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Foreign.
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Hi, I'm Mark Civitelli and welcome to Inside CRE conversations with the people developing the future of commercial real estate. On this podcast, we talk with developers, investors, owners and industry leaders about the ideas, strategies and trends shaping the built environment. The Commercial Real Estate Development association provides education, advocacy and connections to help commercial real estate professionals succeed. Inside CRE is proudly sponsored by Majestic Realty. Today we're joined by Leonard Brody, an award winning techno economist, entrepreneur and venture capitalist. Leonard recently delivered a keynote at NAOB's IconWest conference in Los Angeles where he talked about what he calls the super cycle we're currently living through. Don't worry, everybody, we're going to dive into exactly what that means in just a few minutes. Leonard, welcome to the podcast.
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Thanks. Thanks for having me.
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Well, great to have you here. As we begin today, I want to give our listeners a quick sense of your perspective. You've been described as an innovation expert and a techno economist, and you've also been incredibly successful as an entrepreneur and venture capitalist. How does all that, and that's a lot, shape the way that you look at the global economy today?
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Look, I think that everybody, when they're making decisions or observations about the world, has their own bias. But bias is unfortunately stronger today than it ever was. I look at it through the lens of effectively 300 years of history. And if you look at the moment since human beings began their relationship with technology, which was really at scale. I mean, not about the Wheel of Fire, but since we began our relationship with technology in the Industrial Revolution, there's been a pretty specific pattern that we've been following. And much of that pattern repeats itself. So for me, I tend to focus my energy and insights on when something appears disruptive or it appears different or catastrophic or massive in scale. What does that really mean historically? Have we been here before? I tend to look at those patterns backwards. I tend to not look. It's a bit weird because sometimes people will call me a futurist. I'm not a futurist. I'm really not. And honestly, I believe when people call themselves futurists, you should tune out. It's just, it's, it's super easy. Like if you want to, if you want to talk to a science fiction writer, great. Science fiction is wonderful. But you don't want to talk to people who are giving you theories of the world and then won't be held accountable to those theories. So I tend to not look at it that way. I tend to look. My life is mostly looking backwards. It's kind of like 80% backwards and 20% forwards. And that's effectively how I look at it. So I would be a bit unusual amidst my peers, I would say.
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Interesting way to take a look at it. I mean, you're right, a lot of folks, futurists in particular, always looking beyond the scope. And it's quite the gig if you can get it, because you're just trying to predict the future. But I want to get into right away the concept of the super cycle. At IconWest, you frame the moment we're living in through an interesting historical lens, you know, addressing what you call the collision and clarity that's happening right now in our current environment. What exactly is a super cycle? And to follow up on it, why do you believe we're in one right now?
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Yeah, so a super cycle is something that I would argue has a few components to it. So you tend historically to have these big bang reset moments that are typically driven by a few things and sometimes they're led by one thing and rather than led by another. You typically have four drivers of a super cycle.
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Right.
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One driver would be financial crisis, one driver, and often the biggest driver is technological shifting. Sometimes you have medical, and in our lifetime we've had one minor medical one and one major medical one. And then you also have certain other, like war, for example. And we've been grateful enough that we haven't had a super cycle that's driven by war. But if you were to roll back the tape, if you take those four things, historically, what I think happens is one of those becomes like the lead blocker and it comes out in front and drives those other three behind it with fairly significant change. So the way to think about it is, and I guess apropos to what's going on with Artemis yesterday, if you think about a capsule that's being launched into space and as it hits full orbit, I think what happens if you were to graph these super cycles, generally what happens is they have a lead blocker that causes it. They drag a bunch of other indicators with it. It kind of pulls into orbit. So if you were to look at it on a chart, it kind of goes like, it goes up and to the right consistently, historically. And it causes four massive uncertainties. It creates uncertainty in the economy and sociology. It creates uncertainty in the financial cycles and technology. The key thing I would say is that in our lifetime, the core driver for the most part for these super cycles has been technology, which we should be quite grateful for, because if we were living in 1917, we would have had two massive super cycles driven by war. So all a super cycle is is it's this tornado of change where you've got one instigator that causes an incredible amount of backflow and affects everything else and the uncertainties in your life. And arguably, if you were to map one measure, right, if you just took any core measure of what was the byproduct of a super cycle, and I tend to look at GDP because I think GDP is an interesting global GDP or US GDP is an interesting metric to look at the outcome of a super cycle. You would tend to see it go up into the Right. And so to answer your second question about why do I think we're in one, And I should also preface one thing. A super cycle doesn't. It doesn't mean that one thing is happening. It's actually quite the opposite. It means one thing is the instigator and then it drives massive change in all of the other categories. So I would say now you're in an interesting super cycle because you have a breakthrough instigator in technological shifting through artificial intelligence, which is kind of, I would say historically what we've looked at in these super cycles, one with Internet 1.0 and then mobile and social and now AI. But at the same time, you've got incredible changing going on sociologically, and you've got incredible change going on through political conflict around the world. You know, the, the rise of political polarization, obviously the conflicts in the Middle East. So I would still say that the cycle we are in now is mostly instigated and driven by technology, with a couple of agitators predominantly around geopolitical conflict.
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Is there a period in between these super cycles? Meaning, you know, is it typically, let's say every 50 years, every 20, every five, or is it variable?
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I think it's quite variable, but what you can almost guarantee is that they continue to occur. Historically speaking, you would see that a cycle would last three to four years generally. So if the cycle was instigated by technology, Your median over 300 years, three to four years. If it was instigated by war, your average would be four years. Your median would be eight. So, so it's super cycles that are caused by pure global conflict, like World War I and World War II, they tend to last a little bit longer. But generally speaking, we've been fortunate enough to live through them where they're a little bit shorter and they tend to have a cycle to them. So they tend to, let's say they last a median of three to four Years, you tend to see that in the beginnings of these super cycles, you'll see very quick economic growth, often with very quick economic decline followed by massive economic growth. And so if you looked at it on the chart, it would be spurt decline, large growth. And so the thing I think to remember in all of this is we have yet to have a single historical precedent or one of these super cycles has not ended in economic growth. And so if you go back to like Covid, and this is, I guess maybe part of the point is humans tend to be quite narrow minded in the way they think about their history. And so they tend to think that everything that happens is idiosyncratic to them or is unique when in fact it really isn't. And so Covid was a great example. You know, if you go back and think of where your head was at In March of 2020, you know, it felt like the world was ending and it also felt like we've never, this is new. And you know, everyone has this perspective of like, oh my God, this is, this is the end, this is new. And when in fact it really isn't. And the same is happening with AI. You know, everyone is going through the same false behavior and false pretenses that they did at every other technology from the tracker to the rise of the common Internet. So I think when you end it all, the core thing to remember is that this is a very clear, repetitive 3 century year old pattern. It is certainly possible that that pattern gets broken. It is not probable that that will happen in the next 50 years. And I mean that including AI. And so if you're an executive and you're thinking about the world and one of these big bang moments happens, there's two things you need to think about. One is, is this really historically unique? And the answer is probably no. And secondarily, you have to remember that we have no precedent of this happening where it didn't end in economic growth. And so the question is, how long do you think again, March 2020, how long do you turtle for and get in defensive mode versus how much ahead do you want to be while others are turtling when you know that economic growth is inevitable? And that's where, you know, you hear those old adages all the time about the best companies in the world are built in recession. And that's really what they're saying.
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Yeah, well, one of the other things that you brought up, talking about timelines, when we were in Los Angeles for Icon west, you opened with a line that stuck with a lot of people that the next 730 days will probably feel volatile. What are the signals you're seeing that suggest that we're entering that kind of disruptive but transformational period?
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Yeah, I think for me there are two. There are two core signals that I think are going to make the next 730 days pretty bumpy. I think one is geopolitical. So again, not to go too far down that rabbit hole, but I would say in the political there's two buckets. There's geopolitical and technological. Let's focus on geopolitical for one second. In the geopolitical bucket, there's two sub buckets. One sub bucket is a longer term trend that we've seen occur over the last 30 years, which is an increase in polarization and political view effectively across the world. Now again, that is not atypical and it is clearly a causation of the shifting in way people consume media in shorter form. And I would argue that it's been a move away from intellectualism to a move to intellectual laziness. Because if you think about what were the core principles of Western democracy and Western thought predominantly led us to the middle or the center ground. If you think back to the values of the 50s and 60s, it was very much focused on diplomacy, middle ground thinking, centrist thought. And the problem with centrist thought and middle thought is it's quite required in a democracy, however, it's difficult to do. It's actually quite complex. And so it's much easier to be intellectually lazy and pick a position. You know, like when somebody never trust anyone who comes to you and says I'm a conservative, like really? Do you really know what that means? And I asked you where the conservative movement started. Like, the reality is, where we should be as a society is people have a position based on an issue rather than a camp that they sit in. And so some bucket number one, which I would argue is causing a lot of the problems is this political polarization driven by intellectual laziness and driven by the way we consume media, a breakdown and kind of journalistic trust and integrity. I think the second bucket is as a byproduct of that first bucket, you have governments globally. I don't think this is just an American problem. I think this is happening throughout the world. You have governments that are appeasing to that and therefore those governments are taking policies that are probably more aggressive and unilateral than we would have seen. And I'm not suggesting one is right or one is wrong, but you know, Take a look in the United States. It's what, what's going on with the Trump government. You know, for the first time in arguably since, since World War II, you have an American president talking about leaving NATO. Yeah, I mean, that is it. Regardless of if you as a person agree or disagree with that, that is a very clear signal of a byproduct of a polarization of political thought. And so I think that is bucket number one, you've got massive geopolitical shifting. And in that bucket, it's not all bad or all good. Like, I don't want to represent it as all bad or all good, but one of the things, again, it's very polarizing and there's lots of views on both sides of the fence that are correct. But you also have in this government the willingness and ability to try to root out some of the perceived causes of political instability. So that is going to continue for the next 730 days. And I would argue you're going to see more and more of that under the Trump administration. That will then reflect reactions in the European Union, reactions in Canada. You can see use Canada as a bellwether, and I'll come to bucket two in a second. If you use Canada as a bellwether, you know, Canada's reaction to this polarization has been quite interesting. Canada has moved politically sharply to the middle. So we've moved back to the middle. And there's more conversations. If you think about Canadian history, just given where Canada's the largest neighbor and how tightly our economies were tied, all of a sudden, Canada's reverting back to its pre1960s position where it's much closer to Europe and there's now a lot of tap dancing and discussion about will Canada join the European Union. So that's a big bucket. I think the second bucket, which will both aggravate that exist in parallel and pull it, is technology. So artificial intelligence is without question a mass scale acceleration of technological change. And the implications of it are wide reaching. I think it will have, I don't think it's going to have the labor implications that people think it's going to have. As I said when I was in Los Angeles, we've had zero precedent where you have mass technological shifting and mass unemployment. It doesn't exist. And I don't think it will exist in our lifetime or our children's lifetime. Beyond that, I think it would be irresponsible to opine on it, but I think in the next two generations, it's just not going to happen. And anyone who tells you it is is just an idiot and doesn't understand history, also doesn't understand economic principles like Jevons paradox and stuff. It's just not. It's not real. It's fear mongering and it's people who are looking for a podium and looking to create other opportunities based on that fear. So what will happen most certainly from an employment perspective is you will have employment reshifting, so you will have some labor unrest and some discomfort and people getting readjusted in the workforce and retrained into different positions and stuff. So that will happen and historically has happened. So I think those are your two sort of bullets in the chamber that are going to cause an incredibly bumpy 730 days. And the last thing I would say about technology is the one thing about AI that is quite distinct in comparison to the Internet before it is AI's ability to grow and get better and better is not incremental improvement. It is monumental improvement within months. So the ability for it to grow. And part of that is because now the technology can actually write its own code, so it can actually improve itself without human interaction. And that'll be more and more common, as we saw with Codex 5.3 on OpenAI. So I think that's the thing that's different here. What's different is the pace and speed at which the technology is getting monumentally better is incredibly fast. You can just look at generative AI as a subset or agentic AI, and look how much better it's gotten in 12 months compared to where it was. So those are the two things that are going to create the bumpy two years ahead.
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Well, it sounds like clearly, and you were talking about this when we were in Los Angeles, that one of the central forces in this cycle is AI, if not the central force in this cycle. And you described AI as the defining inflection point of this era. What do you think, though? I'm sure you probably get asked this a lot because, you know, we. You just alluded to the Internet and the last big kind of technological breakthrough. But what do you think makes this technology wave fundamentally different? Different from previous breakthroughs such as the Internet?
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Yeah, I mean, I alluded to it a little bit in what we talked about a minute ago. Look, I think again, I don't think it's good to look at these things in isolation. You have to look at them as it's a drop that happens in a body of water and it has impact. So I would say, as I mentioned earlier, I think that your core lead blocker of what's driving this super cycle is artificial intelligence. However, there are a lot of supporting characters in that cast and it becomes a wave of almost a cycle of impact. And we should come back to the sociological piece because I think that's also very important. But I think what's different technologically this time around is we moved from an era where technology was predominantly a classification and a search or early stage communication protocol. So if you think about the Internet, predominantly, what the Internet did was disrupt communications and disrupted certain forms of transactional behavior. And those are not small things, those are big things.
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Big.
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But when you think about what artificial intelligence has clearly shown us from a capability perspective, it now doesn't act as a extension or service to humanity. It acts as a parallel being to humanity, meaning it can work in parallel to us rather than as a servant for us. And that is a fundamental change. And I think that's what people get freaked out about is, you know, I said in Los Angeles, I mean that you have to, when you use artificial intelligence, even in its form today, even in just the iteration it's in right now, you have to think about it as omnipotent in a way. Not that it necessarily is omnipotent, but if you perceive it as omnipotent, it becomes much easier to understand its capabilities and what you can have it do on your behalf. So the core thing, not to be too academic about it is we shifted gears in AI to away from just classification information media to technology that actually creates and can create independently, to then technology that can now work independently. So you now have the capability to use agents to effectively run parallel path work in the background independent of you having to be there. And that is a. And again, I would say it's, it's pretty good today, but it's not great. I mean, if you're, if you're sophisticated technological, I think you can really manipulate the system to work for you. But it's kind of the William Gibson quote, you know, the future's always here, it's just unevenly distributed. So you can see very clearly how give it 36 months from now and you are going to see agents that are incredibly simple to use, incredibly powerful and incredibly cost effective.
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How about intuitive? Do you think that they'll have that as well?
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Very much so. I think the user interface for most of these agents, I mean even today, if you think about Claude Cowork or you look at systems, that notion that has its own built in agents, they're pretty Simplistic and so, but they're still not capable of doing like I wouldn't let it loose into the wild with things that you really care about. I mean, for example, there's this joke that's been running around the web for a few days now where this Guy was using OpenClaw, which is an open source agent form that people just the Internet fell in love with. And again, some of it was BS and some of it was real, but he basically said, I'm planning a wedding and put into openclaw and let it go and said, I need to bring the food costs down. You handle it. And OpenClaw ended up ordering 200 pounds of raw ground beef or for this event like, because of course, yeah, that's going to make it cheaper. But it's all kinds of assumptions in that. So I think that's what's different. What's different is the technology is much more sophisticated, the back end is much more sophisticated. Now the code can work on its own, it can write itself. So it doesn't necessarily need human interaction. So therefore the scale of its improvement can happen much faster. And I think the impacts on society will be great. And I also think from a sociological perspective, it has deep impacts on who we are as people. And you've already seen the byproduct and sociological change that's gone on because of the Internet and social media. I think this sociological shifting will be dramatic. I mean, it will be incredibly dramatic.
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You were just answering a little bit and something stuck out to me. You talked about the overall adoption of AI, but one thing you mentioned a little bit in Los Angeles you are alluding to here is that companies are a little bit lagging in their adoption of AI, probably more so compared to the regular consumer, you know, that they're maybe experimenting rather than fully restructuring around it. Why do you think corporations are slow to get to the table on this one?
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I think it's just, it's historically accurate is what it is. Most entities certainly since the Internet era have been slow to adopt technology. If you look at Internet one, I always use the Dropbox example. As Dropbox became predominant, most of the people who had, or even just the cloud generally the battle against that was the IT department. So you'd have the IT person sitting in there screaming about the firewall and the dangers and, and what was happening is just consumer behavior was working around it. So if you worked at, I'm making it up. But if you, if you worked at, you know, some IBM, you worked at IBM or wherever you worked, the company would not allow you to use Dropbox, but you'd be using it every day anyway in your own capacities. And the, the it. The IT people just didn't know about it, or they did know about it, but there was nothing they could do. And so I think it's quite common when technology has easy consumer user interface where the employees are driving adoption in their personal capacity and the company lags behind. I think the difference here is you're seeing rates of adoption that are at this stage in its adolescence of AI and that are probably not dissimilar from what happened with Internet 1 and Internet 2. But the risks are higher because if you don't adopt it quickly enough and most companies are just experimenting, but the companies that will hit that velocity orbit will be the companies that are actively using it. And there's multiple layers inside an organization where that can be used. I don't think cost savings is the reason to use it. I think the reason to use it is to provide better experience, better product, quicker reply to customer need and customer feedback. You know, cost savings is just not the most interesting piece about AI. It's, it's over delivering on consumer need and consumer promise. So I think it's quite common. I don't think there's anything weird about the adoption cycle, but I think the risks are a little bit higher now because of what you're missing out on at the rate and pace of change. So the core delta is if the cycle of response is the same, but the movement of the technology is faster and more adapted and more impactful. If you stay in that adoption cycle, you run the risk of being further and further behind.
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I'll tell you what, Leonard, one of the things I quickly took away from that is I think you've given me and everybody else hope that perhaps the end is near to hearing your call is very important to us. Please stay on the line. So on behalf of everybody listening, I think I'm very happy to hear that. But to that end, I want to drill down a little bit further on the consumer side of things, or actually, let me rephrase that more on the corporate side rather, excuse me, because not every employee is equal. You know, you have Gen X folks like me, and there are folks that are just coming into the workplace now, and our skill sets are very different. And one of the questions that we didn't get a chance to get to at Icon, but I thought was a really good one was is how do you actually get people to adopt AI tools when different generations have Very different. Different levels of comfort with technology.
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Yeah, so my view on this is not particularly popular. So, you know, take it with a grain of salt. I don't believe in demographics. I don't believe they're true. I think that demographics are mostly a marketing falsehood and that the buckets of similarities in generations are much closer than people think. If you asked a demographer, they would tell you, oh, well, there's five generations currently living, Gen A, Gen Z, Gen X, Gen Y, Boomers. I believe there are two generations alive right now, pre 2007 and post 2007. Those are the only two demographic generations that exist. And the data, I would argue backs that up. You can create dissimilarity between people when you create a graph that's small enough and tight enough. If I'm measuring characteristics and I make that graph super small, I can create differences between twins. Probably at some point. You know, like if you were to map human characteristic and take two identical twins and you draw the graph small enough, of course the differences would be augmented. But if you put that graph long enough in a historical context, the reality is, are millennials fundamentally different from Gen X? Are Gen X fundamentally different than baby boomers? Not really. They'll have some political views that are different, and there's always differences in certain social cues and certain sociologies, but not really. But if you draw that graph between people born after 2007 and born before, that is a fundamental difference there. You are seeing massive behavioral change. So to answer that question, I think you want to look at it through the lens of those two. The only. What I believe are the only two generations alive today.
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And why 2007 just out of cur. You know, that's usually to your point. You hear about these every 20 year periods, but you've got one line in the sand. What's 2007?
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The birth of the iPhone.
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Okay.
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Because I think what happened in 2007 is you saw a marked shift in human behavior where in science fiction, there's a very common meme that has occurred historically in science fiction, which were demons. So science fiction often predicted that humans would have alternate versions of themselves that, that were kind of part of their personality. There's been lots of science fiction shows that talk about it. And in fact, I would argue that's what the iPhone created. The iPhone created alter egos of humanity. And you can see fundamental shifts. You know, post iPhone. If you were brought up in an iPhone era, arguably, you drink less, you drive less, you date less, you are more isolated, you are at Much higher risk of depression and much higher risk of mental illness. So it's a marked change even on a large graph. Now, to answer your question of generational adoption of technology, I actually don't believe that to be true. I think that within every, to me that's the demographer's myth. I think in every sub bucket, in every age group, there are people who are adopters and there are people who are not adopters and that becomes more or less pronounced Pre or post 2007. But I think the important question you're asking is for those that are non adopters, how do you actually get them to adopt?
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Yeah, I think that's a big challenge for a lot of managers.
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Yeah, I think there's a couple ways to do that. I think one, as a manager you have to be pretty astute as to what people are using in the first place. Like I think you have to understand the tools that people are using in their personal lives, the level of comfort. And then I also think it partially depends on kind of what tools you're talking about. But I think it's important to sort of take technological usage from both, meet it from a bottom up and a top down approach. So I think a, you want to have a really good sophisticated understanding of what the people who work with you use and how they use it, then I think you have to make a core decision based on that and, and the need of the organization as to how you're going to move forward. And you know, in my own world, like in my own companies, I try to follow a couple rules. I tend to be a, unfortunately, I tend to be a top down person. I tend to force the organization in particular directions technologically and just force people to use it. So I moved our entire organization off of Slack and said our official communication channel is Google Chat for a hundred different reasons. Slack is disjointed. It actually becomes quite disruptive. It's outside of the email flow. And so with Google Chat, we're already paying for it. We've already got most of the tools that we need from an organizational perspective. Some people in my company were using Asana, some people were using Trello, some people were using Google. I forced everyone into Notion and just said you all need to become really proficient at notion. And the same with AI. So I tend to be quite top down. I think if you are comfortable with technology, you feel comfortable that you understand the tools. Top down is not a bad approach, quite frankly, to drag people forward, but part of it requires that deep understanding of how people are using another level of adoption because then as you force it top down, you can determine what the timeline is of adoption and how much training needs to go in. And so again, it's not popular. But I do think there's really two demographics. There's adopters and non adopters in those demographics. And I am a believer that if you are a technically sophisticated organization, you need to push top down.
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A lot of great inventions and a lot of great movements didn't come off of what the crowd thought. It came off of one individual thinking differently. I think Galileo would like to have a word about that, for instance. I want to break it up a little bit though. I want to talk a bit about energy because it does not only of course apply to artificial intelligence, but just overall as a political issue. This is gaining a lot of attention right now. I think everybody listening is quite aware that AI infrastructure is very power intensive or it could be power intensive, you know, and now we're hearing companies start talking about alternative power sources like small modular nuclear reactors to support data centers, or geothermal or other green sources as well. But with all of that, nuclear is still kind of the big 800 pound gorilla. Out of all those, do you see that becoming a meaningful part of the energy strategy in this cycle that we're heading into, or at maybe even into now?
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Yeah, I do. Look, there's no question that current compute power requires pretty intensive energy requirements. I also don't think that's. The scale of it is different, but I don't think the need for increased energy is any different than any other mass technological innovations we've had previously. I mean, the industrial revolution required more energy output and so the scale is different. I also think that generally this is another example of historic idiosyncrasies that don't exist. So yes, I think it's more energy intensive. I also think it's historically accurate that most of these technological shifts have been more energy intensive. Yes, it is more intensive than the previous technological shifting that we went through. I also think that it will sort itself out, meaning compute power will become more efficient, we'll find ways to make the energy consumption reduced. And I also think, you know, there's a good piece to this, which is the world really does need nuclear power. I mean, the move to nuclear fusion is going to be very important. And so for a bunch of reasons, you know, not just, you know, we have, there are risks, of course, but natural sources of energy are complicated and need to be augmented. So I think technology is a double edged sword. It has the ability to drive resource in a way we don't want, but it often has the ability to drive resource in a way that's positive societally. So electric vehicles is an example of that. But I do think we will see in the next five years, you'll see compute power become more energy efficient, you will see advances in alternative sources of energy, and I think you will also see a settling out of the compute and data center power required to deliver this. But it's definitely an issue and I think that we have to be mindful of how this cycle exists in parallel to other cycles historically.
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Well, as we get to the close here, I want to finish and build off of what you talked about in Icon when you wrapped up your keynote, because you really ended your discussion with a thought that I think resonated with, with the audience. You know, you said that the most valuable skills during a super cycle are pattern recognition and critical thinking. So for our listeners, perhaps those that weren't able to join us in Los Angeles trying to navigate the upcoming few years, maybe even up to 10 years, how do you develop that ability to see the patterns instead of just reacting to the headlines?
- [37:28]
A
The answer is you have to read. Pattern recognition is an incredibly, incredibly important skill and it requires a mode of self awareness and the ability to be a good student of history and to understand cycling and to understand what occurs, typically occurs in the context of history. And you know, it's, it's simplistic, but the truth is it's very hard to know where you're going if you don't know where you've been. So I, I think you have to really read. I think, I don't think we talked about this in la, but the one beautiful thing about AI and this is a use case that not a lot of people think of. I'm not saying it's good or bad, but if there's in the non fiction and arguably in the fiction world, but in the nonfiction world, if there is any subject you want to know, and I mean anything, and you want to be a real student of it, go to Perplexity, go to Claude, go to ChatGPT and have it write you a book. And most people don't think about this, but you can go right now to ChatGPT and say, I am really interested in learning about historical patterns in technology and the economy. I want you to write me a 500 page book on the history of historic patterning. I want you to put all the citations, triple check the citations, list them. I want balance historically, I Want balance on economic view. And you will be blown away by what you see because the argument is the same. While it's much more complex to learn about, it's actually much easier to get the information. You don't have to go. I'm not saying you should use that as your sole piece of information. You want to read the great economic historical works. But by the same token, if you just need a primer and there's particular things you want to lay in on, go do this right now. Mark, you should do this. When we get on this call, go to ChatGPT and say, I want a history of the thought in critical thinking and all the skill sets required. Give me all the citations. I want you to write me a 3 to 500 page book. And what you will see will blow your mind because ChatGPT will come back and it will actually write a book, proposal, chapter, outlines. It will then check with you, then it will say, do you want me to start writing? It will write chapter one, you can review chapter one, give it guidance, and then it will write the book chapter by chapter. And within 20 minutes you will have a 500 page book that you can download as a PDF, all cross referenced and cited. And the risk of hallucinations in that book is quite low and you don't want to rely on it as your sole source of information. But if you really want to get started, it's a great way to do it because that ChatGPT written nonfiction will point you to 60 other pieces of literature that you can actually go in and read directly. So I think people don't realize you can use AI for that today. So I would encourage, if you're interested in critical thought, you're interested in game theory, you're interested in economic principles like Jevons Paradox and other things, and particularly pattern recognition, go into an AI, have it write a primer book for you like Critical Thinking for Dummies and then follow the citations and go through those citations and look and go deeper. But I do believe those are the two skill sets that are required. Now like you, you don't want to be the person who's watching things on social or seeing things on the news and can't denote bias and can't ask critical questions and can't take an argument. I mean, it's just so, it's, it's so common today.
- [41:24]
B
Like it's easy to get in that feedback loop. I mean escaping it's gotta be hard.
- [41:28]
A
Well, it's, it's also easy to just be misinformed Yeah, I mean, again, I don't want to get too political, but you know, I, I, I'm quite involved in the history of Israel and the state of Israel and, and, and I'm also quite balanced. You know, I'm not one of these people who like says what is right or what is wrong. I just understand the facts and, and it's amazing just on a subject like that. But you could pick any subject. How much time I spend educating people about stuff that they just don't bother to read. And part of this is you're living in a post truth era where you have a president in the United States who discounts truth and critical thought and has, you know, will take a piece of journalism and just label it as fake news. And then a percentage of the population thinks, oh, it's fake. And you have terms that people throw around that they don't know the meaning of, like I'm a conservative, I'm a liberal, this is a genocide. This is a part like there's just no concept or understanding in this post truth era. So I think when you were in a post truth era, you need to be incredibly good at pattern thinking and you need to be incredibly good at critical thought. And one, society will be better off and I'll come back to one point about that. And two, you'll be better off because you'll be ahead of opportunities in a way that other people are. And this goes back to one thing I can't remember if we talked about in LA or not, but there is a movement right now where a lot of people in the entrepreneurial world are telling people to not go to university. You know, you're wasting your money, it's bad debt. And the problem with that lens, it's such a stupid argument because the problem with that lens is these. Now you could argue that the debt may not be good or that it's too expensive and that that's another argument, but that whole movement is about making money. The argument is if you want to be an entrepreneur and you want to build a company, don't waste your time in university because you're going to. Peter Thiel does this all the time. You're going to lose 50,000 in debt and whatever. That was not the role of the university. The role of the university was to socialize people into becoming critical thinkers, into becoming a civilization, into understanding how to not be idiots and how to interact with one another on a social and human scale. Because if you think about it as an 18 year old, it's your first moment when you're alone. You have to fend for yourself. You have to learn how to eat. You have to learn where the groceries are. You have to learn how to live in a dorm with other people and not work, you know, not have your mom and dad deliver food to you every day. Like there's a real socialization factor to university now. You could also argue that many universities have abandoned that responsibility and are not. You know, that's a different argument. Whether the universities are actually a place of good critical thought, that's another argument. But that I think is really critical. And the more we move away from that, both at the institution level and at people thinking of the university as a place to how to learn to make money, the worse off we're going to be because those were your core entities where you were supposed to learn pattern recognition and critical thought.
- [44:39]
B
Well, you know, what a way to go out. Nice, light, easy answer for us today, Leonard. Look, you stirred a lot of people's, I think, way to look at things when we were at Icon West. I have no doubt that our conversation today will also get a lot of people thinking as well. Certainly you provide some very interesting and sometimes contrarian viewpoints and love hearing how perhaps maybe there's a different way to look at things and just hearing your insights on those. I think hopefully people will walk away and be able to engage in that critical thinking a little bit more. Really enjoyed having you with us today, Leonard. Thanks so much for joining us not only here, but at IconWest and providing your perspective. And hopefully we'll get a chance to cross paths again.
- [45:27]
A
I hope so. I really appreciate the opportunity. It was great to meet you and to be part of Icon West. It was a real honor. Thank you.
- [45:34]
B
Thanks again, Leonard. Thanks for listening to Inside CRE conversations with the people developing the future of commercial real estate. And thanks to our podcast sponsor, Majestic Realty, for supporting the show. If you enjoyed today's conversation, please share it with a colleague and subscribe so you will never miss an episode. To Learn more about NAO and connect with more than 22,000 commercial real estate professionals, visit NAIOP.org.