Framers: Human Advantage in an Age of Technology and Turmoil

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Transcript

Rob Johnson:

I’m here today with Kenneth Cukier to discuss his new book, Framers: Human Advantage In An Age Of Technology And Turmoil. His coauthors are Viktor Mayer-Schonberger who he wrote a previous and very, very well known book called Big Data, and a new member of their team, Francis de Vericourt. Thanks for joining me today, Ken.

Kenneth Cukier:

Absolutely. Great to be here.

Rob Johnson:

So, Ken, I’m quite curious, you’ve got the new book, how does it relate to Big Data, and more importantly, at the essence, what inspired you to write this on planet Earth at this time?

Kenneth Cukier:

That’s such a good question. And you’re right to actually point to the earlier book, Big Data. It wouldn’t be so obvious, I think, for a lot of people to realize that here’s a book about cognitive psychology, a book about liberalism, a book about business and business strategy, and that it relates to an earlier book about data, but it certainly does. And the reason why is that when Big Data came out in 2013 and it hit the New York Times bestseller list, which was brilliant and we’re very honored that it made a nice contribution to how people thought about machine learning and artificial intelligence, because, of course, Big Data is shorthand in the valley for machine learning and it certainly was at the time.

We were brandished the evangelists of AI and the evangelists of Big Data and the cheerleaders of it. And I willingly accepted that title, because I felt that there was so much about artificial intelligence to cheer, and I still do think that way. But we were unfairly tarnished as well. And we were unfairly tarnished, because people said, “Well, these guys are just talking about correlations and giving up on causality and they have this view that you can just trust the data and that’s enough, but, of course, you need a model for data and that, that model is really important and you can’t just trust correlations and give up on causality.”

We said, “We met them halfway, if you will.” We do feel that we’re in a world, particularly and machine learning validates this that the correlations are often as good enough although of course, causality is still the gold standard. But be that as it may, we always presumed that the data would exist in a model. We never thought that they wouldn’t and people ascribed and slung arrows at us in that way. So to fast forward, we were listening to the criticisms, but at the same time we were watching what was going on in terms of artificial intelligence, just take off like rapeseed and get improvements that we thought that were faster than anyone had thought was going to be possible and be adopted more commonly than we thought it was going to be even quicker.

And we were the optimist of it. While at the same time, we saw populism and creeping authoritarianism and even a winnowing of the public sphere, because of canceled culture. And we were nervous about both of these trends melding together, where we have AI being endowed with too much authority, too much power and the human being diminished. And we said, me and Viktor and Francis as well said, “No, before there’s a model, there’s a mental model. And so we need to actually focus not on what humans do poorly like Daniel Kahneman and cognitive biases, we need to focus on what humans do really, really well, which is they generate mental models, they apply mental models, they think of the world with a simulation in mind and then by doing so, and if they’re good at it, they can actually change the world so it bends towards their will. And we should celebrate this and we need to get better at it if we’re going to tackle our biggest challenges.”

So from that seedling of Big Data and the success of it, we focused our minds on taking the story to its next increment, which isn’t, if you will, AI, we take as given that AI will be as transformative and positive as we believe it to be and as it will be, but we said, “No, the point is not to focus on the AI, the point is to double down on human beings and get better at that.”

Rob Johnson:

Yeah. I’ll be a little bit technical, but many of the philosophers who I talked to about economics and economic history of thought and dynamics, talk about epistemological or ontological uncertainty. Ontological meaning there are unknown unknowns both in the realm of outcomes and in the realm of probability assignment. Whereas the epistemologists, I’m using a silly metaphor, but God can see the model, but it’s just too complex and all we need is more computing power and then it will come into focus.

And my sense is there’s some ontological uncertainty present. We have gone through this over the years in macro economics, rational expectations, somehow pretends that past is prologue. I have a lot of friends in the insurance industry and they say climate change is scary, because we don’t have actuarial tables about what this looks like. So we got to evolve the model by learning.

Kenneth Cukier:

That’s exactly right. Let me pick up on that, because it’s just so essential. People in the climate change environment look at the data and they say, “Hey, climate change is happening. Look, the temperature is rising.” But then there’s people, statisticians often, who actually know something about data, they look at it and they’re the naysayers and they’re the climate change deniers. They look at it and they say, “The data just doesn’t do what you say it does, just because it’s going up doesn’t mean it’s not going to go down.” Their model is different. So how do you square these two things?

And the dirty little secret in the biz is that the pure statistician approach isn’t incorrect, it is true that if you simply look at rising temperatures as your data point, that does not actually tell you anything about causality and it doesn’t tell you that humans were responsible for that. But what you need is a model and what you need in particular is a counterfactual. And so actually in our book, we open up a chapter on counterfactual by talking about two incredible women. And it’s relevant. Interestingly, it should be women.

Eunice Foote who has been really forgotten in history as the woman who before John Tyndall of the Royal Society was the scientist who made the causal link between… Excuse me, it was pure causality link here of carbonic gas, carbon dioxide, and rising atmospheric temperatures that when the sun rays hits it that actually it gets hotter than with natural air and it takes a longer time to cool down. So it’s a great wind there that you can actually see the mechanism that if you have European factories that are belching out factory smoke in the dark satanic mills that yes, in fact, if you increase the carbonic acid content of atmospheric air, Earth is going to heat up at some point.

Now what then happened is the Baton got… Oh, I should give a date for that. That’s 1850s. Okay. So the Baton gets passed in the 1980s to Inez Fung at Berkeley, previously MIT, who was working for NASA under Jim Henson, the fellow who came up with the famous testimony before Congress, that basically said, “There is such a thing as climate change And every scenario from middling to dire is bad. And all of them are bad. All of the scenarios are bad.” But what she did is she applied the counterfactual to say, “What if you have Earth without humans and if you have Earth with humans, what is the difference of the natural rate of atmospheric temperature change?”

And when you do it that way, of course, you cannot run the experiment, because there’s only one Earth. You need to run a counterfactual model. You need to create a simulation of it. And that idea of the counterfactual is what’s so important. And so one of the features of a mental model or a frame as we call it in the book, is not only is counterfactual, it’s not only causality, it’s not only counterfactual, it’s also constraints. But here we can focus on just the role of counterfactual and that’s how you get, you need the mental model to understand climate change and to identify the role of humans as responsible for climate change.

Rob Johnson:

Yeah. When I used to work as a financial investor, I often would teach at schools or give lectures at schools. And I had a metaphor that I used, which is the only thing you can observe is the price, but behind it, there is a pendulum that swings back and forth the ball, and there’s a fulcrum, but the only thing you see is the ball. And as an investor, you’ve got to figure out is this mean reverting, meaning when the pendulum swings out, it will return back to the balance point, or is the fulcrum drifting from structural change. So when you see it out there, if you take what you might call the other side for the return to balance, you’re going to get rolled over.

So you had to get into the structural dynamics, the instability of models in order to draw proper inference about what’s taking place. And I tried to make a simple metaphor that people could use their mind say to latch on to the dimensionalities that were in play. And you’ve taken it to a much more sophisticated place than I would be able to both as a CRN and as a writer, but I thought that window creates a bridge into the things you were working for to illuminate.

Kenneth Cukier:

Yeah, without a doubt. That’s, of course, behind INET in general, as an institution in which it understands that the world is more complex than we think, it’s more adaptive that we think that there’s an inherent instability that we think. And we make this point in the book as well. In fact, one of the more delightful vignettes that we point to is Andrew Lo’s work, Andrew Lo of MIT, the economist who exactly she’s trying to reframe, if you will, economics away from the mental model of 19th century physics of a world of fluid dynamics and equilibrium to a world of biology, which focuses on a mental model of evolution and growth and change.

And when you do that, suddenly, what it means is that as economists or as a financiers or as even business people or people acting agents in the world, we’re not looking at an entity that has these static rules of which we’re trying to divide what they are and then apply them. That the actual environment that we’re in, that we’re living in itself is unstable, itself is changing and dynamic. And therefore every thing we learn and then when we make an action, changes the underlying environment and state that it’s in and we need to learn and change again. Now, if you take that mental model of not stock, but flow, so to speak, when it comes to thinking about the economy and then apply it to business, you can see that one reason why some businesses do incredibly well and others less well are those businesses that are understanding and have a mental model, the inherent change of the environment that they’re operating it, where there’s constant cycles of turnaround and that what they did yesterday has not zero, but almost zero validity for today.

A lot of companies that don’t operate on that speed and on that clock, if you will, are going to fail or even if they try to, they don’t make those right decisions. Now places like Amazon and others who are able to collect data and have a data advantage are ostensibly better off to actually learn faster, can also hopefully have the right business environment, but if they make a mistake, they can respond and rebound more quickly and better to actually course correct shape shift, meet the market where it is and succeed. But it’s not a given, because before it’s a strategy, it has to be a mental model. And it’s hard for it to be something that you just simply read about in the book and learn, it’s got to be in your DNA. It’s got to be baked in rather than sprinkled on top.

Rob Johnson:

I had a wonderful conversation yesterday that resonates with the things you’re talking about. He’s a gentlemen who works in a bond rating agency and he’s talking to me about the ESG economy, society governance agenda, the broader stakeholder awareness. But he was talking about the change in perceptions. He was talking about the United States in this instance related to race. And he said that, for instance, black colleges get much lower ratings by the ratings agency than white colleges even when their finances are stronger. And he was going through all of these things. But I said to him, “How do you inspire change?” And he said, “In an ESG world, what I tell them is there will be about 50 lawsuits waiting to be heard. And if you invest in municipal bonds with schools or groups or whatever, they get triggered for major losses, a precedent to set the sense of what society’s responsibility changes to be more inclusive of people of color. You’re going to get tagged, your municipal law is going to crash.”

So he said, “You don’t have to be either a racist or someone who’s working for civil rights and inclusion, what you have to be in my business is a guy who sees it’s going to change and it’s not priced in and I’m trying to tell you where the risk is.” And so I thought it was a fascinating analogy that he’s saying the underlying sense of values in a society post George Floyd’s murder is changing. What is going to constitute safety in a bond rating is going to change, because the challenges that are going to come up from this new consciousness will change what you might call the scorecard or the probabilities around different municipal bond environments.

Kenneth Cukier:

Yeah, I think that’s very interesting. And it’s interesting that a bond guy is seeing that and seeing that early. And, of course, they think about risk and of course, in some ways, interestingly, not surprising, that it would be spotted by someone there. In our book we talk about this, because we talk about the value of pluralism. And we talk about diversity as well, in particular cognitive diversity. And if you don’t know if someone is cognitively diverse and brings you a different way of seeing the world, one proxy of that is the outward manifestation of diversity in all of this other manifestations of skin color and gender and sexual orientation and nationality, et cetera, age, certainly is another one as well.

So one of the nice things that we were able to study was the sociology around race relations in America. And in particular, the idea that white middle class families tell their children that they should be colorblind. And that seems like the right approach. In fact, Martin Luther King’s famous speech invoked this idea that we should be colorblind and not see color. And it shouldn’t matter the color of man’s skin, but the content of his character. Beautiful. But the new thinking by African American sociologists is to say, “No, don’t try to be color blind. If you do that, you erase something fundamental about the other in particular.” It almost erases a way a part of their lived experience, which is so different than yours, that it actually does some injustice to actually put the pretense of colorblindness out when in fact that can’t be correct, because, of course, there’s implicit racism in all the ways in which we see and don’t see throughout the interactions that we have.

And of course, the Georgia Floyd murder has brought to the fore this emotional awakening of some of those problems. Instead, what they say is, “Don’t try to be colorblind, be colorful, see the difference, go to the difference.” In fact, it’s actually harder to do that, it’s much harder, because it makes you feel uncomfortable. Good, let it make you feel uncomfortable, but take that step forward and have that interaction, see the difference. He says because black parents are teaching their children don’t be colorblind, you be colorful, you’re black. And that means you’ve got lots of different interactions that you need to be aware of and you need to know how to govern yourself with as opposed to a white child. You can imagine what the myriad of those are. So it’s different as well. That idea, that shift of, if you will, reframing how races can interact from the colorblind to the colorful and that’s in some ways would be more respectful is I think a really interesting way that helps us understand and clarify the importance of mental models.

Rob Johnson:

What I find fascinating as I was reading through your book, I want to come back to the bridge, to the Big Data book. There was a sense that I experienced that people sometimes think everybody’s anxious. The world’s very uncertain. So Big Data is the thing that can make us all feel calmer or the economist who pretends to be able to see the future even though we can’t, which we might call a demagogue, is reassuring until his false projections are unmasked. What I’m getting at is that in your book really gets into this emotion is very present here. The yearning for certainty can, what you might call, make you susceptible to mirages.

You said in this, just the last portion of this conversation, the pain of looking in what you called colorful, can create an aversion where people block out the discomfort. They don’t want to grapple with it. And then they simplify in a way that, what you might call, abstraction enables cruelty. But so I’m looking at a book and I think I remember I read this, Will-I-am, the musician and entrepreneur gave you an endorsement. He said, “A great book filled with fresh perspective to help us during the rise of AI so we can usher in the age of humanity.” So I’m back at the inspiration out of Big Data and into this role, the role of radical uncertainty and the role of emotion.

Kenneth Cukier:

Exactly. So it is strange. What is he talking about? Why is Will-I-am endorsing our book? And why is he talking about the age of humanity and the age of AI? And the reason why is that we start from talking about AI and take as a given that AI will be as transformative and as positive and beneficial as we want it to be. So we’re the optimist of AI, we’re not the naysayers of AI. However, we believe that, that’s not where the focus needs to be. It’s because AI, although it can do great things for us and hope that it does, can’t do something very fundamental that humans can do in that frame. That is to say, generate mental models, apply mental models and re-invent new mental models if the old models don’t work. And the reason why is, because the very components that make a frame useful are the very things that artificial intelligence cannot do.

In particular causality, AI has no understanding of it. Humans are extremely good at it. In fact, you might even say that the flaw of humans is that we’re so good and we even see causality where it doesn’t really exist. We projected, but that’s not such a bad thing in and of itself. The reason why is, because it presumes that the world is an understandable place, it’s a predictable place and a repeatable place and that with our intellect, we can understand some of these features of it and then take a causal template of how the world works and apply it to other circumstances. So we can make abstractions based on that causality.

The second thing, and of course, artificial intelligence cannot do that. In fact, if you make one small adjustment, an example, if you were to play chess and you were to take away some squares that just couldn’t be played, the computer would fall down completely where the human being would simply adapt. And the reason why is we have a frame of the game of chess and with that model, we can easily adapt it and change it and make small little side cuts to it and still apply it. Another way of thinking of a causal frame is I see butter melting on a stove. I now can tell you all about what might happen if I put zinc in a furnace. Artificial intelligence simply cannot do that, because it cannot make instructions, it can’t generalize, it can’t take that representation and apply it to something new. It has to relearn it all like an animal has to relearn everything from scratch again.

Second thing is counterfactuals, right? It’s to say the counterfactuals of what if question is not the world that is the world that could be. The whole point of artificial intelligence, the best technique that we have in deep learning, but also the others like reinforcement learning and others is that it learns from a large body of data. It needs actually gargantuan amounts of data to learn to overcome the fact that it can’t read your abstractions. The point about human beings is that we don’t have the information we invented, because we can actually use our counterfactual thinking to imagine a world that isn’t to come up with data that we don’t have or experiences that we have observed and make decisions based on. So, for example, how do you go to the moon? How do you relate an engine in the middle of space in which there’s no atmosphere, there’s no oxygen?

Well, we did that, not because we’d never done it before, we did an experiment, we could do experiments on Earth, but the point is that before we experiment on Earth, we come up with a mental model and then we render it. And then the third is the constraints. We impose constraints, the meaningful and the right constraints that are right for the time in the given circumstances and we’re not great at it, but we’re pretty good at it and because of that, we can do things well. We as humanity, sometimes flounder, but often as humanity, we exceed ourselves into great things. A computer can give you counterfactual constraints, yes, it can. It can give you half a trillion of them in 30 seconds, but the point is it can’t give you the meaningful ones in time.

So for that reason, although we’re optimistic about artificial intelligence, we are also vaunted as human capability of framing. And this is coming at the time where on one side we have what we call the hyper rationalist, the people in Silicon Valley and elsewhere who say human beings have such problems with their decision making because of their contract bias, because the data is biased that in fact, what we need to do… We’ll leave the data bias for moment, put that aside. Because human decision making is biased and has limitations in it, then what we need to do is hand off some of these decisions to the machine to make it fair, to make it better, such as loan applications that don’t rely on a white loan officer judging a black applicant, but can simply just look at the data.

Now, there are ways in which that’s the right answer, but in extremists, it’s the wrong answer, because you want human beings who have mental models to it. On the other side or the emotionless, as you said, the emotionless or the populous they’re almost like so weird man who don’t want reflection, rationality, Cartesian facts and logic, because it’s inauthentic. What we want is the soul’s expression of itself face the universe. And this is the world of Bolsonaro and Trump and maybe Boris Johnson in Britain if you’re going to be ungenerous as one should be, and say that this is a world in which the instincts of one’s humanity is the legitimacy that one needs to make decisions.

So you can shake people’s hands at a COVID hospital and lo and behold, you’re on a ventilator three weeks later. So we wanted something that would sit in the middle of that to say, a hyper rationalist don’t have the answer, it’s not a world of ice cold algorithms or should it be, the emotionless don’t have an answer, we shouldn’t rely on populous simplifications to a complex world. Instead, what we need to do is understand our unique ability as human beings to become good framers, to get better at working within a frame or reframing when we need to, in order to solve our problems.

Rob Johnson:

In my own life after finance and politics, I worked in the music and film room for a while. And a lot of my friends who come and watch things at INET from that room, say to me, “What are you doing with all these experts? They’re more emotionless.” And I said, “Well, both left and right brains are necessary or what have you as analogies.” But they come back to me and it’s not that they think the right brain is superior, because it’s heartfelt, they think that experts are not doing analysis, they’re doing marketing for power. And when they’re doing marketing for power, they are becoming cold hearted and personally ambitious and not providing for the public good.

I hear this over and over from people that work, particularly in film, that the, which you might call, the heart mind and what you call the emotionless are anchored to a more loving, if you will, process and the cold analysis is subject to corruption. I think that’s too simplistic and you’ve created both the yin and yang on both sides to this, but it is what I hear in criticism of economics quite a lot.

Kenneth Cukier:

I don’t totally disagree with it. And I think a part of it is the message, part of it is the ground truth, part of it is the messaging. Let me take a step back and speak from personal experience. When TED came around, I was in the early tester of earliest adherent to TED, but not in the way that I think a lot of people would have liked, because I thought I was so angry at it and repugnant. Now, there was TED before Chris Anderson in the 90s of which was a small little sect of interesting people doing extraordinary things paying a lot of money. And then it got sold of course, to Chris Anderson and then they put their videos online.

And I really disliked it at the outset, because it was like pop academia. It was taking what I thought at the time, some of the most scintillating minds on planet Earth and forcing them to speak in 15 minutes about their expertise in a way that I thought that did violence to it, because it was such a simplification. I thought the talks actually were pretty good, but what I really disliked was the chatter afterwards, the coffees, by people who thought they knew all about particle physics, because I heard a 15 minute TED talk and that they had therefore license to challenge one of the world’s foremost physicists about his ideas, because they clearly understood the alpha and omega of it, because they sat for 15 minutes uninterrupted, not texting on their phone, hates it.

And I’ve got 180 degrees. I think that actually they’ve done a brilliant job, because I think there is a great value in the crystallization of ideas by great minds. Absolutely. But the second thing that they’ve done, which is just as important, maybe more important is that they melt at their best, the analytical right hemisphere with the creative, emotional left hemisphere. And suddenly I think the ideas stick better. It’s a great way of communicating. In fact, it’s so important that one of the things I do at The Economist is I run in effect the op-ed page, if you will, it’s called by invitation. And I get our contributors not to simply write their ideas, novel ideas, big ideas, but just I say, “Tell me, why is it that you’re writing it? Tell me, what’s your story in this? Why you give me your credibility?”

I say, “I want to hear about the first person what you have done. And I also want to find a little emotional leverage,” because The Economist is so analytical and we’re accused of being dry. I don’t think we’re dry whatsoever. I think we’re scintillating. However, we’re accused of being dry, because we are so rational, analytical that I want to use this technique of bringing in emotion and finding a balance to it and getting these ideas to stick. And if we can do that successfully, we can have more of an impact in the book and it’s about having an impact. So I agree with those people who criticize economics and even some of the economists as Julien Benda called it in the 1930s, the treason of the clerks, the treason of the scholars of exactly who have given up on their integrity.

In that case, it was about playing a role in policy and leaving the world of ideas. But if Julien Benda was alive today, he would point to his scholars who are giving toxic Goldman Sachs for six figure speaking fees and giving up on their integrity of having influence in the world, but being unblemished with Luker. The rise of Trump was in part, because you could look at the governing class, the elites for lack of a better term, in American politics. And he was able to say, “Hey, they’re all on the tape.” And they didn’t have a response to that. I think that’s too bad, because I’ve got nothing against talks at investment banks. In fact, I think the world’s a better place if you have these porous ideas that go from academia to investors and vice versa.

In fact, the point about the book is ultimately reinterpreting liberalism through the lens of cognitive science and arriving at pluralism, but a cognitive pluralism. And pluralism does not mean that it’s not that we all agree with something that we’re all open minded, it’s that we can allow differences and different ideas to clash. And in that tension, we can funnel and challenge that channel, that tension productively to arrive at a better place.

Rob Johnson:

Well, I have a lot of thoughts on that, but I always tell people… They say, “What design is supposed to do?” I said, “Foment critical discourse.” We don’t have a vision of it that we try to create that pluralistic and get everybody on stage, nobody’s shut out, open up the journals a little bit to foster that pluralism. I’ll also mention a book that I’ve mentioned several podcasts recently, it’s called The Recovery of Confidence and John W. Gardner. By the way, Chris Anderson’s wife was mentored by John W. Gardner, Jacqueline Novogratz who’s been a guest on this podcast.

But Gardner talked about the need to foster that discourse and that tension to create credibility and ultimate trust in governance. And he was writing after the period of the riots in the 60s. He had been the Secretary of Health, Education, and Welfare. And then with Dr. King’s murder, Bobby Kennedy’s murder, the 68 conventions and all of that turbulence, he was writing about what I might call the healing of a Republic that was in despair. He went right to the place you did.

The other thing I mentioned is I was listening to you. I was reminded, well, I have a home in Northern California and I knew a lot of the people around that early TED group. But what triggered me was when my children were in preschool, I heard Sir Kenneth Robinson speak and I read his book, which is called Out of Our Minds, that one in particular. And it was about the process of education, originally, looking at Britain, which was where he hailed from originally, was about working on the production line, but now the value added was knowledge, intensive creativity, and it required a whole different set of skills. And he told many stories in what… I don’t know what the ranking is. At all time, for many years, that was the number one most watched TED talk that I synthesized left and right and brought all these different dimensions together in the spirit of illuminating where we need to go into education.

Kenneth Cukier:

And that is exactly right. Sir Ken Robinson was a remarkable man, sadly, the late Sir Ken Robinson, because he passed away about 12 months ago. And I think everyone is touched by his famous account of the young girl who formal education is willing to give up on. And one psychologist says, “Now, listen to this place,” the music leaves the room and looks into the window and says, “She’s a dancer.” And it is beautiful. One thing that I think he didn’t explore, but I think a lot of people today would immediately think about and say, “I wonder she sounds cognitive atypical. She seems cognitively diverse.” Maybe she was autistic and that, that would explain why it was difficult for her to sit still in class. But why, when music played, she could do something with her body that was just transformative and touched people in a way that they couldn’t imagine being touched.

I like the idea of a world in which we see cognitive diversity, and particularly, I should say neuro diversity as a feature that we could learn from and become a better society from. In the book we don’t discuss that, but what we do talk about is the role of education and the role it could play for helping people to frame. Now, if I’ve mentioned what framing was, this idea of generating abstractions and a mental model of world that we can apply, the revolution that’s taking place right now is we can take this basic feature of cognition and turn it from an aspect of something that we do all the time to a tool we can deliberately use to improve how we mentally size up the world. And by framing things better or reframing when it must that we can generate new alternatives, different alternatives and therefore by increasing the range of choices, make better decisions and therefore get better outcomes in society.

And so you think about this and you say, “How would we do that in education?” And so the first thing we could say is, “Well, we actually do, do that.” And one place that we talk about as a vignette is the case study method. So Harvard Business School introduced the case study method exactly 100 years ago this year. And the reason why is that there was a new dean at the business school, who of course, was a good Harvard man, but if the school has only been around for a decade, what that meant is he went to Harvard Law School. And so the Harvard Law School had created the case study method in the 1880s for obvious reasons that hint is in the name, legal cases, he studied the cases.

And so before that, legal education had been just memorization, this is the Civil Code, this the Criminal Code going under Harvard voice and sing. Now, what it was, was actually classroom discussion and debate of the cases, state the case. Professor Langdell used to say… Christopher Langdell, of course, enshrined as the famous law school hall. So Dalton was his name, the dean of Harvard Law School says, “Well, we need cases here as well.” So he gets a professor to write different representative cases of business. What was interesting about the case study method at the outset was that they didn’t want the answer, what they wanted were the students to conceptualize the problem that’s going to be important, because you fast forward, now, basically 90 years, 80 years, you look around, but from the 80s to recently the case study method in some ways is very good teaching people different mental frames with which to apply, but also really bad because it presumes there’s one answer.

So Joel Podolny who was at Yale and became the youngest Dean of Yale, this is about 10 years ago, by the time he was 40, was revitalizing the Yale School of Management by not teaching the case study method with one professor and one answer, but with multiple teachers, he called it team teaching, in which they could all debate multiple frames, multiple ways of seeing the same problem. And the reason why it’s so important is that when you have a frame, you can literally put it through here and see different things. You have the same data, but the frame that you have gets you to see different alternatives and therefore different choices and therefore different outcomes.

So the case study method when taught in this way leads to a more richer way of seeing the world and coming up with answers to problems. A guy this creative is not going to stay long at Yale, although he’s being tipped for being a potential university president. Steve jobs, none other knocks on his door when his counselor comes back from a mission and tries to lure him to head up Apple University is successful and now Joel Podolny runs Apple University teaching this same approach of multiple ways of seeing problems and the tension that’s created and making that productive clash to Apple executives. Maybe it’s one of the reasons why Apple is doing so well.

Rob Johnson:

Again, going back to my time in finance, there was a famous economist who had been my teacher as an undergraduate at MIT named Rudiger Dornbusch. And he did some work with me and my colleagues. And he said to me one night, we were walking down the street and he says, “How is it that you guys get paid so much and I was your teacher?” And I said to him, I was being playful with him in it, and I said, “Rudy, you are very valuable, because you stretch the imagination, the range of things that we could imagine and consider.”

Our job is to pick the right model and both are valuable, but I guess the market is putting more energy on what you might call the right model. Well, the reason I bring that up is there’s a gentleman that you and I are both familiar with, who I’ve known somewhat, not deeply, but I’ve been inspired by named Peter Schwartz, who wrote a book called The Art of the Long View. And it was about, if you will, when you can’t know the model, but it might come into focus, there are ways to exercise the mind like Rudy Dornbusch did for us and stretch the imagination so that when something arrives, you’re there ready and sensitive to perceive it and integrate it into the adaptation of your model. And I know he’s worked in many different contexts with Shell Oil and with Salesforce and I’ve seen him at World Economic Forum and so forth. But I’m curious because you’ve written about him in this book, how Peter Schwartz fits into the story that you illuminate?

Kenneth Cukier:

Absolutely. Yeah. I’m so happy you asked that, because Peter is such a remarkable fellow and I was really pleased, in fact, honored that I could write about him and his work. In fact, you could say the history of my life has been trying to find ways to write about Peter Schwartz all throughout my career. And I’ve done it many times in my career, but this one caps it. And the reason why, in fact, it came out of a conversation we have at Davos in 2019 in which we were talking about Minority Report. And he reminded me something that I know, but I had forgotten, which was that he was asked by Steven Spielberg, who was a childhood acquaintance of his to create the setting of the film Minority Report.

And so he tells me the story at the Salesforce pavilion amid snowy Switzerland while we are gorging on chocolates. And it was so captivating that I said, “Peter, when are you in London so we can sit down and really thrash this out?” And he said, “Well, I’m going to be there next week, leaving Davos and heading to Buckingham Palace.” So there we were at The Economist headquarters in a private room with the recorder between us. And so we did a podcast on this and as well as the material for the book. And the story goes like this. So Peter Schwartz, people should know was at Shell and was doing scenario planning. He was the guy who started thinking of a scenario in which oil prices spiked outside of its normal range. And of course, there was the oil crisis.

He also had as one of their scenario, the idea that there would be the dissolution of the Soviet Union. Everyone thought he was mad, he was crazy, he was ridiculous, he looked like a Merlin, but without any. Soviet Union was in fact quite collapsing thereafter and he’s now held as a genius, put forward. So the scenario plan was this, if you’re going to create an imaginary world, you need to both think of it in terms of stretching your imagination and being creative of what would be and what is likely, but also live in a universe that’s highly bounded by constraints and in particular, by continuity. And getting that balance right is very, very difficult. And sometimes you have to fail, because of creative reasons.

So the first thing that you’re doing is you’re looking at the setting, the Minority Report by Philip K. Dick is only several pages long. So there is no setting there. So he has to create a world of what’s going to be 2050. And all the set designers want these monthly sets of Albert Speer black granite buildings of ministry of fear that are 80 feet tall and there’s no humans around except these small diminutive beings and images, this barren landscape of dark marble. And he says, “No, that’s not going to work.” He says, “It’s a national capital, Washington, DC. National capitals are preserved. They’re not just raised to the ground and built new.”

And the designer said, “What are you talking about? Why should that matter? This is the future, isn’t it?” And so all of the other geeks that were invited to a three day ideas summit at the Shutters Hotel in Santa Monica, just also jeered at the set designers and said, “No, don’t you understand a city has time depths? There’s buildings and structures that were created hundreds of years ago and there’s buildings and structures that were created just two or three years ago and they all have to coexist.” So, if you will, that was one of the areas which you had to have consistency.

And one of the great things about the film Minority Report is at the very beginning, you see Tom cruise and others descend down in jet packs, and where do they land? Wood frame and brick buildings in Georgetown in a playground. So it was that juxtaposition of the hyper modern, the hyper future in the setting of something that’s very familiar. That was so essential that they did that. And it was because they were in a world that was the counterfactuals that were constrained and were consistent. Now, where they had to break it is Schwartz does a beautiful job of recounting it to me. Stephen Spielberg says, “I got jet packs.” And Peter Schwartz says, “Steven, the physics is not going to give you jet packs.” And Steven Spielberg says, “Steven, in my film, my cops are going to have jet packs.”

And Steven Schwartz says, “If you’re Steven Spielberg, you’re cops get jet packs.” The other thing was that the car, that beautiful car, that’s now vertical and zipping around at tens of thousands of miles an hour, there was a problem. And that was, there needs to be a dashboard. And all the geeks said, “Well, it’s going to be self driving.” And Steven Spielberg said, “Well, I still need a dashboard.” He said, “But it’s going to be voice activated.” And Steven Spielberg said, “I still need a dashboard.” And they said, “Why do you need a dashboard if it’s self-driving and it’s voice activated?” And he said, “Because I’m making a film, I need some place for the character to look and I needs a place for the camera to point.”

And so hence you had to break that continuity in that counterfactual. But those are the ways in which if you will having a frame, which is the point of the vignette of Steven Spielberg, is important that when you are reframing that you can actually play with counterfactuals, but they have to be consistent with that.

Rob Johnson:

We’re coming back. Moving towards the latter parts of your book, I was reminded as I was reading the last chapter of another very human episode, some people I know well, were consulting with a Silicon Valley firm about their workforce, racial diversity, gender diversity and what have you, at the time, when this firm was creating AI algorithms to monitor people and detect who might become a criminal. So it was what you might call an early warning cinema system designed to protect society by catching ahead of the crew who should be watched. So weak out in the old westerns, head them off at the past so the crime never gets committed, the injury never is incurred.

But what happened was this wasn’t a human improvisational thing, this was a database created by white people. And in the algorithm, all kinds of probably unconscious not mean intent, but unconscious triggers, when the algorithm was tried, it encouraged law enforcement agencies to essentially hound and track black people. And what was interesting was my friends who were working on this could see the demoralization of the black employees and they were considering leaving and they were very vocal to these consultants. And the response was to actually have those people join the design team to inject that broader sensitivity and humanity.

So I’m trying to relate to your book, you’re not giving up the value of AI, but you’re humanizing the AI in a way that makes it serve mankind better. And I thought it was a fantastic experience. And your last chapter, I think it’s called Vigilance, jump off from there and tell me a little bit about what is your recommendation to all of us in light at the pinnacle of this book in that realm.

Kenneth Cukier:

Yeah. So that’s a beautiful that you shared. And I think that also shows a lot of wise management, shows a lot of patience and decency among the employees as well, because they could have petitioned management to discontinue doing this. I think both of those answers would have been insufficient although I can appreciate why people would embrace them. Far better is to engage and to say, “Okay, this is a problem, how can we fix this? What would be the solution? What role can I play?” And as you pointed out, bringing them into the design team is exactly right, it brings their frame, their diverse way of looking at the world into the product design and therefore into the outcome that’s going to be driven from it, because, of course, the question is, well, what was wrong in it?

And we should be very distilling in terms of where the problem is. Was the problem that we were actually trying to apply an algorithm to make a prediction of crime, maybe not, because, of course, we really want to use algorithms to predict things like cancer, just as Amazon likes to have algorithms predict what we’re going to purchase. So it’s a lot easier for us to find the books or to listen to music if we’ve got these predictive algorithms. So that’s not the problem. With the algorithm itself, in fact, you would say, oh, there was a problem with a bias in the algorithm, but I think that was a shorthand that you said, I think, if you thought about it and rewound. You’d say, “Well, that’s not really a problem per se, the algorithm wasn’t biased, the algorithm was just the algorithm.” In fact, the algorithm is just simply the mathematical representation of a formula that might probably be changed based on the data itself as these algorithms are, but it’s not the fault of the algorithm. The algorithm is fine.

The flaw is in the model and the model that the algorithm generated was flawed, because of something else and that was the underlying data. That data has an information quotient to it. Data is a representation of something that’s informational. It is always a mirror to the ground truth, it’s not the thing itself, it is the abstraction of the thing itself in the same way that the map is not territory. So if the data itself, the information quotient of the data is somehow wrong and biased, because there’s some implicit bias in society. For example, if you did it on arrest records, bookings or better yet even convictions, it would be completely wildly different.

A conviction doesn’t say that somebody did a crime. And it does say that somebody did a crime got caught, went through the judicial system and got sentence, right? There’s a lot of chains of causality in that. It’s because, of course, if you have a really good defensive lawyer or you’re the person who for whatever reason can talk your way out of getting brought to the station at the first instance, you’re not even going to get to that last stage. People who don’t have a lot of resources or might have the wrong color skin are going to get convicted as we know from the data at a great much higher rate than other classes, whether you’re wealthy or whether you’re white, you wouldn’t get to that point.

So the point is that the data itself was biased in some way and therefore when it generated the model, the model recreated that bias that was seen in society. So what do we do about that? So the idea of having a predictive algorithm that could identify where crime is, might be a really valuable tool when police forces are stretched and they need to focus their firearm where the resources are best put to keep our community safe. And that’s something that we should all sign up. For me, that sounds a very reasonable thing. Everyone has an interest in public safety as long as it’s done well under the rule of law and the constraints are put on our guardians in our community. It’s a never ending battle.

However, the idea of bringing those people in is really important. And so where we end the book framers is the idea of vigilance that we need to be masters of this technology, not our servants, that we need to embrace artificial intelligence, but we also need to embrace our humanity and impose our frames on it and direct it where it goes. At the same time, we need to live together and work together, but it’s not simply about cooperation, that’s the Yuval Harari story in which we all need to cooperate, we all need to get on the same page and see things the same way. And that is not what we are saying. We don’t need this homogeneity and uniformity of thought though we lock arms as brothers and sisters of our shared human experience and march into our future.

Kenneth Cukier:

Let us accept our differences. Let us accept the fact that you frame things differently than I frame things. And we should allow this flourishing of multiplicity of frames provided that your frame does not invalidate or try to deny the existence of my frame. That is the red line that we invoke like Karl Popper’s Paradox of Intolerance that we can’t broach, but barring that the fact that we don’t see things eye to eye, the fact that you interpret the world differently than I do is not a drawback, it’s actually a feature of our world. And the only way we’re going to solve our global problems together is if we can accept each other’s mutual frames and try to find in good faith a way to accommodate them so that we can solve our problems and integrate them for better decision making.

Rob Johnson:

I want to pick that up and go to a place that when you and I chatted for a few minutes before, is the relationship between the United States and China. The story I tell is that I believe it was in 2010, Zbigniew Brzezinski gave a speech, I believe in Montreal to the Council on Foreign Relations meeting there. And he said, “The great financial crisis has unmasked a failure in governance and the, what you might call, unfairness of some of the bailouts, particularly in the United States where people like Joseph Stiglitz said the polluters got paid.” He said, “It’s heightened everyone’s awareness to politics and the growth of the internet facilitates that.”

He said, “But now with everybody having suspicion discord and heightened awareness, we moved from a G7 world, which we might call a white, Judeo, Christian, advanced country governance to a G20 world where Eastern philosophy and Cartesian enlightenment and thinking are both at the head table, and how they decide together what to do to restore order in confidence is an overwhelming challenge.” Well, you and I talked a little bit about your work with Chatham House and work that I’ve done. We’ve got climate change on the horizon. We’ve got a world to manage what we’ve just been through a very stressful chapter that I would say Donald Trump accelerated.

But if you go back and look at the reports of the Council on Foreign Relations, the polarity vis-a-vis China was building in evidence in reports by gentlemen like Mr. Blackwell and others in 2014. So this clash that Orville Schell wrote about in his book, Wealth and Power, is coming up. You’re talking about people having different deep seated ways of perceiving, different, what you might call, models in their mind, but we need a model together. In light of your book, in light of the challenges between the United States and China and the necessity of collaboration, what do you recommend? How do we move forward?

Kenneth Cukier:

Well, certainly, we need to see a model together. We need a shared sense of purpose. I would question that to some degree. I think we need a model that suggests mutual coexistence, but I don’t think we need actual agreement. It’d be nice if we could agree on fundamental questions of decentralization of power, of the role of the private sector, of territory and diplomacy and interactions with neighbors. But it’s not certain that we’re going to get that. As you mentioned, I am on the board of directors of Chatham House and one of the things we do talk about is, well, what is our role, our purpose, we were founded 101 years ago in the ashes of World War I, and the purpose was to fuse a declining Britain to a rising America. The Council of Foreign Relations, which I’m also a member of, was founded at the same dinner in Paris at the Majestic Hotel in 1990. And, of course, created in 1920.

So when you think about it, we have these two great institutions that have to play a role. At Chatham House what we want to do is we want to be an interlocutor to both sides, to be a trusted intermediary, not to say that we don’t have our own values and our views, but then we want to play a cautious role. Actually, I speak for myself, because I don’t speak for the organization, but I advocate… I’m a militant for passivism, if you will. And I advocate that we play this role as an interlocutor for the purpose of peace. I think that piece is very fragile. I think that we haven’t had existentially serious conflict in our lifetimes. And as a result, we forget the ease with which violence can erupt and the terror with which you can sweep through very quickly.

And all we have to do is remember that in 1939, Polish Forces went to the front in cavalry on horseback, and six years later it all again were dropping atomic bomb on Japan to see the speed with which military thinking can go far beyond the mental models that we were in. So I’m very nervous about the risks of the international community to global order and to global peace and feel. It’s very important that we find a way to accommodate that and to live together. I think framing can play an important role in that by accepting the fact that you can have your frame and I can have my frame and that together, as long as we have good faith, that we accept each other’s legitimacy, cognitive and even existential legitimacy of being and sizing up the world and seeing it through this simulation and mental model, which is what the brain does, that we can actually come together and then work in the areas and solve the problems together where we can find common ground and work.

And that might be the environment, and it might be in other classical areas, counter terrorism, responding to a pandemic, while we also acknowledge that we see things fundamentally different in other ways and we’re going to have to accept that, and we’re going to have to live together on this planet. I think the problem is that when one frame tries to dominate another, that’s going to create a tension that, that it’s just harder to put the genie back into the bottle after she explodes out in ways that we can’t control. So I feel very passionately that, that is one of the essential risks of our time. And it’s important that we have a wisdom that is rare in politics and in foreign policy and in the public sphere to embrace these differences and strive for a pluralism of frames.

Rob Johnson:

It’s interesting. I recently met a gentlemen who goes by the name, Patrick Lawrence, and he wrote a book that I read in preparation called Somebody Else’s Century. And it was a prediction. I think he wrote the book in about 2011, about how the United States was not going to be able to impose its framework. And this is a man who had written books about Japan. He was a friend of Chalmers Johnson who wrote many books on Japan as well as about American military blowback nemesis and what have you, a book about meaty. But anyway, Patrick and I talked and this idea was whether it was in China or Japan or Korea, people from Eastern philosophy really do question, “Are these the things I want?” The things that they’re talking about is their success. I’m not sure if those are success from the way I see the world.

And I guess what I’m saying is from reading his book, I came with a deepening conviction that there is a challenge here and there is a confusion or a need for mutual respect so that those two models, those two different frames can continue to evolve in a constructive direction.

Kenneth Cukier:

When Lee Kuan Yew in the 90s came up with his idea of Asian values, he got derided by people in the west. And I think there was an irony in him putting it forward, because he played a role that was on the surface extraordinarily democratic and behind it extremely non democratic. But I lived for five years in Japan as the Tokyo correspondent, during the period of Fukushima among others. And I was struck by the degree to which the Japanese as a culture size of the world so differently, in particular, it’s a classic role of shareholders and shareholder rights and what is the value of the company and the obligations of a company to its employees and vice versa. And that’s helped color how I see the world that led to the book framers, because you can’t say that one is right or wrong, it’s simply a good fit for a given situation.

One frame might be legitimate frame, whereas in a given situation where it’s not in another. So even the flat earth frame is legitimate if what you want to do is measure a piece of furniture in your house or if you’re going to go and drive from here to the pharmacy down the street several miles away, you don’t really need to account for the curvature the earth. But, of course, if you want to send a rocket, a Saturn rocket fluttering off out of the atmosphere to land onto the moon, of course, you’re going to need not the flat earth frame but around earth. And that’s the purpose of what a frame is in the same way that Google Earth has all the information, but you don’t need it to drive from one place to another, Google Map, which separates all that information is a much narrower frame actually serves your function well.

So by that same token, the frames that we have, whether it’s a Japanese frame of shareholder rights, the American frame of a hurly-burly capitalism, a Chinese frame that is nervous and uncomfortable with disruption and decentralization, we should have a tolerance of the pluralism of frames and not try to aspire to a homogenization of frames, where we have to see things the same way. Because practically we’re not going to different people in different settings with different values. As long as this central value of accepting each other’s frame as legitimate and therefore as legitimate entities in the world, then we can actually co-exist and solve the problems where we can find agreement.

Rob Johnson:

Well, Ken, I know you host your own podcast called Babbage. And this book, people often ask me, “When you run a podcast, how do you figure out who should be the guests?” And I said, “I look for the people who address the most important questions.” Now that has something to do with what I sense are the most important question, but sometimes the person catches my fancy when I didn’t see it coming. But I want to say in preparing for this and studying your work and so forth, that I want myself and others start to follow your podcast, to follow your book, because you do seem to choose very important questions related to society’s challenges, the means of addressing it. You integrate them well, you and your co-authors and I really admire what you’re doing. So thank you for being my guests today. Thank you for sharing with our audience. And I look forward to both listening to you on your podcasts and perhaps creating another chapter somewhere down the road together.

Thank you, Rob. I really appreciate that. And it was an incredible honor to join you today. Of course, I know and I’m on your website all the time and I’m a great fan of Bill Janeway among others. He’s a mentor to me. And in fact, if you look in the acknowledgements, I was very proud that I actually could put him in the book in the acknowledgements because he is such an influence on me. But all of the work that you’re doing is brilliant. So thank you very much.

Rob Johnson:

Thank you. We’ll talk again soon.

Kenneth Cukier:

I hope so. Good. Thank you.

Rob Johnson:

And check out more from the Institute for New Economic Thinking at ineteconomics.org.