Fairy Dust And Magic 8 Balls: How Good Is Your Data?

Jeffrey Madoff: This is Jeffrey Madoff, and welcome to our podcast called “Anything and Everything” with my partner Dan Sullivan.
 
Dan, the topic of artificial intelligence is certainly a hot topic in so many areas, and I’ve always favored actual intelligence rather than artificial intelligence, but I’d like us to do a bit of a dive into just what is artificial intelligence? How does that affect things? How does that generate data that actually may be misleading, but how billions of dollars of decisions are made, also. Because data’s used to justify almost all decisions now in major businesses, and it’s important to realize—as you and I have spoken about in the past—that all data has one thing in common, and you know what that is. And I’m with my friend Dan Sullivan, and this is “Anything and Everything”, the podcast where we talk about anything.
 
Dan Sullivan: …And everything, and not necessarily in that order.
 
Jeffrey Madoff: That’s right.
 
Dan Sullivan: Yeah. Well, first of all, I’ve seen legitimate proof that it’s something new, but it’s not what people generally misinterpret it to be, because those who I think who are giving the wrong interpretation of this thinks that the intelligence that the machines have is the same kind of intelligence that humans have, but that the machines are faster and faster, and at a certain point, they’re more intelligent than humans are.
 
Okay, and I think that’s the big thing. What they are is increasingly faster and faster computers, and the computing is not only in the chips. I mean, the chips are Moore’s Law, although it keeps being predicted. it’s coming to an end, it’s still going. Gordon Moore in 1965 simply said that, “I’ve observed from three data points that every time we take a jump, it seems to get twice the computing at one-half the cost of the previous computing, so it’s like a four-times multiplier.” Double the computing result at half the previous cost, and that’s all he said. He just wrote a paper on it, and everybody grabbed it and made it into a self-fulfilling prophecy. He said, “It’s not really a law.” I mean, Gordon Moore—I’ve read a lot of what he wrote on it—said, “It’s not a law,” but he says, “It kind of is a metaphor for human aspiration,” and he says basically that it gives people a way of dreaming bigger and striving bigger. He says, “I’ve made a lot of money off of it,” because he was one of the founders of Intel and he made a lot of money, but he never took him himself seriously like it was Moore’s Law.
 
It’s like Murphy’s Law, really, in reverse to a certain extent. So I think that’s the big issue about it, that machine intelligence—they got to call it something, so they call it intelligence—but it’s a combination of faster chips, and cleverer and cleverer algorithms that they build into the software.
 
Jeffrey Madoff: By the way, sort of a fun footnote; when Gordon Moore founded Intel with Robert Noyce and they were part of the Traitorous Eight.
 
Dan Sullivan: Fairchild.
 
Jeffrey Madoff: Yes, yes, and prior to that, they got to Silicon Valley because they went to work for Shockley Semiconductor, and the original name wasn’t Intel. The original name was their last names, and it was Moore Noyce, and it was Noyce’s daughter who said, “Dad, that sounds like you’re saying ‘more noise’.” So they came up with Intel-
 
Dan Sullivan: Which actually was quite prescient on her part, because that’s what it turned out to be is a lot more noise.
 
Jeffrey Madoff: Well, that’s true, and the name became Intel, which a lot of people now, because of how the branding is, think it means intelligence, but it actually meant “integrated electronics,” and that’s how they got the name. I just like those bits of cocktail party trivia.
 
Dan Sullivan: No, no. It’s very important to do that. I just wrote one of my little quarterly books and the title is You Are Not a Computer, because I saw Ray Kurzweil about 10 years ago, and he’s the official creator of a techno-eligion called The Singularity.
 
One thing, if you grew up with a very, very deeply embedded traditional religion, like you grew up in one culture and I grew up in another culture, the value of that very, very deeply ingrained religion when you’re young is that when you’ve retired from it, you can spot other people’s attempts to create new religions.
 
Jeffrey Madoff: Correct.
 
Dan Sullivan: And it is. It’s a religion, and The Singularity is like the Messiah coming: At a certain point, there will be this super-intelligence that will free us up from all the damage caused by our stupidity.
 
Jeffrey Madoff: Well, probably not.
 
Dan Sullivan: Yeah, but here’s where I see if I can just give an example. The fastest-growing economic market, I think probably for the next 50 years, is regenerative medicine. One part of it is the cracking of the code on stem cells of being able to take almost any human cell and return it back to a undifferentiated cell, and then differentiate it to solve other problems. And that was Dr. Yamanaka, and I met him. I actually met him last... It was like meeting Einstein, because he really opened the door for stem cell science.
 
But the other thing is it was the application of artificial intelligence program to the testing process in labs where they can do 10,000 tests digitally in the same time it would take to do one manual test, and that’s where the great breakthrough is, where you have to go through large amounts of complex data and you want to sort out that which doesn’t work from the very small thing that works. This is a phenomenal breakthrough.
 
Jeffrey Madoff: Well, as we usually do with catapulting to other areas, but I want to circle back to our beginning when the one trait that all data has in common, and of course, you know what that is.
 
Dan Sullivan: It doesn’t last very long.
 
Jeffrey Madoff: Well, it’s about the past.
 
Dan Sullivan: Yeah. Yeah. I’ve got a famous Dan quotations, and I said, “Artificial intelligence at its very best predicted something of what happened yesterday.”
 
Jeffrey Madoff: That’s right, and of course, then people still bring up Nostradamus.
 
But I want to get drill a little bit, first of all, into data and how data is gathered, because putting it in the business world, how did the first salespeople know what was selling?
 
Dan Sullivan: They went to the stores.
 
Jeffrey Madoff: Yeah, that’s right. Or the open-air markets, I mean-
 
Dan Sullivan: Yeah, they were in touch with the sellers, and they were in touch with the buyers.
 
Jeffrey Madoff: And they could count because they were present at that time with the merchandise they were selling. As stores grew, as chains grew, and as technology grew, it reaches beyond just what’s selling, and one of the areas that was really mystifying was radio: How do we know who’s listening so that they can establish advertising rates in some meaningful way?
 
And I don’t know if most people know this, but Nielsen, who is famous for TV ratings, started off doing radio ratings. I had become friendly with Frank Stanton, who was one of the co-founders with Bill Paley of CBS. Stanton got his start doing Nielsen, and he was a Nielsen rep and what they would do... I didn’t even know they started with radio, and actually, I went to the University of Wisconsin, and Nielsen is an alumni of the University of Wisconsin, so there’s the Nielsen Tennis Stadium there, which is really cool. Those were the days you could play 50 cents an hour in beautiful indoor tennis courts.
 
Anyhow, the way that they measured on the radios, that was before the Nielsen boxes on the TVs, is the tuner. If you ever looked inside a radio, there was a cylinder and there was a belt, and the tuner would be on some part of the belt, and what they saw is the belts were wax. They would put a wax cylinder in there, then they would measure the depth of the groove, because that meant you spent more time on that station. “Here’s all the ones that they skipped over,” so you would look, and it was really pretty primitive. Yet, even back then in radio, tens of millions of dollars decisions for advertising were made on something that primitive.
 
Dan Sullivan: Yeah. You gave me a great book by Tim Wu. You recommended it, and he gives a wonderful history of how advertising first took hold in the late ‘20s and early ‘30s, so we’re going back almost 90 years when this became important.
 
Jeffrey Madoff: Yeah, it was fascinating because when it switched to television, then there was the Nielsen box. I believe this is accurate, but it’s within this ballpark. There were only 1,200 Nielsen homes, yet billions of dollars of advertising decisions were made on this really shaky ground.
 
Dan Sullivan: A very, very small sample.
 
Jeffrey Madoff: That’s right. That’s right, but the decisions were made as to who bought what, when, where, and how much they’d spent because of that, and that technology lasted for decades.
 
Dan Sullivan: One of my clients in Chicago took me to the Chicago Yacht Club for dinner one night, and his wife was from Argentina, and she had joined Nielsen’s in Buenos Aires, and then she became so good that they moved her to the Chicago office, but Nielsen’s is still all over the world.
 
Jeffrey Madoff: Oh, yeah, and it’s very interesting because data went from, you looked down at the table at the open-air market and saw that you sold out of tomatoes, to gradually getting more and more sophisticated in terms of how data was gathered, and it was thought the more data, the better; the more informed the decision that you could make and so on. Yet, there’s so many products, so many movies, so many books, so many things that data is used to determine whether or not to bring them to market or to continue trying to sell it, so many of those products fail that I always wondered, “Well, why is it that people have such belief in data when there’s so many counter examples to it?” And then you hear that it was Bloomingdale because from the gut, he was a merchant and knew what to do, and he didn’t care about data.
 
Dan Sullivan: The other thing is that one of the specialties that I remember, you told me the meeting that you had had, I think it was about six months ago, where you were invited to this conference of top merchandisers around the world, and they were saying how much they felt that they were going down a blind alley with data. They were just losing touch with so much information that in the street market days, in the early department days, they had, and one of them was there were buyers in all these department stores. They were in touch as much as they could be with the buyers, the sellers, and the manufacturers, plus they were in touch with culture, what culture was doing. They were able to interpret music. They were able to interpret… I mean, what you’re always want to be on top of is the youngest possible consumers when they have money to consume.
 
I mean, usually 20 to 50 is the big labor market, the population labor pop—, but it’s the big consumption market, too.
 
Jeffrey Madoff: Well, I don’t know if I ever told you this story, but I love this story. It’s right on target with what you’re talking about. A good friend of mine was a woman named Dawn Mello. Dawn was the first-
 
Dan Sullivan: I think you brought her up in that conversation on the podcast. We weren’t going deep like we are today, but you brought it up that they were saying, “We’ve got big data coming out of the gazoo, but it’s not telling us anything useful.”
 
Jeffrey Madoff: Well, she was for fashion. She became the head of Bergdof, and then the head of Gucci, so she was a highly, highly respected person. She unfortunately passed away a few years ago.
 
Anyhow, back in the early ‘60s, she was working for May Company, who I believe they’re based in Cleveland, if I’m not mistaken.
 
Dan Sullivan: Cleveland, yep. I’ve been to the May Company.
 
Jeffrey Madoff: So she was the canary of popular culture that they’d sent her into the coal mine—and by the way, these positions have been eliminated at department stores all over the country, so that being in touch and being able to get that visceral, “This is what’s happening and it’s percolating, and I recognize that because of… I can recognize things that are percolating.” So she was in London and she went to this little club. She heard some music. She loved the music, invited the guys to sit down and said, “Look. We have stores across the United States. How about if we sponsored a tour? You could sell your records. Do you have a label in the United States?”
 
“No.”
 
“Are you interested in the American audience?”
 
“Oh, yeah.”
 
Dan Sullivan: And Paul said to John, and John said to George...
 
Jeffrey Madoff: And you got it. That’s right, and the great thing about the story is that the president of May Company, she played a record for him, and he said, “Who’d want to listen to this? No way.” And as you remember, it was The Beatles. And there’s always going to be somebody who has got their eyes on the horizon and seeing the silhouette of something new that is beginning to form, and you don’t get that from data.
 
Dan Sullivan: Yeah, it’s very interesting. One of the great clothiers in Canadian history, and I knew him personally, I was one of his last personal clients, the name Harry Rosen. When he retired, he retired, really stepped down about seven years ago when he was 85, but I knew him from when he was 78 to 85, and I got to really know him. I actually wrote a little book of Harry Rosen’s wisdom. I said, “How do you stay up to date?” And he says, “Clubs, clubs. Three nights out of the week, I’m finding what the hottest club is for young people, and I go down there. I dress as casually as I can. I just go in. I just ask them why they like this and why they like this, and how they’re dressed, and what are they noticing and everything like that.”
 
So he is doing that three nights a week at 80 years old, 82 years old. So he says, “That’s the basement. That’s the basement. The young people we always have in the basement. Then the basement becomes the first floor, or the second floor. The top four is bespoke, so that moves more slowly. But he said, “I listen to the music. I want to know what the trends are. I want to know what the slang is. I want to know everything, and I’ve been doing this for 50 years.” He says, “You always go to the clubs.”
 
Jeffrey Madoff: Which makes sense, doesn’t it? And you’re also going to find out things there that you aren’t finding anyplace else. And so how low do you think that the reliance on data has affected business? You deal with a lot of tech entrepreneurs. I mean, that’s like they have a steady diet of data that they think somehow is a Rosetta Stone for whatever it is they’re trying to do. Well, how do you see... What is the effect of data?
 
Dan Sullivan: It’s so important that in the last 10 years, I’ve never heard one of them even talk about it. That’s how important it is.
 
Jeffrey Madoff: Interesting.
 
Dan Sullivan: And what they have is five, all of them, and we teach this as part of Coach, a thing called DOS, D-O-S. It stands for Dangers, Opportunities, and Strengths, and they have a group of about 10 clients or customers who are their most successful clients and customers, and generally, tend to be the most innovative customers and clients, and they enjoy being invited to be part of the creative process of the business. So he’ll meet with him individually or he meets them in groups, and he says, “If we were having a discussion and it was a year down the road, and you’re looking back over that year, what has to happen for you to feel happy with the progress you make over the last year?”
 
They lay it out and then he says, “So what dangers do you have that have to be eliminated right now? Dangers you have right now that have to be eliminated, and then opportunities that need to be captured, and strengths you already have that you want to maximize.” And they’ll talk, and they just lay out their game plan, and then he takes 10 of them, the game plans, and they have a picture of how the business can be useful in a product. It may suggest product. It might suggest service, but mostly, it’s how the business owners should actually think about the next year, and then the business owners have the data, so our entrepreneurs don’t need the data because their best clients have the data, but only a small portion of it is important, vis-à-vis their dangers, their opportunities, and their strengths.
 
I mean, what data’s important? But I mean, I’ve got two pieces of data. It’s first thing in the morning. What were the registrations for yesterday, for the week, for the quarter, and for the year? The number of sign-ups, that’s our receivables, and then what was the exchange rate between the Canadian dollar and the U.S. dollar? Because 80% of our income is in American dollars, but 80% of our expenses are in Canadian dollars—so American dollars in and Canadian dollars out. But very, very little information other than that.
 
But I pay attention. I mean, first of all, I’m coaching for 48 years, and I still coach more people personally inside the company than any of our coaches.
 
Jeffrey Madoff: So do you think that your experience with these entrepreneurs, and you’re saying many of them not paying attention to data, but we know that many, many businesses do?
 
Dan Sullivan: Yeah.
 
Jeffrey Madoff: Do you think that data enhances the potential for innovation, or do you think it hampers the potential for innovation?
 
Dan Sullivan: It depends on the business. Services, not so much; retail, much bigger. I mean, there’s all sorts of data, but it’s very market-specific data. For example, I have a new client in my top group. He just joined on Thursday. I just met him for the first time, and he’s in the Central Valley of California. He picks up and transports 25% of the tomatoes in the world to processing plants.
 
Hunts is the big tomato sauce, ketchup… So he has to pay attention to market prices. And then one of the big things is shipping costs in the whole system, and that’s the thing that has been most disrupted for the last two or three years because the cost of transportation inside the country and outside the country has gone through the roof.
 
Transportation cost is the number one cost factor because the margins are so small that if you go from 1% transportation costs to 3%…
 
But usually the data that we’re talking about is economically strategic data. I’m only guessing at the kind of data that the big honchos that you were talking about are looking at. Is predicting… Are they using it for prediction purposes, guessing purposes?
 
Jeffrey Madoff: I mean, they are using it for how much raw material do they purchase to meet the projected sales needs that they’re going to have. And large businesses most are notoriously risk-averse, so data, they believe, helps them hedge their bet, and there used to be a phrase back in the early ‘70s that... What was it? “You won’t get fired for buying an IBM.” So it was very vanilla, what it was. But the data showed that at least you weren’t taking a risk. At least that’s what the belief was, which also meant there wasn’t going to be much innovation.
 
Dan Sullivan: Yeah. Well, I think the other thing is that—a couple things, and this is just outside observer because I don’t really have a feel for what goes on. I think that digital technology is used to disrupt things without knowing what kind of value you’re going to create after you disrupt it. And I think that the process of innovating new disruptions has speeded up exponentially.
 
I observe that Silicon Valley now is not actually interested in creating anything. They’re interested in making a bet on fairy-dust, and then making as much money as they can on other people betting on fairy-dust, like Las Vegas. I mean, it’s kind of like the business model of Silicon Valley is more and more like the business model of Las Vegas: Doesn’t matter who wins, who loses, the house makes 17%, and I think Hollywood, probably…
 
So I think the big changes that you’ve observed in your lifetime, and you’re much closer to these type of industries than I am. My businesses are small- to medium-sized and largely service business, so it’s not big inventory businesses. But one thing is that let’s say the people who created the big department stores in New York, Philadelphia, Garfinckel’s, Macy’s, and everything like that, they actually lived in the community that included people who were buying their stuff. They didn’t live in gated communities when they were in the city. I mean, they had their places in the Berkshires and they had their places otherwise, but they actually lived among people. They were members of the city and they were owners.
 
But I think that the big corporations, now, they’re hired guns. A CEO is a hired gun. A chief financial officer is a hired gun, and the tenure is usually six years, then they’re onto something else, and the only data that they’re looking at is what the quarterly stock price will look like.
 
Jeffrey Madoff: True.
 
Dan Sullivan: It was like Lehman, the Lehman Trilogy, if you think about the Lehman Brothers supplying supplies to the plantation owners and basically saying, “We’ll just give you the materials and when the harvest comes, and you pay us for what we’ve done.” So the original Lehman Brothers in Alabama, and then you get the latest guy, and all the data’s spinning like this. I think it was a perfect example of what’s happened over 150-year period to merchandising, and in its latest stages, Lehman Brothers didn’t make anything, especially not a profit.
 
Yeah, but I think that the abstracting of business processes, I think that confidence comes with data in a way that an intuition doesn’t give them a sense because intuitions are always risky. “I’ve got a hunch. I’ve got a hunch.” That doesn’t go over at the boardroom table, “I’ve got a hunch,” but look at personality in creating your play. It was based on a hunch.
 
Jeffrey Madoff: Yeah. I mean, I guess you could look at it-
 
Dan Sullivan: You didn’t have any data to put this whole thing together in four or five years, I don’t know how long, from the first thought, but we’re four or five years down the road, and it’s all been judgment and hunches.
 
Jeffrey Madoff: Well, quite the contrary. As a matter of fact, you’re correct, but it even runs deeper than that: Choosing to tell a story about someone that these days most people haven’t heard of, and they don’t know the story because what they do in theater is, of course, try to give you something you already know.
 
Dan Sullivan: And I find it boring. I find it boring.
 
Jeffrey Madoff: Of course.
 
Dan Sullivan: I thought that the two that I find kind of interesting, I found Million Dollar Quartet kind of interesting because it was a story that nobody knew; that these four, Elvis, and Jerry Lee Lewis, and Johnny Cash were in the same studio in Memphis or Nashville, I forget which one it was, and they were recording and they were earlier in their career, and it was an afternoon in a recording studio, and they had good impersonators for…
 
Probably Jersey Boys was the best because that was kind of like the first one, and I thought Motown was good. I really liked Motown, especially the story, but the first half was a lot more interesting than the second half, and then I started seeing, because this became the thing, now. You get a star, you tell their story. You don’t have to write the music because they wrote the music, and you play it.
 
After a while, they just get really, really boring because it’s just imitative, but yours is really great because first of all, nobody even knows the history of how Rock and Roll got started, and nobody knows the history of this one individual who, if you took from 1950 to 1955, he was a giant in the field that paved the way for a lot of other unknown people to get a chance, and actually make their way into a brand new musical genre.
 
Jeffrey Madoff: Well, and the point being that, I mean, I was seduced by the story, and I like stories about unsung heroes, and things that people you didn’t know about, but I think you should because they had such an impact on their culture that it’s important to know these things, and there isn’t any data that exists, but you do.
 
Jersey Boys would say, and this is just, I don’t know what the real number is, so just for example, they had 20 number one hits, so that proves to somebody who’s got money, that there is an audience for what they do. And I think that the joy is in the discovering something new, not in having it fed to you. So we have a story that is a journey of discovery and that people seem to really relate to.
 
Dan Sullivan: Yeah, but this is all a hunch. This is all-
 
Jeffrey Madoff: That’s right. No, that’s right.
 
Dan Sullivan: This is intuition, and hunch, and guesses, and bets. You’re not looking at any kind of data on anything.
 
Jeffrey Madoff: Well, that’s right, and the thing is that raises, I think, a very fundamental question about data is do we actually even understand what it means? So when you look at... I wasn’t in on the pitch of Jersey Boys, but I’ll bet you it had to do with how many hit songs they’ve had, and does that translate into a successful theatrical process? Well, it did in that case, but it didn’t on Elvis. There was a movie about Elvis, All Shook Up. I mean, not a movie, I’m sorry, a play. It tanked, and if anything, you’d think Elvis would be the most bulletproof one out there, and it didn’t work.
 
Dan Sullivan: No. No, and Tina Turner’s, that was the one I was trying to think I saw in London, and it was Tina’s revenge, two hours of revenge against Ike and everything else. That’s the way it was written, and after a while, you said, “All right, you got a sad story to tell and everything, and it sounds to me like you got a decent amount of revenge, but not very interesting.”
 
Jeffrey Madoff: Well, and so I think we don’t often know what the data means.
 
Dan Sullivan: No.
 
Jeffrey Madoff: So you can accumulate barge-loads of it, but how do you interpret it?
 
Dan Sullivan: Well, it’s very interesting. I talk to people about inputs that you get from the world every day, and I said, “A lot of data,” and usually you see it at the bottom of the screen where they have the Wall Street and that data that’s going across the bottom of the street now, it changes every 17 seconds, so any price you see, that’s the speed with which Wall Street prices change. Now, it’s 17 seconds, on average, a price changes every 17 seconds, and they’ve got the technology to handle that, and then there’s information.
 
So data is momentary. It’s today’s reading of yesterday’s data is already 50% off. It’s starting to smell, that data. It’s a little bit stale, and then there’s information, and that’s where somebody’s taken data and said, “Well, therefore, over the next two or three weeks, these are trends that we can look for.” So they’ve taken all the data and they’ve moved it down to information, but the information is very perishable.
 
Knowledge used to be quite lasting. We have a lot of doctors, and he said, “The half-life of what you learned in medical school is about two years. Everything you learned in medical school now is about two years,” and he says, “My biggest challenge is because I’ve got very informed patients.” This one doctor I was talking to, and he said, “On things that they’re specifically interested in, they come in and see me with more knowledge than I have because I haven’t really looked as deeply as they have in a particular issue. I don’t know if their knowledge is good or it’s faulty, but I should. As a doctor, I should know whether it’s faulty information or not.”
 
But he said, “I have to develop a whole way of talking to them where I ask them questions about what they think about what they know.” Well, that’s not how doctors and patients interacted 30 years ago.
 
Wisdom, wisdom is in a class by its own. Wisdom is a different thing. There’s stories told 3,000 years ago that still have the same hit today as they did 3,000 years ago.
 
Jeffrey Madoff: How would you define wisdom?
 
Dan Sullivan: Well, it’s accumulated, tested knowledge by millions of people over decades and centuries that still kind of rings true. I mean, business. There’s two pieces of data. Make sure you have more coming in than going out.
 
Jeffrey Madoff: Of course, we both know people that made fortunes who had a lot more going out than coming in, and then they were able to pass that hot potato off before it all collapsed.
 
Dan Sullivan: I was watching Warren Buffet and Charlie Munger. They’re the two partners at Berkshire Hathaway. They’re 95 and 96 years old, and they were talking about the FTX, you know the recent-
 
Jeffrey Madoff: Uh-huh?
 
Dan Sullivan: Warren Buffet was sort of clinical about it. He said, “If you bought a ton of gold in the Year One of the current era, and it had a value in relationship to the local currency in Rome, whatever that was called in those days, and you brought it back up to our age, 20th Century is over, it wouldn’t have appreciated in value one bit, generally. It may for two months or three months, but he said it would have exactly the same value as it would’ve had 2,000 years ago in relationship to U.S. dollars, which is the current currency. There’s no productive value for gold. The other thing is that it’s not a currency because its only value is when it’s translated into dollars, which is the currency.”
 
So he said that, and then Charlie Munger says, “I won’t be as critical as my partner here, but what’s happening is that you just noticed that your neighbors are getting rich from selling turds. Okay? And you say, ‘I don’t want to be left behind. I don’t want to be left out and left behind. They’re getting rich by selling turds. ‘ So you start selling turds with the belief that there’s some other fool who will pay you more for the turds than you paid for the turds.”
 
Jeffrey Madoff: Yeah. Well, a friend of mine, Patrick McGinnis coined the term FOMO, Fear Of Missing Out, and I think that’s exactly what you’re talking about.
 
Dan Sullivan: It’s called the Greater Fool Theory, that no matter how big a fool you were, you’re betting that there’s a greater fool.
 
Jeffrey Madoff: It’s probably a pretty good bet.
 
Dan Sullivan: Yeah, and I think there’s a lot in the economy that goes on this momentary flipping, but even there people, as we learned a month ago, there’s tens of billions of dollars that’s never going to be found out of all that flipping that was going on. People will say, “They’ve got to regulate that,” and they regulate that, and I said, “Well, they should regulate the guilelessness of investors.” I said, “Nothing happened with cryptocurrency that didn’t happen with something else 2,500 years ago at some Mediterranean port. They just pulled you into some sort of deal. Tulips, in-
 
Jeffrey Madoff: I was just going to say, yes.
 
Dan Sullivan: ... “1,700 Holland tulips and railroad stocks, American railroad stocks in Britain in the 1800s.”
 
First of all, we live in a world of data, so it’s like the weather. You have to learn how to negotiate it. But I think that if everybody’s doing it, then the person who’s succeeding by not doing it is probably onto something.
 
Jeffrey Madoff: Well, I agree with you and in the business that... One of the areas that I’m in, the first question I got asked when I was pitching my book was, “How big’s your social media following?” Because that’s data they used to justify the decision to even pay you an advance or even publish the book. Then sitting in the rooms when fashion shows are being cast with the models. It became a thing, as of a few years ago, what kind of Instagram following? What kind of Twitter following?
 
Dan Sullivan: In addition to their measurements, they had another measurement they had.
 
Jeffrey Madoff: That’s right. That’s exactly right, and because they would think, “Well, if this model gets photographed wearing it, that’s going to get a lot more play online,” and so they wanted to try to reinforce their decision on who they would hire, again, based on data, as opposed to what it used to be: “God, she looks great in her clothes. She really knows how to move, looks fantastic.” It’s, “No. She’s got seven million Instagram followers.”
 
So data translates into making decisions about things with the hope that the greater public will perceive that to also reinforce the data that helped you make that decision, and I think that it’s fascinating because we don’t really know.
 
Dan Sullivan: No.
 
Jeffrey Madoff: And one of the things that’s happened, and there’s data to support this, which I find incredibly ironic, therefore, I like it because it’s so weird, is that there’s a substantial amount of data out there that shows we’ve become increasingly disenchanted with almost everything. And what does ‘disenchanted’ mean?
 
Dan Sullivan: No magic.
 
Jeffrey Madoff: Yeah. That’s right. Exactly. Exactly. A good friend of mine, Josh Sapan, actually, we had breakfast together today, and he was the head of AMC networks and built that into a power, and he green lit “Mad Men”, “Breaking Bad”, “Walking Dead”, a number of hugely successful films and streaming series. And I said to him, “How do you test things?”
 
And he goes, “We put in front of an audience. They’ve got a box with two dials. They turn this one this way, this one this way when they’re interested, when they’re not. We see the fall off, all that kind of thing.”
 
“So you’re doing data-gathering of that specific program in front of your test audience, the focus groups?”
 
He said, “That’s right.”
 
And I said, “Well, how come there’s so many shows that don’t make it? Because there’s way more that don’t make it than do.”
 
And he laughed, he said, “That’s what I love about the business: the magic, because we don’t know how to predict that.”
 
And I love that because you’re right. So that disenchantment means that we’re not under the spell, but when something does come out that really resonates, we are enchanted again, but for the most part, we’re no longer happy or sad. We’re disengaged, and I think that’s a real problem in our culture, that people are disengaged and the data is showing that.
 
I want to add one more thing and get your response to it, is that I find it also really interesting that when you go to a website and you log in, you have to prove to a robot, basically, that you are a human.
 
Dan Sullivan: I just did one this morning. It was interesting because I tried out a little AI program this morning. It still had one of the old checkout that you’re human, and it was nine photographs, and which ones have steeples in them? And you say, “Three.” And it said, “Good.”
 
But the new one is really, really interesting because it’s a puzzle piece. Okay?
 
Jeffrey Madoff: Yes. Put it in the right direction.
 
Dan Sullivan: You have to bring the puzzle piece over so that it matches up, so they’re trying out different techniques.
 
Very interesting that it was a little AI program, which is called Character.AI. It’s capital C, capital A, capital I, and what it is a character that you can chat with, and they have all sorts of cartoon characters that have been created, and Elon Musk is on it about five times, and all they’ve done is poured in public utterings of someone, and they take it, and they’ve got an AI that when you chat and ask questions, there’s a little delay. It is about a three or four-second delay, and then the bot will chat.
 
I did Socrates because, first of all, I’ve read all the Platos, and I was asking him about intellectual property. I said, “What’s your take on intellectual property?” And it was very clever, and I found the response. There was about five or six responses, and then they cut me off because I haven’t actually signed up with money to use this, so they just give you a little taster.
 
I found it very, very interesting because all they do is come back and it says, “Well, from the way you ask the question, it seems to me that you’re thinking about an idea or something you imagine that has the value of property. Okay. Is that what you’re thinking?”
 
So what I noticed with it, it has absolutely no content of its own. It’s simply deriving content from what you’re doing. I mean, it’s actually kind of intriguing. It’s kind of intriguing. I’ve run into humans who couldn’t do what this AI program… actually listen to what I’m saying and actually listen to the words. I found it very, very interesting, but you can go on and create your own chat bot.
 
If you feed them a lot of your stuff, they’ll create a AI version of me, and quite frankly, I’d probably get more out of talking to myself and having myself ask me questions about what I was doing, but I was just really intrigued with it.
 
It’s around the surface of human thinking that AI is attempting to bring things that speed up certain processes, and my sense is that it’ll get better and better at probably telling you what you don’t need, but it will never tell you what you want.
 
Jeffrey Madoff: Well, when you were talking about the bot that you were speaking to, what I thought of was, remember when we were kids, the Magic Eight Ball? You’d shake it up and you’d ask a question, you’d shake up the Eight Ball, then it would then answer interesting to ponder or whatever.
 
Dan Sullivan: Yes. Yeah, like those horoscopes.
 
Jeffrey Madoff: Exactly.
 
Dan Sullivan: It’s like a horoscope, and you say, “You will have to do some fundamental thinking about your finances today.” And you say, “Yeah, I should look.”
 
Jeffrey Madoff: Yeah.
 
Dan Sullivan: Every day is a day when I should give some thinking to… Yeah.
 
Jeffrey Madoff: That’s right.
 
Dan Sullivan: But a lot of people are operating at a semi-conscious level, so a direct question like that just throws them. They say, “How do they know that?”
 
Jeffrey Madoff: Well, yeah, so it’s like the horoscope or the Magic Eight Ball. Remember those things, the paper things? You’d go like that, and then there would be a question. Then you go like that and there’d be an answer, but I don’t see it as much more credible than that because it is those generalities, but it’s really interesting to me is that we are having to convince—not convince, that’s not the right word—pass the test that we are a human rather than a bot, and we’re doing that to a bot, so we’re trying to prove to a bot that we’re not a bot. We’re a human.
 
Dan Sullivan: Yeah. It’s really interesting. My cartoonist, so all my books have cartoons in them, and so as not to get somebody’s nose out of joint, he doesn’t actually use somebody’s picture. He uses a AI program that creates realistic-looking people, but it’s really interesting because he showed them to me and I said, “They’re kind attractive,” but after I looked at, I said, “These aren’t real people. Are they?” There was something about them that I could tell wasn’t real, but a lot of people I think would be fooled by them like that, but there’s something that’s just a little not-programmable about every human face. There’s just something about it. There’s a quirk or an odd thing about everybody, how they show up, that kind of puts you off.
 
So they’re talking about the fakes that they can put together. Now they can take a political leader and they can-
 
Jeffrey Madoff: Deepfakes, yes.
 
Dan Sullivan: ... deepfakes and everything, and I said, “I think our senses are going to go up to the challenge.” In other words, I think that, we’ll… First of all, we have in the back of our mind, “This could be a deepfake,” so already we’ve got a filter up. I mean, you’ll get fooled, and then your greatest skill and my greatest skill after 40, 50 years in the business world is that we have a much faster ability to size up people and size up situations than we did 50 years ago.
 
Jeffrey Madoff: Oh, absolutely. Absolutely, and I think what’s fascinating about that is machines don’t learn. We hear about AI and its companion machine learning, but machines don’t learn. It’s just that they have more information to sort through, and as you were saying earlier, they can sort through it a lot faster.
 
Dan Sullivan: Yeah. You know where I suspect they’re being put to best use right now on the planet right now is the Ukraine-Russian War, but only from one side. One side is doing it, putting two or three things together. The Russians have just lost an enormous number of high-level officers. They’ve lost 15 generals. They’ve lost like 100 colonels, and it’s just way beyond statistically. I mean, they’re not frontline fighting. They’re just getting killed behind the scenes. And what it is that, first of all, the Americans trained the Ukrainians for the last eight years since when the Russians took Crimea.
 
This is an AI story, so I’m not off-topic in telling you this story. Okay?
 
So you have to understand. I mean, the Americans were preparing to fight the Russians from 1946 onward, and then in 1991, without anyone’s permission, they quit. Okay? So the U.S. has all this lore. They’ve thought this through from a million different ways. They just have all this understanding of how Russians think about war, and how they prepare for war, and how they organize for war.
 
The other thing is they’re really sloppy. They’re really sloppy. They have poor maintenance. They have bad logistics, and that’s been true forever. They just never got on top of it. They make some superior technology and then they don’t maintain it. So the Russians arranged for the Ukrainians—and the Ukrainians are as sophisticated technologically as the Russians are—on the first day of the war, when the invasion started, they knocked out the encryption system that the Russians used to communicate to their senior officers, and the senior officers use an encryption system. So they had to use their own personal cell phones to talk, and the Americans had all these cell phone numbers. They had every general going right down to the captain level in the Russian army. They had every cell phone number, and they fly an AWAC at 40,000 feet, about 250 miles outside of the battle zone, and they’re just detecting in the way that they detect things where these personal telephone numbers are, and they have an AI program that takes it in, and anytime they get a dozen of them that are in a close cluster, they send an automatic missile to one of the mobile missile launches, so the Ukrainians, and it fires it and hits them right in the middle. They’re drinking. They have a drinking party, and they just take out 12 of them right in a room. And they have to get together. They have to get together and talk, and they’re using their cell phones, so everything they’re saying on their cell phones is being taken in, so there’s probably a statistical thing of “How many do they have? How many we’ve killed?” And that’s useful data, and a lot of the demoralization of the troops is that their officers are scared, which is always bad for morale.
 
Jeffrey Madoff: Well, because they’re feeling more risk because they’re surprised more than they thought they would be, significantly more than they thought they would be.
 
Dan Sullivan: Yeah, so I think probably in the military, this stuff is being used to good effect.
 
And if you remember, a lot of computerization really came from the Second World War experience, the Bletchley Park, Alan Turing, and decoding, and interpreting. The first computers were really used to figure out trajectories of bombs, and missiles, and everything like that, so I think that there’s real-world stuff where there’s certain numbers that are really, really very, very important.
 
But in the area of making up things and trying to sell them, it may be life and death for your career, but it’s not. Your life is not at stake.
 
Jeffrey Madoff: Well, for instance, you talk about Alan Turing and the group who was trying to break the Enigma code, which I believe was changing 48 million variables every 24 hours or something.
 
Dan Sullivan: Yeah.
 
Jeffrey Madoff: The type of computers we have now, they probably could have done it in a small fraction of the time. Again, that’s processing speed, but what’s always brought up is, for instance, when the computer beats the chess master, is it really smarter? The computer really smarter? I don’t think so, but it can process the algorithms a lot faster than a human can.
 
So I think we’re often diverted by the novelty of what we think computers can do, but in reality, there’s an awful lot that they can’t do, and I think that a big part of this—and maybe this is for our next podcast—but just like a hammer doesn’t know it’s hammering and a shovel doesn’t know it’s shoveling, the computer doesn’t know it’s processing.
 
Dan Sullivan: No.
 
Jeffrey Madoff: In other words, there’s no awareness, and in order to be both intelligent and a sentient being of some sort, there needs to be awareness, not just ability to move faster. Cheetahs run faster than us. Are they smarter?
 
So I think what artificial intelligence is and isn’t is a really interesting area.
 
Dan Sullivan: Well, I think this is a major new topic that we’re confronted with because it’s being used in ways that disrupt things, and actually stop progress and cause failure, so I think that’s probably a major area. It’s not a new science, but it’s a new study that now we have to deal with this as a daily social phenomenon that a lot of things are happening that have been triggered by someone’s assessment of big data.
 
Jeffrey Madoff: That’s right.
 
Dan Sullivan: Yeah.
 
Jeffrey Madoff: That’s right, so I think we’re onto yet another thing that’s within our perimeter of “anything and everything”.
 
Dan Sullivan: We’re very precise about this, though.
 
Jeffrey Madoff: Yes. We are, very precise generalities.
 
Dan Sullivan: Yeah, that’s right. Yeah, very precise. Yeah.
 
Garry Kasparov was the loser of the first Deep Blue, or whatever the name of the computer was, and he said, “Within six months after that happened, we just created another league where you had a chess master plus a computer program competing against a chess master and a computer program.” He says, “We just moved up a level. We had new tools and everything else.” And he says, “The same disparities of talent, just jump a level. The real masters that know how to use this new tool. It’s just as competitive and it’s just as unpredictable as the old game was.”
 
We used to do foot races, and now we’ve got cars that go 200 miles an hour, but the good racers are still the ones who have a vast disparity of advantage over the bad racers. We just jump it up a level.
 
But the big thing in my book, You Are Not a Computer, I said, “Take a piece of information, a message, and you have one human being whispered into the ear of another one who whispers it down the line until you have the 10th human being, and that person comes back and whispers the original message into the originator, and there’s usually no similarity between the first message and the 10th message. Do that to a computer, and you can go out 10, you can go out a hundred, you can go out a thousand, you can go out a million, and the message is the same.”
 
The myth and the fiction is that computers are information processors and human beings are information processors, but computers are vastly better information processors. I said, “That would be true.” And I said, “It is true. Computer is a vastly better information processor.”
 
They say, “See how human beings failed at information process?”
 
“I did, but they didn’t fail at meaning-making.”
 
So the first person did it, and the other one said, “I didn’t quite understand that, but I’ll just make up what I think he meant and I’ll pass it on to the second one,” and each of them makes up new meaning. Each of the person created a brand-new meaning for the message because humans are meaning-makers.
 
Jeffrey Madoff: No, that’s right.
 
Dan Sullivan: We’re storytellers, some better than others.
 
Jeffrey Madoff: That’s right.
 
I really look forward to diving in this further and into the whole mystique of algorithms, which are essentially a set of instructions.
 
Dan Sullivan: Yep. Yeah.
 
I’ve got to tell you, there’s been a tremendous breakthrough with the patent bureau’s interpretation because they’ve always gone that it has to be an algorithm, and they changed their basic definition that it had to be attached to technology about five years ago, and now it just has to be a set of instructions.
 
Jeffrey Madoff: Yeah. I mean, a recipe is an algorithm. But you don’t say, “I have the algorithm for chocolate cake,” but that’s what it is.
 
Dan Sullivan: Yeah, but we’ve really had a breakthrough with our clients. I’ll tell you all about it in the next one, but I’m going to show them that receivables, so let’s say, just pick one of your companies and just say, “These are the receivables.” Ours is since 1989, and that’s a large number, but actually, there’s another value here and it’s the intellectual property that allowed us to actually create that income, and the way the Patent Bureau is looking at it right now, that could be equal to the actual receivables. The amount of intellectual property that we had.
 
In 1975, the Standard & Poor, which evaluates the 500 top corporations in the world. It was 84% tangible assets and 16% what are called “intangible,” but which is intellectual property, and that was the valuation, and in 2020, it was the opposite: It was 84% intellectual property and 16% tangibles.
 
Jeffrey Madoff: Well, do you want to say goodbye to our audience and friends?
 
Dan Sullivan: We do.
 
Jeffrey Madoff: Thanks for joining us today on our show, “Anything and Everything”. If you enjoyed it, please share it with a friend.
 
For more about me and my work, visit acreativecareer.com and madoffproductions.com. To learn more about Dan and Strategic Coach, visit strategiccoach.com.