In a 2015 poll, 30% of Republicans and 19% of Democrats supported bombing Agrabah, the fictional hometown of the Disney character Aladdin. In a similar vein, a 2014 poll found that the less people knew about where Ukraine is located on a map, the more they wanted the U.S. to intervene militarily.
To make matters worse, another study done by researchers at Ohio State University found that when confronted with scientific evidence that conflicted with their pre-existing views, such as the reality of climate change or the safety of vaccines, partisans would not only reject the evidence, but become hostile and question the objectivity of science.
It’s become fashionable in certain circles to dismiss experts. Yet as the Coronavirus crisis has shown us, we ignore expertise at our peril. The reason we need professionals with specialized knowledge, however, isn’t so that we can outsource our decisions to them. Rather, we need experts to help us ask better questions, explore options and to make better judgments.
There’s a passage in Ernest Hemingway’s 1925 novel, The Sun Also Rises, in which a character is asked how he went bankrupt. “Two ways,” he answers. “Gradually, then suddenly.” The quote has since become emblematic of how a crisis takes shape. First with small signs you hardly notice and then with shocking impact.
That’s certainly how it felt to me in November, 2008, when I was leading a media company in Kyiv. By that time, the financial crisis was going full throttle, although things had been relatively calm in our market. Ukraine had been growing briskly in recent years and, while we expected a slowdown, we didn’t expect a crash.
Those illusions were soon shattered. Ad sales in Ukraine would eventually fall by a catastrophic 85%, while overall GDP would be down 14%. It was, to say the least, the worst business crisis I had ever encountered. In many ways, our business never really recovered, but the lessons I learned while managing through it will last a lifetime.
In a 2015 TED talk, Bill Gates warned that “if anything kills ten million people in the next few decades, it’s most likely to be a highly infectious virus rather than a war. Not missiles, but microbes.” He went on to point out that we have invested enormous amounts of money in nuclear deterrents, but relatively little to battle epidemics.
It’s an apt point. In the US, we enthusiastically spend nearly $700 billion on our military, but cut corners on nearly everything else. Major breakthroughs, such as GPS satellites, the Internet and transistors, are merely offshoots of budgets intended to help us fight wars more effectively. At the same time, politicians gleefully propose budget cuts to the NIH.
A crisis, in one sense, is like anything else. It eventually ends and, when it does, we hope to be wiser for it. No one knows how long this epidemic will last or what the impact will be, but one thing is for sure — it will not be our last crisis. We should treat this as a new Sputnik moment and prepare for the next crisis with the same vigor with which we prepare for war.
When we think of great leaders their great successes usually come to mind. We picture Washington crossing the Delaware or Gandhi leading massive throngs or Steve Jobs standing triumphantly on stage. It is moments of triumph such as these that make indelible marks on history’s consciousness.
While researching my book, Cascades, however, what struck me most is how often successful change movements began with failure. It seems that those later, more triumphant moments can blind us to the struggles that come before. That can give us a mistaken view of what it takes to drive transformational change.
To be clear, these early and sometimes tragic failures are not simply the result of bad luck. Rather they happen because most new leaders are not ready to lead and make novice mistakes. The difference, I have found, between truly transformational leaders and those that fail isn’t so much innate talent or even ambition, but their ability to learn along the way.
A 2019 study by the Brookings Institution found that over 61% of jobs will be affected by automation. That comes on the heels of a 2017 report from the McKinsey Global Institute that found that 51% of total working hours and $2.7 trillion dollars in wages are highly susceptible to automation and a 2013 Oxford study that found 47% of jobs will be replaced.
The future looks pretty grim indeed until you start looking at jobs that have already been automated. Fly-by-wire was introduced in 1968, but today we’re facing a massive pilot shortage. The number of bank tellers has doubled since ATMs were introduced. Overall, the US is facing a massive labor shortage.
In fact, although the workforce has doubled since 1970, labor participation rates have risen by more than 10% since then. Everywhere you look, as automation increases, so does the demand for skilled humans. So the challenge ahead isn’t so much finding work for humans, but to prepare humans to do the types of work that will be in demand in the years to come.
In the 1960s, the federal government accounted for more than 60% of all research funding, yet by 2016 that had fallen to just over 20%. During the same time, businesses’ share of R&D investment more than doubled from about 30% to almost 70%. Government’s role in US innovation, it seems, has greatly diminished.
Yet new research suggests that the opposite is actually true. Analyzing all patents since 1926, researchers found that the number of patents that relied on government support has risen from 12% in the 1980s to almost 30% today. Interestingly, the same research found that startups benefitted the most from government research.
As we struggle to improve productivity from historical lows, we need the public sector to play a part. The truth is that the government has a unique role to play in driving innovation and research is only part of it. In addition to funding labs and scientists, it can help bring new ideas to market, act as a convening force and offer crucial expertise to private businesses.
When Lou Gerstner took over at IBM in 1993, the century-old tech giant was in dire straits. Overtaken by nimbler upstarts, like Microsoft in software, Compaq in hardware and Intel in microprocessors, it was hemorrhaging money. Many believed that it needed to be broken up into smaller, more focused units in order to compete.
Yet Gerstner saw it differently and kept the company intact, which led to one of the most dramatic turnarounds in corporate history. Today, more than a quarter century later, while many of its formal rivals have long since disappeared IBM is still profitable and on the cutting edge of many of the most exciting technologies.
That success was no accident. In researching my book, Cascades, I studied not only business transformations, but many social and political movements as well. What I found is that while most change efforts fail, the relatively few that succeed follow a pattern that is amazingly consistent. If you want to create change that lasts, here’s what you need to do.
We take it for granted that we’re supposed to act ethically and, usually, that seems pretty simple. Don’t lie, cheat or steal, don’t hurt anybody on purpose and act with good intentions. In some professions, like law or medicine, the issues are somewhat more complex and practitioners are trained to make good decisions.
Yet ethics in the more classical sense isn’t so much about doing what you know is right, but thinking seriously about what the right thing is. Unlike the classic “ten commandments” type of morality, there are many situations that arise in which determining the right action to take is far from obvious.
Today, as our technology becomes vastly more powerful and complex, ethical issues are increasingly rising to the fore. Over the next decade we will have to build some consensus on issues like what accountability a machine should have and to what extent we should alter the nature of life. The answers are far from clear-cut, but we desperately need to find them.
In 2011, technology pioneer Marc Andreessen declared that software is eating the world. “With lower start-up costs and a vastly expanded market for online services,” he wrote, “the result is a global economy that for the first time will be fully digitally wired — the dream of every cyber-visionary of the early 1990s, finally delivered, a full generation later.
Yet as Derek Thompson recently pointed out in The Atlantic, the euphoria of Andreessen and his Silicon Valley brethren seems to have been misplaced. Former unicorns like Uber, Lyft, and Peloton have seen their value crash, while WeWork saw its IPO self-destruct. Hardly “the dream of every cyber-visionary.”
The truth is that we still live in a world of atoms, not bits and most of the value is created by making things we live in, wear, eat and ride in. For all of the tech world’s astounding success, it still makes up only a small fraction of the overall economy. So taking a software centric view, while it has served Silicon Valley well in the past, may be its Achilles heel in the future.
In 1977, Ken Olsen, the founder and CEO of Digital Equipment Corporation, reportedly said, “There is no reason for any individual to have a computer in his home.” It was an amazingly foolish thing to say and, ever since, observers have pointed to Olsen’s comment to show how supposed experts can be wildly wrong.
The problem is that Olsen was misquoted. In fact, his company was actually in the business of selling personal computers and he had one in his own home. This happens more often than you would think. Other famous quotes, such IBM CEO Thomas Watson predicting that there would be a global market for only five computers, are similarly false.
There is great fun in bashing experts, which is why so many inaccurate quotes get repeated so often. If the experts are always getting it wrong, then we are liberated from the constraints of expertise and the burden of evidence. That’s the hard thing about hard facts. They can be so elusive that it’s easy to believe doubt their existence. Yet they do exist and they matter.
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