Changing Directions on Generative AI?

Episode Notes

Transcript

Speaker 1:

Web 2.0 innovation 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 362 as 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 Emily Culbert, product leader of Westlaw’s Practical Law, AI, about the promise and potential of practical law ai. I’m on record as a big fan of Practical Law AI and highly recommend this episode if you haven’t already listened to it. Now we decided to take another crack at generative ai. You might recall that not so long ago Tom prohibited me from even bringing up this topic, and I adhered to that band to the letter as opinions on the potential of AI continued to evolve. We noticed that Tom has turned more bullish on generative ai and I have turned somewhat bearish, so we thought it’d be fun to turn the tables on the enthusiasm we’ve historically had for this topic on the show. Tom, what’s all on our agenda for this episode? Well

Tom Mighell:

Dennis in this edition of the Kennedy MA report, we will indeed kind of sort of be trading chairs at the table to talk about AI from our current perspectives. In our second segment, we’re going to have chat, GPT ask us a question as it has generated from our audience’s point of view, and as usual, we’ll finish up with our parting shots. That one tip, website or observation you can start to use the second that this podcast is over. But first up, have the two of us really shifted our opinions on ai? Is my ban against Dennis bringing up AI really over and am I now an AI evangelist? I’ll point out that Dennis wrote that sentence, and I will contest the fact that I actually put a ban on ai. I complained about Dennis’s incessant bringing it up constantly, but it never had an effect. And I would argue that I’ve talked about generative AI just as much as Dennis has over the past few episodes. So Dennis, I guess what’s most shocking to you that I may have become more bullish or that you become more bearish?

Dennis Kennedy:

You were so bearish at the beginning. Your positive approach is a bit of a surprise to me, but I sort of knew you were coming this way. I guess that I don’t know this shocking. I think it’s often characterize myself as an optimistic realist on ai. So the more I’ve worked with it, I sort of see the constraints, the limitations, which I think are both challenges and opportunities, but I find myself running up against limits more and more, and that’s what I would like to talk about and they aren’t especially surprising to me. So I guess maybe it was surprise people. I would consider myself more bearish, but I think the shack is how bullish you become, and I’m actually interested in why you have left your grumpy AI pessimism behind.

Tom Mighell:

So let’s get it real clear. I was never pessimistic about artificial intelligence or gen ai. I was merely skeptical, and maybe I will say maybe a little grumpy of your apparent obsession with artificial intelligence and G when compared against your enthusiasm. And all of the time you spent constantly telling me how you were running up against your limits with all of the tools that you were using because you were using queries. So often. I can see how when you compare that against your enthusiasm, my reaction could be interpreted in a negative light. So let’s be fair, as you know, and as I have mentioned in the past, I just haven’t had that much time to experiment the same way that you have. And as we will discuss later in this segment, I think both you and I believe that if a lawyer is going to use a tool, any tool, you don’t just start using it, you’ve got to learn how to use it.

If you try to use it, otherwise it’s irresponsible. You can cause either harm to yourself or things just don’t go the way you expect. And with ai, I would argue that that learning curve is a little more daunting than with most other technologies. If I’m going to learn how to use notion versus ai, I would argue ai harder, notion easier, but I am using it more and I’m learning to use it more. And I think that’s why I would call myself much more enthusiastic than in the past. I would not say that I’m any more or less bullish or bearish, I’m just enthusiastic because I’m actually seeing some of the benefits from it that I am able to reap where I in the past did not have time to see those benefits.

Dennis Kennedy:

So two things there. So I think there is this time element that people really downplay. So you got to get your hands on this stuff and try things and experiment, and if you don’t have something to experiment on, I think it’s harder to see that some of the potential for this stuff. Also what you started with is that lawyers say, oh, it’s generative ai. I am going to go right to the hardest thing to do in legal practice, or I’m going to legal research or something and I’m going to be disappointed with that. This is due exactly what I expect. And so my advice to people is you got to put it into time and you want to use it on stuff that’s not what I’d say dangerous or what is that meant for? Why in the world would I learn some new tool and put the most confidential, the most important things I’m working on before I even learn to use it.

So what I recommend to people is you use it as this assistant, this intern that’s tireless, that will do all these things for you. I was listening to a podcast this morning with an author and sort of well-known consultant and someone involved in different parts of business, business, leadership, coaching, things like that. It was Charlene Lee, and she was talking about how that she’s now finding that about 70% of the work she used to do or have a research assistant do. She’s now just initially starting with generative ai. And I find myself, there’s a lot of things that I just say, I can get a start with this stuff with generative AI and it can do a lot of things and I just don’t go into territories where the AI isn’t good. So I’m finding all these things from project planning to evaluating things, give me comments on things, summarizing all sorts of things.

I can do that when I show people I can see from the look in their eyes and what they tell me is they’re seeing magic to them. They’re like, oh my god, I didn’t know you could do this. So I’m finding things that I can do, but I’m also finding things that I can’t do or that are super clunky, but we will get to this in a second. Tom, this is going to be one of my main points about lawyers in ai, but I think lawyers tend to talk about time not having the time when it’s more like the effort to learn something and they think they can just jump in and use this stuff at a very high level and not put in any work to raise their own level.

Tom Mighell:

Alright, so I’m going to talk a little bit about how I’ve been using it and what I’m liking about it right now. And I have four use cases that I want to talk about. And so spoiler alert, Dennis, go take a break. I’m going to talk for a while. There are a couple of things that I’m really interested in, and I think I’ve mentioned this on a previous podcast. The one area that has work and business implications is we are working at my company about finding a way to use generative AI to search out and find record keeping requirements in laws for federal state international instead of legal research, which I think is a fraught subject for generative AI right now, teaching a generative ai, how to understand what a record keeping requirement is and go search for those record keeping requirements is I think absolutely doable.

There are some challenges with it that need to be overcome and we’re doing that, but I see that being able to do research in this way is really going to make our work so much easier and actually provide better value to our clients as well. So I’m very interested in where that’s all going. From a personal standpoint, I have three different use cases that I’m following. One is easy, one is a little harder, and one is the future of what I’m really excited about. The easy one is I’m planning a trip this summer. I asked chat GPT to be my travel agent, and I said, here as my travel agent, here’s what I want you to do. I want you to interview me for this trip. Ask me all the important questions that you would need to know and then plan this trip for me.

And it asked me about seven or eight questions about how much do I want to spend? Am I an outdoorsy person? Do I like luxury? Am I a foodie? What are the things that are important to me? And it did a very workman-like job of giving me an itinerary about maybe 30% of it I appreciated and enjoyed. A lot of it was sort of canned stuff that I was like, eh, a little bit of more work with that and I think it would really get good. Where I’m more interested though now is, as you may know, I have, when I started my blog back up again, back in what? 2020? 2021. During the pandemic, one of them, the things that I was posting were sort of my, what I call my Friday five, the five top subjects and consumer technology stories of the week that I thought lawyers should be paying attention to.

I created my own GPT in chat, GPT that I fed it, my old blog posts, I fed it a lot of information. I said, I want you to be able to, I’m going to feed you five links to technology articles and I want you to create a first draft of my blog post for me or my newsletter. I did a newsletter at the same time and it did a great job of discussing the content. It did a great job of that. It doesn’t quite have my voice. I wanted it to be kind of casual and fun and interesting. It doesn’t quite have my voice, but I like the idea where all I have to do is just say, here are the articles this week, create something new for me and I don’t have to do that work anymore because that was really the blocker for me was I just didn’t want to get started.

It’s like the typical writer’s block. I hate getting started. Once I got started, it was great, but this would make that so much easier. Here is what I’m really truly excited for because I was watching a podcast earlier this week talking about the new Gemini 1.5 Pro, which is Google’s artificial intelligence. And what he was mentioning is that the new capabilities of the 1.5 Pro allow you to feed it so much more information or give it so much more information. What he started doing is, and we’ve talked on this podcast before of using read wise to capture highlights from articles, from books, from podcasts, from Twitter streams for all sorts of things. PDF files and storing it there. You can direct where your read wise stuff goes. Dennis and I right now we have our read wise stuff going. I think Dennis, you’re going to notion mine goes to Notion, but you can also direct it to go to Google Docs.

And what I’m contemplating and what this podcast was arguing is you feed all of that stuff into Google Docs, you now have an artificially intelligent second brain. You can talk to Gemini and say, all right, I want you to tell me all the stuff about all of this and it should do that. It was doing that for this person in the podcast at a very, I would say, limited level and not what I would think I would want out of it, but I’m fascinated with it. I’m wondering, is that the second brain that I’ve been waiting for because I can actually have it write something for me, go out and find all the articles that I saved on this and write me something on it. I’m totally in on that and that’s where I guess I would call myself bearish because, or sorry, not bearish, bullish is the right word.

Sorry. Because that to me is really an exciting, I’m now looking forward to 1.5 coming out so I can take advantage of it. I’m not sure how well it would work on, I think Gemini right now, if you pay for it, you’re still getting the 1.0 version, so I’m interested in that. But alright, I’ve been talking a lot about what I’ve been using and I just wanted to get it out there because you claim I’m bullish. I suppose that what I’m working on and the way I’m thinking about it would seem to be evidence of that bullishness.

Dennis Kennedy:

Yeah, definitely. And I think you have some really cool use cases there. And so the last thing that you’re doing is sort of an area that I’ve been nibbling around in, but I’m looking at if this, then that is the tool and the AI there, which would then allow me to grab feeds and pull them into a personalized newsletter for me. And it could be through Gmail, could go into notion it could do some other things like that. And then I can’t remember what we talked about this on the podcast. I have this book Summarizer Prompt. So the problem with my note taking is I don’t take notes and we talk, I don’t talk either. I don’t take

Tom Mighell:

Notes either.

Dennis Kennedy:

And so I say, I read this book and I have this prompt that does a detailed summary of it. And the idea is that if I have no notes, then whatever the AI captures in the form of notes, which is actually pretty good the way I have it set up, I put that into my second brain and notion and I have this notebook of books that I’ve read and I’m able to search it and do things like that. So those things I agree are interesting. And so the constraints I see are not there. So I think that sort of first pass, first draft solve the blank page problem can be really good. But if as you start to become more refined in what you’re doing, you sort of see how it doesn’t have the sophistication you want sometimes, but we’re in early generations of this stuff.

But more importantly is that you have to pull out of the GPT to get it to what you really want. And so let me explain that. So if I’m making what seemed like small refinements, it sometimes just really struggles with that. So I was putting together a sort of complex agenda for a meeting and then I said, okay, we’ve got these topic covered. So I’d like to do is keep the same agenda, the same sort of timeframes for each part of it and then add these five other topics and just put ’em into the appropriate slots in the agenda, just sort of integrate it in there. And so I had to rerun the agenda and just change the agenda to start with those five specific things. So I’d say, no, no, here’s what I meant. I meant this. And then it just really struggled. And then as I got closer to final, and I would say when you’re saying I like to move this here or renumber these things, that’s when it really struggles.

It’s fascinating. And I was doing this thing, I said redo the agenda after 10 30 and I couldn’t make it get there. It was still going back to 8 45, you do this. And that’s where it was starting from. And so sometimes you see that there is that constraint that you have to, I usually just work around this, but the training date, so it won’t have new information. It’s only been trained through a certain date, which I think with GPT-4 is September, 2023. I could be wrong on that, but that’s what I think. So if you have something new, you need to go out to the web and I don’t like using AI with a web particularly, then it sort of brings in the problems that search engines bring in. So you bring in all those little search engine issues and search engine optimizations and all those sorts of things. So I don’t like that. So I see a number of constraints there. And then there’s some outputs that I like to do that are really hard to do. So two by two charts, other things like that, getting the output that I want is more difficult than I would like it to be. So in the summit now, what are becoming common uses for me, I feel like I’m really up against some of the constraints.

Tom Mighell:

Well, and I think that that just comes from using it as much as you’ve been using it. And the question becomes, does the fact that you’ve been using it so much, is that generating unrealistic expectations on your part? Are you expecting that it can grow and stretch in ways that it’s not able to? And I found the same issue when I was trying to create an image using the dolly part of chat GPT. I wanted to create an image for a presentation where I was going to have somebody working on a computer and have somebody sort of sinister looking over their shoulder, they were trying to hack into their computer. That would be the message and it would get something just about right. And I wanted it to keep the same image but change a detail and it would give me completely different people in the picture.

It never gave me the same information. And it was very frustrating. And so to me, the paths forward are really about understanding the ways in which the tools are still limited and working within those limitations and saying even what they’re there for. The tools are still amazingly powerful. They continue to improve and I guess understand and hope. You talk about how CHATT four is current only as of September. What’s nice about, and I’ve mentioned this on not maybe not the last podcast, but a couple podcasts ago, I’m using perplexity.ai now as my search engine and I know I just now asked it, how did the key bridge in Baltimore fail? What was the cause of the bridge falling? And it gave all of the reasons why, and it cited to resources that would show that. So there are AI tools that are fed more current information and I think that’s interesting. But yeah, I think that we just have to keep looking at here are the ways in which it is powerful, understand the limitations and hope that those limitations are addressed.

Dennis Kennedy:

And I think Tom, in a way, it goes back, if we go back to our early days of blogging where you would say, I had to learn how to do this and I had to learn HTML and there’s this other stuff, and then you sort of become, it is probably not fair to call yourself a power user, but that you’re just used to doing things very hands-on and then the simplification comes in to make it easier for people. Then what happens is you either become like the grumpy old timer or that you kind of adapt to that. But I think that you start to lose a little bit of the control. So some of the things I expect to see now and I run into is that instead of having this ability to customize prompts, maybe you’re going to get buttons that say summarize and you’ll see some other things happening along those lines that just make it user-friendly for you, but eliminate what coders always used to say, if I could just go in and change these things, I could get what I want.

The one I’m noticing is that, I think I’ve said this on the podcast, but I like to think of this as conversational ai. So sometimes it just takes a bunch of iterations and attempts to get to the output that I want. And I noticed in some of the legal tools and elsewhere, I’m starting to see that it stops you after a fairly limited number of attempts and makes you start over. And that I think is problematic because sometimes it does take a number of tries and if you have a limit of five, you just might be starting to bring you to what you want and then you’re stopped and have to start over, which typically will mean a copy and paste and starting over. But that can be a little frustrating as well.

Tom Mighell:

Alright, we’ve got a lot more to talk about, but we’re going to take a quick break right now for a word from our sponsors

Dennis Kennedy:

And we are back. So Tom, some of this comes down to whether lawyers and many others frankly are willing to learn what they need to learn about these tools and put in the work they need to do to understand it. And as I sometimes have said, willing to spend the 20 bucks a month to use a powerful enough version. What are you seeing out there? What’s your feeling about some of that, the willingness to learn? Because it took you a while to get going on this, but now I can see the Tom Mighell who takes these things on and really learns them well.

Tom Mighell:

So when I first started thinking about this, I thought, how is Geneva AI different from any other technology and lawyers? We continue to whine all the time about how lawyers don’t take the time to learn technology. This seems like the technology that lawyers would never learn how to use correctly. But I think that the problem is, is that the barrier to entry for generative AI is not very high, at least initially, the barrier to generative AI to use it well and to get good benefit out of it and be able to use it to be productive as a lawyer in a law firm, probably very high. But the ability to just enter some simple questions and you get some pretty amazing answers just from simple questions. If you get good results from the simple stuff, why bother to learn how to do the rest of it?

I mean, if you feel like this is magic and all I have to do is ask these, why do I need to learn anymore about it? And I feel like that could be a common thought around lawyers and I’ll use the, we’ll come back to the same story, the lawyers who are using chat GPT to do legal research. And it’s because to me, if I was, I try to put myself in their mindset and thinking, why would they do that in the first place? And it’s maybe because it’s easy because they can just ask a question and say, here’s some cases, now tell me more about it. And they were taking the easy button way of drafting their briefs. And I worry that that’s the problem we have with lawyers is until they realize it’s not an easy button, you can only get so far by just asking very simple questions. And there’s so much more, I don’t see lawyers using it to the fullest extent that they should.

Dennis Kennedy:

Yeah, and I think that, so Ethan Malik, who we’ve talked about, who’s a Wharton business professor, has posted something recently that says when he speaks, he finds that less than 20% of the audience uses a GPT-4 level ai. I would say that when I speak to lawyers, it’s even less than that. And then he says that he also asks whether people have spent 10 hours working to learn the AI tools and that’s more like 5% say they’ve even done that, which is a trivial amount. So it takes work. We’re lawyers, we’re saying we have all this knowledge and stuff that other people don’t have, but it takes work to get there. This to me is similar. So I think that’s one thing that’s disappointing to me. And that’s why surprising to me is not surprising. I did predict this, but I see what’s going on in what I’ll call the adjacent professions.

And what I see is going on in other business areas and the ai, degenerative AI is being used more commonly and at much higher executive levels than you would expect to see in law law firms. I’m also hearing lawyers just saying, I’m hoping to avoid this. I’m worried about hallucination, so I don’t want to use it. My firm won’t let me do it. We’re changing our policies and nobody can use it. And they’re sort of saying, I don’t have to worry about that because we’re lawyers and we’re unique while all this other stuff is going on. So that’s a bit of pessimism, Tom. So I don’t know, what’s your most optimistic view these days since you’re the bullish person on the show of where we’re going with generative ai?

Tom Mighell:

Well, let me say, it sounds like where you’re going a little bit is that this is going to result in sort of a retrenchment from AI in the law. And I told you so and the people who were trying to avoid it will be very relieved that they made that decision. I’m going to continue my bullish attitude and I’m going to say I think that unless there is some really negative AI related event that occurs, I don’t see a retrenchment like you do. I see that progress will be ugly, that it will be fits and starts, that there’ll be two steps forward, one step back. But I really think that unless there is some kind of negative event that shakes the legal community, and I’m not talking about these case law research incidents, that doesn’t count. That’s just stupid lawyers doing stupid things. I don’t see that level of retrenchment.

So I would say that’s one of the thing that gives me optimism, which is lawyers will continue. I hope to get better at this, but it’s hard for me to answer this in a really bullish way because I struggle with my natural lawyers still don’t know how to apply styles in Word. Why are they going to learn about generative AI argument? So I am optimistic that many lawyers will learn how to properly use ai, that the big firms will create some innovative tools that can help their clients, I hope can also help and provide people without good access to justice. And I would say I am, maybe let’s not use the word optimistic, maybe let’s use the word hopeful. I am hopeful that education on how to use the tools becomes more accessible because how does anybody learn on it right now? I mean, you can go and find lots of classes that I get advertised for. How do we know what’s good and what’s not good? Should there be an AI class for lawyers other than the one that you’re teaching at Michigan State? Because there are only a limited number of people who could attend that. But it needs to be accessible, it needs to be easier to obtain, easier to use. And I would say that because I am hopeful, that gives me cause for optimism. Dennis, what about you? Let’s end this on a positive note.

Dennis Kennedy:

On a positive note, I believe in the law students, I mean my law students impress me all the time with what they’re doing. They see the implications of this, they understand this, they see what it can do. They’re willing to experiment with things and look at, I give them the framework of this is a personal assistant. We did a thing in class the other day where I have most basically three Ls in my class this semester. I said, let’s use Chad GPT and let’s do a sophisticated prompt that plans out how you study for theBar exam and gives you a whole plan and does it week by week. And you end with that. You’ve taken four practice exams and you’re 10% over the past number and you finish it 15 minutes before the time the deadline. And it put together this brilliant weekly plan that seemed doable to bring you to the outcome you wanted.

And we did variations on it depending on how people learn and stuff like that. And I found that a lot of people, and this goes back to our getting things done conversations, Tom, but a lot of people would say, I’m studying for theBar, so every day I have this thing on my to-do list that says Study for bar, right? And then you start to feel really overwhelmed. So this is generated this thing that says, okay, this week I’m focusing on this, I’m doing these things and I can work with it. And it’s sort of guiding me to what I need to do and the outcome that I want. And they see the benefit of that. The practical law AI stuff is to me just so amazing. And I know I’m supposed to end optimistically, but I’ll tell you something I saw recently, Tom. So I’m on this email list for a CC, and somebody said, and I’ll sort of change this a little bit to protect the innocent, but the very, very small law department need some help.

Were thought maybe practical law with the AI could help them, but it was so expensive it was going to be like six to $7,000 a year to do that for them. So that’s what they said. I don’t know whether that’s exact price. I’m like, wait, you’re totally overwhelmed. You would like to hire somebody, but you can’t. But you’re saying 7,000 bucks is too much and so you’re just going to struggle without that. What’s the thinking there? But I think that as people start to use this, starts to see what’s happening in the other professions. And then also start to say, look, a lot of the work that I do as a lawyer is things other than what I would call pure law. And AI can help in a lot of ways. And I go back to the Charlene Lee thing that as a book editor, developer coach consultant, she’s now 70% of what she would use an assistant.

She’s just going with Gen ai. And that is a mindblower. And that’s where I’m optimistic that I think certain lawyers will see the benefit on different things. They can do that using the AI will really help them both at the low end, the administrative side, the efficiency side, but completely new ways of looking at things. And in my class recently, the other, earlier this week, the students were simulating, they were on an innovation committee and coming up with an idea, a client faced something that would help the firm. And one of the groups came up with something, an AI mentor system where you could use the AI to ask questions that you might ask somebody who is a mentor could also potentially build out to matching people on mentorship. And that’s the type of use if you’re just thinking legal research, contract drafting, that sort of things, you’ll never get. And that’s where the power is. And I think that this new generation does see that, and I’m really, really excited about where they’re going. So that’s where my optimism is.

Tom Mighell:

Well, it will be interesting to see what happens. We will need to revisit this in a couple months and see how things are progressing. But we are way behind. We’re running way late. So we’ve got more to talk about. But before we get to our next segment, let’s take a quick break for a message from our sponsors. And now let’s get back to the Kennedy Mighell report. I’m Tom Mighell. And

Dennis Kennedy:

I’m Dennis Kennedy. We wanted to remind you to share the podcast with a friend or two that really helps us out in our new B segment. We are prompting Chad GT four in a sophisticated way to stand in for our audience and ask a question that our audience might want us to answer that would make us think and maybe push us a bit. So here’s a question from the chat GPT persona I’ve created as our audience, and it’s this, have you thought about doing a live show or an online ask us anything zoom session for members of your audience? And would you consider doing that? Tom, we have talked about that in the past. So what do you think Now,

Tom Mighell:

Dennis was this seriously a question that chat GPT asked? Seriously? I’m a hundred percent I’m really

Dennis Kennedy:

Good at prompting

Tom Mighell:

This sounds like a chat GPT that was fed. Everything that Dennis Kennedy wants to do is what it sounds like to me because how could it come up with, oh my God, I can’t believe it’s actually asking us something that we really wanted to do. So here’s my response. My response is, if I had to choose, I would probably rather do a live show than an ask us anything. Because a live show requires no commitment from the audience. I mean, we could ask for questions and people could ask if they wanted to, but an ask us anything requires questions. It requires people to show up. And I’ve got to be honest, I’m afraid of rejection. I would be afraid that no one would show up or that people would all show up nervously without having questions, but wanting to hear what other people asked. And nobody asked any questions. And I think that people would show up on a live show. So Dennis, if you are asking me which one of these here and now on Live podcast broadcast for our audience, I would say I prefer a live show to an ask us anything Dennis, what do you think? So

Dennis Kennedy:

I mean, the story of our podcast, right time is we’ve only ever done one show where we were both in the same place. There’s only been one of those

Tom Mighell:

Probably. I mean, it would be in Chicago, it’d be when we attended ABA tech show, right? So I dunno if we’ve done that more than once or not.

Dennis Kennedy:

And I don’t think we’ve ever done anything live in front of an audience,

Tom Mighell:

Correct?

Dennis Kennedy:

So either would be interesting. I sort of go with you. I like the Ask Us Anything approach because if you don’t know what’s happening, it’s kind of fun because you get to improvise a little bit. But then as Tom says, if you don’t know what’s coming and you don’t have questions, then there can be awkward pauses and stuff. So Tom, I think I lean with you about doing a live show. We just need to find a sponsor, I guess, who will bring us to a great resort that has a good place to record and an audience for us. It would be great. What’s the Spheres place in Las Vegas maybe might be a good one.

Tom Mighell:

Oh yeah, I would do it in the sphere. Oh heck yeah.

Dennis Kennedy:

So now it’s time for our parting shots, that one tip website or observation that you can use the second to podcast ends. Tom, take it away.

Tom Mighell:

Okay, fair warning to all of you. I am probably going to use parting shots in upcoming episodes around fitness and health and things like that. Things that are important to me at this moment. And I found this great little, I guess what is it? It’s not a tweet thread anymore. Is it an X thread? I don’t know what it is, but it’s a number of posts on X by a personal trainer. And he calls this, it doesn’t matter if you’re 25 or 75, do these 10 exercises for the rest of your life. And they’re all, for the most part body weight exercises, but they all focus on the things that you need to pay attention to as you are getting older. Balance stability, but strength in the right places. So get a hanging bar and hang from it to approve your grip strength. Lift your legs up for 30 to 60 seconds for balance purposes for the day. Make sure that your core is strong. It’s going to help you be more stable. These are simple, simple exercises to do, but they are designed to make sure that when your body is unable is going to be starting to break down and be less able to maintain balance or stability that you’re in a better position and you’re well positioned to do that. So I’ll put the link in the show notes. I am already doing a lot of these exercises, Dennis. Yeah,

Dennis Kennedy:

This is great. And then the AI angle on this is you can grab this information and they just have it do like a checklist and say, on this day you’re going to do these things and stuff like that. So to actually put the routines to give you some variety and other things like that. So yeah, I like that. So I mentioned Ethan Malik before, so he’s sort of the go-to person for me on a lot of really, really interesting uses of generative AI in education and in business as well. But his new book, which is called Co Intelligence Living and working with ai, I believe is, I have it on pre-order, but should already be out by the time you’re listening to this. So I’m going to recommend that even though I haven’t read it yet, I follow all the stuff he’s doing. And then just a really simple one is that being AI has been renamed copilot. And this isn’t surprising in a way, but it’s what it’s really good at is I am finding it as a replacement for the Built-in Microsoft help. So if I have something, a question about using one of the Microsoft Office products, I just go into bing copilot and ask the question. And it’s really good at giving me the answers and telling me exactly what to do.

Tom Mighell:

And 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 Networks page for our show. If you like what you hear, please subscribe to the podcast in iTunes on the Legal Talk Network site or in your favorite podcast app. If you’d like to get in touch with us, remember you can always reach out to us on LinkedIn or we do like to get questions on our voicemail for our B segment. Don’t force us to rely on chat GPT to ask us questions every week, every podcast, leave us a voicemail. That number is 7 2 0 4 4 1 6 8 2 0. 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. If you like what you heard today, please rate us an Apple Podcasts, and as always, a big thank you to the Legal Talk Network team for producing and distributing the podcast. We’ll see you next time for another episode of the Kennedy Mighell report on the Legal Talk demo.

Speaker 1:

Thanks for listening to the Kennedy Mighell report. Check out Dennis and Tom’s book, the Lawyer’s Guide to Collaboration Tools and Technologies, smart Ways to Work Together from ABA Books or Amazon. And join us every other week for another edition of the Kennedy Mighell report, only on the Legal Talk Network.

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