The Current State of Generative AI in Legal

Episode Notes

Transcript

[Music]

Intro: Web 2.0. Innovation, trends, collaboration. Software, metadata. Got the world turning as fast as it can? Hear how technology can help, legally speaking with two of the top legal technology experts, authors and lawyers: Dennis Kennedy and Tom Mighell. Welcome to the Kennedy-Mighell Report, here on the Legal Talk Network.

Dennis Kennedy: And welcome to Episode 343 of the Kennedy-Mighell Report, I’m Dennis Kennedy in Ann Arbor.

Tom Mighell: And I’m Tom Mighell in Dallas.

Dennis Kennedy: In our last episode, we interviewed Ivy Grey of WordRake as part of our new fresh voices of legal tech series. We’ve gotten a lot of great feedback on that episode about Ivy’s insights especially, and a few comments on the good questions that did you and I asked Tom to which was nice to hear. In this episode, we decided we could not ignore the 650 million dollar and growing AI locomotive steaming through legal tech. We’ve talked about generative AI and ChatGPT enough already that Tom has limited my mention of the term in previous episodes but here we are again Tom. Have we reached the top of the hype cycle on AI yet? What are some realistic ways that we need to start thinking about the current AI phenomenon? And what it means? And what it doesn’t mean? Tom what’s on our agenda for this episode?

Tom Mighell: I don’t know that I’ve been very successful about limiting your mentions of the term and I certainly will not be successful in this episode, because in this edition of the Kennedy-Mighell Report, we will indeed be discussing the current state of generative AI in the legal world. Dennis has promised not to be a Pollyanna optimist on the topic. We’ll see how that works out. In our second segment, we’ll discuss the current commotion going on in the world of Twitter and various Twitter killers and what we are doing in the rapidly changing social media world. And as usual, we’ll finish up with our parting shots. That one tip website or observation that you can start using the second that this podcast is over and we’ll see if we can get through without some type of generative AI parting shot. All right, but first up, let’s talk about the current state of artificial intelligence. Generate AI, ChatGPT, large language models, machine learning, conversational AI, whatever else you might want to call it today in the legal tech world for those of you who may have seen the news, Thomson Reuters purchased case text with its co-counsel artificial intelligence tool, Thomson Reuters seemingly putting a stamp of approval on artificial intelligent in the space. I will be honest I have not had one thousandth of the time that Dennis has spent working with tools like ChatGPT, but I do have some opinions on the subject. Dennis, you have promised that you now have a bit of a contrarian view, won’t be a complete cheerleader but I still have my doubts. What is your current thinking about these tools?

Dennis Kennedy: You know, I’m actually on the moderately bearish side generally at the moment and under the legal side, I’m even more bearish but I’m really interested in some of the experiments I’m doing. So, let me sum it up here. I think we’d all be much better off and have more realistic expectations if we thought of where we were now was not ChatGPT 4 but ChatGPT 1.4 because I think that would give us some more realistic set of expectations about the state of the art of these tools and that they are to me as I keep finding, I keep running into the constraints and so I’m intrigued by certain possibilities, but I definitely see the limitations everywhere. And so, I based that on my experience teaching the class in AI, and the law at Michigan State. And also the work we did, talking about AI and law at Michigan State and my class there and frankly hundreds of ChatGPT experiments, I’ve done this summer. So I keep more and more aware of the limitations and that’s one of the things that we will talk about. Tom, I don’t know where you’re at these days.

Tom Mighell: Well, ii haven’t done hundreds of ChatGPT experiments, I’ve done some experiments and they’ve really been less experiments and they’ve been more of thinking —  here’s a problem I need to solve, let’s see what ChatGPT can do for me in this instance. And I will say I reached much the same conclusion. I think there are some significant limitations, even though there are very interesting ways to use the tool that can help get you something that’s quality.

(00:05:09)

I think that there is a lot of limitation. You know, what is interesting to me, what I am paying attention to is that I am hearing about ChatGPT everywhere. News reports you’re talking about, the different industries are talking about, how it can help them. Every day I see 10 different articles on “how generative AI will completely revamp [how insert name of industry] here works.” And the takeaway from that is, you know, to repeat what we mentioned on a previous podcast, generative AI has captured a huge mindshare. Is that everyone is talking about it to some extent which is very interesting to me. But while I see, and I hear people saying here, I used ChatGPT to do this and I tried this out and the lawyer got sanctioned because he used ChatGPT to generate a bunch of fake case citations. I still think, like most technologies, very few people are taking advantage of it. Very few people are using it in their work, in there play and whatever reason. So I still think it has, you know, even for general adoption, we’re still way low on the hype cycle, at least for most people.

Dennis Kennedy: Or way high on the hype cycle, or trending down.

Tom Mighell: Right, right. Correct.

Dennis Kennedy: Yeah, I mean I guess Tom, it’s worth mentioning that we did that episode on the Gartner hype cycle a while back and that’s people are interested in the hype cycle approach to things, which I think is really useful to understand what we’re at in AI. Recommend that that earlier episode. Yeah, I sort of — I just see people — I think there are ways that generative AI has some really fascinating potential and I was doing some things today, where I was definitely seeing that but I think you’re right, people talk about using it in ways that to me just don’t make any sense and then they’re disappointed. Like I had ChatGPT pick stocks and a week later they aren’t up by a huge amount. So therefore it’s not a good tool. I’m like, why would you even use it for that, that makes no sense. But to go back, Tom and I think to echo what you said. I think lesson number one is that generative AI has some constraints and you really hit them quickly. And that’s the thing that I noticed, it is sort of gives you the sort of average, the sort of consensus. It can be repetitive, it can be sort of beside the point, there are some definitely some issues coming from the way it was trained and how you use it and what you have to do with prompting. And I guess the big one, is that it was trained, you know, through up or I guess up until 2021. And so you have to do something separate to get more current information and to connect it to the internet and I think that’s where things really start to break down. So if you ask ChatGPT a question about something that’s current, it will tell you that it was only trained until you know, on data before 2021 and it’s not able to answer that, if you use the banking and Google tools, or the plugins that connect to the internet, I just find that to be, the results you get are just a mess and they’re close to unusable and Tom I hate to say this here, it makes me long for those early days of Ask Jeeves, when you could ask a question and get something that seemed like an answer back. I’m just totally disappointed by what I see comes back when you’re connecting these tools to the internet.

Tom Mighell: I will say the one thing that having AI in Bing and Google is that it does search recent content. So you know, I can go in there and say, you know, how is Alcaraz doing at Wimbledon? And it will tell me how Alcaraz is doing at Wimbledon because it’s got current, it’s not limited to the 2021 constraint of the time. But for me, frankly, that’s the only thing that it has going for it because what’s interesting to me is it doesn’t make the search engine smarter, it’s only retrieving what the search engine would retrieve in the first place. I sort of view the value of AI, you know, search engine is making it easier for you to create a natural language query, as that you can talk to it like a person rather than just enter a couple of key words and it will answer you back. But I’m planning a trip in November and I asked for the best restaurants in a particular city and it may —

(00:10:02)

— well, the first thing it said was searching for best restaurants in city, and it was clearly, it had taken my natural language query and turn it into just keywords, and I’m thinking, this doesn’t feel like artificial intelligence and it brought me the top 10 restaurants that were the same top 10 restaurants in a link and it just gave me four links here. Go check these out, top 10, top 15, best romantic meals in this city. It was no better than just getting regular search results. So I would say the same thing, I’m not real impressed and haven’t really made that much use of the tools that are in Bing or in Google. I have not used Bard. I would say that I get much more value of using ChatGPT even though it might be as dated as 2021.

Dennis Kennedy: Yeah, I actually think in a weird way that working within that 2021 training constraint and that using up to the minute search or research is where for me, I’m finding really interesting uses of the large language models today. So I understand that that’s a constraint, and then I can start to work, you know, within that constraint. So I can say, you know, summarize the, you know, the key concepts and principles of this book that I know is before 2021, and then I can turn that into you know, analysis tool in ChatGPT and I can do other things like that. And so it’s really kind of interesting to me to play with the constraints. And you know, as Tom as you kind of alluded to earlier as I keep experimenting this is things I’m finding as I keep doing more and more with this to say, here’s some problems I’m running into based on the data sets and other things that I see that are useful and then I also see the value, the real value I’m getting is that this is giving you answers to get you the consensus or the average answers and there are certain cases that can be really useful. On the contrary, there are things that I’ve run into where I know of the topic really well and the results are super average, they’re super generic and they’re actually unhelpful, but there are other places where getting that consensus or sort of best practices, other things like that, that are sort of standard as a starting point, can actually be quite useful.

Tom Mighell: Well, you know, for me still the biggest value is in the ability to generate content that I can take then and work with. It’s never going to be a final version but I will tell you, I got a reasonably good result, taking the transcript of one of my companies webinars, I fed it into ChatGPT, I said please summarize this webinar and I broke it into chunks and created through two or three blog posts out of it. I mean it was not perfect when it started but it got to the summarization parts quick enough and easy enough to where it genuinely saved time in doing that. So I find lots of value in that. But granted I’m not spending the kind of time on this as you are which I also assume is running into its own set of constraints.

Dennis Kennedy: Yeah, and I think the ones that people run into if you start to use it for are the limitation in the prompt window. So how much you can put into them. The limited size of documents you can work with unless you really go through some procedures, try to pull larger documents in and then and I guess I need to say this but if you’re using ChatGPT, the open AI version, you really need to spend to $20.00 a month to get the access that you need but you’re still going to run into limits on 25 searches in three hours and other things like that, there will be big hindrances if you really have a big project or you want to try to learn a lot. Tom, break time.

Tom Mighell: Yep, we have more to say on the subject, but for now, let’s take a quick break for a message from our sponsors.

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Dennis Kennedy: And we’re back. Tom, the one thing I see most people in the legal field miss about the current state of generative AI is the essential role of humans in the middle, would you agree?

Tom Mighell: Well, I would agree, but I would say also this applies to all occupations, right? I mean, it’s not just do we’re seeing an illegal field, we’re seeing it in all field. Just say AI is replacing insert name of profession here, and you’ll find people asking that question, you know, a web designer offered to use AI for us to generate some search engine optimized keywords for our website and showed us some examples and one of the people looking at them said, no way these are terrible, we are never going to use them AI for anything, they’re going to replace what we do and I will never do that. But you know, we were able to take that list and work with them as again as a starting point, not as the be-all end-all and that person showed their value in being able to take that information come up with a list that we were ultimately happy with, and that person has now changed their mind about the value of this. And so, you know, I think that’s a major thing that’s missing is people are forgetting, you know, this is not going to replace humans and can’t be expected to anytime soon.

Dennis Kennedy: Well, I think that not seeing, understanding this whole human in the middle approach. So, if you look at chess, you look at the other things is it’s not — it means cliche, but it’s really true but the best chess player in the world now is not a human and it’s not an AI, it’s a human using AI or as an AI working with a human. And so that I think is the big thing for me to understand and that’s why the AI replacing lawyers to me is just almost a waste of time to talk about. So I think what the generative AI tool gives you is a way to kind of put yourself in the middle and then what I find and it gives me first drafts, it gives me first screens and then I usually work it to the point where it becomes very clear that the AI is not able to help me anymore and then I have sufficient information where the next step needs to be that I take it and go further and whether that’s improving my writing or, you know, people who, you know, I can’t even imagine like why people would use this for legal research at the current state in the way that they seem to think they can, or want to use it, I really struggle with that whole concept, but I think you see that the way that this is going to work is to have the humans in the middle and to understand how it can help you and I think that first draft first screen approach is a big thing.

Tom Mighell: I agree with everything you’re saying and I think that you know, what I’m seeing and I think you backing this up is the fact that it feels very similar to when Web3 came out and it feels very similar to when the metaverse came out and suddenly we’re seeing experts on this topic and experts on artificial intelligence, legal experts talking about here are what you need to do. Are you seeing that on your end to? I sort of am amazed that lawyers are able — good marketing lawyers are able to pivot quickly to talk about things that really haven’t been resolved by the technology in the first place.

Dennis Kennedy: You know, it’s a weird thing Tom. I monitor some of the leading voices in the AI field and I’ve been around it for a while and I’m not just talking about legal AI. I tried AI experiments almost every day. I still consider myself a beginner. I’m just starting to learn some things that I would feel kind of comfortable presenting on but as a kind of, we learn it together kind of thing, and I think generative AI and the large language (00:19:37) very new, especially in law, and I just am stunned by how many legal experts are now hung out there shingles, launched their marketing and are speaking everywhere. Like, I’ve seen some of the people speak a couple of times on AI, and there are so many experts in the legal areas. So many presentations and I’ve seen ones on best practices and using AI and law. I mean like seriously this stuff just came in, ChatGPT stuff just came out at the end of November like best practices, I don’t even know what they’re talking about.

(00:20:14)

So I think the news I have for people is caveat emptor and reader and listener emptor when you’re hearing stuff about AI especially in law, there are big issues out there, big concerns, lot of underdress problems with the data sets, other things like that and the idea that we have people talk about best practices, just blows me away.

Tom Mighell: Well, isn’t the best practice of AI, isn’t it user beware? I mean, it’s all seems to be all the same stuff but yeah, I agree. I think there are many things that it is far too early to be opining on and having those types of opinions. What else are you seeing out there Dennis, we’re going to wrap this up soon, but tell me some of the other things that you’re seeing right now, but that either give you cause for concern or cause for optimism.

Dennis Kennedy: I talk to my students about the Gartner hype cycle and how like the hype cycle on AI is felt like it went up to the highest heights of anything that I’ve ever seen in technology and that leads me to think that the slope downward into the trough of despair is going to be super steep and I think we’re starting to see some signs of that where people are disappointed. You see this story about the lawyers’ discipline for using allegedly I would say, I still have our friend Ernie attorney said that you know, there are questions about whether those lawyers really use ChatGPT on their legal research and stuck to the story or whether they just thought it was a good excuse for sloppy legal work, interesting theory from Ernie, you know, but I think there’s some things out there, we know that the regulators have yet to weigh in on AI in general. We know that the bar regulars have now weighed in their concerns about this technology, how it was created, who runs it, who profits it from the biases in it, the concentrations of power which are very real and how will we use and not use? These are complex difficult questions and I think there’s a ton of uncertainty about it. So I don’t know if you have anything to add their Tom and then I have one thought I want to wrap up with.

Tom Mighell: Oh I mean I think with that we can reliably predict that the bar regulators and other regulators will weigh in on this after years of further work has happened and then suddenly someone will recognize that, oh my gosh, this is a problem that we should be dealing with. So I don’t expect this to be any different from any other technology that they have failed to weigh in on in a timely manner. You know, I think as we’ve said before, I won’t waste time echoing it other than to say, lots of good opportunities here, lots of good potential but a whole lot of improvement needs to be made and a whole lot more needs to be learned. I think before lawyers are really going to be able to take better advantage of this technology.

Dennis Kennedy: Yeah, my ultimate take and this is what I told my students in my AI class is it, I think it’s time to roll up your sleeves and learn where it can help you and where it’s not ready for prime time. You know Tom, people who know me know I’m always going to say comes down to jobs to be done and getting clear on what you’re hiring generative AI to do for you. And that’s what I’m working on right now. What is it that it can do for me? What does it work for? And what doesn’t it work for? And I think if we clear on that, that’s going to solve a lot but I do think there’s going to be some backlash of and disappointment of all kinds that I can’t predict where they couldn’t come out. So here in July 2023, I’m moderately bearish on generative AI in legal in the short term and that’s because I expect a big regulatory backlash in a number of forms between now and the end of end of this year. But I’m bullish in some specialized areas of the law practice, especially the long-term. I will say Tom and you might disagree with me on this but I think legal research is not one of the area’s I’m bullish on. I think it’s an incredibly difficult problem and I’m not sure that the large language models are the right tool to attack the job to be done. That’s legal research is. And I say that even though some people have 650 million reasons that they think the contrary.

(00:25:02)

Tom Mighell: Well, I would say that for the 650 million reasons, there are some uses for that particular tool that are good point. The large language model at a large set of discovery and ask for it to find information about something. I think it’s up to that task, but I tend to agree with you, given ChatGPT’s penchant for providing completely fake citations, I don’t know that I would It to do legal research until you’re able to feed it to a correct database and maybe that’s what the 650 million dollar investment is going to lead to is maybe it’s going to make for smarter artificial intelligence, but until then I think we have a ways to wait. All right, that’s always said on this subject for now I’m sure we will speak more about it later but until then, let’s take a quick break for a message from our sponsor.

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Tom Mighell: And now let’s get back to the Kennedy-Mighell Report, I’m Tom Mighell.

Dennis Kennedy: And I’m Dennis Kennedy. In the past week, Elon Musk has destroyed the usefulness of a tool called TweetDeck that I use daily. Then brought it back as a pay only service as part of his latest effort to either drive Twitter into the ground or to make it, and I’m doing air quotes here, successful. I had the biggest influx of followers I’ve ever had, and admittedly that was only about 10 over a couple days on Jack Dorsey’s Twitter competitor, Blue Sky and the legal tech journalism world seemed agog last week with the story of Mark Zuckerberg’s new Twitter killer called Threads on Instagram which I saw today now has a hundred million users, and I can’t even imagine that stream of whatever they’re going to call Thread tweets coming at me would be like. Tom, we talked about Twitter competitors and moving our Twitter several times since Musk took over. I guess we need to hit the topic again if only to let our listeners know what we are currently thinking and doing. Tom, do you even care about this anymore and if so, what are you doing and planning to do?

Tom Mighell: So, what I don’t care about anymore is Twitter and I’m pretty much done with Twitter. Every time I come around now, I have to be logged in all the time, just to view a tweet. I’ve recently heard about the rule that if you are not a subscriber, you can only view something like what is it, 600 tweets a day or something like that, I think that’s the limit of what you can watch. You have to subscribe to see and I guess I hope it’s on unlimited amount if you subscribe. But the rules change from week to week, and it’s new things that you can’t do unless you have a subscription to it. So it’s crazy. It’s just crazy town and I’m completely done with Twitter. I have no — they’ve done away with the API. They’ve done away with all the apps that actually make Twitter and so I’m done. As for a competitor, as for where to go after this, I’m torn because — and I think that the jury is still out on this because you know, I originally thought that some of these other tools, Mastodon, what was the other one, Post, has anybody talked about Post these days? I don’t think so. Blue Sky, I thought Blue Sky has an opportunity here but I did a search yesterday for how many uses round Blue Sky and it blew me away, it says currently there are 180,000 subscribers on Blue Sky and a wait list of 1.9 million people that suggest a real problem with onboarding. I mean, they’ve got some real issues there. But to me a community of 180,000 people is not a community, it’s not enough for — it’s not enough critical mass to make it worthwhile to me. Now Threads is interesting. It’s interesting to me because it immediately got some critical mass but the caveat there and the one thing to pay attention to is that it only got to a hundred million because you made it very simple for the people who are already in Instagram to immediately become threads users.

(00:30:13)

And there wasn’t much friction to getting that done and I think Instagram has over a billion users so really this is 5% of Instagram people have joined. What will be interesting to me is to see how that catches on, and I’m marginally involved, it’s not the right word because I really, I haven’t, I don’t think I’d sent my first thread yet on Threads, but I like it because it’s got a lot of engagement on it and I don’t know that I see that in other places. So I’m at least encouraged by that but I’m still biding my time. I’m still waiting to see, I’m not just convinced in any of these. I’m still mourning the loss of the Twitter that I used to know and that I really enjoyed communicating on. My part of Twitter, not the toxic hateful parts of Twitter that we see more in the news these days but I’m still not sure what my Twitter replacement ends up being and whether that’s — I mean right now, it feels like Threads just because I see that’s where all the people are going, but you know, that might change in two weeks. So I’m not sure at this point. Dennis, what about you?

Dennis Kennedy: Well, I think it’s time for both of us, it’s like 16 years on Twitter, right? Something like that? So it’s hard. It really is hard to you know, something that you use regularly to see it go away as it feels like and there’s a part of me Tom, and I mentioned this the other day that I sort of have this belief, or fantasy I guess that sometime in the next few weeks that Elon will grow tired of this and sell it to a group that cares for a dollar and maybe it will come back to the way it was. But I realized that this kind of fantasy. It’s easy, relatively easy to sign up for social media services. It’s really hard to post to them and to do that consistently into actually use them and be engaged in them. That’s what I think is hard and as I look at Twitter, I’m sort of wondering like what why I need to have this sort of short form text based social media platform anymore. So that’s where my thinking is, and I’m thinking, like, you know, LinkedIn may do most of the stuff that I want. I don’t need like a hundred million users, I don’t need 180,000, if I just had a group on might be networks, which is people who had, who were a community of interest that would be awesome for me. And so, those are the ways that I’m thinking of going. And I hate, you know, that I’ve been on this thing for 16 years and I think I’ve said on the show before time that I evolved this Twitter persona over 16 years today to that now I really like and I hate to kind of kill that persona off but I sort of feel like I have to and that even the days where I try to talk myself out of it, Elon does something that’s just so horrifying that I question how I can even stay on one more day even though I hope that he sells it for a dollar at some point here soon. So, that’s where — I’m sort of thinking of simplification and then really thinking of what it was that I use Twitter for and what I need to do and do I have better, more productive and more focused use of the time that I was using for Twitter. So, that’s where I’m at. Now, it’s time for our parting shots that one tip website or observation you can use the second this podcast ends. Tom, take it away.

Tom Mighell: I just returned from vacation and I will tell you that the most useful technology tool that I used during the trip and it’s been around for a while, so this is not absolutely new, but it was first time I’ve used it out in the wild is Google’s Magic Eraser and I will tell you that is freaking magic because one of the worst things about going on vacation and going to tourist traps, where there’s tons of people around is it’s impossible to take a picture without somebody being there, you sit there and you wait and then that one person wanders up to the very front of the monument you want to take and just sits there and looks at the plaque at the bottom and reads every word for 20 minutes so you can’t take the picture. It’s impossible to take good pictures without somebody being in it and Google, if you haven’t seen a Google photos, makes it very simple to move people with almost a click of the button. I would pull up a photo on my phone, if it identified it immediately, it would give me an option. It said “remove people from this photo” and I’m like you are speaking my language. I press that button. It takes about maybe seven or eight seconds and then it highlights all of the “what they think are people in the photo”, they are 95-98% right about that.

(00:35:09)

You click another button and they vanish as if they were never there, I mean it deleted 15 people from a photo in a tour group that I was in, it’s not just one or two people, it’s a lot of people. I am amazed, it’s not 100% great, there are some areas where, you know, one thing that it doesn’t delete, which is interesting to me is it’ll delete a person, it will not delete their shadow, so sometimes they look a little interesting where the shadow still shows up but the people aren’t there, but I will say I was able to really get my pictures in really nice shape this year and it’s all because of Google Eraser, it’s not just for people who have Pixel phones, although it’s easier on a Pixel phone, if you have Google photos, whether its IOS or Android, you have Magic Eraser and I urge you to use it on your travel photos. Dennis?

Dennis Kennedy: So this is like the positive version of defects, right? Because I can adjust the photo to what I want to be. So I think this is really cool and is there — you think there’ll be like an augmented reality form where you can kind of take people out like while you’re looking to goggles and get them out of your way in real time, that’d be kind of cool too.

Tom Mighell: That requires me to wear goggles though, we are not there yet.

Dennis Kennedy: So I wrote a new column that I turned into this morning. So it should be out by the time that this this podcast is released for legal tech hub and I do a column one on Law Department Innovation and I was talking about Jobs-to-be-Done Theory which I mentioned to get on the show and I probably mentioned on what time like about 40% of the shows that we’ve done over the years. So I think it’s a great time to learn about Jobs-to-be-Done. So I recommend my new article and then I also just to tie it to the first topic is that I played around with doing a summary of Jobs-to-be-Done Theory into ChatGPT and then using that to generate ways to analyze things that I was thinking about doing using the Jobs-to-be-Done Theory and the results were actually pretty good and as I said, I always think of the AI stuff is doesn’t give me a first draft or first screen, we should more than adequately did and it allowed me to do something and gave me ideas and structure for some things that I went on to make more precise and shape what I was doing. So Jobs-to-be-Done Theory, totally great, go back and listen to our Bob Moesta interview show, which Tom always calls the “Dennis buys a new blender show” to get an idea of how it works in action. But nice combination of learning this and then play it using it as an example to play within ChatGPT.

Tom Mighell: And if you are playing the Kennedy-Mighell Report drinking game at home. Dennis did say ChatGPT another six times so drink, drink, drink. So that wraps it up for this edition of the Kennedy-Mighell Report. Thanks for joining us on the podcast. You can find show notes for this episode on the Legal Talk Network’s page for the show. If you like what you hear, please subscribe to our podcast in iTunes or on the Legal Talk Network site, where you can find archives of all of our previous podcasts along with transcripts. If you want to get in touch with us, Twitter is not the right place to go. You can always reach out to us on LinkedIn. You can leave s a voicemail, we love to get voicemail for our b-segment to give us something to talk about or give us questions to answer, that phone number is 720-441-6820. So until the next podcast I’m Tom Mighell.

Dennis Kennedy: And I’m Dennis Kennedy, and you’ve been listening to the Kennedy-Mighell Report, a podcast on legal technology with an internet focus. As always, a big thank you to the Legal Talk Network team for producing and distributing this podcast. We will see you next time for another episode of the Kennedy-Mighell Report on the Legal Talk Network.

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