Episode 101: Smarter Decisions in the Age of AI with Cheryl Strauss Einhorn

Speaker A: Welcome everyone to Wise Talk. This is Maripos monthly podcast providing perspectives on leadership. And today we're excited to have Cheryl Stross Einhorn. She is actually at uh, the Cornell graduation. Right. She's just coming off of that and she's, she's joined us right on the throes of that. So I really appreciate you coming in and helping us start this series off about. I, we will continue, I should say continue the series because we've been really focusing on an A. So welcome, thank you for being here today.

Speaker B: Thank you. I'm so excited to be with you.

Speaker A: So let me tell you, tell everybody a little bit about you and then we'll into some of the questions. So Cheryl Strauss Einhorn is the founder and CEO of Decisive. It's a decision science company that trains leaders and teams in complex problem solving using the Area Method, which we will get into. And that's an evidence based system she developed over 22 decades as an award winning investigative journalist. She's written for the New York Times, Barron's and Harvard Business Review, among others. She's also a longtime educator at Cornell and Columbia Business School and isn't is the author of four books on decision making. Longtime Wise Talk listeners may remember Cheryl from her 2017 appearance when she joined us to discuss Problem Solved, a powerful system for making complex decisions with confidence and conviction. So she's back today to talk about her latest book, the Human Smarter Decisions in the Age of AI A practical framework for using AI to augment, not replace human judgment. So welcome back. Very excited to talk about AI and particularly about decision making. So it's obvious why this is important. But, but tell us a little bit about how you went from the first book, so that was nine years ago, to now this book. Tell us a little about that journey.

Speaker B: Yeah, so, uh, my background originally is in investigative journalism and it was because of the kind of stories that I wrote when I was writing for a publication called Barron's that writes about publicly traded companies that really got me started thinking about decision making, about our heuristics and the mental mistakes that we make. And that became the book that we talked about, Problem Solved. That introduced my Area Method, which is a system that's uniquely meant to control for encounter these mental mistakes so that we can expand our knowledge and improve our judgment. And then I've gone on to write three other books since then. And each book is basically things that I've learned after putting prior books out into the world. So this newest book, well, from Problem Solved, which focused on personal and Professional decision making. I then wrote a book, Investing in Financial Research, which was really focused on how do we take a system for decision making and apply it to business, financial and economic decisions. Specifically, what are the sort of the extra components when you are thinking about those kind of decisions. And then the third book is called Problem Solver, and it focuses on what I call problem solver profiles. It basically reveals that there are sort of five dominant ways that people make decisions. Each has beautiful strengths and each has some, um, individual cognitive biases that can impede clear thinking for the person. And each of those profiles optimizes for different things in their decisions. And that's often why we have friction with people, because we value different parts of the process and we think about things like speed differently, we think about including other people very differently, and so on. And so this fourth book about artificial intelligence basically said, okay, this tool is here to say, this is not a conversation about should we or shouldn't we? We're all using it in everything that we have from our dishwashers, so to speak, to the way that we watch television nowadays. And now we're really, uh, incorporating it actively into our workflows ever since ChatGPT first came out and was accessible to the public. So the question really became, if we're going to be turning to a tool that for the very first time asks us to share some of our cognitive load, what does it look like to protect our own thinking and to take this powerful tool that knows nothing about us and that doesn't care about consequences, actually work for humans who deeply care about the success of our decisions and who care about being able to solve problems that are not always about the best outcome, but are about an outcome that drive towards being aligned with our values.

Speaker A: Okay, sounds good. So I got a couple of like, just, like, just logistical questions that I think before we get into the models and such. The first one is how does one write a book these days and keep up and have it, have it relevant because things change so quickly? Uh, so, so how did you manage that?

Speaker B: Yeah, so that's a great question. What I thought about is the tool is going to keep changing and it's going to keep getting better. But the book really focuses on what is the human role.

Speaker A: Right.

Speaker B: How is it that we're going to lead the machine, and what are the cognitive skills and the critical thinking skills that we need to be able to identify something that we've never needed before? Right. A lot of the talk is, uh, you know, our brain is a muscle, is what I Like to say, and if we just turn over our decision decisions to AI, that muscle can atrophy. But the opposite of that is where I think we also are, which is that this is an invitation to know our own secret sauce for the very first time. Because we each make decisions in a way that works for us. Most of us consider ourselves good decision makers, but we don't actually know what it is that we are actually thinking about when we are solving a problem in terms of identifying the type of data that matters to us, how and where our human judgment intervenes along the steps of complex problem solving. And so what I decided to address is how to help people know more about their own thinking process and where to bring in their human judgment, no matter how the tool changes.

Speaker A: So the book has, no matter what it inputs, outputs. That's right.

Speaker B: And so the book has actually become only more relevant as people realize that what we need now is critical thinking skills more than anything else and human judgment without people necessarily knowing what that means and where that judgment needs to be inserted into AI usage.

Speaker A: So the other logistical question I want to ask that has again, before we get into the meat of this, is how do you use it? So let me, let me, let me say that, that I, I use it less about decision making. Like some people are literally saying, how am I? Like they're asking the, the robot, how am I feeling today? I swear, like that's, that's what we've gotten. The kids these days are using it as an operating system and use it as therapy. So, I mean, so that's a decision, clearly. But let's just assume that that's not happening that much. But there's so many different ways to use it in, uh, our personal life and in our professional life. So tell me a little bit about how you're using it.

Speaker B: Yeah, so first, at its core, I just want to mention it is a tool about decision making. It's a tool that you' to bring your problems to and it will help you solve them. So that's why I thought it would be relevant to actually talk about using it for decision making, because that's what the tool is meant to do. So I, I use it both personally and professionally in targeted ways. I think that it's a, uh, fun when I want to think of like a title for a social media post. I'm not a title writer. Or when I want to look for a specific citation or when I am looking to do research. Right. We all used to use Google. Even now Google has AI on top of it. But now it's more one stop shopping. Right. So you and, and I'm using it also doing things like a vacation planning, right? Totally. Both. Both planning for the vacation before I've gone on it. Having to help me map out a day to figure out do I need a bus in between locations. Also right. When it turns out to be King's Day in Holland and you didn't know and AI didn't tell you that the museums are closed and you need an alternative plan, you can also use it in the moment. So that's really sort of a variety of ways. I use it often before I'm going to talk to somebody new for the first time, give me a little background, show me the articles that they've written. But I've also used it for things like I want to have a career conversation with my daughter who's up for a promotion and um, you know, what types of questions is she going to get when she sits down in front of this level manager who's going to be assessing her at this level. So it can also help me prepare for meetings like that that are personal. Just the way that I would do that professionally when I'm meeting somebody.

Speaker A: Co. All right, this is great. So how has your model. So let's talk about your area model first and then talk about the before and after. Like you know, you developed that model way before ChatGPT was. Well, we were using it. So. So tell us how it's. It's. It's transformed essentially.

Speaker B: Yeah. So area is an acronym for the steps of the process. The first A is absolute up close from the target of your decision. The R is relative information. It puts that narrow information into the broader context because you can have a good solution on paper that may not work in the real world. So those contextual factors are really important. Then after those two mostly document based steps, you come to the ease of area exploration and exploitation. I call them the twin engines of creativity. Exploration is identifying good prospects, asking them great questions that will give you the difference between the map and the terrain. The documents say these things. This is what happens in the real world. And you talk to experienced people. Exploitation is a brand new step that I put in where we really check and challenge our biases. We think about do our assumptions have evidence? What's the diagnosticity of our evidence? And we look at a couple of creative exercises where you can examine the data through a variety of lenses and then that final A analysis of area puts the whole system back together and helps you come to conviction. So that is area in a nutshell. And what it really forces you to do is to step out of your own perspective to make sure you're including a variety of stakeholder perspectives. And it prevents you from relying on a favored type of data so that you have to look at a couple different types of data, contextual data, actual numerical data, people and opinions, and so on. And so in the new book, what I basically say is, okay, people think of it as one tool, AI, but it's actually got two different pathways of usage. And I gave them fun names. I, uh, called them the Surgeon and the Lamborghini Driver. Sometimes we want to make an incision at a very specific spot. We know the problem, we know exactly what it is that we don't know that we're looking for. And you can surgically use AI. Uh, the second way though, that we use AI is you have some big, messy problem. I'm ready to change careers, for example. And you know that you want to go through several problem solving steps. You're not just making an incision. You may not actually even know exactly what the problem definition is. You probably know your motivation. You don't necessarily know the research pathways, you're not quite sure who the stakeholders are going to be, et cetera. When that happens, I call it the Lamborghini driver, because you've got to give the directions. You're sitting behind the wheel of this super powerful tool, but you need to tell it where you want it to go as you navigate, and it can get you there quicker. And so within, especially that second modality area becomes very important. Because what I find is that even people who consider themselves very successful decision makers often have an expectation about the problem that they're solving and they don't stop to define it. Or maybe they haven't communicated to AI their motivation, in which case AI can give you information, but it's solving the problem based on how other people have solved it and what's popular in its algorithm. It can give you so much information that you can have analysis paralysis and so on. And so I talk in the book about how do you drive through the eight problem solving steps. You may not want to go through eight, but this gives you the opportunity to actually see what does it mean to use AI, uh, start to finish for problem definition, motivation, context, research, analysis, biases, stakeholders, and coming to conviction.

Speaker A: Okay, so let's get, let's talk, let's talk about an example. Let's, let's, let's go through something that's

Speaker B: relevant to business so I'll give you an example. I was working with a CEO of uh, an, of a multinational ecotourism company. She had 10 people reporting to her. Her organization had grown very quickly and she came to me thinking that she wanted to hire a chief of staff. And I said okay, let's, let's do the problem solving on this. And we started with the A of area, uh, right. You know, do you actually know exactly what a chief of staff is? Because she had, and most of us do probably have a picture in our mind of what it is. So we looked at, you know, what is the actual job definition, what are the roles and responsibilities. And right off the bat she was able to check and challenge some of the unfounded expectations she had. This wasn't somebody who just communicates what the CEO wants. This is somebody who actually is a senior decision maker sitting at the table who is cross functional decision making authority. So right off the bat that's somebody different than she, than she thought of. And AI was very useful in sort of identifying and getting these definitions. And then in the next step in relative information, she was able to see that this role and its responsibilities look very different at different places, which made her realize that she hadn't really necessarily thought about what specifically do I want this person to do besides help me to reduce the number of people that actually report to me. And then in X exploration I think that AI becomes very interesting because you can have IT role play and help you with stakeholder perspectives. And so she was able to have some very honest conversations with people on her team, with people in human resources, with people who held chief of staff roles and with other leaders who had a chief of staff. And she realized again, an expensive hire, senior level, somebody who she would need to substantially delegate to. This was not going to just be somebody who she was actually going to communicate to and somebody who her own reports thought could actually slow down decision making and actually really impede the process of the work that needed to be done. And so in exploitation, as she was actually analyzing these things, what she realized is she actually doesn't want a chief of staff at all. She took a problem that she thought was external and she realized it was actually an internal job. And so in that final step of the process and thinking about what could she be doing where she could make the changes, we were able to sort of think about several different ways that she could reorganize her schedule, that she could give more decision making authority to the people on her team who she knew were ready for it and keep Some of the younger team members who reported to her as she could help them grow. And, um, therefore she ended up with one problem she thought she was solving. And by using the system and using AI, actually coming to a totally different conclusion that was actually going to be the right conclusion specifically for her. Interesting.

Speaker A: Chief of staffs are interesting because they're. There's lots of different ways to use them. Some people use them as their, like, de facto coo, you know?

Speaker B: Yeah.

Speaker A: So she sounds like it didn't. That wasn't what she wanted. Did she end up hiring anybody else? Playing the other kind of role?

Speaker B: So in. In that, uh, she. She actually. She actually held off on it. She did interview some people, and, you know, what she realized was this. This really didn't fit easily with.

Speaker A: Interesting. Okay. All right. Okay. So let's. Let's talk about, uh, how AI can both affect cognitive offloading. And I guess they're calling it surrendering now. It's a new word, cognitive surrendering, so that your critical thinking does get atrophied. Okay. And so let's talk about that. But also, it could go the other way. I mean, it also could, I think, accelerate because you're getting so much more information that you, if you have good critical thinking skills, that actually could help you. So that's what I find. It's like, it's. It's like magic. Uh, to me, it's like magic. It's like I don't have to think through things in the same way because I can, like, get the result faster and then apply it faster. That's. That, to me, it's like magic.

Speaker B: And where and how are you using it?

Speaker A: I. I'm similar to you. I mean, my favorite thing is, like, I was just in Tokyo. It's like, okay, so I want to go see flowers, and I'm busy in this museum and this area, and I want to go to lunch. Claude, give me a schedule. I mean, it would have taken me two hours to figure that out on my own. Yeah, it took him or her Claudette two minutes.

Speaker B: Yeah.

Speaker A: Yes. That's. I mean, that's just. That's just my personal. But professionally, I, like, for 360s, for example, I'll do them myself, but I also have the backup of Claude to do it as well. So the themes and things. So that saves me time. So I'm doing it probably half the time. Uh, that's one way I'm using it. I will prompt it to look at sales, how to, you know, how to infiltrate some sales situations and. And um, so it helps me think through things that, that I think I want it to be. I want to help me be more creative, like, more than about productivity. Because, I mean, we don't. We're not. I don't have a, you know, a big, huge company here. Like, I'm not having to go through lots of things. And Allison, who works with me, she. She uses it a lot as well. Of course we use it a lot when it comes to writing in terms of editing. So all of our, all of our LinkedIn posts and things are all edited. So that saves a ton of time. Right. But I think that, but that to me is sort of like this basic table stakes. Everybody, you should. There's no question that everybody should be using it for reediting. That's not even a question. So that's easy. But, but I think that jumping off of creating new things is what I'm, I'm most interested in. And, and that's why I asked the question. It's like, how do we, how do we use it as a jumping off rather than. And then. And. But not offloading it so much that we're like letting it do all the work. So. But where's that?

Speaker B: So I think what happens when people surrender is they're not turning to themselves first. Right. The way to really protect your thinking is to always ask yourself first, why am I using the tool? What's my purpose? Right. And what's the goal that I have? Because the machines are about patterns, they're not about purpose. So that is one of the best ways to make sure that you're not surrendering or shifting some of that cognitive load. When I see people who are not thinking first and just using the tool, I think that's a problem. And then it's not only using it first. You are saving time using the tool. It's fetching you something. Right? That's fetching, um, some information. Right. And then the question is, is, so what would you get? Now you have something to react to because you've brought your thinking forward first. You've then used the tool in the middle. And then afterwards, I really like the idea that you can struggle with it. You can say, why'd you give me that answer? What would the biggest critic of this say? Give me the disconfirming data and you can really use it to strength test what you found so that you're not using it for confirmation bias. It's going to tell you, you're brilliant, you're beautiful. And so the way to protect yourself is to Use it both is to bring forward and rely on yourself first and after. Let's say it gives you something and it seems like it is a skill level above you, you can say to it, how did you get to that? Can you teach me the, the, the process that you are your. Now you're learning with it. I think that's really interesting. I think that's great as well.

Speaker A: I think that's great.

Speaker B: So what you don't want to be doing is going to the tool automatically and then just taking the answer because it's your credibility on the line. It takes so long to build a reputation and you can lose it instantly. Trust is a very precious thing. And so that is what I think is you uh, know if you take away nothing else, make sure you turn to yourself first and then make sure that you turn to yourself and examine and struggle with what the output is after as well.

Speaker A: So I think that that's, I think that's a great way of thinking about it. And I think, I mean I, I do certainly a version of that and I think a lot of other people do a version of that. The thing I'm concerned about are people and especially younger people who are using it as their operating system and they're basically asking it before they're thinking. So I'm wondering especially as an educator and I have a 20 year old so. And he's totally anti AI, so he's not even looking. He's on. There's so many uh, all these, all these graduation speakers are getting booed by all these people. These kids are just really like anti AI and it's mostly for environmental reasons I realize, but, but I'm wondering about where they're going to learn the critical thinking skills because when we learned critical thinking skills it was, you know, I. Liberal arts degree. So you know we're in there like struggling with, with the first uh, you know, the original content. Right. And we're writing papers and we're like getting critiqued and, and we're debating and I mean Claude's not going to debate you. It could, I mean you could say this, you can ask for just confirming data. You can also, you know, pit Claude against ChatGPT and see if they come up with the same answer or not. And they probably will come with similar answers frankly. So how are kids these days and how are people not offloading and um, continuing to learn. Starting and continuing to learn its critical thinking skills?

Speaker B: Yeah, I think I just finished a course this spring semester at University of Miami in the business school on AI using my new book, the Human Edge. And you know, the whole course was about that topic. How do you turn to yourself first? What does that mean to bring your human judgment forward? How do you identify the problem that you're solving? How do you identify what you care about and what your motivation is? How do you share with the tool what's in your context so that it knows the factors that actually are gonna make or break the success of a decision? So I think we need to be teaching these foundational decision making skills both with the tool and without it at universities. And I think some of the best way to use the tool as we were just talking about is not only having it wrestle with you, but, you know, but, but asking it when you are not sure how to do something. I don't want you to give me the answer. I want you to act like a college professor who knows how to teach to first year students in this topic and teach me how to, how to draw. Where do I start? Or you know, teach me what, whatever the, whatever the topic is. And it's endlessly patient. And I do think the fact that, that there doesn't have to be publicly raising my hand and saying, I don't know, that we can sit in the privacy of our home and with our laptop, I do think that that will be liberating for some people, for introverts, knowing that, yeah, that they can have, you know, this world class teacher as long as they know that the machine hallucinates and that they have to check the answers. So I think we have an obligation in the schools in terms of making sure that we do things without the tool. I think we need to teach people to use the tool to bring forward their human judgment and to recognize that human beings are not perfect and we're not looking for perfection. Most people to really form relationships. What they need is authenticity. And what I kept telling my students who wanted to use the tool to make polished papers that they can turn in is I need to see you in your writing. I need to see that you've addressed the learning outcomes that we're driving towards. I need to see nuance and depth. AI does not actually naturally have those things. And so if you're using the tool well, it's because you are bringing those things to the tool.

Speaker A: Right.

Speaker B: And you are evaluating what you're getting back.

Speaker A: Are you cool with having the kids edit using it?

Speaker B: Uh, you know, I think for college that's not, that's not the purpose. Right. Because I wasn't teaching a writing class and What I wanted to see was their actual thinking. And if I suspected their AI use, I discussed it with them. I don't see you in this. This has the hallmarks of AI. The terms in it are generic and so on. So while it can edit, I think

Speaker A: while I mean copy, edit, really not, not edit, not like, I mean copy literally.

Speaker B: I think, look, I think the copy editing is interesting because it really favors certain types of grammatical corrections. And, and so people know that you. Right. People know that you've used it. And if you're okay with that, because you know what part of the thinking is yours, no problem, no problem. But for, but for other people, you know, you actually, the, the writing is an expression of themselves, not just in the content.

Speaker A: I, I have a friend who I play trivia with, who's a Stanford professor and Young. Young, right. She's like, I don't think she's, she's already been a journalist once and, and she's, she's now an African studies professor and she's brilliant. And uh, she doesn't give papers. And because I said to her, like, how are you dealing with AI? Like what? I get papers. I go, what do you mean you're a history professor? Yeah, like I have them go interview people. I have them, you know, do video. I do, I have them do everything but papers. I'm like, that's freaking cool.

Speaker B: So, yeah, go ahead. Yeah, I was going to say in my class, that's exactly. We did videos, we had them do interviews, but we also had them actually use the system that's in the Human Edge book for their final project, for a decision of consequence, a high stakes decision in their own life. And they had to be able, we gave them the rubric. They had to be able to demonstrate how they thought first, what kind of output they got from AI, how they worked with AI in an iterative, um, conversation, and then how that impacted their own thinking. And they had to show that all the way through. And it was just so interesting to see it can be done. And they found this hugely impactful for something that they truly cared about. What city to live in? Am I going to have roommates? Which job to take? How am I going to save money when I'm out of school? What type of long term plans should I be mapping into the present that I also want to be planning for? You know, these are big decisions of consequence.

Speaker A: A little off topic, but I'm curious because you're in it. I mean, how are you seeing how AI is going to affect 18m year olds and their parents wanting to send them to schools that cost 90,000.

Speaker B: Yeah, I've thought about this. You know, I think that, I think there's a lot more access to, you know, online education and cheaper alternatives. And some people may choose to go out into the workforce and use their AI for some of their upskilling and that will be right for some people. Universities are wrestling now with how to incorporate the tool, where to incorporate it. Do professors each get to choose how implemented? M. But you know, uh, there's a lot of reasons though why you go to college because you're looking to meet the world on a camera.

Speaker A: Right.

Speaker B: I certainly know that it changed me. So. But it's not just that also, you know, it can completely change the trajectory of what you think you're going to be doing as well. So if you're using AI as your education, you're probably also looking for something specific and that may be narrower, but it may also be much more, much more effective. And cost is a huge component of um, the problem of higher education and therefore access and equity.

Speaker A: Yeah, totally. And I mean I went to bars just teaching in two liberal art schools. I mean it's, it's so, uh, that cost is, I, I just can't believe how much it costs. So I, I think that it's, I think liberal art. I don't think the Ivies have to worry too much, but I think these little liberal art schools are going to have to really figure out what's their value, like what are they bringing to the table.

Speaker B: Yeah, you know, well, we've seen almost 150 of them close.

Speaker A: Oh really?

Speaker B: Right. I mean the, the, yeah, the cost of education and, and probably the fact that there's other ways, there's other ways to go about it.

Speaker A: Uh, interesting talk with me about taste. So I, I talk a little, I talk a lot about taste in terms of decision making and creativity. And, and that, that I said to a friend of mine who happens to be a designer, graphic designer turned strategist, I said, you know, you're going to be okay in this, in this new world because you are creative and the creators are going to win. And so I say that somewhat flippantly, but not really. I mean I really think that the large language models are going to spit out the same thing. In fact, they're running, I was reading something about they're running out of data to actually analyze. We're getting to the point where there's just, yeah, there's, it has a word for that. I can't think of it. And if you go to three AI, uh, three chatgpts or three gen AIs are going to probably give you similar outputs. So it's up to us to have the taste and the discernment and the judgment and the critical thinking, all those things. But taste is a little bit different because it assumes that there's some creativity, there's some design. How do you think about that and how does that play into making decisions?

Speaker B: I think what you're getting at when you say taste is that you know different people think differently and want different things from their decision. Right. And so when you're coming to the tool and this tool knows nothing about you and it doesn't care about consequences, you've got to share what you care about, what that taste is. I'm, you know, I'm actually not solving this problem to make the most money. I actually want to be in business with this person because I want to invest in a long term relationship that I think is foundationally good for my business. Right. And AI might tell you that it's a bad deal to get into because it doesn't look like it's going to make money right away. But AI doesn't really understand about the value of time to individuals in any way, shape or form that we often are not just solving for the moment, that we often have a long term game plan that matters to us. And so you've got to bring that discernment, that judgment that unique you ness to your AI use because otherwise it's not going to be as helpful. It's just going to give you somebody else's answer that can look very logical but that may not feel satisfying for you. When you say to AI that you are looking for a new job, it doesn't know if you're doing it for personal growth, to do something that feels more meaningful or if it is to make more money or if you're and right and you want a more stable schedule. All of those things you have to input it. Calling tapes, what I call judge.

Speaker A: Yes, those are, that's part of it for sure. And I think that uh, there's been a lot of talk right now on LinkedIn and you know, whatever, Reddit, all of them. This is just like, okay, so especially because the business we're in, it's like it's, it's about subjectivity and, and taste and decision making and judgment and emotional intelligence and all that because the robot and I look at all the aisle robot is, is gonna do all the hard cognitive work. So it's then in terms of just like getting the data, the input, output, but we have to be able to put our, you know, our taste, our decision, uh, what we care about, as you're saying. And I think that that's similar, what we care about in taste or similar on it to it. And, but I'm concerned with people being able to know what that even is like. I don't know if we have the skills of empathy, of critical thinking. Uh, and so I think while people are trying to learn AI skills, which they should, and get more fluency, they all, they also need to be learning empathy skills and taste and critical thinking. So how do we, how do we do that?

Speaker B: Yeah, well, AI is never going to sit across from a human being and be able to have the relationship that you have with them. Right. You know, it's not necessarily even if it learns how to read body language. Right. Uh, I mean we get so much, right? We get, right, we get, we get so much from the relationships that we have because at its core, right, what we're, what we're all looking for is connection. And there are going to be times where even though we have AI in our pocket, where we're not using it and we need to be able to connect with somebody else to have a conversation. And so while the tool is going to be an important and integral part of many things we do, it's not going to be the only thing that we do. We're still going to be the ones living our lives. And the argument that my book makes is you've got to stay the chief decider in your own life. You know what your hopes and dreams are and you know what really matters to you. And you can use the tool to help you to strengthen some of your decisions, but ultimately you need to live with them. And so it's going to be the world that you, that you choose to live in. Right.

Speaker A: I think, I think for those of us who have gone through the world of, uh, learning as knowledge workers, learning to be critical and debate things like that, I think that that's going to be fine. And also who value connection. But when Harvard Business Review or whoever, whatever it was, some, something Harvard study comes out and says these are the top uses for ChatGPT. Well, uh, Gen AI and the number one top use is therapy slash companionship. You're like, whoa, okay, let's peel this back a bit. So I agree with you that we aren't going to, we shouldn't use chatgpt Gen AI as the end all be all. But people are so there. So there's. So the question I asked you about taste and critical thinking is one thing, but then they're also using it for connection. And so you'd hope. And I've been writing about this since day one, about, like, technology is effing up our connecting with other people. I mean, you just look at anything, you know, the Internet, the social media, you know, mobile devices, looking at our phones all the time. Like, you're walking down the street pumping, your people are bumping into you because they're looking at their phones. Okay, you're going to dinner and you see all these people on their phones. I mean, I mean, so this is just a much more accelerated version of it, but it's a little different in that it's more people. Like, it's the most people like that we've come to in terms of the. This. The robot can be more people. Like.

Speaker B: Yeah.

Speaker A: And I don't, I mean, I don't. I don't think it is, but I think some people do think it is, so that's a concern.

Speaker B: So I spoke at a, uh, at a psychology and technology conference a couple months ago at University of Virginia's Darden Business School, and there were several presentations about how teenage and young men in particular were finding real companionship with AI about topics they. They didn't feel comfortable talking to other people about. Right. And there's a positive and a negative to that. I would also say for much older people, uh, my parents are in their mid-80s. My mother can't move around. Well, you know, having. Having, you know, something like this, that sounds warmer than talking to Google. Kind of nice sometimes, right? Yeah, right. At the, at this. And I think there are not. There are also some good uses around having AI help you think about stakeholders. I was mentioning before, you know, when you're preparing for a conversation with somebody, if you want to investigate perspectives that are beyond your own, that are harder to. And you have AI role play. But I don't think that that denigrates or takes away at all how important it is to then be able to close the machine and to go talk with your daughter or your coworker or your colleague. And so I think if we can think about using AI to help us have an easier time as human beings, that's a very nice way to do it. And all of these nefarious uses where AI has run Vogue, Rogue, and there's now all these lawsuits about how it's helped people do things that harm themselves that all that all has to get itself worked out. And I think we as parents and as, you know, people who have friendships and relationships that we care about, it'd be really nice if we also help look out for each other.

Speaker A: Yeah, we had two role models. I have a 20. I don't know how old your kids are, but I have a 20 year old. And it's, it's, you know, these. All the kids that are in college went through high school and Covid. And Covid did a number on folks. So we have got this sort of double whammy of co. Well, triple Covid social media and now AI that is just like briefly pushed down. I mean, you know, adolescence. The show, I mean, is a perfect example of, you know, what social media can do in terms of negative. And you know, that kid. Do you see the show when I talk about the one on Netflix?

Speaker B: No.

Speaker A: Well, if you.

Speaker B: It's.

Speaker A: It's a really important show. It's in terms of like, you know, being bullied on social media. And this poor kid, I mean, played, you know, he won the Emmy and it was amazing. But that could be any kid. Like, it wasn't right. It's not like this. Is this like a screwed up kid. You know, uh, he, you know, he killed another kid and. And uh, it was portrayed like he was crazy and, and maybe he was, but ultimately that kid was pushed and that could have happened to almost anybody, especially males. And then I know that Scott Galloway's talked a lot about this and I think that in his new book and I think it's a real concern and of course we're off the subject here a little bit, but it's all kind of related how we're using the tools and not using the tools. So this has been lovely. Thank you so much for coming on our show again. And I really appreciate the conversation and, um, just appreciate that you're willing to talk about really all the edges of AI because it's not just about decision making. There's a lot of other things that, that it touches. So, um, again, the book is the Human Smarter Decisions in the Age of AI Cheryl Strauss Einhorn. And just want to put another plug in for the book and for anything that Cheryl does because she clearly has thought a lot about this and is a deep thinker and I think that, uh, I've learned a lot, so I appreciate it very much.

Speaker B: Thank you so much for having me

Speaker A: and have a great rest of your day. I think I said Cornell, you're probably at Columbia today, right? Teachers College.

Speaker B: Yeah.

Speaker A: Okay. Well, wishing you well for the rest of your day.

Speaker B: Thank you. You, too.

Speaker A: See you later, Cheryl. Bye.