About ten years ago, IBM invited me to talk with some key members on the Watson team, when the triumph of creating a machine that could beat the best human players at the game show Jeopardy! was still fresh. I wrote in Forbes at the time that we were entering a new era of cognitive collaboration between humans, computers and other humans.
One thing that struck me was how similar the moment seemed to how aviation legend Chuck Yeager described the advent of flying-by-wire, four decades earlier, in which pilots no longer would operate aircraft, but interface with a computer that flew the plane. Many of the macho “flyboys” weren’t able to trust the machines and couldn’t adapt.
Now, with the launch of ChatGPT, Bill Gates has announced that the age of AI has begun and, much like those old flyboys, we’re all going to struggle to adapt. Our success will not only rely on our ability to learn new skills and work in new ways, but the extent to which we are able to trust our machine collaborators. To reach its potential, AI will need to become accountable.
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When’s the last time you changed your mind about anything substantial? Was it another person that convinced you or an unexpected experience that changed your perspective? What led you to stop seeing something one way and start seeing it in another? I’ll bet it doesn’t happen often. We rarely change our minds.
Now think about how much time we spend trying to change other people’s minds. From sales pitches and political discussions, to what we’re going to have for dinner and when the kids should go to bed, we put a lot of time and effort into shaping the opinions of others. Most of that is probably wasted.
The truth is that we can’t really change anyone’s mind. Only they can do that. Yet as David McRaney explains in his new book, How Minds Change, there are new techniques that can help us be more persuasive, but they don’t require brilliant sophistry or snappy rhetoric. They involve more listening than speaking, and understanding the context in which beliefs arise.
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When I first moved to Kyiv about 20 years ago, I met my friend Pavlo, who is from Belarus. Eventually our talk turned to that country’s leader, Alexander Lukashenko, and an incident in which he turned off the utilities at the US Ambassador’s residence, as well as those of other diplomats. It seemed totally outlandish and crazy to me.
“But he won,” Pavlo countered. I was incredulous, until he explained. “Lukashenko knows he’s a bastard and that the world will never accept him. In that situation all you can win is your freedom and that’s what he won.” It was a mode of thinking so outrageous and foreign to me that I could scarcely believe it.
Yet it opened my eyes and made me a more effective operator. We tend to think of empathy as an act of generosity, but it’s far more than that. Learning how to internalize diverse viewpoints is a skill we should learn not only because it helps make others more comfortable, but because it empowers us to successfully navigate an often complex and difficult world.
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There are a number of stories about what led Hans Lipperhey to submit a patent for the telescope in 1608. Some say that he saw two children playing with lenses in his shop who discovered that when they put one lens in front of each other they could see a weather vane across the street. Others say it was an apprentice that noticed the telescopic effect.
Yet the more interesting question is how such an important discovery could have such prosaic origins. Why was it that it was at that time that somebody noticed that looking through two lenses would magnify objects and not before? How could it have been that the discovery was made in a humble workshop and not by some great personage?
The truth is that history tends to converge and cascade around certain places and times, such as Cambridge before World War I, Vienna in the 1920s or, more recently, in Silicon Valley. In each case, we find that there were ecosystems that led to the inventions that changed the world. If we are going to build a more innovative economy, that’s where we need to focus.
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I still remember the excitement I felt seeing Kyiv, Ukraine for the first time in 2002. I had been living in Eastern Europe for five years by that time and had the privilege of witnessing first-hand how formerly communist countries moved boldly into a new future of peace and prosperity. Still, Kyiv was different somehow, bigger, more raw and bursting with potential.
An often repeated quip at the time was, “Ukraine is like Poland in 1993… and always will be.” Unlike the Visegrad countries of Poland, Czech, Slovakia and Hungary, Ukraine had been an actual Soviet Republic and the degree of institutional and societal rot created greater challenges. Kyiv in 2002 was, in many ways, a cynical place.
Today, no one can deny that a paradigm shift has occurred. No longer seen as a corrupt backwater, Ukraine has inspired the world with its ingenuity, humanity and courage. Its president, Volodomyr Zelensky, is an international hero. Yet the transformation, while still incomplete, didn’t come easily and it has important lessons that we can learn from.
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Anybody who has ever been married or had kids knows how difficult it can be to convince even a single person. To persuade dozens or hundreds—much less thousands or millions—to change their mind about something important seems like a pipe dream. Yet that doesn’t stop people from spending significant time and energy to do just that.
In fact, there is a massive industry dedicated to shaping opinions. Professionals research attitudes, identify “value propositions,” craft messages and leverage “influencers” in the hopes that they can get people to change their minds. Yet despite the billions of dollars invested each year, evidence of consistent success remains elusive.
The truth is that the best indicator of what people do and think is what the people around them do and think. Instead of trying to shape opinions, we need to shape networks. That’s why we need to focus our efforts on working to craft cultures rather than wordsmithing slogans. To do that, we need to understand the subtle ways we influence each other.
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Roger McNamee is one of the smartest investors in tech, seemingly always ahead of the curve. A long-time sounding board to Bill Gates he was an early investor in companies like Palm, Electronic Arts, and Facebook. He has also not hesitated to be fiercely critical, writing an unsparing book about the danger social media poses to democracy.
So his recent op-ed about “Big Tech’s Lost Decade” is something we should take seriously. McNamee points out that the enormous tech valuations—more than 1000 startups have been valued at over a billion dollars—is more due to a loose financial and regulatory environment than to significant innovation.
The signs have been there for awhile. I wrote about how the digital era was ending five years ago. Yet McNamee takes it further, calling for stricter regulation and a “transformation in culture, business models and industrial structure.” It seems that reckoning is approaching. Hopefully, it will make our economy safer, more equitable, innovative and productive.
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There’s no question we have entered a transformative age, with major shifts in technology, resources, demography and migration. Over the next decades, we will have to move from digital from post-digital, from carbon to zero-carbon and from the Boomer values to those of Millennials and Zoomers. Migration will strain societies’ social compact.
Unfortunately, we’re really bad at adapting to change. We’ve known about the climate threat for decades, but have done little about it. The digital revolution, for all the hoopla, has been a big disappointment, falling far short of its promise to change the world for the better. Even at the level of individual firms, McKinsey finds that the vast majority of initiatives fail.
One key factor is that we too often assume that change is inevitable. It’s not. Change dies every day. New ideas are weak, fragile, and in need of protection. If we’re going to bring about genuine transformation, we need to take that into account. The first step is to learn the reasons why change fails in the first place. These three are a good place to start.
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I have a friend who was once ambushed on a TV show panel. Being confronted with a clearly offensive remark, she was caught off-guard, said something that was probably unwise (but not untrue or unkind), and found herself at the center of a media-driven scandal. It would cost her enormously, both personally and professionally.
I often think about the episode and not just because it hurt my friend, but also because I wonder what I would have done if put in similar circumstances. My friend, who is black, muslim and female, is incredibly skilled at bridging differences and navigating matters of race, gender and religion. If she fell short, would I even stand a chance?
We are encouraged to think about matters of diversity in moral terms and, of course, that’s an important aspect. However, it is also a matter of developing the right skills. The better we are able to bridge differences, the more effectively we can collaborate with others who have different perspectives, which is crucial to becoming more innovative and productive.
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In 1954 the economist Paul Samuelson received a postcard from his friend Jimmie Savage asking, “ever hear of this guy?” The ”guy” in question was Louis Bachelier, an obscure mathematician who wrote a dissertation in 1900 that anticipated Einstein’s famous paper on Brownian motion published five years later.
The operative phrase in Bachelier’s paper, “the mathematical expectation of the speculator is zero,” was as powerful as it was unassuming. It implied that markets could be tamed using statistical techniques developed more than a century earlier and would set us down the path that led to the 2008 financial crisis.
For decades we’ve been trying to come up with algorithms to help us engineer our way out of uncertainty and they always fail for the same reason: the world is a messy place. Trusting our destiny to mathematical formulas does not eliminate human error, it merely gives preference to judgements encoded in systems beforehand over choices made by people in real time.
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