Join the discussion: Ask Enam and Jordan questions about AI and law
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Connect with Enam Hoque: LinkedIn Profile
In a rapidly evolving digital landscape, businesses are increasingly embracing artificial intelligence (AI) to stay competitive and drive growth. However, the transition to an AI-first world is not as straightforward as it may seem. While the potential benefits are immense, business owners and decision-makers face both challenges and opportunities along this transformative journey.
Harnessing the Power of Data:
One of the primary challenges in transitioning to an AI-first world is ensuring access to the right quantity and quality of data. Many organizations today lack the necessary data to run AI algorithms effectively. This highlights the importance of building robust data collection mechanisms and unifying data warehouses. Business owners need to work closely with data engineers to establish reliable data pipelines to fuel their AI initiatives.
Addressing Trust and Reliability:
Trust is a critical factor in the adoption of AI technologies. To encourage buy-in from executives and stakeholders, businesses must address any skepticism surrounding AI by showcasing AI's ability to deliver reliable results. This requires investing in data quality, transparency, and ethical considerations, while ensuring accuracy and compliance with regulatory requirements. Building trust in AI is a gradual process that requires a focus on governance, legal frameworks, and establishing best practices within the organization.
Balancing Novelty and Tangible Outcomes:
While experimenting with AI and exploring its potential is exciting, businesses should not overlook the need for tangible outcomes and real value. Implementing AI purely as a novelty can erode trust and hinder broader adoption. Instead, business owners should emphasize the practical applications of AI that drive improved decision-making, higher productivity, and cost optimization. Demonstrating tangible results is crucial for securing executive support and facilitating the integration of AI into everyday business operations.
Promoting a Culture of Continuous Learning:
Transitioning to an AI-first world requires a culture of continuous learning and upskilling within the organization. Business owners should invest in providing employees with the necessary training and resources to adapt to new AI-driven processes and tools. This includes ensuring that employees understand the capabilities and limitations of AI and encouraging them to engage in ongoing professional development. A workforce equipped with AI literacy will be better positioned to exploit the full potential of AI and drive organizational success.
While the road to an AI-first world presents challenges, business owners who embrace these challenges can unlock significant opportunities. By prioritizing data quality, establishing trust, focusing on tangible outcomes, and fostering a culture of continuous learning, organizations can position themselves as innovators in their respective industries. The time is ripe for business leaders to navigate this transformative journey, harnessing the power of AI to drive growth, improve decision-making, and stay ahead of the competition.
Topics Covered in This Episode
1. Challenges businesses face in implementing AI
2. The importance of data quality and collection
3. Essential steps in AI implementation
4. Business results and productivity opportunities with AI
Jordan Wilson [00:00:18]:
One thing I always think about is what's gonna happen now with lawyers and attorneys and just the law in general now that Generative AI is getting better and better. Are we still gonna pay these really high legal fees? Is is is law gonna become, you know, legal representation gonna become affordable and more accessible? I'm I'm I'm excited to actually have someone that can give us Great insights on today's episode of Everyday AI. Welcome. Thank you for joining us. My name is Jordan Wilson. I'm your host. And if you don't know, everyday AI is a daily livestream, podcast, and free daily newsletter helping all of us all of us everyday people Learn and leverage generative AI. So we're gonna do that, and I'm very excited to talk about today how AI will transform, the business of law.
Jordan Wilson [00:01:11]:
I'm very excited for you all because we have a great guest with, just extensive background, in this field. So, before we get to that, as we always do, let's go over the AI news. And if you're joining us live, Let us know right now. What are your questions? What are your questions? Get them in now so we can, tackle them and answer them live on show. That's one thing about everyday AI. That's a little unique as as we take your questions live and get them answers by, answered by experts. So alright. Let's jump into the AI news because there's actually Some big, big things going on today.
Daily AI news
Jordan Wilson [00:01:45]:
Let's start with Samsung. They're making some historic moves. So, the electronics giant just launched a generative AI model made for its own Samsung devices called Samsung, called Samsung Gauss. The presumption is that the Samsung Gauss model will come to Samsung's popular smartphones such as the Galaxy S 24, And looks like they're probably gonna be apple to the punch and the 1st to bring, generative AI to a major mobile device. Samsung Gauss is named after the legendary mathematician, Carl Friedrich Gauss. I think I'm pronouncing that right, and includes language code and image functions. Alright. Samsung's not the only big tech name making some moves.
Jordan Wilson [00:02:29]:
Amazon as well. Y'all have heard of that. Right? This this little company called Amazon, I think they sell books. But they've, they're entering now the large language model game Reportedly. So, they are working on their own large language model code named Olympus according to a recent Reuters report. So Amazon, is investing 1,000,000 in training a large language model called Olympus with, 2 trillion parameters, which would make it, one of the largest large language models to date. Amazon has obviously already been investing in a lot of other companies in their large language models, Specifically, a reported $4,000,000,000. That's billion with a b.
Jordan Wilson [00:03:09]:
Yes. Investment in Anthropic and their large language model, Claude 2. Alright. Last but not least, Meta is requiring advertisers to disclose AI use in political ads. So a freshly, released, announcement from the Facebook and Instagram parents company, is saying that this new policy, applies to Facebook and Instagram ads and requires advertisers to disclose when AI generated or altered content is featured and political, electoral, or social issue ads next year. Obviously, this decision comes as lawmakers and regulators are preparing to address the use of AI In political ads, as we get closer ahead to the 2024 presidential election, my only comment on that is, like, what what took so long? Like, We've we've we've seen, you know, leaders from both parties, you know, already, use AI generated ads. So, I'm I'm wondering what took so long. Like, we know that it shouldn't be or it should at least be disclosed in political ads.
About Enam and his law career
Jordan Wilson [00:04:13]:
Right? Alright. But You did not come here to talk and chat about the AI news. Maybe you did, but, you're probably wondering about How AI is going to transform the businesses of of of law. I'm extremely excited about that one. And for that, let's go ahead ad And bring on today's guest. I'm super excited to have Enam Hoque, consultant at law beta. Enam, thanks for joining the show. Appreciate it.
Enam Hoque [00:04:39]:
Yeah. Yeah. Yeah. No problem. It's early in the morning here, but we're we're ready to go.
Jordan Wilson [00:04:43]:
Yeah. He makes he he makes the elite list of people that have joined The live show from the West Coast. So thank you for that, Enam. Maybe just let's start high level. Give everyone just a real quick background, of of of your career and, you know, kind of some of your experience in loss. We can kinda set the stage here.
Enam Hoque [00:05:00]:
Oh, of course. Of course. So I spent the 1st 10 years of my career at law firm in New York, you know, doing corporate finance. Spent the next, maybe 8 years or so at Moody's, a debt rating agency, where I was studying legal risks incorporating some of that into the ratings platforms and, their own analysis. And we were doing a lot of manual work, but really turning this documents into structured scores, things like that that investors could use. So I spent almost, 20 years doing that. And really just, I'm the type of lawyer that actually does not has never been to court. You know? Nothing like, you know, fancy like that.
Enam Hoque [00:05:37]:
Like, Not the ones you see on TV, more or less the negotiating lawyer or the one on the phone. But what's interesting about that, That experience was that I really just only did one type of law my whole career, and then I subsequently did the same thing at Moody's. So, I'm really, really, focused on leverage finance, leverage loans, and corporate finance, and that that's sort of, my legal background. But I've been a technologist pretty much all my life. It's kind of my my passion, my love. I've been into it, as far as I can remember, maybe 56 100 baud comp you know, CompuServe Internet in 1988, maybe. So it's it's been a while, and, You know, it just, and now I'm getting to now that the law and sort of artificial intelligence, machine learning, and these technologies are sorta colliding, It's everything I love now all packed together, so that's kind of, the skinny of it.
About LawBeta and AI
Jordan Wilson [00:06:30]:
It's it's it's great, and I I kinda feel the same way. Right? Like, I've always even for me personally, I've always been kind of a dork, and I've always been fascinated by the creative side and, the tech side, New Internet innovations and, you you know, for yourself with your law background. I mean, maybe let's even talk, like, how did this culmination of events and kind of your, creation of of, law beta. How did that kind of all play out?
Enam Hoque [00:06:56]:
You know, the seed for it, honestly, was probably in high When I had done, in 1997, I did, like, a whole presentation on a legal a law firm that was gonna be online. It's gonna be like law.com, something like that. And so the seed was definitely planted there. I kinda had an idea that I was gonna be a lawyer for a long time. I think what really accelerated all this for me personally was probably COVID, to be honest. Being in New York City, sort of being trapped in an apartment for, you know, a year, I decided to really lean into that sort of area of my life that I hadn't really, hadn't had time to really focus on. So it was learning Python, taking you know, refreshing, taking, like, Harvard's free CS 50 class. Like, doing all those kind of things and getting Getting back into it a little bit just because that was my passion.
Enam Hoque [00:07:43]:
That's what I actually would like to do. And so that that sort of, culminated obviously with perfect timing about, you know, these Large language models and, you know, the paper from 2017 and then OpenAI, and everything just sort of came together. So that was, that was basically it.
Jordan Wilson [00:08:01]:
Yeah. And and just, you know, generally speaking, what is kind of the focus that that you're doing with law beta? You know, is it more helping, you know, others kind of understand the, kind of AI in the in the technical side of of law and where it's going?
Enam Hoque [00:08:18]:
Yeah. Yeah. Yeah. And on a broad level too, I I should say, because I know you've had a few speakers in the past, maybe touching on law. So my my particular effective is really through the prism of sort of, elite law practice in New York and in, you know, firms, like internationally, things like that. But that's just one segment of the law, you know, that I happen to be, specializing in, but I think if you look at it from all the sides, I mean, these technologies are gonna improve the whole landscape. So for me, yeah, it's definitely sort of getting I mean, lawyers have historically not been tech savvy, like these firms and some things. And I'm not gonna say all lawyers because there's an incredible ecosystem of lawyers, At least right now too that are just gunning for these technologies, pushing, you know, full panel to the metal.
Enam Hoque [00:08:59]:
But, historically, if you look around, the IT departments were kind of lagged behind. There wasn't a huge investment in this stuff. Machine learning tools have been around for a while on Wall Street, and they to firms and rating agencies and things like that, but it didn't really hold. You know? It didn't it didn't come through. And I think what's great about this time, and I think you could appreciate this too, is that that I think, honestly, ChatGPT has just captured the imagination of people to be able to interact with it, to use it. You're not talking about Having to go train a document or a system or something like that, but just to kinda see what it is is just incredible. And I think that's really the spark that was needed to accelerate the adoption of these technologies, which is my whole goal with La Beta is to try to really accelerate the adoption of these technologies. So I'm eager to work with partners clients that really wanna take advantage of these systems and not just get to the middle ground, not just get to where everybody's gonna be.
Enam Hoque [00:09:52]:
Everyone's gonna have a large language model of some kind in their in their their systems and their law practice, whatever. But it's almost like my brain space is always about, okay. And then where do we go? Right? Then what can we do? How can I differentiate ourselves? How can we differentiate ourselves? How can we gain a competitive advantage here? How can we start using all these data lakes?
Jordan Wilson [00:10:12]:
Yeah. And and I'm oh, I I I can't wait for the rest of today's conversation. I have so many questions. And, hey, as a reminder, everyone joining us live, Jay saying thanks for joining us. Enam, thanks for joining us. Tara saying good morning from Nashville. Val, good morning. Rodriguez, good morning.
The future of law and LLMs
Jordan Wilson [00:10:27]:
But, yeah, what questions do you have, about kind of the, the future of law and and what this means, kind of the business of law with AI. I'm gonna start here. I'm gonna start here. Let's go to the let's go to the end. How do you think this is ultimately going to play out? Because I think, you know, I'm like, For for good reasons. Right? Like, you know, probably big companies, that are have big, you know, law firms on retainer and are probably hesitant to to use large language models, but I know that there are even, you know, specific large language models now that are being developed specifically, for the legal side. So how do you think this is all going to shake out? You know? Not asking you to predict the future, but how do you think this is going to shake out with, large language models becoming so popular, so powerful, and so niche that can really perform well in a certain vertical.
Enam Hoque [00:11:21]:
Yeah. I mean, I think this is still just the beginning here, to be honest. And and all the capabilities that people are dreaming of and and building the whole ecosystem of legal start ups right now is incredible, and it's really just the beginning. But I I would think that I think we're Sort of overestimating what's gonna be done in a year or two and underestimating what's gonna be done in a decade here. And so I think that these technologies You're just gonna find like, we we we can we can mark the calendar and talk in 10 years, but this is gonna be everywhere. The these These technologies are so good at sort of getting rid of and this is a theme that I think you've had with many of your guests on the podcast, but that that gunky work, that that stuff just feels like where you don't have a lot of autonomy, where you don't feel like a good, you know, employee or you're not having a good career because you're just kinda stuck in this. And especially with law in this in the world of what I call the world of small print. You know what I mean? Like, if you ever go to a sports venue or something, you look on the other side of the ticket, there's, like, Font and 3.
Enam Hoque [00:12:21]:
That's the lawyer's world right there. You know? Like, these little, you know, things or, you know, you get a beach ball the other day, and It said, like, do not use as a flotation device. You know? Like, okay. So there's a store there's a story there, obviously, but there's also, like that's that's the world that they live in. It's very, You know, unfortunately, I think with lawyers, they're they're very risk averse, and they're also always talking about risk. They're always thinking about what could go wrong. That's why documents have ballooned in size. I've done studies just to see, like, where a credit agreement started 20 years ago to today.
Enam Hoque [00:12:50]:
It's just adding words, more and more words, because it's thinking of all the hypotheticals that could go wrong. And you're gonna be really glad if something goes wrong, that you had a lawyer there and you had all this stuff really prepared. But for the most part, some of this is just not gonna ever come up. It's all theoretical. The best lawyers that I encounter and the ones that will, I think, use artificial intelligence tools and get creative and become sort of market intelligence platforms themselves, They're the ones that don't give, you know, a client, okay. Here's a 100 theoretical risk of everything that go wrong with the deal. They boil it down with their judgment, Their own strategy, their own sort of experience to 10 items, 20 items, the ones that actually matter. And so I think that that's really where I think the practice is gonna shift, At least from, like, sort of the corporate, you know, negotiation strategy transactional angles.
How AI can help lawyers
Jordan Wilson [00:13:39]:
Sure. And and and some you you know, speaking of Some of that mundane work, and, yes, we talk about that a lot on the Everyday AI Show. But one thing, at at least, you know, I'm an I'm an outsider. Right? I have no clue. But, you know, when I think of lawyers, I think that there's obviously many different types, many different roles, you know, in in in law firms, but I think that they're spending a lot of time reading, you know, related case law. I think they're spending a lot of time analyzing it. I think they're spending a lot of time writing based on their analysis of the reading. So when I put those things together, I I I say and I think, can't most large language models, and we've seen the testing, can't they consistently do that At the level of the best lawyers out there.
Jordan Wilson [00:14:28]:
I I mean, is that the case? Is that not the case? Help help us all understand that.
Enam Hoque [00:14:32]:
I mean, I think I think it is the case and and that the a lot of that sort of analysis about you know? Like, the the work I'm doing right now was about, like, how can we sort of ingest these things and have the the the computer or the the system sort of spit out that top 10 issues list, the top 20, To understand somehow the risks in involved in there. And, yeah, a lot of the work is that, but I will say that freeing up From that sort of wrote you know, you don't wanna look through, 300 pages of a of a of an agreement just to really care about the 10 pages, and the lawyers spend a lot of time getting there to that point. You just wanna kinda get to that point. A lot of legal documents for the most part are are sort of boilerplate. You just they're not negotiated. You don't have to deal with it, a lot of it. I would say, like, 80% of it. The fireworks are all in that, you know, the 80 20 principle.
Enam Hoque [00:15:22]:
Same thing applies in law. Right? It's the 20% of the words that actually have the most impact, and that's where imagine now you're free to just focus on that. It's being served to you really elegantly by a by a system, And then you can just spend all your brain space there thinking about that, not worrying about sort of how to summarize something or extracting information or trying to find outliers or precedents or, you know, you're doing a lot of control f to find things. All that's gonna be gone away. Now you'll have time to really think about I mean, I actually think this is gonna improve the practice a lot quite a bit because you're just gonna have. Right now, everyone's kinda doing their own thing. Like, I know there's a big movements now, and I love to see this, like, one NDA. Like, everyone's trying to move to, like let's get to, like, forms that we can all agree on and Get rid of all these, like, millions of, you know, sort of firms that are forms that are out there.
Enam Hoque [00:16:12]:
That's a step in the right direction for sure, but, What's what's what's the company you're representing, your client? What industry are they in? What are the hot buttons there? All the research that goes into it. What what kind of, problems have they encountered, not just like legal is not a vacuum. You know what I mean? Richard Troman's from artificial intelligence is a good friend of mine and holds a lot of conferences. You just did this great think piece about how just legal tech is not a vacuum. And at first, you know, I read it, and I'm like, well, that doesn't seem that insightful. But if you really read his piece on LinkedIn, it's It's a it it's profound because it just means, like, this legal is never just on its own. Right? It's always tied to a client, to an industry, To, you know, a government regulation, whatever it is. It's so large that it'll it'll have sort of tentacles everywhere, so you can't really just Think about it in a vacuum, and lawyers will no longer be in a vacuum when all these tools are available.
Issues with ChatGPT hallucinations
Jordan Wilson [00:17:10]:
Yeah. And and it seems like, To me that there's the the very infamous case, you know, a couple of months ago of the the New York attorneys who, submitted, essentially information to the courts that contained hallucinations from ChatGPT. So they they use ChatGPT to help, you know, write a a a summary or a brief, submitted it, and it turns out that they weren't using ChatGPT correctly. It hallucinated. It lied. Do you see that as a potential ongoing problem? And, also, did that incident in its high visibility in the earlier parts of kind of the, Gen AI boom. Did that set the legal space back and, you know, people were too afraid?
Enam Hoque [00:17:54]:
Man, I I heard a rumor that somebody thought that that was a plant by the New York Times just to slow this thing. But, you know, I will say this. First of all, I don't think I think that's all gonna be solved. Right? They've already if you look at ChatGPT today, it's got sources. It's doing real time data analytics on, like, and Actual found you know, truthful foundation matters, ground truths, things like things like that. That will all be sorted out. I will say too because I have to give an ode to the engineers that I work with a lot because I really try to study these technologies, not to program and engineer them, but to understand the theoretical Limitations of them. I need to know what they can and can't do for my clients.
Enam Hoque [00:18:31]:
And, one thing the engineers always tell me is, like, everyone calls it hallucinations, but they call it creativity. Right. You do want that system to be able to be creative, to give you ideas. You know, people think like, oh, well, if it's trained on all this data, it's just gonna know what it's already exists, But it's really not the case. And, again, this is just delving a little bit into I don't think this is a hot take, but it's delving a little bit into, like, well, these things are like Prediction machines. They can do probabilities. They're very good at that, and they can take, you know, all that to language. But, you know, just remember that we communicate in language.
Enam Hoque [00:19:04]:
It's the most effective way, and way, in person communication with language, probably the most effective way to communicate, but also, like, our thoughts themselves are just language, right, in your head. Most people have a little voice that talks to them. They think it's them. So there's a lot of things about what patterns and predictions it saw there to recognize that, to be able to interact. You know? And you can see, like, OpenAI's announcements even from Monday. I think they're thinking the future of computing is not gonna have one of these anymore. Right? Mhmm. I think it's they're really leaning towards you're just gonna you know, it's gonna be like Star Trek.
Enam Hoque [00:19:34]:
You know? That you'll just talk to your computer and all that stuff. So I'm definitely aware, I think, things are gonna head with that hallucination issue and all that. It probably was good for the space to took up take on a little bit of a break, because I felt like law firms particularly were starting to panic. You jump into bed with the wrong vendor. You know what I mean? The wrong you you bet on the wrong horse, the wrong You get dazzled by an AI, you know, demo. I always tell my clients, like, never just be like, oh, show me your AI. I wanna see it, and they Dazzle you with and demos can be anything. Right? Like, I've done demos before.
Enam Hoque [00:20:08]:
Like, you can make them up, and the text isn't even real behind it. You know? But Sometimes, you know, when you put on that show, that's not the way to go. The best way to approach it, and I give this advice totally for free. You don't have to consult with me or anything is Yes.
Jordan Wilson [00:20:22]:
Wait. David Money here on the show. Alright. Here we go.
Enam Hoque [00:20:25]:
Here we go. Here we go. Here's a $550 advice. Right? Always come with a problem, a real problem, because the first question is whether or not AI is even the solution here. I mean, yeah, it's the it's the sexy thing right now, but, like, If it's a one off project and you just need it done, most times, a manual human, that's gonna be the way to go until some technology maybe improves it, but it's no sense of you spending that money and r and d or CapEx or whatever it is to get that solution if it's not really needed. So, You know, it obviously works for repetitive things, and it's gonna get to be it's gonna start impacting work that's even not just repetitive anymore. I think you'll be able to I heard somebody talk about how, Oh, we'll probably never be able to do, like, a supreme court brief the way that, like, appellate lawyers do supreme court briefs. I don't think that that's the case.
Enam Hoque [00:21:14]:
You know, because I could feed a machine Every elegant supreme court brief going back to the 1800, get get principles extracted from them, incorporate that back in, and then add because these systems, right, you can just Add this spirit knowledge and have it folded in. So you take, you take a book like Robert Kianni's persuasion, all the principles from that guck in. You take, whatever, death by PowerPoint principles. Throw that in, and then all of a sudden, it's gonna generate for you an argument that's got psychological components. It's got the legal components. It's got the flash. It's got everything. And so that's where I think, like, why would we say that these briefs are not gonna be able to be that good? It's just very shortsighted.
Ways AI will change the law landscape
Jordan Wilson [00:21:53]:
Yeah. And I'm gonna I'm gonna throw in a personal story, and then I want your take on this. So, you know, I started a, a venture company about 9 months ago. And so So when I was looking for attorneys, one of the first things I asked them is, how do you use artificial intelligence in your practice? Do you use it? Obviously, I hired the person that I thought was using it correctly because I believe that's the future. And even when you think, okay. Well, I want to pay an affordable rate. I don't care if I'm paying someone more an hour if they're using their hours correctly. How do you see even the accessibility, for the everyday you know, the average person or the average small business, the average entrepreneur? Is it gonna become more affordable to hire attorneys? Are we going to see, kind of, you know, AI first or AI led companies that, our our very high quality and use this technology, and and they're going to start to create an own category, or do you think it's still gonna stay how it is for a while? What are your thoughts? I I
Enam Hoque [00:22:55]:
mean, I think in the short term, it's gonna stay a little bit how it is for a while, but I think in the long term, I think, personally, what excites me the most about this space, And it's not necessarily the work I'm doing right now for my clients, but I would really I'm really trying to barrel into that space here. And I've had great exposure to some of the leaders of that movement, you know, at Stanford or at Berkeley out here in in Silicon Valley in California, it's just as equal access to justice. Right? That's gonna be the thing here. So it's not really the business of law, but There's a huge unmet legal need in the United States just because people can't make it work. The numbers work. Right? People don't have a lot to everybody really does need a lawyer Or has legal issues, right, a a lot. You know? You it could be evictions. It could be, just credit card debt, identity theft, whatever it is.
Enam Hoque [00:23:43]:
Right. You usually need a lawyer to kinda navigate and go through that. But a lot of times, there's there's all this unmet need because people even people that are just, Like, maybe not working at firms that are charging, you know, $700 an hour, but something much more reasonable, and they still can't really cater to that clientele. This is the most promise this technology has to actually close that gap, but there's a bunch of hurdles in the way. One of them is sort of There's this general principle of the unauthorized practice of law in the United States, meaning that, really, lawyers are the only ones that should be practicing law. You know? And it's a regulatory scheme, and it's, you know, some people think, well, maybe is that just a competitive sort of moat that they've created around lawyering, just like, You know, other kind of licenses and things like that, or is it more? But I think that's gonna just have to be, like, really, really modified and changed because
Jordan Wilson [00:24:31]:
Is Is there is there a way to even I'm just wondering now. Is there a way to even police that? Right? Like, let's say 1 1 lawyer starts a firm, And they're tapping into artificial intelligence and maybe a large language model may be specifically set up for legal. Maybe it's doing the majority of the work, and it's just the lawyer Signing off on that. Is that allowed? I mean, can you even govern something like that? You know, if if now lawyers are spending let's just say, If they're tapping in and and leaning into AI so hard and becoming overreliant, at what point are they still The lawyer versus maybe if they're really leaning heavily into generative AI and large language models.
Enam Hoque [00:25:12]:
That that's a great question. That's a great question because I think that that that's the $1,000,000 Question here because, again, these technologies are so good that at a minimum, I think the language models are always gonna get you average or better Because it's gonna take all of all of that data. It's gonna plot it somewhere in the middle. And then, obviously, with prompting and other, you know, knowledge bases and things like that, it can start to improve toward more of But it's always gonna start off as an average lawyer, so everyone's gonna be able to get that at their fingertips. The issue is gonna be ethical issues. Right? So lawyers have, Like, have you have you actually done the diligence here? If you're just rubber stamping something that you think the machine could do And that's it. That that may be a competence issue for you, ethically speaking, especially if something goes wrong. You know? Because these systems, let's let's be totally clear about it.
Enam Hoque [00:25:58]:
As much as I believe that they're gonna just do everything that you could possibly imagine and more in terms of, like, sort of the future of law, Right now, the accuracy is not there. Right? Let's call it 80% to start, right, which sounds good on its face, but imagine if only 80% of planes landed every day. There'd be millions of, like you know what I mean? There'd be problems. So it's not a good number. You need that number to be 99 or 6 sigma, 99.999, whatever. But it needs to get improved, and it will over time. But right now, you know, if you were just to, like let's say, I have a I I'm authorized to practice law in New York, New Jersey. If I just sorta hung out a shingle on the Internet and said, hey.
Enam Hoque [00:26:36]:
Bring it all in, and I'll just I'll write your complaints, and I'll do that. Like, if something goes wrong, I'm gonna find myself in front of the bar committee, you know, having to sort of say, like, what what about what about doing? Is that zealous representation of my client? Am I actually doing the diligence? And that's what's you know, every bar association in the United States is having this discussion about how to fold in generative AI. Sort of overheard a conversation 2 weeks ago where I listened in on a meeting of, the state of California's sort of, to the committee that's sort of addressing these issues. So it's not obviously the recommendation or it's not floated up yet. But when they're talking about it, they were talking about, like, the billing. Like, okay. Let's say, like, an average lawyer, it wouldn't take an 8 hours. Now I can do it in 8 minutes.
Enam Hoque [00:27:18]:
Right? Where do I bill that at? Some people are saying, well, if you bill it at 8 hours, that's fraud. And I'm like, is it really fraud if that's the market Price for it, is that gonna impact hourly billing? You know? Is this finally gonna be the the so called death of the billable hour that people have been talking about for 20 years? I don't know, but there's definitely something there we'll we'll have to think about because these tools are gonna be incorporated so well. And that's why you know that these tools are gonna be huge if all the bar associates are already doing exploration Exploratory committees and adding rules and all that. So there's gonna be an ethical line landmine there.
Jordan Wilson [00:27:51]:
Enam Hoque [00:27:51]:
I didn't touch on, like, bias of these systems either. Right?
Jordan Wilson [00:27:55]:
For sure. And and, you know, this is honestly, this has been a conversation, and and I'm I'm glad we can have you on the show because this has been one I've been wanting to have for months because I do remember when, OpenAI released GPT 4, which was back in in March. So it's it's been a long time. And even at that time, their initial scores I don't I don't know what any of these scores mean, but, apparently, they, took the bar exam, scored about a 298 out of 400, which placed it in the 90th percentile, which I think is pretty good, but it goes to your point. If only 90% not very good. But then I guess on the other side, that's a very old model. You know? OpenAI just is just released or is releasing this week, GPT 4 turbo, which is supposed to be much more powerful, a much more capable model. Like, at what point do we as a society say, okay.
AI vs professional law
Jordan Wilson [00:28:51]:
Well, if generative AI, if large language models, if if And and this is always like, the different exams. They always have them take the exams to see, oh, how good is it? How smart is it? But at what point do we as a society say, hey. If if these large language models can score in the 99th or 99.5, like, percentile, like, at what point do we have to shift and say, okay. What are our odds of hiring the the lawyer that's in that 0.1 percentile. Like, is that is that a crazy thought to think that it might be Safer to rely on this kind of technology, or will lawyers just become better in In the future when they're spending less time on this knowledge work and being able to think more creatively, more strategically.
Enam Hoque [00:29:37]:
Yeah. I don't think the professional law is going anywhere. No matter what, like, McKinsey says about their you know, I think, enterprising lawyers will always find a way, and there's always gonna be a need for you're not you're never gonna do better firm litigation and and use a a a lab. I'll say this too about benchmarks just really quickly because I'm involved in one called, legal bench. It's a Stanford paper. It's going to a machine learning conference this fall, and it's all about, like, real lawyers, real professionals like me that have been in this space have given to computer science majors, PhDs, and sort of the tech side all this data so that they could actually assess these models. One thing to make clear is that, like, sometimes, even though it looks like a model and I'm sure gbt 4, they took all the precaution necessary. But as it swallows all that data, you never know if it an old exam, right, and and just understood just knew the answer because deep down, somewhere in that neural network, it pulled it out.
Enam Hoque [00:30:28]:
Right? So there's always like, benchmarking is really, really tricky, You know, because you always have to have something that's totally segregated from the Internet or not available yet to do a real time what what they do is hand score these things. Like, Open the eye for all its technological prowess and things like that when they really get down to it. They're hand score. They're grading these things by hand because that's, like, the old school way to make sure that this isn't it's a new exam and all So I'll I'll say that first. But second, that other question, I think about, like you know? I don't know. I I wouldn't give much credence to, like, LSAT performance or bar exam performance translate into law at all. And I think any real lawyer would never would never say, yep. Yep.
Enam Hoque [00:31:04]:
Every lawyer that got in the 99 percentile is an amazing supreme court litigator and a big law firm partner and all that. That's just not the case. Those things are so Abstract and really not related to law at all. You know, maybe there's some sort of logical thinking that they're analyzing, but I wouldn't give it any credence. So, again, it's gonna lean into the future of I think lawyers are just gonna be better with these tools. They're gonna be able to express their, talent in different ways to people and really start and Exercising strategic judgment. I and I think going back to sort of what a lawyer used to be. You know what I mean? Which is just it's not a paper pusher.
Enam Hoque [00:31:36]:
Just remember, we live in a world where legal is really just looked on as a friction. Like, in the work that I did, they never really respected lawyers in the sense of, like, It was just a thing in the middle of the other thing. You know? They wanted to do an m and a deal, and so their financing lawyers had to come to get the money to buy the company. That's not their primary objective. They just want a check, you know, at the end of the day. All that paperwork, all that paperwork just so they can send a wire because, really, what they want is to buy a business. So, again, everyone's looking at it like friction, and that's why I think that if it's not happening yet, just wait. But corporate clients of major law firms are gonna start, Especially if they're using AI in their own legal departments, you know, companies like Ironclad that are doing great things with contract management and all that life cycles.
Enam Hoque [00:32:18]:
Once clients start demanding, hey. We're using this. We're having success. You better start showing us this on your end. You know what I mean? I don't wanna see Bills inflated with associate hours and all that. So it's gonna be the practice of law in that sense of, like, being trained initially by your on your client's dime, that'll have to change. It's just gonna have to be other other methods that that I go into my clients because we're building tools to even address that.
Enam's final takeaway
Jordan Wilson [00:32:41]:
This has been a good one. You know, thank you so much. As as we wrap up here because we've taken this all over the place, and I love that you've been able to give us fact based insights. The fact that you know? And and we're gonna share, about the work that you're working on, with legal bench, in the newsletter today. But, you know, just just as we wrap everything up and as we look forward, What's the what's the one takeaway that everyday people, can can, you know, use this conversation whether they're hiring an attorney for their selves, maybe, You know, someone that's going into the legal field. You know? Maybe they just passed the bar. You you know? What's I I mean, what should people be be be looking at and paying attention to To help make sense of generative AI in the future of of the business of law.
Enam Hoque [00:33:24]:
I think for for future lawyers, you know, the people that just Taking the bar exam or or whatever, know that these tools are coming. And so if you're not already conversing in them, get conversing in them because it's it is gonna dominate the industry in 10 years. That being said, you don't have to necessarily don't I think and this could go broader than just lawyers, but No one should feel like they missed the boat here, that, you know, that they that these tools are just off and done, and it's all you know? Like, These large language models could only be created now. Like, we're living in the now, and this is when they were they're available because of all the data and all the compute that was available. It just took on this amount of time. So everyone's here together, and we're at the ground floor. And I think know knowing how these technologies work is helpful. I don't think you need to say you have Program or engineering them, but getting some framework that you just kind of roughly understand how they work is a good thing and obviously using these tools.
Enam Hoque [00:34:20]:
I I feel like the lawyers are gonna be able to write emails quickly or, you know, what I do these days, it's incredible. Like, I just take notes just kind of Randomly, really, but it's so good at organizing them, packing them nice, making them more, you know, presentation worthy. So it's it's things like that that start using these tools right away. You know, whether it's I would I'll obviously recommend ChatGPT, the premium version too. Do not get stuck in some other model. But, you know, look around. There's Perplexity. There's other tools too.
Enam Hoque [00:34:47]:
There's MidJourney for art. There's so many incredible things that you should be leaning on. It's not just like don't think about, is this a work thing? This work thing can become a lot of different things. You know what I mean?
Jordan Wilson [00:34:58]:
So good. So many good insights. You know, thank you so much and For joining the Everyday AI Show, we really appreciate it. Thanks thanks for your time.
Enam Hoque [00:35:09]:
Thank you very much.
Jordan Wilson [00:35:10]:
Alright. And as a reminder, There was a lot here. We impact so much. I'm I'm super excited. Yeah. Like, people don't realize. I'm still, like, I'm a human. After I get off this conversation, I'm gonna get up, relisten to it, type in all the insights.
Jordan Wilson [00:35:24]:
So we talked about legal bench. A lot of other, great Insights dropped in today's episode, so make sure you go to your everyday AI.com. Sign up for the free daily newsletter. If you're listening on the podcast, check-in the show notes, and And we hope to see you back tomorrow and every day for more everyday AI. Thanks y'all.