While lawyers probably hear every day how Artificial Intelligence is going to change the legal industry, many are still uncomfortable discussing it simply because they don’t understand what exactly AI is, and if it is going to be a good thing or a bad thing for them personally. Kira Systems’ Noah Waisberg and Dr. Alexander Hudek are releasing a book on February 3rd that addresses these issues. AI For Lawyers: How Artificial Intelligence is Adding Value, Amplifying Expertise, and Transforming Careers walks through the questions and gives some easy to understand explanations on how AI is being used in the legal industry. Whether it is document automation, e-discovery, legal research, or a myriad of other legal issues, AI is becoming normalized across practically every task a lawyer or legal professional does. As with most advanced technologies, AI may sound scary, but eventually, it becomes ubiquitous.

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Information Inspirations

The Strategic Knowledge and Innovation Legal Leaders Summit (SKILLS) went online this year using Shindig, and it was a great experience. The audience and presenters found ways to interact, and while LegalWeek may not have happened this year, it was nice to still be able to seek out our conference friends online. Speaking of friends, our fellow 3 Geeks contributor Ryan McClead from Sente Advisors, along with Nicole Bradick of Theory and Principle won the video presentation at SKILLS for their new Map Engine software.

Early podcast guest, Jae Um has a five-part series on what to expect in a post-pandemic era for the legal market. It is a must-read.

We thought that last year’s bar exam was a bit of a mess. Turns out it was more like a mean game of musical chairs. There were definitely winners and losers.

The University of Texas Center for Women in the Law is putting on a free CLE featuring Nina Totenberg and four former clerks of Ruth Bader Ginsburg to celebrate the beginning of their Ginsburg Initiative.

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Please take the time to rate and review us on Apple Podcast. Contact us anytime by tweeting us at @gebauerm or @glambert. Or, you can call The Geek in Review hotline at 713-487-7270 and leave us a message. You can email us at geekinreviewpodcast@gmail.com. As always, the great music you hear on the podcast is from Jerry David DeCicca.


Marlene Gebauer: Welcome to the Geek in Review the podcast focus on innovative and creative ideas in the legal industry. I’m Marlene Gebauer.

Greg Lambert: And I’m Greg Lambert. This week, we sat down and talked with Noah Waisberg and Dr. Alexander Hudek of KIRA Systems about their upcoming book, AI For Lawyers: How Artificial Intelligence is Adding Value, Amplifying Expertise, and Transforming Careers. So the book gets released on February 3, and Noah and Alex give us some insights on what they’re covering in the book and why they wrote the book in the way that they did.

Marlene Gebauer: So stick around for that. But now let’s get to this week’s information inspirations.

Marlene Gebauer: So I want to give a quick shout out to SKILLS which stands for strategic knowledge and innovative legal Leaders Summit. Hey, Greg, that’s us.

Greg Lambert: Yeah, that’s us.

Marlene Gebauer: So normally, we have this meeting right after legal week in New York. But well, pandemic. So we took it online, we used a platform called Shindig, which worked really well speakers were on the podium presenting, and the audience could have video or normal chat sessions during networking time. And I gotta tell you, I mean, it was kind of fun to chase people’s pictures on the screen and jump into the conversations. So the content was excellent, as usual. And we had a number of new faces and speakers this year, talking about all things KM. And what was really nice is that the second day was broadcast to the public on YouTube. And I hope that continues.

Greg Lambert: Yeah, I actually was able to sit in and watch a few sessions.

Marlene Gebauer: And our good friends, Ryan McClead have sent advisors and Nicole Bradick of Theory and Principle, one for their new product Map Engine, which automatically creates maps from all your 50 state surveys. Greg, you and I had a sneak peek before the conference. And it seems very easy to use and super useful.

Greg Lambert: Yeah, yeah, it was. In fact, I was listening to a podcast that was talking about child seat safety across all 50 states. And the first thing I thought of is, ooh, I could use the map engine for this.

Marlene Gebauer: I have to say, Nicole and Ryan sounded a lot like you and me on the pod. You know, they even had outtakes so you know, I think I think we need to cut to the prize.

Greg Lambert: I’ll talk with both of them see what we can see.

Marlene Gebauer: All right, let’s make that happen.

Greg Lambert: So Marlene, our friend and early podcast guest Jae UM, just put out a five part blog post series on the Legal Evolution blog where she discusses the #GreatExpectations for the #GreatReset for the post pandemic legal market. And you know, Jae’s style. So the writing is full of emojis and graphics. And you know, it’s a bit lengthy.

Marlene Gebauer: I have them saved, I have I have the part saved. So to read, and I’m gonna like do it on a Sunday.

Greg Lambert: Yeah, so the final post came out at the end of last week. So for those of you waiting to sit down and read the whole series in one sitting, now’s your chance. Jae’s run of the timeline from revisiting the great recession and how the legal industry woke up to the tensions between the buyers and sellers of legal services. She covers that in part one, and in part two through four, she shifts over to who will be the winners and losers in a post pandemic legal economy. And then finally, the last of the series covers trends to watch out for for the next five years. And of course, legal technology and innovations are factors but you know, it can be a bit tricky and so she wraps up the series with a variation of Forrest Gump’s Mama’s saying of Stupid Is As Stupid Does by saying, like Jay said that innovation is his innovation does. And she states and I wanted to quote this and “in some ways, technology is both the driving force and the great red herring of our time. Organizational transformation of any flavor is a human endeavor. No matter the external pressures or intrinsic rewards, meaningful change doesn’t just happen. Persistent people and committed teams make them happen.” So it’s it’s a really good series, I suggest people go out and read them. One of the things that really made me happy was as I was reading through the series, a lot of people that she mentions and companies that she mentions have been on this show. So so it kind of validates what What we’re trying to do here with innovation and creativity in the legal space.

Marlene Gebauer: That’s great. Yeah. We’ve discussed the bar exam during pandemic many times on the show and how it seemed the approach was very haphazard, to put it mildly,

Greg Lambert: Yeah just mildly.

Marlene Gebauer: Well, now we have some stats to back us up the Collaboratory. Did you even know that was a word I did not know there was a word on legal education and licensing for the practice reports that the July 2020 Bar Exam resembled a harsh game of musical chairs. Jurisdictions postpone the test, limited seats, switched formats, and announced last minute changes, candidates struggled just to stay in the game. The Collaboratory also reports that the number of qualified applicants went down from 46,000 approximately last year to approximately 38,000 this year. The Collaboratory finds that for candidates with resources to wait, the delayed paid off, pass rates rose in many jurisdictions in New York, the overall pass rate rocketed to 84% on the October exam, which was administered online, compared to just 65% on the July 2019 exam. But for candidates who lacked those resources, the pass rate was zero. That’s the dark side of this year’s summer/fall bar exam. More than 8000 qualified candidates never took the exam. And women, people of color, and people with disabilities are the most likely to be deterred by the burdens of the exam. Just another reminder that reform is needed for licensing.

Greg Lambert: Marlene, my second inspiration, you know, I usually don’t recommend CLE presentations, but I’m going to make an exception for one that’s coming up on February 2, that’s being put on by the University of Texas law school in order to launch the Ginsburg initiative at UT’s Center for Women in the Law. The panelists are just amazing. But the moderator is someone that everyone should know. And that’s Nina Totenberg from who is NPRs legal affairs correspondent.

Marlene Gebauer: Boom.

Greg Lambert: Yeah, but the the panelists the the speakers include four former Ruth Bader Ginsburg clerks. And you know, what can be better than this type of content, the moderator and the speakers. And, and if that’s not enough, it’s free. And on top of that, if you’re in Texas or reciprocal state, you also get one and a quarter hours of CLE credit so it’s a win win win win situation.

Greg Lambert: Well, that wraps up this week’s information inspirations.


Marlene Gebauer: While some of you may know Noah Waisberg through his work with Kira systems, some of us also know him through his children’s book,

Greg Lambert: Robby the robot learns to read I have a signed copy myself.

Marlene Gebauer: Yes, we both do. He and his colleague, Dr. Alexander Hudek, have decided to write a new book on AI. But this time, it’s focused on a more mature audience in the legal field.

Greg Lambert: We’d like to welcome Noah Waisberg back to the show along with Dr. Alexander Hudek, to discuss their upcoming book AI for Lawyers: How Artificial Intelligence is Adding  Value, Amplifying Expertise, and Transforming Careers, which gets released on February 3, Noah and Alex, welcome to the Geek in Review.

Noah Waisberg:  Awesome to be back. Thank you for having us.

Alex Hudek:  Thank you,

Marlene Gebauer: I suppose the books like these are inevitable when you put a lawyer and a PhD in computer science together, and they start talking about what is possible in the legal field, if you add the potential of artificial intelligence. So Alex, give us a bit of the backstory of how you decided to write this book. And why does this book need to exist?

Alex Hudek:  Noah and I have been selling legal technology and AI, in particular to law firms. Now for for many years. One of the biggest hindrances to adoption is really just understanding what AI is how it can affect people, how do you use it, and how it can change business, you know, there’s often a lot of fear around it, because of misunderstanding. And so we felt that writing this book would be the best way for us to conquer some of those fears for people and really just give them the insights, they need to really understand it, apply it and cut through the various hype and misinformation that’s being thrown around around AI.

Noah Waisberg:  So I don’t know that it’s inevitable that we wrote a book at all, we’ve got one book under our belts, Robbie the Robot Learns to Read our very nice children’s book on machine learning. I think what we end the main project for us with a lawyer and it comes my PhD has just been building care systems, which we’ve done over the last decade, and a majority of the world’s largest law firms user tech to do contract review work. The book came to us, as Alex says, for a sort of specific problem that we’re trying to solve, which is that there’s a lot of information out there on the “what” of legal AI, right, like there is this company doing this, and this company doing that, and there are good bloggers and journalists covering the legal AI space now. But there’s a deeper problem, which is getting lawyers like whether that’s lawyers at large firms, lawyers in small firms, in house lawyers, getting them to actually care that this is going on and having them understand like why this is important to them. So this book is there’s lots of sites and information on the details of legal AI, if you feel like it, what we really tried to do is make a case for “why” lawyers should know that it exists, and why they should care and why they should embrace or ignore it.

Greg Lambert: So before we talk about what’s actually in the book, I want to back up and take a 30,000 foot look at just what we’re talking about when we say artificial intelligence when it comes to the scope of what the legal industry needs. So Alex, what makes something authentically an AI product or process?

Alex Hudek:  Wow. So that is a that is a loaded question. So people have been arguing about what is it authentic AI is we’re, you know, decades, right? And back and way back when in the early days of computing, it was people were like, Oh, hey, look, a computer can play chess, that is a clearly an intelligent task. This is AI. Whereas now today, people snap that off and be like, wow, it’s just like, you know, computing stuff in advance, but really smart, right? And so there’s this trend moving goalposts, that you know, things become when a technology becomes normal suddenly becomes not AI just becomes planning

Greg Lambert: or a longer magical. It’s just a process.

Alex Hudek:  Yeah. And, you know, today, today is like even more challenging around AI, because, you know, it’s, again, a hyped up thing. People call all sorts of things AI, there are some products even out there that have a mix of computers and actual people behind the scenes doing things and they build themselves with AI too. So it can be really, really difficult to navigate what things are really AI and what things are not. In the general, so in the book, we don’t try and answer that question definitively. Rather, what we do is we define what it means to us. And what it means to us is really technology that does, you know, human like reasoning or intelligent tasks. And that could be something like machine learning or deep learning, which is what you see dominating the world. Or it could be something like rule based systems, expert systems, for example, were very, very popular in the past and they’re still used today, although they’re not as hyped as much. So all of those things to us can be AI I’m trying not to draw a hard line. Definitely though. If you Humans doing and that’s not a.

Marlene Gebauer: So no. In the book, you say AI is an actual modern job creator. How does that work? And will there be winners and losers, as AI becomes more integrated into our processes?

Noah Waisberg:  We say AI is a modern job creator, because one of the fundamental things going on that we see in law right now is that there’s way more work to be done than is being done. There’s this massive sort of latent demand for legal services. That’s not getting answered. And you see that certainly on the access to justice side, right, where there’s tons of people who can’t get representation who need it. But you see the middle class people too, like, I wonder if the Geek in Review podcast has great sort of lawyer negotiated contracts, or if he just kind of winged it was stuff like that? And then go on a step above that, even like the biggest companies in the world, like a JP Morgan or a GM or a Tesla still have tons of things, they don’t know that their legal situation, and don’t bother to track because it’s just too expensive, too time consuming, too difficult to solve. And there’s this massive opportunity in solving these problems for these people who have legal needs that aren’t being met, and what AI can do. One way that it can be a monitor job creator, is it can just allow us to solve problems that we would never solve without AI. Now, you ask, Is this sort of like, flatly applied across the profession? Right? Is everyone gonna benefit from this? And the answer is no. Like, there are gonna be people who take advantage of this technology enhancement, and are taking advantage right now of this technology enhancement, and it’s allowing them to serve their clients better, to do sort of higher quality work, faster work, but not even that, like also do things that they’re non AI supported, competitors can’t. And those people, I think it seems pretty reasonable to think that they’re probably going to win. People who are just doing things the same old way, it’s hard to see how that plays out super well from them. And I think one kind of misconception is that you can just sort of buy a piece of software and then like, you’ll catch up immediately. But I don’t think that’s necessarily the case, like Marlene is, you know very well, it takes a lot of effort to just learn and to get people trained, and to get people thinking about doing work differently. Like that’s a multi-year process. And if you’re doing it you better get started right away. Like, to me an analogy that I always think about is I used to practice law at Weil Gotshal. And Weil had one of the premier private equity practices and the premier bankruptcy practice, and basically the reason it had that like while had smart lawyers, but like, so we did lots of other firms. The reason it was so good in those two practice areas is it got there earlier, right. Like it was just there first, like, even as I think even Skadden and Wachtell, like, obviously populated by super smart lawyers. But like, they were not that big of a deal, pre the m&a boom of the 80s. But like, again, they just got there first and spend more time and I think it’s reasonable to think that AI is gonna be the same kind of thing, like you spend more time thinking about how this can impact your practice training your people on it, just seeping them in and making them think about what’s possible with it. It’s gonna improve your benefit.

Greg Lambert: You mentioned one thing in the book that really caught my attention. And I have to be honest, I hadn’t heard of it before. I think it was like Jevons paradox or something like that I

Noah Waisberg:  Javons Paradox

Greg Lambert: Jevons Paradox, but, you know, basically, I’m, and I’m just remembering off the top of my head here, but basically, it it’s driving additional demand by making giving more opportunities for a certain service in it. And just by happenstance, this morning, I was I was on my Twitter account, and there was a, like a bankruptcy startup online bankruptcy startup. And they were getting into a fight with some bankruptcy attorneys saying that they were stealing their work, you know, and he was like, Look, these people can’t afford a bankruptcy attorney. So it’s either us or they don’t file for bankruptcy. And so we’re creating an opportunity here. So I think that’s kind of a, you know, a rough example of what I think you can do by expanding the base of people that that you can provide a service to.

Noah Waisberg:  I think, so. Choose our responses. Number one, like if the work can be automated, we’re supposed to work in their clients best interest and like, like the protection of bankruptcy lawyer incomes or something like that. Like I think it’s hard to say that that’s like a really legit consideration. You’re certainly not certain people, if you think it can be done as well by software and technology can do anything like great, like bad should happen. Because there’s lots of other work for bankruptcy attorneys like perhaps a bankruptcy wave hasn’t materialized as heavily as some thought it might with the pandemic, but like, I would have to imagine that there is work these days available for bankruptcy lawyers. But Jevons paradox, which point here is a super interesting concept. Right? So the idea of it came from the first Industrial Revolution. And the idea was that there were these innovations made that that made the use of coal more efficient. And what this William Stanley Jevons noted was that you think if an innovation makes makes the use of coal more efficient, that you’d use less coal, but what he saw paradoxically, was the more efficient technology got at harnessing the energy out of coal, the more coal people used, and that was sort of paradoxical. Hence the Jevons Paradox, right? So you see lots of examples of this, like one example that we point you in the book is the Ford Motor Company, right? So Ford got more and more efficient in building cars through use of the assembly line, right. And you think that that would mean that like, greater efficiency means less factory workers. And that’s not exactly how it played out in the auto sector, it became much more efficient at building cars, which meant that many more people could get cars, they sort of brought them to a level of affordability that more people could afford them. And that meant way more auto worker jobs. And I think when people have historically been like, I’ve been on ILTA panels and the like, for years, and you know, remember back in like, 2014 2015, it was like, you know, let’s fast forward to 2024, they’re gonna be more or less lawyers, with AI, and everybody was like, there’s definitely going to be less. Like AI reduces the amount of labor that goes into people and the seeds of the book, we’re really are thinking back then that like, no, that’s not necessarily the case. Like as people get more efficient at doing work, that creates opportunity to actually sell more of that work to people who wouldn’t buy it, when it was more expensive when it was more slow. So that’s how we see Jevons Paradox playing out and legal, like just this greater efficiency. It’s not a given that it means less lawyer work. And in fact, we think it’s very possible it means more lawyer work,

Greg Lambert: You have a chapter written by some of our friends in your book, friends of ours over a CaseTexts such as things Jake Heller, Laura Safdie, and Pablo Arredondo. They wrote a chapter on legal research in AI. So know what has your research for pulling this book together, talk to you about the current state of AI and legal research and where you think it might take us.

Noah Waisberg:  Just stepping back. The reason that we pulled Jake, Laura, and Pablo into the book, is Alex and I know sort of a few things super super well. Number one, we know contract analysis, software really well. Like we were some of the first people in the as part of that industry and like doing it for a long time. And our software is pretty heavily used for that gets the consensus software used by most big firms in the world. So we know that area super well. So like when it came to writing a chapter about contract analysis, like Alex and I felt pretty good. We also know kind of, in a thought a lot about making the case for AI, right, the thing that I was talking about before about why lawyers should even care that AI exists and how it might impact their practice. We know that case really well. And over the years, we’ve heard lots of reasons that lawyers are nervous about AI sort of objections that they have and fears that they have, so that those are things that we felt super well qualified to write on. But when it came to things like ediscovery, or legal research, or expert systems are in small law firms, or legal prediction, like those are things where we knew there were other people that knew them so much better. And happily from sort of having been in the community for a really long time. We knew who smart people were on the topic. And the CaseText crew definitely stands out to us is super sharp. And so it was great to get them involved in the project. I think the legal research space is super interesting right now, in terms of AI like you have Thomson Reuters and others have been putting AI into their legal research projects or products in various forms for like decades. don’t necessarily get credit for that but over the last few years, especially Casetext, but Also, I think we saw other efforts with like Ravel and Judicata of people really trying to bring something new and really pushing the world forward there. And I think it also appears that like Lexis and others have put a lot of effort into kind of keeping up and you know, even surpassing where they can, I would have a hard time saying like what the exact future is going to be. But I think the overall concept is that with legal research, you’ve got people spending vast amounts of time trying to find little needles that are super important to a given case. And what the AI is going to do is get even closer and closer to finding the right precedent at the right time. The other thing that I find super fascinating about legal research is all the stuff like Casetext is done with thinking about like whether someone should have to enter a search to find appropriate precedent, or whether it might be better to just put in your brief or your opponent’s brief and have the software think about what’s appropriate there and maybe even start drafting the response. And I think that’s super cool. And really just thinking very that example of them and others thinking really deeply about their users, and what the problems are they face in dealing with case law.

Marlene Gebauer: What do you say to lawyers or legal professionals who oversee AI implementation within the legal space? And who agree that the practice of law is messy and inefficient,  but that AI is complicated, difficult to implement. And so they’d rather deal with the devil they know. And maybe Alex, this is one for you.

Alex Hudek:  Yeah, sure. I would say it depends entirely on the vendor and the solution, some AI solutions absolutely are complicated to, you know, implement. But that’s true of a lot of software. Right? There are, there’s certain software’s out there, you know, in finance, and ERP software that is fantastically challenge, challenging to implement. But that’s not true of every software, and every vendor and AI can be easy to implement. There are plenty of vendors that have very straightforward and easy to install software packages. The harder challenge is actually around changing the way you do your work internally, in a law firm. Just you know, imagine something like SLACK, if you’ve never used instant messaging, you’re used to using the phone all the time, and you’re implementing SLACK. I mean, slacks not complicated, it’s really simple. But changing the habits and the process within a company that does take some time. That is true of AI and other technologies. When we talk to law firms, we do a lot to try and help them understand, you know how to change their practice to adopt AI, and do provide them a level of guidance around that. And we find that it’s quite important to the firm’s in helping them adopt. But it is definitely not the case that AI has to be confusing and challenging, and difficult to implement.

Marlene Gebauer: Yeah, it’s interesting, you talk about change management. And I’m glad to hear that you are offering guidance to your customers in terms of how to change the practice in order to make the adoption more smooth, because a lot of times what happens is, people are busy with their work. It’s again, it’s not that they don’t think it’s important, but I guess they don’t see it as part of their role now to the part of the role, in addition to practicing law is really, you know, keeping on top of these things, and being present, to try these things out and give opinions on them. And I know that’s sort of the bane of lots of vendors, because they just can’t get the feedback. They just can’t get people to pay attention. Because you know, people don’t think or feel that that is their, their role. So what types of guidance are you offering? Or would you recommend offering?

Noah Waisberg:  Well, first thing is just this book, right? Like what we’re trying to do with this book really.

Marlene Gebauer: Of course!

Noah Waisberg:  No, like really, the way that look, one thing that we found over the years is that if you get actual partners engaged, and like intellectually engaged with, like, if they have a desire to do this, and like they think this is the way things should be done at their firm, it goes a lot smoother, right? Like they actually care. And so what we try to do with this book is just explain it to them in a way that’s like super readable and understandable about why they should care and why this is good for them. So I think that’s like the first part, if you can engage lawyers like partners, associates, clients and make them just sort of ask about this, think about this and ask why aren’t we doing this better? I think that’s the first and most important step, like if they desire to get to the destination, there are a lot more likely to get to the destination. Second thing that we can do is we can help share stories about what we’ve seen work. Like what we’ve seen work at different firms, what we’ve seen work within a firm, like maybe we know that Michelle, in the private equity group has had a bunch of projects that have gotten really successful using AI. And we can try to spread Michelle’s story to others in that firm. Or maybe we can say to a firm like, you know, you guys aren’t doing so well, but your big competitor across town, like they’re leading the way. And thankfully, because we have a good enough client base, we actually have like pretty good insight into that. And one of the quirks that I think both you two would know about the legal spaces, these firms are like highly competitive with each other in some ways. They’re highly collaborative around technology, adoption like it, which we see with ILTA and the like, right that a lot of the times the firm’s really all would like to implement best practice. And the administrators often work really, really, really well together. And so we can take learnings from one firm and help share it to another firm and even connect people at the different firms that they can learn from other people with relevant experience. So I think, I think that’s the second part. And then there’s other things that we’re trying to do a lot more of now, like, just create on demand video training, that’s like, you know, a two minute video on how do you do this? Or how do you do that, and had lots more in app communications and the like, and more automated ways of getting people that information. So I think those are three things like number one, just getting the senior, and all the lawyers on how to understand the why of why you care about changing. Number two, taking the learnings from within a place and sharing it to others within that place, and to other places that are trying to have success. So just sort of raising the benchmark of what’s possible. And then number three, just trying to do automated, use automated methods to just help spread understanding of how to do work. Lots more to

Marlene Gebauer: imagine, it’s like a it’s a never, it’s always changing, you know, in terms of

Noah Waisberg:  not changing too much. We are trying  to standardize stuff. Like it’s a I would say it’s a constant battle, right? You can always do better. But I actually like I say that, but then there’s tons of examples of great success of technology adoption with lawyers, right? Like we give lawyers tons of grief over their technology adoption. But in fact, like, you think about how ubiquitous electronic legal research is, or virtual data rooms are or redlining software is, and like, none of those were at one point in time, right? Like they were the exception, and then they were sometimes used, sometimes not. And now they’re ubiquitous. I think the same is gonna happen with some of these AI technologies, and is already on the way there with things like contract analysis.

Greg Lambert: Well, Noah, when I thought of this question, I thought it was outside the box. But I think it actually expands a little bit on on your second point of your what you just answered. For anyone who has sold products to a law firm or practically any legal services, that they know that the sales cycle in these firms and other legal services is extremely long and extremely slow. Firms don’t just tend to jump in immediately and try new things out. And I imagine this is especially true with products that they say, uses artificial intelligence in order to make their products superior to the other products on the market. So how are you seeing successful companies overcome this obstacle of getting law firms and others to buy and actually use the products?

Noah Waisberg:  Well, it’s like, like the adoption question is just a constant battle and a search do things better. Yeah, in the early days, we did extensive proof of concepts, right, where a firm would go to a firm and tell them, this can make you a lot better at doing this work. And the firm would say, I don’t know if we can do better, but maybe we’ll try it. And see, they would run a proof of concept. And they would do that in different ways. Like sometimes they might have one group doing the project using the software and another group doing the project the traditional way, another time, they might just have a group after doing a transaction, have another group go back and try to do the transaction again. Using the software can be kind of dangerous to do that because sometimes you find stuff with the software that you should have found with the humans so that can be a really good way to to see the value of AI but also raises some risks. Or the third way to people to improve concepts is they would just try the software on a matter too and just anecdotally see how people liked it. Today,  w like for at least KIRA Systems a place where a majority of most competitors have a firm are using the software already, we don’t necessarily have to do that as much. There’s still some firms that might feel like you’re a proof of concept. But I think more often you really try to show that they get value out of the software. So the sales cycle has shifted a little bit of background noise as well, it’s Toronto is in full lockdown. So

Greg Lambert: yeah, luckily, my college students are crying in their dorm.

Noah Waisberg:  Definitely bouncing off the walls without play with their friends. So I think you’re always just trying to get people to go faster. But I think, you know, as we’re talking about adoption, like the most important part in the adoption story, as well as the buying story is getting lawyers to actually desire being more efficient. And like understanding that this AI technology can help them run a better law practice. And we find like, if you can solve that problem, the rest of the problems tend to go a lot easier. And like things can speed up a bunch,

Marlene Gebauer: What has the pandemic done to either amplify or mute the impact of AI in the legal industry?

Noah Waisberg:  Oh, a bit of both probably, I think, the pandemic, there’s definitely people using digital tools in ways that they might not have pre-pandemic. And so the tools are digital tools. So they get included in that. But I think there’s lots of non-AI tools that have also been lifted by that. The other thing that’s done is it’s raised some problems that actually can help solve, like, for example, early in the pandemic, if you were trying to figure out the implications of force mature, or termination for convenience, or the like, it was a really quick way to help people do that work that needed to be done really quickly. So there was definite use case around that. On the other hand, adoption is always just adoption and getting people to use it as always a hard battle. And one of the really nice things about having people sort of in office is easy to get someone who was like, you know, on the 31st floor of their office building, they go and talk to their neighbors and kind of like, Jawbone them into using technology like you might have the knowledge management or invasion, people might be more likely to hear that someone was working on a project just through the grapevine and be able to tell them about using AI. And I think that a totally my sense is that’s not happening as much. So there’s good and bad about the pandemic for pushing AI. Ultimately, I think client pressure for efficiency really helps the adoption of efficiency technology. And I think the pandemic is sort of pushing clients and pushing their budgets, which is going to push them to get their lawyers to be more efficient, which, which should yield more business for AI companies. But But I would say it’s a bit mixed. In terms of what we’ve seen, like, there’s definitely a lot of firms, also where people are just strained, like they had a lot going on. And you know, a lot of IT departments, there’s been a lot of time spent just on like keeping the lights like the virtual lights on. And so they’ve had to put a lot of effort into that and take it away from thinking about ways to do things better.

Marlene Gebauer: I wonder if the people are realizing that perhaps they are more flexible in terms of learning these things quickly than perhaps they thought they were beforehand, just you know, because they had to do it out of necessity. So I’m wondering if that’s one of the changes too

Noah Waisberg:  Yeah, I think it definitely could. Like I’m sure there are people who you know, used to dictate everything or handwrite everything to their assistant and like, or physically talk to people and they realize that like this video conferencing stuff isn’t too hard. Like, it’s actually pretty easy to look at files online, as opposed to getting someone to print them out for you. I think that has happened. I think this will help long term but it’s not like video conferencing software or something like that, where it’s like, clearly way up.

Greg Lambert: Well, Alex, if you could pull out your crystal ball and look into the future. What do you see when it comes to when there’s a time when AI is no longer a novelty that we discuss on podcasts like this? And it’s simply part of everyday life for the lawyer or the legal professional?

Alex Hudek:  Yeah, I mean, so in many ways, actually, you can see what the future will look like by reflecting on today. The problem with a term like AI is that it’s so broad. And the reality is that you need to think more about specific domains. You know, for example, voice recognition. This is arguably solidly under the AI camp. It’s certainly under the machine learning camp. And there was a time where, you know, the idea that a computer could understand human voice was like, Mind blown, right? Everyone today takes it absolutely for granted. However, we’re still talking about AI just in different things in different areas where AI previously couldn’t do anything or wasn’t accurate enough to make a big impact. Now you’re seeing those new things or where it is being able to make an impact, like in law, and, you know, document review. And so we’re talking about those and very likely in the future, when that becomes normal, there’ll be some other tasks and some other domain where it’s like, Wow, now suddenly, we have these capabilities, where it can do things that we didn’t think it would be able to do. And we’ll be ended up talking about those. So I do think we’ll end up talking about AI for a long time to come. However, in any given domain yet, it’ll suddenly eventually it’ll become boring. Like, how many people talk about Siri versus Google Assistant? Now? You know, just a few years ago, that was a big deal. Now everyone’s like, yeah, of course, I can ask my computer what the weather is, and it’s no big deal.

Noah Waisberg:  Alex and I went out for dinner. We like literally told his car, that this pre-pandemic, literally told his car, you know, where we felt like going, and then it drove us part of the way there. And it felt surprisingly normal.

Greg Lambert: Yeah, Very interesting. Well, Noah Waisberg and Dr. Alexander Hudek, thanks for taking the time to talk with us. You have a book coming out on February 3, called AI for lawyers how artificial intelligence is adding value amplifying expertise, and transforming careers. Where can we locate that book once it’s out?

Noah Waisberg:  Your favorite bookseller? I know I gotta keep a copy. But it’s been published by Wiley, who is like a major publisher. And one of the reasons that we did that like we self-published, Robbie The Robot Learns to Read our really excellent children’s book on machine learning

Marlene Gebauer: It is it is. I can vouge for that.

Greg Lambert: I have a signed copy.

Noah Waisberg:  Having done that we sort of we realized that, you know, was actually a pretty good book, and we could have gotten so much more pickup of it if we use real publisher we thought so with this one, we really felt like going with big publishers, because Wiley is the publisher, you should be able to get it like anywhere. Like I don’t know if it’ll be on the airport bookshelves these days, but that’s the kind of thing that why we does. Excellent.

Greg Lambert: All right. Well, Noah and Alex, thanks for talking with us.

Alex Hudek:  Thanks for having us.

Noah Waisberg:  Yeah, this has been fun. Good to see you guys.



Greg Lambert: Marlene, it was nice catching up with Noah and Alex and to talk about their new AI for Lawyers book, it sounds like Noah is having the same situation that many of us are having to go through with trying to take care of work and home and children all at the same time.

Marlene Gebauer: You know, I just feel good that it wasn’t me this between the dog and the kids, you know, sort of running through and talking to me. So, you know, it was a relief to know that other people also have these issues.

Greg Lambert: So thanks again to Noah Waisberg and Dr. Alexander Hudek. for joining us. Again, we have links for their AI for lawyers book and the show notes. And like Marlene said the book comes out on February 3 so pre-orders are available.

Marlene Gebauer: Please take the time to rate and review us on Apple Podcast. Contact us anytime by tweeting us at @gebauerm or @glambert. Or, you can call The Geek in Review hotline at 713-487-7270 and leave us a message. You can email us at geekinreviewpodcast@gmail.com. As always, the great music you hear on the podcast is from Jerry David DeCicca. Thanks, Jerry.

Greg Lambert: Thanks, Jerry. All right. Marlene. I will talk to you later.

Marlene Gebauer: Okay, bye-bye.