You Teach The Machines

Kay Koplovitz

MJ interviews Kay Koplovitz, Forbes Top 250 Innovator, CEO of the first satellite cable network, venture investor, and founder of nonprofit Springboard Enterprises. Springboard accelerates women-led startups, over 950 to date creating $76 billion in value! Kay: Overcoming challenges together has a lasting positive effect on our value. How we value ourselves. And I'm not talking about dollars. (0:21) [Intro music plays: "Where, oh where are you tonight? Why did you leave me unread on my phone? I searched the world over and thought I found true love. You met an AI and poof, you was gone."] MJ: To our listeners who can't see, we were all bobbing our heads and dancing to the music. It's a great way to get in the mood a little bit. But I'll go ahead and introduce our guest today. Kay Koplovitz, who is a businesswoman, entrepreneur, and author who has spent her career looking to the future. She was the first woman to head a television network when she founded USA Network in 1977. And she was a visionary, helping sports television reach cable by negotiating contracts for the MLB, NBA, NHL, among others. She launched the Sci-Fi Channel, chaired the bipartisan National Women's Business Council, and used her platform to launch Springboard Enterprises, which is a global network of entrepreneurs, investors, and advisors accelerating the success of women entrepreneurs in technology and life sciences. She's a champion for female entrepreneurs and an inspiration to young women everywhere, and an inspiration to me. Kay Koplovitz, thank you so much for joining us today. Kay: Oh, what a great pleasure to be joining you for your podcast today. I'm really looking forward to our discussion. MJ: Yeah! Well, so you've spent your career sort of looking to the future, innovating. I know that you started the Sci-Fi Channel partly because you thought that it was what we were all headed towards, right? And now we're kind of at the forefront of that sci-fi reality. Kay: Hal is beckoning at our door right now. People here listening know who Hal is from 2001: A Space Odyssey. Kay: He's still around. MJ: Yeah, I think that a lot of our listeners are friends of mine and people my age. And I know that when you were in school, you did your Master's thesis on satellite programming and how it could sort of impact the social order by spreading information. And AI is kind of another way that we are spreading information. I wondered if we could just start there with your experience working in media for so long. How you think that the spread of information is changing now, and for people my age, what feels different now than it did when you were an expert in your field with cable? What feels the same? Is this a familiar beast, or is this a whole new ball game? Kay: Well, technology always changes everything. I've been present for the change at various times. Way back, I wrote a Master's thesis in 1968 on satellite technology and how it could change communications around the globe. It was something that we didn't have access to. And for people that are listening, historically, we were in a Cold War with Russia and China. We didn't know what was behind the Berlin Wall or the Great Wall of China. Today, both of them—one's gone completely, the other one, the Great Wall of China, is a tourist attraction today—but we didn't know what was there. And I thought geosynchronous orbiting satellites, high-altitude satellites, only needed three to communicate all around the earth. It was a real breakthrough in technology and potentially a big breakthrough in people's ability to communicate with one another. So you have to start there with the satellites and what they did to change communication around the globe. So things advanced, computers came along for personal use, the internet sprung up, people started communicating through the internet. And eventually, we launched cable networks, USA Network in my case, Sci-Fi. And Sci-Fi, I was not a kid who read sci-fi comic books and things like that. But I grew up in the age of Sputnik, President Kennedy challenging us to put a man on the moon. You have to have vision. Students today, if you want to innovate and be an entrepreneur, for example, you need to have a core position that you really, truly believe in and want to really reach for if there is no solution yet. And one way to learn about that is to actually jump in and work for a company that's a young startup company. You can learn a lot of things working for big corporations, but you won't learn those skills because they're not the same skills. And I always say to students, if you really want to learn, "Well, am I really an entrepreneur? Can I really do this?", the best way to do it is to start at a very young company and see how it operates and see what the challenges are and learn from those experiences. When you're young, it's the time to do it. It's the time to try different things. You are free to try. And today it's free to access. When I started out, the television market was pretty closed. Cable television, people were like, "What's that? Why do we need more than three networks?" They challenged everything that we wanted to do. And I said, "Well, there's a lot more out here." And to me, it was opening up the global communication sphere. And that was using high-altitude satellites to communicate around the world, to communicate with people directly on phone services and things like this around the world. So it's gone back to also low-orbiting satellites. You can launch thousands of them; there are millions of them out there. And so we all know, for example, in the war-torn country of Ukraine, their communication is basically by Starlink and their field operations. But furthermore, for people with just communicating with each other, the streaming that has overlapped what the cable networks did, now the cable networks are being disrupted by the streaming networks. And so communication has become literally among billions of people around the world. When we started off, it took a few years to get to like a million people, and then get to ten million people, and then get to twenty and thirty, fifty... it took time. Today, you can instantly have the opportunity to communicate with billions of people around the world. Now, what does that mean? It's hard to communicate with a billion people at a time, you know? MJ: Right. Kay: But also as a young person, your point about getting into entrepreneurship now, this being one of the best times to start, we have access to everybody across the globe and all of their information. It's easier than ever to just get your feet wet, right? Kay: It's easier than ever, you're absolutely right, but the challenge is to gather your own community. Because there's so much competition out there. There's so much opportunity out there. And people say to me, "Oh, you know, the consolidation of the broadcast networks," which is happening. The consolidation of the cable networks, which has been happening for the last couple decades and now really more so. Those are consolidating and coming together. The big challenge is not "can you get in?" You can get in. Anyone can get in with a cell phone or a desktop or a laptop or anything, an iPad, whatever you have. But who are you going to reach? Are you going to reach your own community? And that's really where a lot of influencer marketing has come into play with a lot of celebrity stars from Hollywood, television stars, and people say there's not enough creativity. There are so many companies that have launched on TikTok, that have launched on, certainly, YouTube. There are many, many different opportunities. What is your goal? What is your business plan? How are you going to support this? This is, and advertising revenue, of course, has supported Meta, Facebook, and how are you going to create a business? First of all, establish yourself. What is your position? Is it clear? Can you attract your community? And then how do you want to monetize that community? Is it a freemium model? Is it free at first and then we'll charge you? I think we're all familiar with that. Or is it just advertising-supported like FAST channels that are available through like Roku and all the manufacturers of sets of all kinds and computers of all kinds have advertising revenue? It's very hard in the vast community of billions of people to find your niche. But if you do have a strong following on your niche, you can create businesses that way. It's not a matter of access, it's a matter of performance in the end. MJ: Right. Jeff: Performance. A couple of things that stuck out to me from what you said, Kay. One: the phrase "gather your community." Kay: Let me give you an example. I'm a whitewater rafter. And the people who are in whitewater rafting who are the guides that I've been on Class V trips with, they show up in different parts of the world. It's just this community of these nutcases who love to go whitewater rafting. We just loved it. I mean, it was just so exciting. And then we'd go to South America, we'd go to Chile, and the next time we'd go over, we'd be in South Africa and the same guy—"Oh, hey! It's so good to see you again!" MJ: A community that you found of rafters! Kay: That's sort of fun. And then you can say to them, "Hey, have you done this river and what should I expect of it?" Give you an example of something that's a small community that people are integrated together in and respond to each other quite quickly. Jeff: You know, if you have access through all these different channels—streaming services like Twitch—if you have access, that is an incredible opportunity in that there's no barrier anymore. But without a community, you don't have a voice, right? And a quote stuck with me from a student of mine: "Get over yourself and start the conversation you want to have." Because another point you made in a couple different ways was you have to have a strong point of view and direction. And having the conversation that you want to have is crucial when there's every opportunity to make more generic noise, content, whatever. But you're not going to gather a community without that point of view. Kay: Yes, that is true. One of the things I would say—and I'm concerned about students today and trying to make choices among chaos—I have always believed that there is enormous opportunity in chaos. When everything is static, it's very hard to get in. There's so much chaos right now that the other opposite side is true: there's just so much chaos, where do I plant my flag? How do I...? People know when you're authentic and when you're not. The thing that I worry about is I think social media is dividing us. I think social media started off to connect people, connect families, "share my videos" and this and that... all these sorts of lofty ideas which were wonderful. But today, a lot of the business models are based on hostility. More: the more people are angry and shouting from different sides at each other drives up the use, the attendance, the participation. And I worry about how that aspect of it—that business plan, and let's be honest, the business plans of Meta and Google and companies like YouTube and companies like that—to some degree or lesser, they depend on that high friction. And nothing has to be true. It's what you say is true. It may have nothing to do with truth. People can project a lot of lies and just make up things and try to get people to believe them. And I think that's really destroying our soul being in a lot of ways, and having people against each other, and then even family members against each other. I don't think that's a good thing. And I'd like to go back to the idea that individual communities should be the challengers or the people who have the mission of that community and have their judgment as to what is the proper communication that they should be having. And if they don't, they'll kick them out. And we had companies like that years ago, but today it's... I think students know what is authentic, but they drift into things, too. It's easy to be pulled into things by a friend or somebody that you know or somebody that you met and go down a path that is not... Jeff: Or by an algorithm that's tuned to deliver dopamine to you. MJ: Yeah. We're not just an AI podcast; we talk a lot about the influence of technology and social media. And because you have been in media since before social media, you sort of talked about how we went from like one or two cable news networks and now we have this influx of information across the board through social media and how it kind of divides us because fear sells, right? You get more engagement if it's more extreme, and maybe the companies that are giving us access to social media are less concerned about the integrity of the information and more about engagement. I wonder, are there any pros when it comes to media specifically, going from like one or two cable news networks to everything at your fingertips? I wonder if you've seen differences or if you think that there's any benefit to that. Kay: I always think it's beneficial to hear different points of view. I don't think it's productive to have just groupthink. Whether you agree with "that's your groupthink" or somebody else's groupthink, I always listen to people that have different points of view than I have because I always learn something from them. I don't have to necessarily agree with them, but I learn something from them about why they think the way they do. So sometimes they change my mind because I say, "Now, that's an interesting thought. They have a point there; maybe I should think a little bit more about that." So, I think it's a benefit to have access. What I'm thinking about when I think about Artificial Intelligence and AGI: I think it would be great to be able to use technology to qualify for ourselves—as individuals—qualify what we're reading and understanding through these different social media platforms, people, individuals. And it's kind of interesting because when you do research—and I use it for research just to look at things that bring things to my attention that I may not know exist because there are so many sources of information out there—I think it would just be great for us as individuals, or people in our group, to be able to get instantaneous analysis of what are facts or not facts that are listed here with what people are saying. I think that's the next best step that we can make because I don't think we can really depend on regulation, like national, state regulation of any kind, self-regulation. Look, we had self-regulation in the cable industry for a long time. You know, and some of it was good and some of it wasn't. And I think this is true today too, but I think we have the ability to at least instantly today check the viability or the truth of what are these stats, what is this information that we're... Here we are, we're talking to each other. Now, if we want to go and find out, well, is Kay Koplovitz telling us the truth or not? You could find out like that, you know? "No, she's just telling a story." So I think there are ways that we're starting to understand, if we're interested people and not just there to, let's say, spread our—whatever we want—the message that we want, true or not true or whatever it is. This would be a great way to use the different platforms of technology that are coming into the core right now for us to be able to double-check ourselves. We don't have to have an outside source. We do have outside sources now checking on the veracity of a lot of statements that are being made, let's say by politicians. Sure, there's a lot of that going on out there, but wouldn't it be great if just we as individuals could get the same just fact-check like that and say to ourselves, "Oh, I really thought I was believing this person, but actually what they've just said is not true. Here are the facts." Wouldn't that be sort of cool? That then each of us could have that responsibility. Some people are trying to deceive you. There's all kinds of people like that out there. MJ: It's almost like both the problem and the solution is the fact that we have access to all of the information, right? It just takes a little bit more... Kay: It's overload! Our brains can't consume it all at one time. MJ: But it takes some more personal responsibility, right? To care about whether or not the facts you're consuming are true. Kay: Now, on the other hand, someone can use it for evil. They can use the same technology to, let's say, bring in people who they're spinning a yarn to and get them to believe it. MJ: It's a double-edged sword. Kay: Because they've said it so many times and people start becoming believers, and we do see that a lot today, let's say our political environment, we do see that. Jeff: I wonder if you think that—I'm sure you've had it, the experience of catching a bot, whether it be Google's or Claude—catching a bot in an inaccuracy is actually a good thing because it teaches you to be skeptical, to ask follow-up questions, those sorts of things. Kay: I don't know if I've really had the... I don't think about it as catching a bot. They make mistakes too. We make mistakes. Like I use it for research. It could be a contract. I could say, "I want analysis of the contract if I've forgotten something or need something out of my head." And boom, you get an answer. Well, okay, well that's... I better check that out. At least I find it very, very good. Jeff: So I think we all can feel that there's a lot of chaos swirling around us right now. And Kay, you brought up that chaos can be an opportunity. MJ, your perspective is that there's a lot of chaos right now, but in that, there is opportunity. Just coming back to that point you made, Kay, about for young people, a great way to learn a lot quickly is to work in a small company, a startup, a growth company, maybe not. How does that relate to this concept of there being opportunity in chaos? MJ: I think that my entire generation feels like anything we do post-grad is kind of taking advantage of a chaotic moment, and that can feel pretty crippling. I think that there's a lot of uncertainty about what the workforce looks like moving forward, how different technologies impact the way that we experience the world, the way that we contribute to the world. But I also think that if you can get over the lead in your stomach from that crazy uncertainty about what even the makeup of the workforce looks like, there is a lot of opportunity to be the people that are coming up with ideas of what it could look like—envisioning that future. And that means that even if you're in an entry-level role right now, you have to be inventing what an entry-level employee does now because AI can sort of automate the basics of that role. So we have to be a lot more proactive about proving our value early. As scary as it is and as much as it feels like it's setting us back, I really think that it's something that's going to push my generation forward because we have to much younger decide what our point of view is, decide what we want to say, decide how we can demonstrate our value to people that might employ us. Because generating sort of mediocre content is something that AI can do now, right? They can summarize an email and make a PowerPoint. And so something that I've grappled with as I'm looking at the beginning of my career is: what do I care about? What can I do that is interesting? What are the questions that I can ask? And also I think it's sort of a lot of my life experience, including the pandemic and then AI, has sort of forced me to reckon with the fact that humans and human connection is something that is so important to me and something that is how the world is going to move forward, right? Post-pandemic, I was so grateful to be able to be in person with the people I love. And I think that that gratitude is getting even bigger as I realize that interpersonal connection and human-first companies are the future because AI kind of automates all of the tech babble. And it comes down to who are you? How do you connect with the people around you in a meaningful way that only humans can do? And what do you have to offer, and what are the questions you want to ask, and how are you going to solve those questions? Those are my thoughts. Kay: Yeah, well, I think you're hitting on something that's extremely important, and that is relationships—human, face-to-face relationships. And if someone your age is to say to themselves, "Well, I want to go into the art world and I want to deal with art," then maybe they want to go work for an art company. Maybe they want to work for Sotheby's or maybe they want to work for an art studio. Even technology is changing how people access that, but being able to be there in the environment with the people that you admire and want to learn from is extremely important. That's why I think, in many ways, return to the office is beneficial. I think it's been harder for people starting out only on screens looking at each other. You've got a connection to the people, but it's not the same as having that really personal relationship and understanding the other person. And so you go into a company—let's say you're not really thinking about being an entrepreneur, you want to go into a company—even if that's a bank, you want to go into banking or something like that. I mean, it's hard to establish those key people that you want to follow when you never get to see them personally. You don't get to sit around a room and have a cup of coffee with them. You're just a face on a screen. And I think that there's a good thing about being able to communicate with people around the world in all kinds of different media that we have available to us today, but I think you're focusing on something that's really, really important to the future of humanity. And that is personal, personal relationships with people. There's nothing that can substitute sitting around the table or working in an environment where you can go down the hall or around the various cubicles that people are in and talk to someone. MJ: Yeah. Kay: To bring it back to a startup, I think that there's something valuable about the foundation of a small company that is mission-driven and you're working in the chaos and it becomes so much about how each individual person in that company contributes to the mission, what they can bring to the table in terms of problem-solving. Specifically in life sciences and tech startups where maybe you're trying to solve a healthcare issue. It's about the people that you're trying to help. There's a human-centric mission. And when you're in a small company, every person's voice matters, everybody is all hands on deck, and you have to bring value to the table in terms of your ability to jump in and work with each other. Your experience working with small companies, with startups—how do you feel it kind of ties into the human connection piece? But the chaos, and it actually is an opportunity maybe for individuals to really shine and showcase their talents and figure out what they care about. What are your thoughts on that? Kay: Yeah, well Springboard Enterprises, which is the non-profit accelerator that was launched 26 years ago now, the mission was to find women in science and technology who are starting companies and connect them with potential investors and advisors that they needed. It's a perfect example of mission-driven entrepreneurship because it didn't exist. People said, "Oh, you know, women don't do that kind of thing." And I said, "Oh yeah? I think they do." And they said, "We never hear from the venture capitalists; no one ever comes to pitch us, no women ever." They didn't know each other. So we had to go out and find the original companies that we brought in. And we were stunned when there was no internet for us; we didn't have an internet connection, we didn't have a website or anything like that. Six of us went out and just sent out to groups that business organizations, colleges we went to, we just tried. And to our surprise, 300—over 300 applications showed up on paper. Whoa, what are we going to do with this? And we were very fortunate to have Stanford and Berkeley MBA students help us sift through them all and we came up with 26 companies. We said, "These companies can grow big, we think." We're going to have to see what we can do with them and help them establish. So that's how we established our first initiative in bringing women to the marketplace. And when we actually had a Demo Day in January of 2000, some 300-some people came to listen to them. And they were like, "Where did you find these companies?" You know, we found them by going out to look for them. We didn't just sit in a room and wait for them to show up. And I think this is like a mission-driven thing now because these women over time have raised over $14 billion, have created over $76 billion in value for their investors, 28 IPOs, 240 M&A events... I mean, they are really kicking ass out there. And I really, I'm very proud of the work. And talk about something that's mission-driven, this is a community of people who are there to see them succeed. Not punish them, not interrogate them, but to give them tough love. I mean, tell them the real truth about what they're doing and how they have to change and what they can do to help them through the gates. And this is a community, what you're talking about in many ways. Mission-driven community make a difference. MJ: A community that you found, yeah! Jeff: I'll reflect: MJ and I were fortunate enough to attend the 25th anniversary gala for Springboard Enterprises last October. We got to see Kay there in her element, in her community. And I will say that afterward MJ said something to me that was really important. She said, "Dad, I've never been in a room with 250 women and I didn't hear anybody say 'I'm sorry.'" Because every woman in that room, every person in that room, had a strong point of view, was probably looking for chaos to take advantage of. MJ: Yeah, I think that what I meant by that—that's "sorry" is kind of a running thing in our family where my dad noticed that my sister and I apologize constantly for things that we have nothing to be sorry for. And I think that it's sort of an ingrained female thing to be a little sheepish. And so when we were younger, he would always say, "Take your sorry back. What do you have to apologize for?" And I think that I used that as an example because I was in a room full of women who held eye contact, had something to say. There was none of the sort of socially ingrained spatial apology where women feel the need to make themselves small, right? These are all women who have voices, are confident, who know what they want to say, and when you have conversations with them, they are unapologetic in taking up that space. And it was honestly one of the most incredible professional experiences I've had. It's the beginning of my career, so it's a short list, but I've never been in a room full of women who were all so inspirational. And it was a really profound experience for me. So thank you for that. Kay: Well, I'm glad it was a good experience for you and there are legions of us. And I was at the Femmys Awards this week here in New York, all women in Fintech. Men and women in Fintech supporting women in Fintech. And Fintech is chaotic. There are massive changes in the financial market going on, whether you think it's crypto or you think it's blockchain or you think it's stablecoin... I mean, all this stuff that's going on in finance. This is the time for people to really come out in front, you know? Because it's very chaotic and it's also very exciting. And you know what? Entrepreneurship is exciting and frightening at the same time, which is probably why it attracted me, because it's... it's frightening. But it's also exciting. And some days you get up and the problems are so heavy, you're just saying, "How am I going to get through this day? Or how am I going to pay my employees?" And then you say to yourself, "I can do it. I can get this done. How am I going to get it done?" And then I go, "Okay, I'm going to do this first, then I'm going to do that, and I'm going to get it done." And that's how people, you know, you move forward one foot at a time. Jeff: You do it together. My experience in startups was one where—you think about a startup as maybe the stereotypical male startup of the "sainted soul," you know, Steve Jobs or whoever. Zuckerberg. But my experience in startups is that it is way, way more of a collective endeavor. And startups by their very nature are going to be smaller than enormous multinationals, and so you can be more collective. There are fewer layers of middle management and command and control because it's a smaller group of people so you don't need those things in order to be productive. And when you wake up and you don't know how you're going to make payroll, it's much more likely that you're going to have a conversation with somebody in person across the way who might offer a perspective that gets the whole organization to a solution a lot faster. And that kind of shared sharing in the experience of overcoming adversity is a critical element of being human and of humanity in the sort of best and most positive sense. I clearly have an agenda here which is to encourage any of our younger listeners to consider working in a small company. Kay: You're absolutely right. It's a small group of people, you've got a mission, you've got a business that you're trying to get into the marketplace, and you come to the table and each person—it might be three people, it might be five people—but you're there together. And overcoming challenges together has a lasting positive effect on our value. How we are as people. In fact today, I have another of my group from USA Network. We've been out of USA for 26 years, 27 years maybe. We are still together. Every other month, we get in a different locations. Some of us are in New York, some are in LA, some are in other places that they are, in Europe or whatever. We still get together because we had that amazing experience of building something from an idea to a powerhouse together and we had to bridge a lot of challenges. And there isn't anything that can substitute it, really, in a lot of ways. And it's not about money. It's about our value together and what we did together. And I think to me that's one of the most exciting things. Now sometimes people get that from being in larger corporations and people, but if you join a bigger company, it often depends on who's leader of the team that you're on and what is their success. It may have nothing to do with you in terms of success or failure because if that person falls out of place, all of a sudden you're lost. Your team has to go over to this team and then this team may not want you on their team and people navigate their way successfully to the top of corporations. I'm not saying they don't, but it's a different experience than being an entrepreneur. Jeff: I'm going to plug two books today. Yours in just a moment, but also Julie Wainwright wrote a book called Time to Get Real about her experience building The RealReal. And she's got a great section—I actually taught it in my class in January—she's got a great section on that corporate environment and how it works, and she's being sort of empirical and objective, and how you're going to have a different experience there than you are in a smaller company where you do have more of a natural environment for pulling together. Can I read you a couple of quotes from your book? It's called Bold Women, Big Ideas. You may not have the whole book memorized after 25 years because you published this in '01 or '02. Kay: Remind me what I said! Jeff: I read it over January into February. I found it to be incredibly relevant to today's moment because you were chronicling the peak of the dot-com capital craze, the peak of the dot-com facilitated rapid change in business and society because of new technologies, not just internet but also biotech as well. And a lot of the dynamics that you describe are what we're experiencing today with the latest emergence of a new disruptive technology that we're all having to adapt to. Bear with me, but I'm going to ask you a question at the end of a few quotes. So, the first is not a quote of yours, it's from a mentor of yours, Reuben Mark, who was CEO of Colgate. And he said to you, "Kay, it isn't enough for you to be a role model as CEO. Just because you're the CEO doesn't necessarily get others to realize that women minorities are worthy of it. You've got to be proactive. You've got to inspire others to think and act the way you do. If you really believe in helping others, that's your obligation." Take that as the backdrop to start. Then you say, "There's something seductive for me in traveling into the unknown. The journey itself thrills me and I don't think I'd ever feel altogether happy if I didn't know there was risk involved. Surely the risk of the unknown that takes me down Class V whitewater rivers and to the top of peaks, and it's not so different in the business world." And then you say, "The simple truth is that once I get a big potent idea, it moves me to distraction. I feel compelled to try to move others with me. At the risk of repeating myself, I'm very motivated by the power of ideas." One of the ways that you inspire me is that you have built a career both in service to a community and in the business and material success of that community and of your own. So you didn't sort of go off sit in the nonprofit world at a key juncture in your career and you didn't go off and just slay dragons as an investor at that key moment in your career. You've found a way to balance both service and success in the business world. And you've done that for 25 years and that room at the Springboard gala was full of just a small number of the people who've been inspired and empowered by this duality. My question is: how does that continue to sustain you? And a two-part question: how does that continue to sustain you, and what's the big idea that you're most—that you're locked in on right now? I could imagine there is one. Kay: Let me go back to Reuben Marks for a moment. Because what Reuben was saying to me is it's not enough for you to be the leader of the change of what a leader looks like. At that point in time, studios had bought in. One of them was Universal and Paramount, the other was Time Inc. And Sid Sheinberg, the head of the president of Universal, every time I walked into his office to see him if I was in LA and stopped by to see him, he'd say, "Here comes the CEO. You don't look like a CEO," he'd say to me every time. And I said, "Get used to it, baby. This is what a CEO looks like." So we would get—we had this little thing that we'd do all the time, you know? But I was trying to say to him, "I don't have to look like you." Reuben Mark said to me something else that was important. He said if you really believe in diversity as a key element of your success in your business, then you have to motivate people internally and you have to adjust their bonuses to actually perform and have diversity in... So the head of sales and the head of distribution and the head of advertising and the head of the... within a corporation, part of their bonus had to focus on the fact that you wanted to have diversity within the company. You wanted to have different—I didn't want everybody in my legal department to be Jewish. I didn't want everybody in my sales department to be Italian. I didn't want everybody in my... it was sort of a little bit like that. And I said, "You know what? Reuben's right. I've got to do that." I had to change the motivation for people within my own company even though I was a leader of them all. That sort of thing I thought was really kind of important for people to understand. Why do I, after 25 years of, you know—when I started the whole thing was Springboard, it wasn't like I had this idea that I was going to do this for the rest of my life. I just wanted to get it off the launch pad. But then the dot-com bust. And I knew that women felt they were going to get shoved out and I said, "I can't leave them out here. We're not leaving them, we're going to go on." And we went on, we went on to Washington D.C. that year, we went on to Boston that year in the year 2000, and we made it very clear: we're going on. You're going with us. I didn't want them to feel that they were being abandoned because everybody was being pushed out, but it felt very bad for women who had just started to get in. Actually out of that first year, we had five IPOs eventually. So it was, you know, they were companies that were actually well on their way when we found them. So I think that what motivates me is learning. I am a constant aggressive learner. And these people teach me every single day. It's like I am going to university every single day. They know more than I do. I'm pretty good at some things, but they—people in biotech, I was in biology as a minor, I liked operating on my rat. I would carry my rat around in my... and the history of science was my favorite course in college, in my undergraduate for... I didn't know that was going to be my favorite course! I just love learning things. And I think some of the biggest wins going forward from today are going to be in biological sciences, in the administration of our healthcare in this country and around the world, that people are going to have better access to their own—it's going to be much more individual. I believe very strongly that people, once the individual understands what their condition is, they will make choices based on cost and outcome. And this is—you're seeing this already. When you saw a year and a half ago actually now, when Eli Lilly took their GPL-1 treatment direct to consumer. Well they were trying to stem actually Ro and Hims & Hers and other people that were generic producers of it, but that has now becoming a more viable way for people to access those types of drugs for diabetes and weight loss. You're going to see more movement into the market. And in this country, in the United States, we need improvement. Our healthcare system is very difficult to navigate. Most people don't have a concierge. Many people still don't have a viable healthcare plan. And currently many are being pushed out. You say "what are you excited about?" There are so many things. I'm still in space; I've still got stuff going on in space. But if you ask me what I think is going to be the best improvement for us going forward in the next several years, I would look in this space. There is so much that has to be improved, should be improved, and we can improve. And we can take better care of ourselves knowing more about ourselves individually because we have the tools to be able to measure ourselves today in a variety of different ways. I'm very excited about that. And I learn from the entrepreneurs every single day the pathway. So you ask me what's exciting to me? That's exciting. Jeff: Balancing service and success through a love of learning for the 25 years that you've been an investor and have, you know, been whether you planned it or not, you know, been one of the many amazing people but one of the key person driving Springboard. And I'm with you on the health thing. It's a really exciting time. And talk about chaos, I don't think we've seen anything yet in the most positive sense when it comes to individual health. Kay: Well Jeff, you know a lot more about it than I do, you know, so I'm going to learn from you as well. And MJ is going to teach me what the younger people are, because you know, we all live in our time. So we have to adjust to our time, whatever that is. And I have a lot of—as I said—grandnieces and nephews who are the same age you are, and you know, I watch how they're making decisions about what they're going to do. I have a PhD in chemistry, on the other hand I've got a welder. And he actually creates bronze artwork. And welders aren't going away. MJ: Yeah! Well Kay, thank you so much for joining us today. It was a really incredible discussion. You are such an inspiration. Thank you for taking the time to give some advice to the people my generation. Hopefully we can seize the moment and embrace the chaos and follow your advice. Kay: Thank you very much for inviting me in. Thank you so much, it's been a pleasure! I'll keep learning from you. Jeff: Thank you, Kay. Take care! Kay: Okay, bye-bye. MJ: Bye-bye. (28:22) [Outro music plays: "Ones and zeros, vectors and scalars. What do you see in that machine? I gave you my heart, my warmth and Snapchat. You chose a robot, now I'm alone."] Jeff: You Teach the Machines is hosted and produced by me, Jeff Pennington, and co-hosted by my daughter, MJ. Please take a minute to review and subscribe to You Teach the Machines wherever fine podcasts are downloaded. Copyright 2026. Any and all use of the audio recording of You Teach the Machines for training or other contribution to artificial intelligence models or their application is expressly forbidden without the permission of the creator. And we'd love to give you permission, so long as you come on the show!

18 mrt 2026 - 43 min

Audiobook: Chapter 5 Make AI Work For You

CHAPTER 5: Make AI Work for You (Not the Other Way Around) If you're a student or recent graduate, you're almost certain to be a regular user of AI. Believe it or not, you're among the only existing group of experts at using modern AI. If you're further along in your life and work, you're less likely to deliberately use AI. It's a tool you may use here and there for a specific task. You may do some experimenting, but it's most likely not yet a no-brainer, go-to resource. Students, I'm jealous of you. Everyone else, I get it. I write this in my early fifties. Artificial intelligence is the first technological change in my lifetime to challenge my ability to adapt. When the personal computer became accessible, my parents were in their thirties and got one right away. I learned to use it at home after elementary school. I learned to type and use spreadsheets on a computer in my public middle school. When dial-up services came on the scene, I connected my PC to the first internet communities and chatted online in high school in the eighties and college in the early nineties. A few years after Tim Berners-Lee invented the World Wide Web in 1989, my friend Sam showed me a primitive website with pictures of ancient caves published by someone far away from our college. A few years after that, I worked at Ask Jeeves, an early web search company. When the cell phone became ubiquitous in the late nineties, I texted my friends last minute social plans, to the amazement of my parents' generation. When the smartphone came out in the mid-2000s, I started using one without thinking twice. But AI makes me feel the calcification of age. It's the first widespread technology in my lifetime that I just don't want to deal with. I'm fortunate to be an insider. It's my job to help my organization understand and use AI. I see so much potential to positively impact the world I live in and the world my grandchildren will live in. But it's really hard. Contrast my situation with that of my daughter who is experiencing the start of AI in the same way I experienced the dawn of the World Wide Web. ChatGPT arrived during her freshman year of college. Her brain and expectations were what neurologists call plastic—still moldable. She started using AI because she didn't know any different. It's been amazing to see how rapidly her methods of accomplishing her schoolwork have evolved. My daughter is responding to AI under a new evolutionary pressure. We're used to thinking of evolution resulting from something "bad" happening. A comet striking the earth. Climate change. A new virus. Artificial intelligence is not that, though it may sometimes seem so. Artificial intelligence is like the printed book. The invention of moveable type was an evolutionary pressure that accelerated and widened the exit of civilization from the Middle Ages. Europe's Middle Ages were not romantic knights and princesses. Picture population decline, feudal subjugation of peasants, plague, famine and wars. One war lasted so long, it was called the Hundred Years' War. It was so bad, that some historians referred to the whole mess as the Dark Ages. Europe got out of this civilizational decline because of printed books. More and more knowledge was captured in books. More and more people learned to read. People could contribute, could create value beyond their back-breaking manual labor, fighting ability, or birth. A kid who learned to read could grow up to do anything. People living in Europe through historical periods following the Middle Ages came to value book-enabled knowledge and education for pulling them out of their grandparents' and great-grandparents' desperate times, when the graves from the plague were still fresh. Books and education were so revolutionary in terms of human well-being, people in Europe and elsewhere established public libraries and schools to further share and democratize knowledge. Let's jump into the future and rewrite that last passage: "More and more knowledge was captured in AI. More and more people learned to use AI. People could contribute, could create value beyond their mind-numbing office labor, their access to expensive higher education, their network of rich friends. A kid who learned to use AI could grow up to do anything. People living through historical periods following the chaos and stagnation of postmodernity came to value AI-enabled knowledge and education for pulling them out of their parents' and grandparents' desperate times, when graves from the pandemics were still fresh. AI was so revolutionary in terms of human well-being, people established public large language models." I see AI as having the same potential to improve our fragile world as the book did hundreds of years ago. Enough to quit my job and write this book. Enough to creakily learn to use AI so I can respond to its evolutionary pressure just as my ancestors did with books. And it's both as simple and complex as that. Use AI. The more we use AI in a thoughtful, informed way to improve the quality of our work and our lives, the better the long-term outcome for us as individuals and for our society. Like it or not, AI is an inevitable and inextricable part of our lives, just like all the revolutionary technological changes that came before: the printing press, the household telephone, the pocket camera, the personal computer, the World Wide Web, the smartphone, and social media—all of which became extraordinarily beneficial when put to creative use by billions of humans. All of which have their own side effects and pitfalls. In every case, recognition of the costs, benefits, and creative use of the technology by people like you steered (or is steering) these industries to better human outcomes through user (consumer)-driven change. The same can happen with AI. Where to start? Augment Your Life Start by answering three questions: What are you good at? What do you want to be better at? What do you need to do but takes an unsustainable amount of time or effort? If this feels like therapy, or is maybe a bit uncomfortable, you're not alone. Another word for augmentation is "self-improvement" or "self-help." It can be challenging to take a critical look at your life and how you live it and then try to make changes. It's even weirder to do that and then consider getting help from "artificial intelligence." But doing so can help you succeed, lead, and remain engaged in the modern era. Let's take myself as an example. I'm good at coming up with creative ideas. I want to be better at doing my laundry regularly. I need to keep my email inbox clean, but it takes too much time. We turn the tables on technology when we approach it with the goal of living a more satisfying life. My ultimate goal isn't to "use AI" any more than it is to "use a smartphone." My goal (and yours) should be to get more out of my natural efforts and abilities, enhance creativity, and pursue new and different projects that I might not be able to tackle on my own. How can AI be a means to this end? I'll go first. I started a completely unrelated podcast as a creative outlet about a year before writing this book. While I was writing, my daughter and I started another podcast to share stories of living with AI, also called "You Teach The Machines." We figured that since this is all so new, lots of people are going to have new and different experiences with AI and it would be helpful for others to hear about them. A fun podcast needs music, so we made a theme song with a music generation AI. I wrote the lyrics and set a few other parameters, and in about an hour we were able to dress up our human discussion with machine-generated music. My creative contributions were the lyrics I wrote and the direction I gave the AI. Artificial intelligence helped me make more of my ideas by generating a catchy tune, along with vocals. It has turned out to be a hit with the college students we interview! Now, do I value this music as much as the original music I paid my friend Jay Nash to write, perform, and record for my other podcast? No. My collaboration with Jay led to a live performance on stage together and ongoing creative human collaboration. Did I create a fun little musical addition that enhances our AI podcast more than generic stock music? Yes! It's always fun to learn in areas where you're already familiar, so if you're new to AI, music is a great place to start. Everyone is familiar with washing dirty clothes. We have to do it; we don't want to do it. I want to be better doing my laundry regularly. My clothes build up on both the dirty and clean side of the washing machine cycle. My hamper is always full of two to three loads, which creates an artificial mental block in and of itself. I feel great when I manage to run it all, fold it, and reflect confidently on a two-week supply of clean underwear. But that's not happening regularly. So what's a way that AI could help? (Besides a laundry robot—we're not there yet, and, tbh, the waiter robots I saw in a dim sum restaurant in Chicago were both creepy and entertaining, but I can't imagine having one in my house.) We'll start with the ground rule that the machine isn't going to do my laundry for me. A simple use of AI to improve my laundry habits is to use tools for behavior or habit change. I asked both my smart speaker and the digital assistant on my phone to set weekly reminders to start a load of laundry on Thursday evening, switch to the dryer Friday morning, and prompt me to fold on Friday evening. You may already be doing something similar in your life. Guess what? It worked! Gentle reminders are a good start, but what if I had less laundry in the first place? I enlisted AI to reduce the amount of laundry I have by finding clothing that doesn't require as frequent washing. Retailers have been working on AI-enabled wardrobe recommendations since the dawn of e-commerce. In fact, a social media algorithm recently profiled me as an "outfit repeater" as it served me an ad for odor- and stain-resistant pants. Long ago, in a dot com boom far away, I worked as a software engineer at Ask Jeeves, an early attempt at AI-enabled web search. We didn't call Jeeves "AI" at the time; that term was out of vogue, redolent of mid-century science fiction. Instead, we called Jeeves "Natural Language Understanding," the marketing term for natural language processing, which we defined in Chapter 1. We built a wardrobe recommendation search engine so Jeeves could pick out a Gap or Nike outfit like a proper digital butler. Fast forward twenty-five years and I can try using any number of free AI-enabled personal clothing assistants "who" will set me up with an entire wardrobe of outfits I can "repeat." In fact, I did just that while writing this book! There are a bunch of clothing recommendation apps available on your smartphone. Turns out that using X resulted in Y. What don't I have time for but need to get done? This one is straightforward and probably something you're already benefitting from anyway. Go into your email account and look for your spam or junk folder. Open it and witness the result of teaching a machine to do beneficial work. We discussed this in a previous chapter, but it's worth revisiting. Spam email is a fact of life. Artificial intelligence controls spam. You couldn't pay me enough to filter spam out of my inbox. I'm very grateful for the AI that does it for me. Now It's Your Turn Start by answering these three questions for yourself: * What am I good at? * What do I want to do better at? * What do I have to do but life gets in the way? Try not to overthink it; just write down whatever comes to mind for each. Now go through the exercise of looking for ways to augment your life using AI for each question. If you get stuck, it may well be that there isn't a ready answer—yet! If that's the case, consider what you would want from an AI tool and be on the lookout. If you find an option that seems helpful, remember to always evaluate the AI using what you've learned in the previous chapters. You are an informed user and consumer of AI, and you are capable of making a decision to use or not depending on your own viewpoint. It's important to step back and focus on your humanity now that you've considered AI in your life. The most important thing you can do is recognize what makes you uniquely human. You don't want to be a machine. You'll never compete successfully with a machine. So don't try, and instead focus on your human abilities. That's the point of a wonderful book called Futureproof: 9 Rules for Humans in the Age of Automation, by Kevin Roose. Here's an example. My friend Jean is an architect with a thriving independent practice. Another architect I know, David, is getting out of the business after seeing his income erode. David is incredibly technically proficient. His eye for design, proportion, and ability to model is top notch, but he's not so great with people. Jean is an excellent designer, but maybe not as good as David. What Jean has is empathy, patience, and an understanding of how to help her clients navigate the rocky emotional and financial experience of designing and building something as personal as a home. Jean brings her humanity to bear on her business. She has what some call emotional intelligence, and importantly, the ability to use it in her work. David, not so much. David and Jean are already subject to the pressures of automation. AI-enabled architecture design software is becoming ubiquitous. I'm not worried about Jean in the coming years, but David is smart to seek alternatives. Augmentation shouldn't be about becoming a cyborg. Futureproof is a great read because it illustrates that if you just use machines to hustle harder, work faster, you'll eventually be replaced by a robot. Augmentation should be about helping yourself be more human, doing more of the things humans can do. Cyborgs and Terminators are creepy because they are machines pretending to be humans. When we use AI to try to make ourselves more machine-like, we're creepy too. Use AI to be more human, not the other way around. Reading Futureproof can help you understand your uniquely human qualities in a world of increasing automation. It's an important book because it can help you develop a defensive strategy for the change AI is bringing. Help you differentiate yourself by strengthening your best human qualities. In this book, I strive to present an optimistic offensive strategy. I hope to help you build on the message of Futureproof and use AI so you can make informed choices, influence how AI develops, have more fun, and have an even greater impact on the world around you. Using AI for Personal Safety My mutt dog, Lilo, is a perfect example of specialized, superhuman intelligence in action. She lies dormant on the couch or bed until her sensors detect something of concern. It could be footsteps on the driveway, the scent of a fox approaching our duck coop, or the sleepwalking of one of my children. I will never surpass her ability to hear, smell, or intuit. I will never beat her vigilant cognitive processing that detects and responds to concerns at all hours, day and night. Even while in a deep sleep, upside down, looking ridiculous, she will lift a head, cock an ear, sniff the air to gather more information. She growls a warning above a certain threshold. When a threat is confirmed, she loses her mind, barking and scratching at the door to defend her humans from possible harm. If I were allergic to dogs, I would want a machine or alarm system that could do all of this for me. Safety concerns present humans with one of the greatest opportunities to benefit from AI. A machine can be taught to be ever vigilant and to detect possible harm before we can. Machines can learn from our environment what is "normal" and what may be something to worry about. A machine can learn that the mail is delivered every afternoon. Which, apparently, my dogs can't do because they attempt to murder our mailman, Bill, every day at two-thirty in the afternoon, even though he leaves them dog biscuits. Safety-critical situations are a great place to take advantage of AI. You're building layers of redundancy by adding a machine into your life to keep you safer. In my own life, I have seen major safety benefits from the AI in my car. Imagine Lilo perched on the dash of my car. She stares intently through the windshield, never blinking. I put the car in reverse to back out of the driveway and she runs to the back of the car, furiously scanning through one hundred and eighty degrees for any hazard. She barks at the sight of a pedestrian walking into the path of the car, out of my line of sight but visible to Lilo's well-trained eyes. I brake and the pedestrian strolls safely by (hopefully without a dog of their own so I don't end up with the two knuckleheads barking uncontrollably in the car). The good news is you don't have to train a dog to be your safe-driving assistant. Most new cars now include AI systems that do even more to keep you safe on the road. As we discussed in chapters 1 and 2, these systems are trained to recognize a bunch of hazards through cameras, radar, and driver inputs to the steering wheel. Some even watch your eyes and can detect when you're getting sleepy. Every time you drive a car with one of these systems, you're putting the machine through continuing education. The car records and uploads data about the safety system to the manufacturer to help improve the AI (and probably sell your data to Starbucks so they can decide where to put a new store, but let's focus on the positives). Driving safety is a very positive outcome from all of us collectively teaching machines. I know I'm a safer driver in my reasonably priced 2024 Subaru that came standard with Advanced Driver Assistance Systems (ADAS). My ADAS has prevented at least two collisions where I absolutely would have rear-ended another driver. In both cases, it detected a car coming to a sudden stop in front of me and slammed on the brakes just before I did. The machine saved me from an expensive inconvenience at best, and from hurting another driver and myself at worst. When our teenage drivers go on long trips, this is the car they take. My wife's and my criterion for a kid's car used to be the cheapest car with air bags and a top crash safety rating. Now, when we can afford it, we help them replace their old beaters with cars running AI safety systems. Never going back! This safety feature also helps my dad drive safely at night now that he's lost vision in one of his eyes. When he got his first car with an AI safety system, his stress levels dropped from knowing that everyone would be safer when he had to drive my mom to the hospital or come home from a concert after dark. I am a car enthusiast and truly enjoy the raw driving experience. I own and drive three classic vehicles (1982 Jeep CJ5, 1982 GMC C6000, 1995 Toyota Tacoma) that don't even have airbags, much less sensors and AI safety systems. Warning beeps and robots making decisions for me seemed like an intrusion into a meditative escape. That can be true, but the value of these systems is so clear, I now do ninety-nine percent of my driving in a 2024 Subaru with the help of AI. AI can really, truly improve our safety, the safety of our loved ones, and the well-being of people with whom we share the road. Be a Smarter Patient The potential for AI to help us be healthy, or at least less unhealthy, is remarkable. If AI captures human knowledge and makes it accessible at scale, then the knowledge of clinicians could have a great impact through its careful use. The health industry is an enormous, nearly $20 trillion-with-a-T sector of the American economy. Venture capitalists are already investing in AI startups and directly in the sector and are certain to invest more with that much money at stake. The typical economics of health mean that investment follows the money, as has been the case in the pharmaceutical and medical device industries. In my work, the earliest adoption of AI is in hospital financial operations—billing, collection of unpaid bills, and pre-approval and increased approval of insurance claims. These are all worthwhile efforts to gain incremental efficiency in the complex financial enterprise of a large hospital. After financial operations, AI is being used to sustain or increase the margin of already (relatively) high-margin treatment and diagnostic care. In both cases, investment follows returns. But there is so much more potential. So how is a patient to profit from AI? First, try to avoid being a patient. Health screening is an excellent area for the use of AI. At a minimum, when it's time for your colonoscopy, you can look for a gastroenterologist who also uses GI Genius or another computerized adenoma detection tool. Ask them how it has affected their adenoma detection rate. It's a good sign if they have a concrete answer. For other types of screening, get a sense of the growing number of health AI systems approved by the Food and Drug Administration (FDA), listed on their website (https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices [https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices] at the time of publication). More than one thousand had been approved at the time this book was written. Ask your doctor, nurse, or hospital administrator what they're doing to evaluate and adopt AI systems that improve the care they provide. You may be surprised at their answer. Ask them how they are paying for the system so you can evaluate how their incentives align with your own health needs. Ask them how they have ensured the AI will perform fairly for all patients. Ask them how they are checking the performance of AI over time to make sure it continues to perform. Cornucopia What follows is a collection of real stories from people just like you who have tried using AI. Consider these stories encouragement to try AI for the same use, or for a different but related use. Ask yourself what aspects of the story could translate to your own life or work. Get in the habit of asking people you know how they are using AI. You may be surprised at their creative problem solving. Awesome Editor Ann, the developmental editor of this book, used AI for the first time to edit the Introduction. She started by editing the raw draft manually, using her laptop and Microsoft Word. This gave her a version she was happy with as the product of her decades of expertise. She then went back to the raw draft and fed it into an AI service, asking the AI to edit it for clarity and enhance it for content. We then sat down together and compared the two results, one entirely manual by a human expert, one done by an AI. We found that Ann made edits the AI did not that were important to me, the author. She had acquired a sense of my "voice" through our multiple meetings to develop an outline and her subsequent reading and editing of my draft. Her editing helped bring my voice out and make it stronger in the written words of the Introduction. Watch a singer with their vocal coach and you'll see the coach help the singer find more expressive, impactful vocalizations of the sounds they are creating. That's what Ann does for me. In comparison, the AI is like the auto-tuner used by recording studios and pop musicians to polish and make vocals appealing. You hear about "heavy" versus "light" use of the auto-tuner. The Introduction we got back from the AI was like the auto-tuner turned up to eleven. Technically, my words and ideas, so very polished, but no longer… me. The AI-edited Introduction appears in the Appendix, along with the prompts we used to generate it. Decide for yourself which is "better." Japanese Dinner My friend Rob used AI to teach himself to put a seven-course meal on the table while everything was hot. Rob loves to try new things in the kitchen. He recently started learning traditional Japanese ingredients and recipes, cooking one dish at a time using cookbooks, videos, and online information. After getting familiar with a bunch of dishes, he wanted to do something special for family and friends and cook a multi-course meal. The problem was that it was really hard to learn how to time the preparation and cooking of a wide variety of dishes so they would all come to the table hot at the same time. He asked an AI for the ordered series of steps required to prepare, plate, and serve all seven recipes. He followed the composite recipe and succeeded at serving a hot seven-course meal the first time he tried. Memorial Podcast My friend Diane wrote a memorial message at the passing of her mother. She read it aloud to friends and loved ones at her mother's funeral, sharing a warm remembrance of a life well lived. A number of people who could not be there heard about Diane's message and asked for a recording of her reading, which didn't exist. Uncomfortable with making a standalone recording, she decided to try an AI service typically used to create audio podcasts from written information. The resulting podcast had two perfect-sounding human voices sharing Diane's written message as a warm conversational tribute to her mother. She sent the audio to far-away friends and family, who took grateful comfort from the tribute Wholesale Metal My friend Johan uses AI to read metal supplier specification documents from hundreds of suppliers to his wholesale metal business. He works with many suppliers to build and maintain a diverse inventory of products from space-age alloy tubes for building airplanes to rough steel stakes for farming tomatoes. Each supplier sends an electronic copy of a document describing the metal product, lot, and batch information along with the actual metal products on a truck. That information needs to be transferred into Johan's inventory and sales database. It's challenging because every supplier uses their own document format. Stock-keeping unit, description, batch number, lot number, and safety information all appear on every document, but in slightly different places. He used optical character recognition (OCR) software for years to partially "read" the documents, with limited success. Recently, he started experimenting with AI systems that have been taught to retrieve information from different parts of documents based on a prompt such as "give me a list of all stock-keeping unit identifiers along with the accompanying description." He hopes this tool will help improve the quality and timeliness of inventory and sales information so his sales team can sell more and his warehouse team can fill more orders. Robotic Coffee Machines My friend Stephan uses AI to help his coffee machine customers troubleshoot problems in faraway places. He cofounded and leads Poursteady, a robotic pour-over coffee machine company. But these coffee machines are global. Poursteady machines are installed in coffee shops as far away as Korea and the Middle East, meaning that when a customer needs help, it could be the middle of the night in Brooklyn. He subscribed to an AI service that "read" all of the technical and how-to documentation and the ten years of customer-support emails Poursteady had collected. This was an example of fine-tuning a pre-existing generic foundation AI so it can help with coffee machines. The result is an AI chat "bot" that can answer questions and help troubleshoot problems based on its prior knowledge of the world (from the foundation AI model) and what it has learned about Poursteady's products (the fine-tuned AI). His staff further teaches the AI by asking it for help based on their expert knowledge of what has gone wrong in the past and confirming or correcting its answers (something you do when you use ChatGPT). With a well-taught machine in hand, his team hopes to give it to their distributors in Korea and the Middle East so they can better use the knowledge captured from Poursteady experts in Brooklyn. The economics of Stephan's young business are such that he can afford to either manufacture his coffee machines in Brooklyn or hire humans to do twenty-four-hour customer support, but not both. He is choosing to manufacture in the U.S. and scale the customer support knowledge of his expert team with the help of AI. Boat Influencer Dockdeals is an Instagram account run by an anonymous boat enthusiast who uses AI to quickly create high-quality visuals for boat-for-sale listings he is excited about. He uses a service called Canva to process low-quality pictures from the for-sale listing into high-quality images that jump out and better represent what he thinks is cool about the boats. He learned that Instagram's algorithm favors high-quality pictures and will show his posts to more people if he uses AI to improve the images. Team Builder My friend Jason runs a consulting company that uses AI to put together the best possible teams. His company builds financial analysis tools for businesses all over the world. Projects are successful when one or two of his analysis tool experts work as a team with one or two financial experts from the business. He subscribed to a service that uses an AI model to match people into high functioning teams or at least identify possible personality conflicts to be on the lookout for and work to avoid. He used the AI service with a few projects and found that it had helpful suggestions that improved the performance and satisfaction of the teams. Insurance Appeals A former colleague used early AI to automatically appeal denied insurance claims and pre-approvals to pay for prenatal diagnostic testing. This system overwhelmed the insurance companies, who then came to the table to negotiate blanket approvals. In my experience, insurance companies deny and delay payment in the hope of creating disincentives that reduce the rate at which they pay claims, likely with the help of AI. In this case, my colleague fought fire with fire and used AI to level the playing field. Financial Reporting A friend uses AI to analyze and generate summaries of why financial results change from quarter to quarter for the divisions of a holding company. Every division—and there are many—is required to explain why their sales, expenses, and profits are up or down. The head of the division provides a narrative explanation, really the only way to analyze and capture the complexity of the situation. In addition to human analysis, they use AI to read all the explanations, identify unique events, find possible trends, and generate summary explanations across an incredibly complex array of subsidiary businesses. Search My godson uses ChatGPT instead of Google for all his web searches. He was in his freshman year of college when ChatGPT was released. He started playing around with it early on. When I heard he bought a paid subscription to ChatGPT, I felt it said a lot about the utility he found in the tool. On top of not having much money because he's a full-time student, he's also frugal in the nicest possible way. Generous to others, but it pains him to waste money. He uses ChatGPT constantly to look up information and identify trees and buildings from pictures he takes with his phone. Study Aid My daughter used AI to generate practice problems while studying for a final exam. She struggled with a class in college one recent semester. It was a requirement for her major, and she needed a C or above. There was a real possibility of a D or worse! It wasn't enough to go to all of the professor's office hours, seek help from the teaching assistant, study with classmates. She prompted AI by asking it to generate practice problems for concepts in the lecture that hadn't been covered in prior homework assignments. Retail An engineer I interviewed for a job on my team used AI to help convenience store retailers stock their shelves to maximize sales-per-square-foot. The next time you go into a large chain convenience store, look up at the ceiling for dark plastic bubbles. You're right that these are for security to detect and prevent shoplifting, but if the store is a customer of my candidate's company, they do more. The convenience store AI has been taught to watch how individual people move through the store, browse shelves, choose items, and make purchases. After a few weeks of watching customers, it recommends changes to the store layout and to where products are displayed. The process continues after the changes are made, in a constant cycle of optimization and adaptation to changing customer behavior. Grocery stores are increasingly using this technology as well. Next time you notice that your favorite candy bar or bag of chips has moved to a new location, it's because AI thinks it'll sell better there. I could go on, but in the end the best way for you to learn about AI is to use it. Hopefully, the variety of these stories can help you see how AI could be useful to you. AI is changing and evolving so rapidly that it's not feasible to write a definitive "how to" instruction manual. Also, the best AI should be easy to pick up and learn. With the information in this book, you now understand the fundamentals of how you and people like you teach machines and can choose how you engage with AI on your own terms. You are better equipped to recognize AI in the world around you, and with a healthy awareness of the current AI industry, you're a more knowledgeable consumer. Use your knowledge to influence how you live with AI by voting with your feet and wallet. You are better positioned to see the value of your data and decisions and to help your own school, business, or employer maximize the value of both in the use of AI. Keep Up! I started a podcast with my twenty-something daughter, Maryjane, so I can keep up with the evolution of AI in the real world—more how it's impacting people's lives as they use it, less the evolution of the underlying technology. We talk to students, educators, and experts about their life with AI. It's called "You Teach the Machines" and you can find it wherever you get your podcasts. We started the podcast because this book is simultaneously the best way to share a holistic view of AI and the worst way to keep up with the constant change happening at the time you're reading or listening to it. Artificial intelligence evolved significantly in the time it took to write and publish this book. When I started writing in November of 2024, the latest available language AI were capable of responding to your prompt or question with a single answer. Four months later, the latest available AI was able to respond with an answer backed up by the steps it took to figure out the answer! It shared its reasoning! As an insider, this was both hugely necessary and mind-blowing. The steady and rapid pace of change will continue, punctuated by Black Swan events. My hope is that by reading this book you shed uncertainty about AI and the fear it can cause. I hope that any remaining fear of the Five D's are rational and help you make better decisions. I hope you are better able to recognize your own Survival Signals when bad actors in the AI industry try to manipulate you in their marketing, and that you choose to support the AI companies that take the high road. I hope you are better equipped to manage unexpected change brought by future Black Swans. I hope you are better able to think critically about side effects and pitfalls of AI and, as a more informed consumer, can make choices consistent with your values. I hope you have a new appreciation for the incredible value of your data and the data you generate—truly how you teach the machines—and exert more influence over how it is used. Most of all, I hope you see AI for the incredibly useful tool it can be when it augments your life. I encourage you to seek out AI and experiment with it in your life and work. Be the windshield, not the bug. You teach the machines! References Roose, Kevin, 2021. Futureproof: 9 Rules for Humans in the Age of Automation. Random House. U.S. Food and Drug Administration, 2025. Artificial Intelligence and Machine Learning (AI/ML)‒Enabled Medical Devices. (Retrieved on May 10, 2025, from https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices [https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices])

10 jan 2026 - 38 min