2 (31:36):
Tracy, I'm imagining a lot of very annoyed judges by
like pro.
Speaker 1 (31:40):
Saying frivolous lawsuits.
Speaker 2 (31:42):
No I mean no, I mean like someone who did
their own research, because nothing's more annoying than someone who
does their own research. And then they're like they're like
citing all these cases that they learned about yesterday and
stuff like that. Like it just seems like you have
a high potential for obnoxious, obnoxious people who think.
Speaker 3 (31:58):
They know No, no, you're democratized in case. Yeah, that's
what I say.
Speaker 4 (32:01):
I want to be clear, they're already getting that.
Speaker 5 (32:04):
The judges are getting a lot of it, especially pro
SA prisoners who get to spend a lot of time
in the legal librarian or filing cases. And some of
them are excellent, but sometimes they're not so good. I
clerk for a federal judge, and we saw a lot
of this litigation, a lot of it pro se. I
don't know that they're you know, providing AI access in
prisons unfortunately in terms of litigation. But I think, I
(32:28):
actually think there are going to be a lot of
annoyed judges because there's going this is going to happen.
It also might be the case that it raises the
floor of You see a lot of bad legal writing,
even from lawyers, and I could see it getting it
actually getting a little bit easier to be a judge and.
Speaker 3 (32:43):
A clerk if everything becomes more volume oriented or the
business model becomes more about the volume rather than the
billable hours. Do you see a situation where I guess
the emphasis on sourcing deals in corporate law or sourcing
cases in plaintiff, Does that become more important, Like that's
(33:05):
the skill set that you actually need, that sort of
like matchmaker process.
Speaker 4 (33:09):
I think that there's yes.
Speaker 5 (33:11):
I think finding the deals, making the economics of the
of the relationship work is going to go up a
lot in value. You know, I think it's already the case.
You all see legal advertisements for personal injury lawyers everywhere
all the time. So I mean legal search terms on
(33:33):
Google are the most expensive cost per click. I mean
these thousands of dollars for cost per click. Case acquisition.
I think is might go up even more because if
you can just get the case in and you're still
you're working less on the case, but you're still getting
your third contingency fee, you might be willing to pay
even more and more to just generate this volume. I
(33:55):
mean already mills exist, they call them, you know, plaintiff's mills.
People who are doing you know, six hundred cases per
you know, every couple of attorneys or something like that.
The economics of that and just acquiring the case are
going to go I think, way way up until maybe
they start competing on price because they can do so
much more volume.
Speaker 1 (34:12):
I want to talk about advertising.
Speaker 2 (34:14):
Have you, Tracy Orgel, have either of you heard the
radio ads for top Dog Law?
Speaker 4 (34:18):
Yes?
Speaker 3 (34:19):
I have not you.
Speaker 2 (34:20):
Every listener go to YouTube and just type top Dog
Law ad. They're the most incredible, aren't they, Joel, Like
they're really incredible.
Speaker 3 (34:29):
Yes.
Speaker 2 (34:30):
Just go search right now or when the episode and
listen to some of these and do you buy ads
on Google?
Speaker 5 (34:36):
I've done some Google ad campaigns. I haven't really there's
actually another topic we're interested in. But a lot of
I mean a lot of plaintiff side civil rights lawyers
are buying. It's just not how I've chosen to compete.
I do more referrals from defense lawyers that sort of thing.
But I mean I actually have started to think about, Right,
(34:58):
we know this stuff about young people are starting to
use chat, GPT and other services as they're sort of
portal to the Internet. They're using it for search and
so right, all of these law firms spend a lot
on SEO, but what is SEO in a generative AI
world is sort of an interesting question? What are people
what are the engines turning up in terms of search terms?
(35:21):
What do you have to have on your website in
order to get people to find you through GPT rather
than Google?
Speaker 3 (35:28):
Is Lexus and Nexus doing anything what they are?
Speaker 4 (35:30):
They are?
Speaker 5 (35:31):
I have not really used their AI products Lexus and
I know West Law is doing the same.
Speaker 4 (35:36):
I use Lexus.
Speaker 5 (35:37):
I assume Bloomberg Law, which is also is doing something similar.
But right now the models that they're using just aren't
as good as three.
Speaker 4 (35:47):
It's basically and so if.
Speaker 5 (35:49):
You're still calling to a four era GPT or similar
from claud or whatever, that sort of quality, I just
don't think that they're getting good enough recent I think
it really was whatever that step change was to O
three's level, I think has made the research so much
better that I just use it, and then I'll go
(36:10):
look at all the cases on lexus.
Speaker 2 (36:12):
The difference in what you can actually learn from four
h or whatever for zero, I don't the name it.
Convention first all three it really is a very big deal.
And I think like a lot of people formed impressions
pre three impressions. What other tools are out there that
are interesting or that come across your world, whether it's
like I mean, you know, we've been talking a lot
(36:34):
about three, and you mentioned that other one brief something.
Is there anything else out there that's exciting or interesting
or promising.
Speaker 5 (36:40):
There's one I looked at that look promising. Uh, it's
like Ecutis or ike iq Idis something like that, and
they looked pretty interesting in terms of sort of being
full swite and wrap around. There's Harvey AI, but they're
really focused on big law firms. But I know that
they're working with a lot of big firms. But you know,
the technology you know, for me that looks promising would
(37:02):
be people where I can safely upload medical records and
get instead of trawling through two hundred three hundred pages
just like what was each progress note?
Speaker 4 (37:10):
What did it say? What's the injury?
Speaker 5 (37:11):
That sort of thing, And I think that's coming there
are I think it's maybe something from case text or
that summarizes depositions. And of course that's another thing where
I've tried to use it in the past and it
wasn't very good. I think just the context windows that
they were able to use haven't been sufficiently large. But
(37:31):
I think with RAG and with more and with better models,
I think that will get better and better, you know,
like this is the Ben Thompson line of this is
the worst there ever going to be? Yeah, is something
that I'm constantly trying to think about because I've used
these these products in the past or tested them and
they haven't been very impressive. But I also used four
(37:52):
oh and wasn't very impressed at it's legal research and
have seen that jump. And so I assume in terms
of taking depositions and and getting concise summaries, of the
most important facts for your case. That's going to get
a lot better. I just think the products aren't there yet.
And maybe because the API calls for the lms just
aren't to their newest models yet, or it's too expensive.
(38:12):
But I assume that's getting cheaper every you know, more's
loss still applies.
Speaker 3 (38:17):
If you had to bet, if you had to put
actual money on this question, would you say there will
be more or less lawyers, say ten years from now as.
Speaker 1 (38:28):
A percent the population.
Speaker 4 (38:29):
Yeah, that's a great question.
Speaker 3 (38:32):
Thank you for the caveat check.
Speaker 4 (38:33):
It's important and I hadn't I hadn't thought about this one.
I would.
Speaker 5 (38:37):
I would bet on fewer, but not that much. I
would say, I don't think this is, you know, going
to wipe out lawyers. I think fewer and what they
do will change a lot.
Speaker 2 (38:50):
Could you imagine, you know, tech people are obsessed with
the mythical who will be the first person to have
a billion dollars startup with no employees? Could that be like, okay,
you have you hung a shingle out. I think sometimes
people use Could you imagine a megafirm with one employee?
Speaker 5 (39:12):
I could imagine mega lawyer with you know, so right,
you think of se Selena and Barnes, those sorts of big,
big plaintiffs law firms. I think they that I actually
don't know, but it's a lot, and it's all across
the country. But so much of what they do is
make the discovery demand, respond to the demands, do the
(39:34):
get the medical records, send out a settlement demand letter,
Negotiate with the opposing council or the carrier from the insurer.
You know, my client has a torn rotator cuff and
a torn meniscus or something like that from this car accident,
and they have an exact expected value of the case,
and it's just negotiating that. And I think they could
(39:55):
go from you know, let's say one hundred cases per
attorney to a thousand or two two thousand because they
could set up an automated workflow a lot easier, I think,
And so you know, that person could could start making
fifty million or one hundred million a year per one lawyer.
Then the you know already five million that they're making
or something like that.
Speaker 4 (40:16):
These top firms.
Speaker 2 (40:16):
One last little question I mentioned your a poker player.
In poker, you know, big thing has been the emergence
of solvers and you go back and you like, look
at that, did you play it very well? But it's
all about what you kind of what you described of,
like your calculator EV right and.
Speaker 1 (40:32):
Did you play it right? And you don't always win.
Speaker 2 (40:33):
And you may have calculated ev right and you took
on the case, but you don't get the outcome. How
scientific is that the calculating evy on a given case
and has it is there a technology that's working on that?
Speaker 5 (40:46):
So it's not very scientific at all. You know, it's
a you can assess liability, I think pretty reasonably. Is
this going to be something where we're definitely going to win?
You know, the personal injury car accident lawyers to say,
you know, the police report says this person made an
a legal left turn. Perfect liability. I'm going to win instantly,
and then you're just evaluating the damages. One thing I've
(41:07):
actually explored is is looking into whether lms can estimate
the damages based on the injuries that you describe pretty well.
Go through the case law where there's cases this is
called remitted, or cases where you might hear like, oh,
this person got one hundred million dollars for their you know,
hot coffee or whatever. You know, these sort of classic cases,
(41:30):
and a judge will knock it down. They'll say, this
case with this injury is only worth this much. But
you could take all that language and start to estimate,
you know, quantify because words or numbers. With these programs,
you could start to quantify what are the injuries worth
in the in the case law and then multiply that
by So I think that sort of thing is going
(41:50):
to get a lot more scientific, and they're going to
use it on the carrier side. So Geico is going
to be able to say, you know, you've described these injuries.
We have a database of a thousand cases just like this,
and this was what we you know, and then you
could haggle, oh, well this is a great plaintiff or
something like that, and they're super sympathetic and you know,
have that negotiation. But I think that process of evaluating
(42:13):
the exact value of an injury or of a case
is going to get a lot more scientific and facilitate
settlements to happen quicker.
Speaker 3 (42:23):
I imagine AI might be especially useful in class action
lawsuits as well, where you're dealing with like finding thousands
of people potentially to attach to a case and then
actually contacting them and getting information from them.
Speaker 4 (42:36):
That seems reasonable to me.
Speaker 5 (42:38):
Also, in the class action cases, you just got a
volume of data that you have to do discovery on.
But it hadn't occurred to me. But you know, I
do know that sometimes class actions start because somebody finds
a Reddit thread and they see on Reddit, you know,
all the people are all complaining about this same issue
with this product or something like that, and the lawyers,
(42:59):
you know, reach out to them, and so it is
entirely possible.
Speaker 4 (43:03):
I could I could see that.
Speaker 3 (43:04):
That's another thing where you could have AI just trawling
the internet for possible cases.
Speaker 4 (43:09):
I think so.
Speaker 5 (43:10):
Or you know, what are people posting about on Twitter?
What are they all getting harmed by?
Speaker 4 (43:15):
I don't know. So it's it seems entirely plausible.
Speaker 1 (43:18):
Since you mentioned it.
Speaker 2 (43:20):
I just want to say you mentioned illegal lefts and
tracy and listeners. I had a issue last year whereight
I'm not going to get into it, but it involved
taking an illegal left.
Speaker 3 (43:32):
Turn a criminal.
Speaker 1 (43:34):
I'm not.
Speaker 3 (43:36):
Where you found innocent.
Speaker 1 (43:38):
I am not a criminal.
Speaker 2 (43:40):
Thanks to a referral that our guest here, Joel helped
make for me. I'm not going to say it. We're
not going to talk anymore about the case. It was
super annoying. I'm not gonna say anything more, but I
just want to. I'm it's my disclosure for this episode.
So Joel Wertheimer, thank you so much for coming on
odd last.
Speaker 1 (43:56):
That was fantastic.
Speaker 4 (43:57):
Thank you for having me.
Speaker 1 (44:12):
Tracy.
Speaker 2 (44:13):
Before we talk about conclusions, I must press upon listeners
again to search for top dog law firm ads. In fact,
after we do this episode, we walk back to our desk, Tracy,
I'm going to insist that you watch.
Speaker 1 (44:25):
A few of them.
Speaker 3 (44:25):
I love that your priority for this episode. The one
thing you must get out of this episode is listening
to top dog ads.
Speaker 2 (44:31):
No, I swear I was an uber home several months
ago and this ad came on the radio and just
like nothing I had ever heard my entire life. Nothing
will prepare you for this, this law firm's ads. Anyway,
I am very intrigued. Yeah, all right, well that was
a fantastic conversation.
Speaker 3 (44:47):
Yeah. One thing I am wondering is, you know, in
the US, there's a lot of talk about an overly
litigious society, and I kind of wonder if AI is
potentially just going to make it worse.
Speaker 2 (44:59):
It sounds very to me that it will make it
worse or better or worse. But I think, like, you know,
it does. My guess is that there's going to be
some sort of you know, Jeffen's paradox thing where like
some existing labor will get really cheap or maybe completely unnecessary,
and then other you know, the optimistic version is that
(45:20):
defendants or people without a lot of money get better
quality representation. I get, you know, it feels like it's
not gonna just it's gonna probably have very big distributional
and qualitative shifts on the industry.
Speaker 3 (45:32):
Yeah, and this is the thing I'm also wondering. So, Okay,
junior associates, maybe they they're doing less work, maybe they're
slightly happier. But I guess the idea that more of
the value just accrues to the partners at a time
when it's harder to become partner. Uh, that seems to
be the downside if you're going into the legal profession.
Speaker 1 (45:52):
Yeah, no, totally.
Speaker 2 (45:53):
Like it feels like we're at this moment and this
applies to a lot of actually AI economics quest and
we should definitely do more on them where people imagine
or people maybe even rightly surmised that you know, there
will be a lot of benefits for you know, existing
holders of wealth or companies can do layoffs, right, and
(46:16):
I don't know the degree to that which is really happening,
but at least in theory, and there's going to be
firing of junior workers, et cetera. But that's like a
temporary condition because you know, first of all, like, Okay,
a company saves a bunch of money by firing what
eventually becomes characterized as gruntwork. Well, what do they spend
that money on, right, because that's savings and so does
(46:37):
that do they invest in? Does that turn into consumption
for the partners? Like there are a lot of you know,
people are like, oh, it's gonna be mass layoffs. But
I never find these questions joy satisfying because the money
doesn't disappear. It's someone's savings, and someone's savings either become
someone's consumption or someone's investment, and its anyone's consumption or
investment becomes someone else's income. So therefore, you know, thinking
(46:59):
through some of these next level things I think is
really important. And AI clearly seemed just like ground zero,
and I do think O three is really good and
everyone no, seriously, everyone needs to check it out and
update their views if they haven't yet on the quality
of the research you can do.
Speaker 3 (47:15):
It does sound like it's maybe solved. The hallucination problem
was that everyone was making fun of earlier.
Speaker 2 (47:21):
Yeah, I mean like they're still there for sure. But
because you can actually find links to documents and stuff
like that, the speed with which you can get up
to speed on anything is very impressive.
Speaker 3 (47:31):
All right, I'm gonna go test it. Shall we leave
it there?
Speaker 1 (47:33):
Let's leave it there.
Speaker 3 (47:34):
This has been another episode of the Oudlots podcast. I'm
Tracy Alloway. You can follow me at Tracy Alloway.
Speaker 2 (47:39):
And I'm Jill Wisenthal. You can follow me at the Stalwart.
Follow our guest on Blue Sky Jill Wertheimer. He's at Worthwhile.
Follow our producers Carmen Rodriguez at Carman armand dash Ol
Bennett at Dashbod and Keil Brooks at Kilbrooks. From our
Oddlots content, go to bloomberg dot com slash odd Lots,
where we have a daily newsletter and all of our
episodes and you can chat about all of these topics.
(48:00):
Twenty four to seven in our discord. We even have
an AI.
Speaker 3 (48:02):
Channel in there, and if you enjoy Odd Lots, if
you like it when we talk about the impact of
AI on various professions, then please leave us a positive
review on your favorite podcast platform. And remember, if you
are a Bloomberg subscriber, you can listen to all of
our episodes absolutely ad free. All you need to do
is find the Bloomberg channel on Apple Podcasts and follow
(48:23):
the instructions there. Thanks for listening.
Bloomberg Audio Studios, Podcasts, radio News.
Speaker 2 (00:18):
Hello and welcome to another episode of The Odd Lots podcast.
Speaker 3 (00:22):
I'm Joe Wisenthal and I'm Tracy Alloway.
Speaker 2 (00:24):
Tracy, I was at my cousin's wedding this weekend, and
I have a lot of lawyers in my family, and
every time I know that, yeah, yeah, and my extended
family a lot of lawyers in there, and I'm always
asking them, like what they do and stuff. Within like
five seconds of any conversation, I'm like, tell me about
trials and techniques like swathe the jury, etc. The stuff
(00:45):
I see on TV. I am aware though that that
is actually not that big of a part of many
lawyers like day to day.
Speaker 3 (00:52):
Well, I have a lawyer in my family too, an
ex lawyer, my husband, who did big law, big corporate law,
absolutely hated it and got out of it luckily. And
so I have a feeling in this particular episode, I'm
just going to ask a lot of work life balance
questions based on my own experience of my husband's experience. Yeah,
(01:15):
but it is a huge industry, and it's one of
those industries that I think all financial journalism actually doesn't
do a good job of covering along with accounting. So
we should talk about it.
Speaker 2 (01:27):
We definitely should talk about it. We should talk about
it way more than we do. Within the AI conversation, specifically,
you hear a lot about the prospects of this being
either like a force multiplier or a labor reducer, because
my understanding is that a lot of like, especially like
junior lawyers, they're up all night. What are they like
(01:47):
looking for misplaced commas because those could be a big
deal in contracts, right, and so in theory, and again, Tracy,
I'm sure you know way more about this than I do.
But in theory that sort of seems like something a
I might be good at, Like, oh no, if the
is not here and it's there, then that totally changes
the definition of this clause or whatever.
Speaker 3 (02:04):
There's a famous case involving a commo that did exactly that.
So many points to make here. First of all, I
am vastly in favor of anything that makes corporate lawyers
lives slightly more efficient and happier, so AI could be
useful here. But I also wonder, you know, the lawyer profession,
they have things like templates and standard forms and stuff
(02:26):
like that. So I also wonder how much of an
improvement AI will be here. So I'm excited to talk
about it.
Speaker 2 (02:32):
You know that, Tracy, when they get the AI tools
really in place, they're just going to give them more work.
Speaker 3 (02:36):
Yeah, well that's what I suspect.
Speaker 1 (02:38):
Yeah, yeah, no, one's.
Speaker 3 (02:39):
Actually by the way, I have a lot of stories
of like partners calling from their fishing boats on the
weekend demanding that junior lawyers go into the office and
like fix a comma and things like that.
Speaker 2 (02:51):
All Right, Well, I'm really excited to say we do
have the perfect get. Someone that I've known for a
very long time, someone who just knows about a lot
of stuff. Someone who is lawyer. We're going to be
speaking with Joel Worthheimer. He's currently at Worthheimer Fleet LLP
of civil rights firm here in New York City. He's
previously at the White House. He's done big law in
(03:12):
the past. He knows a lot about a lot of stuff.
He knows a lot about poker, he knows a lot
about AI. Someone I think we had just talked to
about anything. He knows a lot about elections. He just
sort of knows everything. Joel, Thank you so much for
coming on Odd Laws thrilled to have you here.
Speaker 4 (03:27):
Thank you for having me.
Speaker 2 (03:28):
Why do you real? Quickly tell us, like who you are,
what do you do? Why are we talking to you.
Speaker 5 (03:32):
I run my own civil rights law firm. I just
partnered up, and we sue the government mostly for violations
of civil rights. Sometimes that's false arrests or wrongful convictions.
Sometimes that's wrongful removals of kids and let's say child
services for a shaken baby that was a false accusation,
that sort of thing, And we try to get people
(03:53):
compensation for the wrongs of their constitutional rights. That's about
eighty percent of what we do.
Speaker 3 (04:00):
Question. Are civil slash criminal lawyers? Are they happier than
corporate lawyers?
Speaker 5 (04:04):
I would say on average, sure, but the distribution is
probably pretty wide for each you know. Look, I do
think on the nice thing on the plaintiff side, and
it's like I'm my own boss. I get to, you know,
determine how much I work, and each extra case it's
just more money or less money if I if I
decide not to take it, and so I can sort
of set my own work life balance when I do that,
(04:28):
you know, and it's it's constantly a decision of sort
of what's the expected value of a case and is
it worth it to me in terms of the hours
I have to put in.
Speaker 2 (04:35):
So let's talk about when you were at a big
law and you know, I joked that you know people
they're up at one am and they're looking at commas.
I know that's a little bit of an exaggeration, but no,
it's not, and it really isn't.
Speaker 1 (04:46):
Yeah, I guess it's not.
Speaker 2 (04:48):
And I know that lawyers are really obsessed with billbile
hours and I think they even like measure things in
ten minute increments, like so six minutes, six minute increments.
If you're a junior associated or enter a law firm, whatever,
what is the modal use of your time? What are
you mostly doing when you're clocking those six minute increments?
Speaker 4 (05:06):
Right?
Speaker 5 (05:06):
So it's gonna I can only really speak to litigation
because of corporate you're I think we're just reviewing contracts
and deal points constantly. For litigator, A lot of your
your time is in discovery, and that's true small law,
big law, but you are reviewing documents, uh, synthesizing what
they say. Maybe you're trying to do a privileged check
(05:27):
and say, okay, this document we can't turn over. You know,
that's changed some actually with machine learning, the predictive coding
has shrunk the amount of time that you know, junior
associates are spent doing that legal research, fights with opposing counsel.
You need to give us these documents you're saying they're privileged,
they're not privileged, that sort of thing. And then there's
(05:49):
the smaller section on taking depositions, you know, briefing things
to court. So that's very broad overview of those six
minute increments, and yes, editing and reviewing, looking for hanging commas,
you know, hanging headers. That was always the ban of
my existence, was forgetting that there was a hanging header.
Speaker 4 (06:07):
Yeah, and getting ye all that for it.
Speaker 2 (06:09):
That sounds bad, you know, the economics of a big
law firm. It feels like this very big pyramid structure,
which I think is replicated in many industries around the world,
probably in finance to some extent, and then I think
even academia to some extent. But talk to us a
little bit about like how that value accruise to the
(06:29):
entire firm and the partners and the distribution of the
fees that the clients are paying.
Speaker 5 (06:35):
Right, so you have what they call leverage in a
law firm, So you have equity partners. Some firms have
equity partners and income partners who don't actually own a
chair of the firm, but the partners are trying to
get leverage on the associates. So one partner to say
four associate ratio, all of the big law firms basically
(06:55):
pay the exact same amount to their associates.
Speaker 4 (06:58):
This is called the Cravat scale.
Speaker 5 (07:00):
You can look it up and it'll say a third
year associate makes two hundred and fifty thousand dollars and
gets this bonus each year.
Speaker 4 (07:08):
Let's just say for.
Speaker 5 (07:11):
The average associate bills seven hundred dollars an hour and
is expected to bill about two thousand hours a year.
So they're generating one point four million for the firm
in revenue in terms of build out, and they're getting
paid i'd say with taxes and everything, five hundred thousand.
(07:31):
So the partners are making nine hundred thousand dollars for
every extra associate. So if you have a four to
one leverage, nine hundred thousand profits per partner three point
six million. And that's how they're trying to think of it,
and the big partners, the rain makers are the ones
who can generate enough work to support those associates. And
if you can't support those associates, your leverage goes down,
(07:53):
your profits go down.
Speaker 4 (07:54):
You might have to let people off that sort of thing.
Speaker 3 (07:57):
It's nice to be a partner at big law. But
on that note, so my understanding, at least in corporate
law is that it is harder to make partner nowadays
than it used to be. And this is part of
the reason why it's a miserable experience, because it used
to be in the past. You know, you work really
really hard, basically give up your life for like two
decades or whatever, and then you get rewarded with a
(08:18):
huge salary and you don't have to do as much
of the grunt work. Your job is basically sourcing deals
and making the intros and stuff like that. Do you
get that impression as well on your side?
Speaker 5 (08:30):
I definitely see from the outside that it seems harder
to make partner. I think that's led to people more
people leaving earlier to do their own firms. I think
it's easier than ever to start.
Speaker 4 (08:41):
Your own firm.
Speaker 3 (08:42):
And why is that.
Speaker 5 (08:43):
I mean, for one, I mean for me, for example,
I didn't need an office when I started. I started
in January of twenty twenty one. I had a desk
at a you know, at another law firm that collected mail.
I think the number of services are just easier to access,
even things like you know now if you really wanted to,
like cut, you could start with a cheaper legal research
(09:04):
service than West Law. Things like that, I think, and
you've seen it in the in the business creation numbers.
I think you see a lot of professional services, you know,
splitting off from firms. But I definitely think it's harder
to make partner.
Speaker 4 (09:16):
They have had that.
Speaker 5 (09:17):
They've added this income partner level, so you make partner,
but you're not an equity member of the firm. I
think consolation prize, that's right, and you get to shop
the title.
Speaker 4 (09:27):
I think it's the other reason. You know.
Speaker 5 (09:29):
So let's say you want to go in house somewhere.
Now you're a partner at this firm and you can
say you're a partner at the firm even if you
haven't bought in.
Speaker 4 (09:36):
But I think that structure has been around longer.
Speaker 5 (09:38):
Honestly, it feels like the same thing it's in academy
it's harder to get ten here now, it's just the
latter's getting pulled up.
Speaker 4 (09:44):
I guess in the sort of.
Speaker 2 (09:45):
Industry, would anyone go into a big law firm if
they knew in advance that they wouldn't make partner? Like
there's some like the angel of the future comes to
them in a dream and says, you know what, you're
not going to make partner? Would that still be worthwhile?
Or is the prospect even if it's declining of making
(10:08):
partner like? Is that crucial towards that decision? If you
knew in advance you weren't going to make it? Would
anyone make that decision?
Speaker 5 (10:15):
So they do have staff attorneys at big law firms
that are people who are not on partner track.
Speaker 1 (10:20):
Okay, and those are fine careers.
Speaker 5 (10:23):
And they're fine careers I think people you know, but
they also have less expectation of how much they're going
to work.
Speaker 4 (10:30):
You typically wouldn't do it.
Speaker 5 (10:31):
And the reason they have this up or out sort
of system at the big law firms is because the
prospect of being partner drives you to sell you twenty
twenty five hundred hours, how many it is you're showing.
Speaker 3 (10:44):
How well the light at the end of the tunnel, right.
Speaker 1 (10:46):
That's right?
Speaker 5 (10:47):
So you know, I think, Look, the training is really good,
the cases are really interesting, Like I actually quite enjoyed
some of it, But that pressure to bill and work is.
Speaker 4 (10:59):
You probably wouldn't I want that.
Speaker 1 (11:01):
When you say training, like, you know, I don't, like
what's the deal? Like in law school you don't even
learn about any of the things you actually do as
a lawyer.
Speaker 5 (11:09):
You certainly learn, you know how to think about the law,
but you're not learning in the city and you have
a leader.
Speaker 1 (11:15):
Because I think this is.
Speaker 2 (11:16):
Actually important for the AI component of like, Okay, what
is how do you actually learn to be a lawyer
if you don't really do it in law school? And
then you know AI is going to take over more
and more of these functions like the prospect where do
you learn?
Speaker 3 (11:30):
Right?
Speaker 5 (11:31):
So what is So here's an example. You don't learn
how to have a dispute about discovery in law school. Okay,
you know I sent out discovery demands you owe me documents.
Right under in the American system of law, somebody you get,
you end up in a lawsuit, and each side is
obligated to exchange documents with each other. And you you
(11:51):
send out demands and you ask for a certain category
of documents and they come back and say we're not
going to give them to that request was overly burdensome
or they're not really or they say they lost them,
or they say they lost them, and you have to
have a fight about getting the documents. What keywords did
you search, who did you collect documents from? All of
those sorts of things, and how to have that dispute,
(12:14):
how to make the request so you don't get the
denial those sorts of things, and what the writing looks
like and feels like you just don't get. In law school,
you just the and even writing a brief, and what's
a persuasive brief? The edits those sorts of things. You
learn how to do legal writing, but it's just you
can't do it until you're doing it.
Speaker 1 (12:35):
Got it okay?
Speaker 3 (12:37):
So on that note, I mean, AI seems possibly most
at home replicating the work done by say a mildly competent,
maybe not too tired, junior associate. And historically you do
that work for many years and you build foundational skills
of being a lawyer, like attention to detail and issue
(12:59):
spot and I guess, risk triage, and that sort of thing.
If those tasks, those formational tasks are now outsourced to AI,
what do you see as the impact on junior lawyers.
Speaker 5 (13:11):
It's a great question. I think it's going to be
hard for junior lawyers at big law firms to get
their sort of that training. On the other hand, it
may just be that they are doing more work and
so on the same things, but more efficiently. Maybe they're
now going to have more fights about documents and less
(13:35):
time spending reviewing the documents. Maybe they can increase the
volume of things they demand, that sort of thing. I
certainly think that the leverage model and the build our
model is going to run into some difficulty. It'll also
make their lives easier, just in terms of you know,
as an example, you.
Speaker 4 (13:55):
Get discovery requests.
Speaker 5 (13:56):
I talk about discovery a lot because it's truly like
a lot of the work of being a lawyer. But
they come, you know, the other side will send you
a PDF with a bunch of demands, and then you've
got to respond to the demands, and even just the
moment where you have to convert the PDF into a
word document and start editing the work word document it's
like the true bane of my existence. And I've actually
(14:17):
started using this AI program which it's called brief Point AI,
and and they are it's also very templated, right, so
you're constantly trying to find templates. Hey, other associated in
this law firm, can you send me, you know, a
previous document?
Speaker 4 (14:34):
Now I can?
Speaker 5 (14:35):
They have you know, eighty different objections that you're used
to making, and they convert them and it's a lot
more pointing click And of course you have to know
what you're doing when you're you know that these objections
are valid. But just the document formatting and getting it through,
you know, and it looked to look good and and
(14:57):
not have to fight with Microsoft Word for three hours
is really valuable.
Speaker 3 (15:02):
I realized I should have asked this earlier. But when
we say AI, what does that actually entail in the
legal field, Because, as you point out, I mean template
standard forms, those sort of things have been around forever
and a lot of law firms already use template software
to quickly duplicate ork or make document packages or whatever.
So when we talk about AI in law, what exactly
(15:25):
would that be?
Speaker 4 (15:26):
I think it can be a lot of things.
Speaker 5 (15:28):
One, it can be making that template process a lot faster,
and uh, you know that will free up labor time
for sure. The you know Chatgypts three pro is doing
legal research now that is quite excellent.
Speaker 2 (15:43):
This is really important. People who think that this that
three is dumb or is a hallucination machine are not
or that chagpts have not used oh three.
Speaker 4 (15:53):
That's that's my view.
Speaker 5 (15:54):
And you know, there's this professor at Georgetown I think
its name is Danny Wels Townsend who's just sort of
every time a new model has been coming out, has
been running sort of exam questions that he gives to
his students. I think it's in his Federal Courts class
about you know, how they do on each of these questions.
(16:14):
And when O three came out, not even O three PRO.
When O three came out, it was it answered them all,
some of them excellently, and even got what he was
called an issue spotter question. So it wasn't on the
face of the question it was an appellate jurisdiction question.
If you really were thinking hard about it as a student,
(16:34):
you would have noticed this issue that he wasn't asking
about explicitly. But there might not have been jurisdiction to
even bring the appeal that he prompted you about. And
O three caught that. And when I've used it, you know,
you hear a lot of these cases lawyers getting sanctioned
because they're, you know, submitting things with hallucinated cases.
Speaker 3 (16:53):
And there's some funny examples of that.
Speaker 4 (16:55):
They're they're amazing.
Speaker 5 (16:56):
And the thing I think to myself is you would
never admit as a as a partner at a law firm,
you'd never submit whatever the junior associate just turned over
to you. Sometimes they didn't understand the case exactly right.
And so that's the job is checking the cases. Shepherdizing
is the I think the Lexus term for it, and
making sure the cases stand for what they say, that
(17:18):
they're still valid precedent.
Speaker 4 (17:19):
That's the job of being a lawyer.
Speaker 5 (17:22):
And now I can rely on three to start some
of the research for me, point me even just to
point me to the cases and exciting to the cases.
And this is without access to Bloomberg Law or Thompson
Reuters or anything like that. I assume it's coming and
once it's going to be integrated with those databases of cases.
(17:42):
Right now, it's just trawling the Internet. I think it's
going to do a fantastic job. And you spend so
much time as a lawyer, as a litigator thinking of
the Boollyan search terms for lexus, the and or these
sorts of things, and you don't know the exact term
that's going to come up in case, you know what
the all of the precedent use this term, and not
(18:05):
having to think about that, I can run it in
the background as I'm doing another task and for twenty
minutes and something comes back from three It's got the
five cases that I need to to dig in and
find the right you know, language to then go on
Lexus and then to chase it down.
Speaker 2 (18:20):
I've been using three more for just sort of my
own like intellectual questions from time lawsuits. No, I haven't
done any I haven't started any lawsuits yet. But this
is really the way that I've been using it, which
is that it's a fantastic tool for just like discovering
the existing research that's out there. I was looking at
(18:42):
something I was curious about, like trade barriers within China
between provinces, you know, something like that. There is a
lot of research that's been done on the question of
like Okay, if each of these provinces has some motivation
to promote their champions, is there any tension?
Speaker 1 (18:56):
There is something?
Speaker 2 (18:56):
I would have it found all of this all. It
had the links to the academic research that's been about it.
It had summaries of them. The summaries may have been wrong,
but I'm not in the I'm not going to like
copy and past summaries and present it as my work.
I could click on it most of the time, it is,
they are pretty correct. It's so what you say in
(19:18):
terms of like just even like being able to find
the relevant case law, et cetera, seems extremely powerful and
time saving.
Speaker 5 (19:25):
It's truly been life changing for me. Well, and I
like doing legal research. I like getting into the cases,
but just you know, if there's a new issue and
you just don't know where to start, you know, that's
that It was always I think for a juniors, where
do I start? And I think it will make their
life easier in that regard, even if it might also
make their.
Speaker 1 (19:46):
Lives you know hard.
Speaker 3 (19:55):
Okay, time saving making associates lives easier, that sounds great
from a personal perspective, but what does that actually mean
for billable hours? Because of course, the whole business model
seems to rely on eking out as much work as
many billable hours as possible, right, and that includes grunt work,
which theoretically could be done by AI. Now, and I'm
(20:17):
not sure Big law or any law is going to
be necessarily incentivized to use AI if it means a
reduction in billable hours. I suppose they could make it
up in volume. Maybe that's that's the idea they can
take on more cases. But is that the expectation they
might be able to make it up in volume. I
(20:38):
do think things like they call them alternate fee arrangements
are going to become more popular. We get a flat
fee of let's say five million dollars to do this
deal for you or something like.
Speaker 1 (20:50):
That, then you're incentivized to do it in the fewest
hours possible. That's right, keep going.
Speaker 5 (20:54):
So that's one possibility that the model just changes the
billable hour, it stops being the model. The other thing is,
you know the way it works right now is it's
been a while for me, so you know, the big partners,
let's say they're building out at two thousand dollars an
hour or fifteen hundred dollars an hour and the associates
are seven hundred dollars an hour. I think in a
lot of ways, what the client is paying for is
(21:16):
the is really like five thousand dollars an hour for
the partner and four hundred or three hundred for the associate.
But it just gets built out sept differently. And I
think one thing is that partners might just accrue a
lot more of the value with fewer associates. They still
have the billd hours, they're just a lot more efficient.
(21:37):
And you know, in particular, I think for general counsels
who are hiring at the big law firms, they're hiring
for safety. You know, nobody ever got fired for hiring Cravat.
It's sort of like a way to think about this
or a big law firm, if something goes wrong, you
want to have hired the best lawyer you could and
(21:57):
say to your board or your CEO, look I hired
a great law firm, and they just they just missed it.
But look this is everybody agrees this is a great
law firm. Which is all to just say that. I
think one possibility here is the bill hour remains, but
all the value accruise to the top top lawyer.
Speaker 2 (22:15):
Yeah, I mean that seems like it'll have implications. We
should talk about that further. Something I have done is
I'll take episodes transcripts of odd lats, and afterwards I'll
do a little self criticism session. Well, I'll like say, like,
where could we have pressed this? Where were the weaknesses
in the guests?
Speaker 1 (22:35):
Answer?
Speaker 2 (22:36):
Where should we have pressed further and harder? What were
some of the logical flaws? What would you have done differently? Etcetera?
And sometimes I've found that to be useful. Have you
been able to use AI for essentially like building better
arguments or finding weaknesses in an argument or anything like
that yet.
Speaker 5 (22:53):
I haven't done that yet. I'm sure I will. I
have used it for taking audio and making it into
oh transcripts. I mean that's just like a foundational thing
for me. Prison will produce an audio of a hearing
or something like that, and I need the transcript and
I need to like just read it instead of listening
to it for forty minutes.
Speaker 2 (23:11):
But self criticism, Yeah, but it also it does sound
like you mentioned the issue spotter question, like actually being
able to identify real legal questions.
Speaker 3 (23:22):
Not just an identify precedent.
Speaker 2 (23:23):
Yeah, not just identify president, but actually logical sequences or
where like it sounds like if you're getting.
Speaker 4 (23:29):
That, I'm sure it is coming.
Speaker 5 (23:31):
And I think as I, you know, get as the
models get better, and I have to produce a brief
and maybe I can start running it through. Of course,
lawyers all have huge confidentiality concerns so everything they do,
so I'm very careful about what I'm putting into GPT. Yeah,
you know, and I can run your own deep sea instance.
(23:53):
I think that that's right. And I think the big
law firms are having sort of servers on site with
their own models, but those models aren't as good as
three yet, and so I think as you can start
to have great models in house on your own servers,
that's going to really be the thing that launches it.
I can't do that because it's just me and I'm
(24:14):
not going to host a server farm, but I do know,
right the new Apple chips on these very nice the
news they can run you know, things like Lama very well,
and so it's coming. But I think for the top models,
I'm sort of reluctant to put everything up there that
makes sense.
Speaker 3 (24:30):
This is exactly what I was going to ask next,
which is how do clients feel about AI in the
legal industry, because I imagine, you know, nobody ever got
fired for hiring Kravath as you mentioned, or some other
magic circle law firm. But on the other hand, if
Kravath is now using AI, I imagine on the client side,
(24:50):
maybe there's some concern over having their material contracts or
employee data or financing documents or whatever getting uploads to
off site servers. And then there's also the question of
what if AI just makes a mistake, although, as you
pointed out, no partner would ever submit something done by
(25:11):
a junior associate without actually reviewing it first, so maybe
that's not as much of an issue. But are there
any qualms I guess coming from the client side that
you see.
Speaker 5 (25:21):
So I can't speak to the big law as much
any sure, And it's very different I think on my side,
and I think, you know, my clients are their qualms
are much sort of bigger in terms of privacy and
much more you know, focused on the government and are
wanting to get just the best representation they can. So
(25:42):
but for example, I'm getting medical records from my clients
a lot. That's a lot of the job of a
plaintiff side lawyer is documenting injuries things like that, and
they're certainly concerned about their medical privacy, and so I can't,
you know, use AI yet to take the medical recD
and condense them into you know, the quick summaries. But
(26:05):
those programs I'm sure are coming where you know you
have there's there's privacy and security and all of the things.
They probably exist already. I'm just not using them yet
to make that part feasible. I am sure that you know,
if you are Goldman Sachs and you hire a big
law firm and they've been doing your your deals or
your IPOs such as they exist right now, and you
(26:27):
don't want the law firm training on your documents to
go use them in other deals. I'm sure this is
an issue. On the other hand, you know it might
reduce your legal costs by by half, and you can
fight about that, and so you know what they're willing
to do.
Speaker 4 (26:42):
I don't. I don't know.
Speaker 2 (26:43):
Let's extend forth some of these economic questions, because allowing
the senior partners to accrue more value by not needing
to allocate as many hours to the junior lawyers, that
makes total sense for this specific generation, right, because Okay,
some people are lucky enough to have made partner before AI,
and then other people are going to be in this
(27:04):
situation which their value may be could be done more
cheaply or for a few hours, but ten years from
now whatever, a lot of those partners are gonna be retired, etc.
Like what is the downstream consequence of your view in
your view of some of these shifts that happen right now,
because you know, eventually all the partners you know, ventually
Evere's get die and there's gonna be new, Like where
(27:25):
does this go?
Speaker 1 (27:26):
Like what's the next? What are the consequences?
Speaker 5 (27:28):
So I think that the skills that will be valued
in lawyers are just going to change a lot. The
interpersonal skills of client management, walking your client through the
risks that they have, their nervous they're getting sued. These
are bet the company litigations. The lawyers who can make
them feel safe and let them understand what's happening to
(27:51):
them and what their odds are. Those sorts of things.
The lawyers who are great at taking depositions and the
lawyers who are great at oral argument, those skills are
going to go up and up. I think in skill
in value and the skill of legal research or just
being great at writing a brief, I do think that
that's going to get maybe not the ninety ninth percentile
(28:13):
brief writing the people who are going to the Supreme
Court and who are just truly excellent.
Speaker 4 (28:17):
Maybe that will take time.
Speaker 5 (28:18):
But the sort of gruntwork, you know, solid junior associate,
mid level associate, senior associate who are writing the brief,
that I question whether that skill will have the same value.
But there's a lot of interpersonal skill that matters a
lot for being a lawyer, and that's going to go
up in value.
Speaker 2 (28:37):
Now. Question with any new technology is does it because
one argument is clearly, okay, there's an x amount of
demand for legal services and there's an x amount of
people who supply them, and maybe you save some money.
Could the market for legal services grow such that if
capacity to do legal research and some of this other
(28:58):
stuff gets cheaper, that there are more areas it's like, oh,
you know what, maybe this is worth filing the laws.
Speaker 3 (29:05):
This was actually going to be my question as well,
but particularly for poorer plaintiffs who normally can't afford a lawyer,
what did they call them.
Speaker 5 (29:14):
In indigent and they sometimes will file pro se and
their on behalf.
Speaker 1 (29:18):
Or maybe more.
Speaker 2 (29:19):
Lawyers like you take on cases, take other cases that
five years ago the economics wouldn't have made sense, but
today the economics made sense.
Speaker 1 (29:27):
Like could it just be you know, Jevin's paradox?
Speaker 5 (29:30):
But for law I think that's absolutely going to happen.
You know, I can just sort of walk through the
economics in one of my cases. You know, somebody comes
in and they say they had a false arrest case
against the NYPD and they spent let's say five hours
in custody. We sort of know what the expected value
of that case is. You know, you're doing what chance
are you do you have to win? And what are
(29:51):
the damages you are going to get when you win?
And I can sort of and then I I a
contingency fee, typically a third in New York, and you
can sort of do that math of the expected value
of the case and then think about how many hours
it's going to take to win that case or get
to a settlement. And if I'm using AI to make
myself more productive in my research, the number of hours
(30:13):
that I'm expecting to put into that case goes down.
Suddenly my hurdle rate for you know, what it takes
to take on that case has gone down, and I
can take on more cases for the same number of hours.
And so that I definitely think is coming. It's also
the case that right and because of that, because lawyers
have to think in that term of you know, how
much is it going to cost me to do this
(30:34):
case in terms of labor, there are a lot of
cases brought pro sae in the court system right now.
I think it's like twenty twenty five percent of cases
are from pro se litigants. These are other people represent
the who represent themselves because they can't afford a lawyer
or you know, my cases are contingency. People aren't paying
out of pocket, but so I can't afford to take
on the case because the damages aren't potentially high enough.
Speaker 4 (30:56):
That's how I have to sort.
Speaker 5 (30:57):
Of think about it. And so I think there's going
to be a lot more representation.
Speaker 4 (31:02):
Of those people.
Speaker 5 (31:02):
It's also the case probably that pro say it lawyers
are going to start getting better that you know, you
said you were doing research on your own, you know,
with three it's possible that you know, if it was
just a little dispute with somebody over some amount of money.
You might think I can do this myself rather than
trying to go find a lawyer. And so, you know,
(31:23):
but for legal aid, for people who are criminal defense
attorneys at legal aid, those attorneys that I think are
about to go on because of how overworked they are
and underpaid they are, they they might get a lot
more efficient and be able to represent a lot more people.
Speaker 2 (31:36):
Tracy, I'm imagining a lot of very annoyed judges by
like pro.
Speaker 1 (31:40):
Saying frivolous lawsuits.
Speaker 2 (31:42):
No I mean no, I mean like someone who did
their own research, because nothing's more annoying than someone who
does their own research. And then they're like they're like
citing all these cases that they learned about yesterday and
stuff like that. Like it just seems like you have
a high potential for obnoxious, obnoxious people who think.
Speaker 3 (31:58):
They know No, no, you're democratized in case. Yeah, that's
what I say.
Speaker 4 (32:01):
I want to be clear, they're already getting that.
Speaker 5 (32:04):
The judges are getting a lot of it, especially pro
SA prisoners who get to spend a lot of time
in the legal librarian or filing cases. And some of
them are excellent, but sometimes they're not so good. I
clerk for a federal judge, and we saw a lot
of this litigation, a lot of it pro se. I
don't know that they're you know, providing AI access in
prisons unfortunately in terms of litigation. But I think, I
(32:28):
actually think there are going to be a lot of
annoyed judges because there's going this is going to happen.
It also might be the case that it raises the
floor of You see a lot of bad legal writing,
even from lawyers, and I could see it getting it
actually getting a little bit easier to be a judge and.
Speaker 3 (32:43):
A clerk if everything becomes more volume oriented or the
business model becomes more about the volume rather than the
billable hours. Do you see a situation where I guess
the emphasis on sourcing deals in corporate law or sourcing
cases in plaintiff, Does that become more important, Like that's
(33:05):
the skill set that you actually need, that sort of
like matchmaker process.
Speaker 4 (33:09):
I think that there's yes.
Speaker 5 (33:11):
I think finding the deals, making the economics of the
of the relationship work is going to go up a
lot in value. You know, I think it's already the case.
You all see legal advertisements for personal injury lawyers everywhere
all the time. So I mean legal search terms on
(33:33):
Google are the most expensive cost per click. I mean
these thousands of dollars for cost per click. Case acquisition.
I think is might go up even more because if
you can just get the case in and you're still
you're working less on the case, but you're still getting
your third contingency fee, you might be willing to pay
even more and more to just generate this volume. I
(33:55):
mean already mills exist, they call them, you know, plaintiff's mills.
People who are doing you know, six hundred cases per
you know, every couple of attorneys or something like that.
The economics of that and just acquiring the case are
going to go I think, way way up until maybe
they start competing on price because they can do so
much more volume.
Speaker 1 (34:12):
I want to talk about advertising.
Speaker 2 (34:14):
Have you, Tracy Orgel, have either of you heard the
radio ads for top Dog Law?
Speaker 4 (34:18):
Yes?
Speaker 3 (34:19):
I have not you.
Speaker 2 (34:20):
Every listener go to YouTube and just type top Dog
Law ad. They're the most incredible, aren't they, Joel, Like
they're really incredible.
Speaker 3 (34:29):
Yes.
Speaker 2 (34:30):
Just go search right now or when the episode and
listen to some of these and do you buy ads
on Google?
Speaker 5 (34:36):
I've done some Google ad campaigns. I haven't really there's
actually another topic we're interested in. But a lot of
I mean a lot of plaintiff side civil rights lawyers
are buying. It's just not how I've chosen to compete.
I do more referrals from defense lawyers that sort of thing.
But I mean I actually have started to think about, Right,
(34:58):
we know this stuff about young people are starting to
use chat, GPT and other services as they're sort of
portal to the Internet. They're using it for search and
so right, all of these law firms spend a lot
on SEO, but what is SEO in a generative AI
world is sort of an interesting question? What are people
what are the engines turning up in terms of search terms?
(35:21):
What do you have to have on your website in
order to get people to find you through GPT rather
than Google?
Speaker 3 (35:28):
Is Lexus and Nexus doing anything what they are?
Speaker 4 (35:30):
They are?
Speaker 5 (35:31):
I have not really used their AI products Lexus and
I know West Law is doing the same.
Speaker 4 (35:36):
I use Lexus.
Speaker 5 (35:37):
I assume Bloomberg Law, which is also is doing something similar.
But right now the models that they're using just aren't
as good as three.
Speaker 4 (35:47):
It's basically and so if.
Speaker 5 (35:49):
You're still calling to a four era GPT or similar
from claud or whatever, that sort of quality, I just
don't think that they're getting good enough recent I think
it really was whatever that step change was to O
three's level, I think has made the research so much
better that I just use it, and then I'll go
(36:10):
look at all the cases on lexus.
Speaker 2 (36:12):
The difference in what you can actually learn from four
h or whatever for zero, I don't the name it.
Convention first all three it really is a very big deal.
And I think like a lot of people formed impressions
pre three impressions. What other tools are out there that
are interesting or that come across your world, whether it's
like I mean, you know, we've been talking a lot
(36:34):
about three, and you mentioned that other one brief something.
Is there anything else out there that's exciting or interesting
or promising.
Speaker 5 (36:40):
There's one I looked at that look promising. Uh, it's
like Ecutis or ike iq Idis something like that, and
they looked pretty interesting in terms of sort of being
full swite and wrap around. There's Harvey AI, but they're
really focused on big law firms. But I know that
they're working with a lot of big firms. But you know,
the technology you know, for me that looks promising would
(37:02):
be people where I can safely upload medical records and
get instead of trawling through two hundred three hundred pages
just like what was each progress note?
Speaker 4 (37:10):
What did it say? What's the injury?
Speaker 5 (37:11):
That sort of thing, And I think that's coming there
are I think it's maybe something from case text or
that summarizes depositions. And of course that's another thing where
I've tried to use it in the past and it
wasn't very good. I think just the context windows that
they were able to use haven't been sufficiently large. But
(37:31):
I think with RAG and with more and with better models,
I think that will get better and better, you know,
like this is the Ben Thompson line of this is
the worst there ever going to be? Yeah, is something
that I'm constantly trying to think about because I've used
these these products in the past or tested them and
they haven't been very impressive. But I also used four
(37:52):
oh and wasn't very impressed at it's legal research and
have seen that jump. And so I assume in terms
of taking depositions and and getting concise summaries, of the
most important facts for your case. That's going to get
a lot better. I just think the products aren't there yet.
And maybe because the API calls for the lms just
aren't to their newest models yet, or it's too expensive.
(38:12):
But I assume that's getting cheaper every you know, more's
loss still applies.
Speaker 3 (38:17):
If you had to bet, if you had to put
actual money on this question, would you say there will
be more or less lawyers, say ten years from now as.
Speaker 1 (38:28):
A percent the population.
Speaker 4 (38:29):
Yeah, that's a great question.
Speaker 3 (38:32):
Thank you for the caveat check.
Speaker 4 (38:33):
It's important and I hadn't I hadn't thought about this one.
I would.
Speaker 5 (38:37):
I would bet on fewer, but not that much. I
would say, I don't think this is, you know, going
to wipe out lawyers. I think fewer and what they
do will change a lot.
Speaker 2 (38:50):
Could you imagine, you know, tech people are obsessed with
the mythical who will be the first person to have
a billion dollars startup with no employees? Could that be like, okay,
you have you hung a shingle out. I think sometimes
people use Could you imagine a megafirm with one employee?
Speaker 5 (39:12):
I could imagine mega lawyer with you know, so right,
you think of se Selena and Barnes, those sorts of big,
big plaintiffs law firms. I think they that I actually
don't know, but it's a lot, and it's all across
the country. But so much of what they do is
make the discovery demand, respond to the demands, do the
(39:34):
get the medical records, send out a settlement demand letter,
Negotiate with the opposing council or the carrier from the insurer.
You know, my client has a torn rotator cuff and
a torn meniscus or something like that from this car accident,
and they have an exact expected value of the case,
and it's just negotiating that. And I think they could
(39:55):
go from you know, let's say one hundred cases per
attorney to a thousand or two two thousand because they
could set up an automated workflow a lot easier, I think,
And so you know, that person could could start making
fifty million or one hundred million a year per one lawyer.
Then the you know already five million that they're making
or something like that.
Speaker 4 (40:16):
These top firms.
Speaker 2 (40:16):
One last little question I mentioned your a poker player.
In poker, you know, big thing has been the emergence
of solvers and you go back and you like, look
at that, did you play it very well? But it's
all about what you kind of what you described of,
like your calculator EV right and.
Speaker 1 (40:32):
Did you play it right? And you don't always win.
Speaker 2 (40:33):
And you may have calculated ev right and you took
on the case, but you don't get the outcome. How
scientific is that the calculating evy on a given case
and has it is there a technology that's working on that?
Speaker 5 (40:46):
So it's not very scientific at all. You know, it's
a you can assess liability, I think pretty reasonably. Is
this going to be something where we're definitely going to win?
You know, the personal injury car accident lawyers to say,
you know, the police report says this person made an
a legal left turn. Perfect liability. I'm going to win instantly,
and then you're just evaluating the damages. One thing I've
(41:07):
actually explored is is looking into whether lms can estimate
the damages based on the injuries that you describe pretty well.
Go through the case law where there's cases this is
called remitted, or cases where you might hear like, oh,
this person got one hundred million dollars for their you know,
hot coffee or whatever. You know, these sort of classic cases,
(41:30):
and a judge will knock it down. They'll say, this
case with this injury is only worth this much. But
you could take all that language and start to estimate,
you know, quantify because words or numbers. With these programs,
you could start to quantify what are the injuries worth
in the in the case law and then multiply that
by So I think that sort of thing is going
(41:50):
to get a lot more scientific, and they're going to
use it on the carrier side. So Geico is going
to be able to say, you know, you've described these injuries.
We have a database of a thousand cases just like this,
and this was what we you know, and then you
could haggle, oh, well this is a great plaintiff or
something like that, and they're super sympathetic and you know,
have that negotiation. But I think that process of evaluating
(42:13):
the exact value of an injury or of a case
is going to get a lot more scientific and facilitate
settlements to happen quicker.
Speaker 3 (42:23):
I imagine AI might be especially useful in class action
lawsuits as well, where you're dealing with like finding thousands
of people potentially to attach to a case and then
actually contacting them and getting information from them.
Speaker 4 (42:36):
That seems reasonable to me.
Speaker 5 (42:38):
Also, in the class action cases, you just got a
volume of data that you have to do discovery on.
But it hadn't occurred to me. But you know, I
do know that sometimes class actions start because somebody finds
a Reddit thread and they see on Reddit, you know,
all the people are all complaining about this same issue
with this product or something like that, and the lawyers,
(42:59):
you know, reach out to them, and so it is
entirely possible.
Speaker 4 (43:03):
I could I could see that.
Speaker 3 (43:04):
That's another thing where you could have AI just trawling
the internet for possible cases.
Speaker 4 (43:09):
I think so.
Speaker 5 (43:10):
Or you know, what are people posting about on Twitter?
What are they all getting harmed by?
Speaker 4 (43:15):
I don't know. So it's it seems entirely plausible.
Speaker 1 (43:18):
Since you mentioned it.
Speaker 2 (43:20):
I just want to say you mentioned illegal lefts and
tracy and listeners. I had a issue last year whereight
I'm not going to get into it, but it involved
taking an illegal left.
Speaker 3 (43:32):
Turn a criminal.
Speaker 1 (43:34):
I'm not.
Speaker 3 (43:36):
Where you found innocent.
Speaker 1 (43:38):
I am not a criminal.
Speaker 2 (43:40):
Thanks to a referral that our guest here, Joel helped
make for me. I'm not going to say it. We're
not going to talk anymore about the case. It was
super annoying. I'm not gonna say anything more, but I
just want to. I'm it's my disclosure for this episode.
So Joel Wertheimer, thank you so much for coming on
odd last.
Speaker 1 (43:56):
That was fantastic.
Speaker 4 (43:57):
Thank you for having me.
Speaker 1 (44:12):
Tracy.
Speaker 2 (44:13):
Before we talk about conclusions, I must press upon listeners
again to search for top dog law firm ads. In fact,
after we do this episode, we walk back to our desk, Tracy,
I'm going to insist that you watch.
Speaker 1 (44:25):
A few of them.
Speaker 3 (44:25):
I love that your priority for this episode. The one
thing you must get out of this episode is listening
to top dog ads.
Speaker 2 (44:31):
No, I swear I was an uber home several months
ago and this ad came on the radio and just
like nothing I had ever heard my entire life. Nothing
will prepare you for this, this law firm's ads. Anyway,
I am very intrigued. Yeah, all right, well that was
a fantastic conversation.
Speaker 3 (44:47):
Yeah. One thing I am wondering is, you know, in
the US, there's a lot of talk about an overly
litigious society, and I kind of wonder if AI is
potentially just going to make it worse.
Speaker 2 (44:59):
It sounds very to me that it will make it
worse or better or worse. But I think, like, you know,
it does. My guess is that there's going to be
some sort of you know, Jeffen's paradox thing where like
some existing labor will get really cheap or maybe completely unnecessary,
and then other you know, the optimistic version is that
(45:20):
defendants or people without a lot of money get better
quality representation. I get, you know, it feels like it's
not gonna just it's gonna probably have very big distributional
and qualitative shifts on the industry.
Speaker 3 (45:32):
Yeah, and this is the thing I'm also wondering. So, Okay,
junior associates, maybe they they're doing less work, maybe they're
slightly happier. But I guess the idea that more of
the value just accrues to the partners at a time
when it's harder to become partner. Uh, that seems to
be the downside if you're going into the legal profession.
Speaker 1 (45:52):
Yeah, no, totally.
Speaker 2 (45:53):
Like it feels like we're at this moment and this
applies to a lot of actually AI economics quest and
we should definitely do more on them where people imagine
or people maybe even rightly surmised that you know, there
will be a lot of benefits for you know, existing
holders of wealth or companies can do layoffs, right, and
(46:16):
I don't know the degree to that which is really happening,
but at least in theory, and there's going to be
firing of junior workers, et cetera. But that's like a
temporary condition because you know, first of all, like, Okay,
a company saves a bunch of money by firing what
eventually becomes characterized as gruntwork. Well, what do they spend
that money on, right, because that's savings and so does
(46:37):
that do they invest in? Does that turn into consumption
for the partners? Like there are a lot of you know,
people are like, oh, it's gonna be mass layoffs. But
I never find these questions joy satisfying because the money
doesn't disappear. It's someone's savings, and someone's savings either become
someone's consumption or someone's investment, and its anyone's consumption or
investment becomes someone else's income. So therefore, you know, thinking
(46:59):
through some of these next level things I think is
really important. And AI clearly seemed just like ground zero,
and I do think O three is really good and
everyone no, seriously, everyone needs to check it out and
update their views if they haven't yet on the quality
of the research you can do.
Speaker 3 (47:15):
It does sound like it's maybe solved. The hallucination problem
was that everyone was making fun of earlier.
Speaker 2 (47:21):
Yeah, I mean like they're still there for sure. But
because you can actually find links to documents and stuff
like that, the speed with which you can get up
to speed on anything is very impressive.
Speaker 3 (47:31):
All right, I'm gonna go test it. Shall we leave
it there?
Speaker 1 (47:33):
Let's leave it there.
Speaker 3 (47:34):
This has been another episode of the Oudlots podcast. I'm
Tracy Alloway. You can follow me at Tracy Alloway.
Speaker 2 (47:39):
And I'm Jill Wisenthal. You can follow me at the Stalwart.
Follow our guest on Blue Sky Jill Wertheimer. He's at Worthwhile.
Follow our producers Carmen Rodriguez at Carman armand dash Ol
Bennett at Dashbod and Keil Brooks at Kilbrooks. From our
Oddlots content, go to bloomberg dot com slash odd Lots,
where we have a daily newsletter and all of our
episodes and you can chat about all of these topics.
(48:00):
Twenty four to seven in our discord. We even have
an AI.
Speaker 3 (48:02):
Channel in there, and if you enjoy Odd Lots, if
you like it when we talk about the impact of
AI on various professions, then please leave us a positive
review on your favorite podcast platform. And remember, if you
are a Bloomberg subscriber, you can listen to all of
our episodes absolutely ad free. All you need to do
is find the Bloomberg channel on Apple Podcasts and follow
(48:23):
the instructions there. Thanks for listening.
Hosts And Creators
Joe Weisenthal
Tracy Alloway
Popular Podcasts
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.
The Joe Rogan Experience
The official podcast of comedian Joe Rogan.
Dateline NBC
Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations. Special Summer Offer: Exclusively on Apple Podcasts, try our Dateline Premium subscription completely free for one month! With Dateline Premium, you get every episode ad-free plus exclusive bonus content.