AI Superpowers

by Kai-Fu Lee

  As I’ve said before, some form of guaranteed income may be necessary to put an economic floor under everyone in society. But if we allow this to be the endgame, we miss out on the great opportunity presented to us by this technology. Instead of simply falling back on a painkiller like a UBI, we must proactively seek and find ways of utilizing AI to double-down on that which separates us from machines: love.

  Admittedly, this won’t be easy. It will require creative and different approaches. Executing on these approaches will take a lot of legwork and “heavy” solutions, reaching beyond the digital sphere and into the not-so-neat details of the real world. But if we commit to doing the hard work now, I believe we have a shot at not just avoiding disaster but of cultivating the same humanistic values that I rediscovered during my own encounter with mortality.

  MARKET SYMBIOSIS: OPTIMIZATION TASKS AND HUMAN TOUCH

  The private sector is leading the AI revolution, and, in my mind, it must also take the lead in creating the new, more humanistic jobs that power it. Some of these will emerge through the natural functioning of the free market, while others will require conscious efforts by those motivated to make a difference.

  Many of the jobs created by the free market will grow out of a natural symbiosis between humans and machines. While AI handles the routine optimization tasks, human beings will bring the personal, creative, and compassionate touch. This will involve the redefinition of existing occupations or the creation of entirely new professions in which people team up with machines to deliver services that are both highly efficient and eminently human. In the risk-of-replacement graphs from chapter 6, we expect to see the upper-left quadrant (“Human Veneer”) offer the greatest opportunity for human-AI symbiosis: AI will do the analytical thinking, while humans will wrap that analysis in warmth and compassion. In that same chart, the two quadrants on the right-hand side of the graph (“Slow Creep” and “Safe Zone”) also provide opportunities for AI tools to enhance creativity or decision-making, though over time, the two left-side AI-centric circles will grow toward the right as AI improves.

  Human–AI coexistence in the labor market

  A clear example of human-AI symbiosis for the upper-left-hand quadrant can be found in the field of medicine. I have little doubt that AI algorithms will eventually far surpass human doctors in their ability to diagnose disease and recommend treatments. Legacy institutions—medical schools, professional associations, and hospitals—may slow down the adoption of these diagnostic tools, using them only in narrow fields or strictly as reference tools. But in a matter of a few decades, I’m confident that the accuracy and efficiency gains will be so great that AI-driven diagnoses will take over eventually.

  One response to this would be to get rid of doctors entirely, replacing them with machines that take in symptoms and spit out diagnoses. But patients don’t want to be treated by a machine, a black box of medical knowledge that delivers a cold pronouncement: “You have fourth-stage lymphoma and a 70 percent likelihood of dying within five years.” Instead, patients will desire—and I believe the market will create—a more humanistic approach to medicine.

  Traditional doctors could instead evolve into a new profession, one that I’ll call a “compassionate caregiver.” These medical professionals would combine the skills of a nurse, medical technician, social worker, and even psychologist. Compassionate caregivers would be trained not just in operating and understanding the diagnostic tools but also in communicating with patients, consoling them in times of trauma, and emotionally supporting them throughout their treatment. Instead of simply informing patients of their objectively optimized chances of survival, they could share encouraging stories, saying “Kai-Fu had the same lymphoma as you and he survived, so I believe you can too.”

  These compassionate caregivers wouldn’t compete with machines in their ability to memorize facts or optimize treatment regimens. In the long run, that’s a losing battle. Compassionate caregivers would be well trained, but in activities requiring more emotional intelligence, not as mere vessels for the canon of medical knowledge. They would form a perfect complement to the machine, giving patients unparalleled accuracy in their diagnoses as well as the human touch that is so often missing from our hospitals today. In this human-machine symbiosis created by the free market, we would inch our society ahead in a direction of being a little kinder and a little more loving.

  Best of all, the emergence of compassionate caregivers would dramatically increase both the number of jobs and the total amount of medical care given. Today, the scarcity of trained doctors drives up the cost of healthcare and drives down the amount of quality care delivered around the world. Under current conditions of supply and demand, it’s simply not cost-feasible to increase the number of doctors. As a result, we strictly ration the care they deliver. No one wants to go wait in line for hours just to have a few minutes with a doctor, meaning that most people only go to hospitals when they feel it’s absolutely necessary. While compassionate caregivers will be well-trained, they can be drawn from a larger pool of workers than doctors and won’t need to undergo the years of rote memorization that is required of doctors today. As a result, society will be able to cost-effectively support far more compassionate caregivers than there are doctors, and we would receive far more and better care.

  Similar synergies will emerge in many other fields: teaching, law, event planning, and high-end retail. Paralegals at law firms could hand their routine research tasks off to algorithms and instead focus on communicating more with clients and making them feel cared for. AI-powered supermarkets like the Amazon Go store may not need cashiers anymore, so they could greatly upgrade the customer experience by hiring friendly concierges like the one I described in chapter 5.

  For those in professional sectors, it will be imperative that they adopt and learn to leverage AI tools as they arrive. As with any technological revolution, many workers will find the new tools both imperfect in their uses and potentially threatening in their implications. But these tools will only improve with time, and those who seek to compete against AI on its own terms will lose out. In the long run, resistance may be futile, but symbiosis will be rewarded.

  Finally, the internet-enabled sharing economy will contribute significantly to alleviating job losses and redefining work for the AI age. We’ll see more people step out of traditional careers that are being taken over by algorithms, instead using new platforms that apply the “Uber model” to a variety of services. We see this already in Care.com, an online platform for connecting caregivers and customers, and I believe we will see a blossoming of analogous models in education and other fields. Many mass-market goods and services will be captured by data and optimized by algorithms, but some of the more piecemeal or personalized work within the sharing economy will remain the exclusive domain of humans.

  In the past, this type of work was constrained by the bureaucratic costs of running a vertical company that attracted customers, dispatched workers, and kept everyone on the payroll even when there wasn’t work to be done. The platformatization of these industries dramatically increases their efficiency, increasing total demand and take-home pay for the service workers themselves. Adding AI to the equation—as ride-hailing companies like Didi and Uber have already done—will only further boost efficiency and attract more workers.

  Beyond the established roles in the sharing economy, I’m confident we will see entirely new service jobs emerge that we can hardly imagine today. Explain to someone in the 1950s what a “life coach” was and they’d probably think you were goofy. Likewise, as AI frees up our time, creative entrepreneurs and ordinary people will leverage these platforms to create new kinds of jobs. Perhaps people will hire “season changers” who redecorate their closets every few months, scenting them with flowers and aromas that match the mood of the season. Or environmentally conscious families will hire “home sustainability consultants” to meet with the family and explore creative and fun ways for the household to reduce its environm
ental footprint.

  But despite all these new possibilities created by profit-seeking businesses, I’m afraid the operations of the free market alone will not be enough to offset the massive job losses and gaping inequality on the horizon. Private companies already create plenty of human-centered service jobs—they just don’t pay well. Economic incentives, public policies, and cultural dispositions have meant that many of the most compassion-filled professions existing today often lack job security or basic dignity.

  The U.S. Bureau of Labor Statistics has found that home health aides and personal care aides are the two fastest growing professions in the country, with an expected growth of 1.2 million jobs by 2026. But annual income in these professions averages just over $20,000. Other humanistic labors of love—stay-at-home parenting, caring for aging or disabled relatives—aren’t even considered a “job” and receive no formal compensation.

  These are exactly the kinds of loving and compassionate activities that we should embrace in the AI economy, but the private sector has proven inadequate so far at fostering them. There may come a day when we enjoy such material abundance that economic incentives are no longer needed. But in our present economic and cultural moment, money still talks. Orchestrating a true shift in culture will require not just creating these jobs but turning them into true careers with respectable pay and greater dignity.

  Encouraging and rewarding these prosocial activities means going beyond the market symbiosis of the private sector. We will need to reenergize these industries through service sector impact investing and government policies that nudge forward a broader shift in cultural values.

  FINK’S LETTER AND THE NEW IMPACT INVESTING

  When a man overseeing $5.7 trillion speaks, the global business community tends to listen. So when BlackRock founder Larry Fink, head of the world’s largest asset management company, posted a letter to CEOs demanding greater attention to social impact, it sent shockwaves through corporations around the globe. In the letter, titled “A Sense of Purpose,” Fink wrote,

  We . . . see many governments failing to prepare for the future, on issues ranging from retirement and infrastructure to automation and worker retraining. As a result, society increasingly is turning to the private sector and asking that companies respond to broader societal challenges. . . . Society is demanding that companies, both public and private, serve a social purpose. . . . Companies must benefit all of their stakeholders, including shareholders, employees, customers, and the communities in which they operate.

  Fink’s letter dropped just days before the 2018 World Economic Forum, an annual gathering of the global financial elite in Davos, Switzerland. I was attending the forum and watched as CEOs anxiously discussed the stern warning from a man whose firm controlled substantial ownership stakes in their companies. Many publicly professed sympathy for Fink’s message but privately declared his emphasis on broader social welfare to be anathema to the logic of private enterprise.

  Looked at narrowly enough, they’re right: publicly traded companies are in it to win it, bound by fiduciary duties to maximize profits. But in the age of AI, this cold logic of dollars and cents simply can’t hold. Blindly pursuing profits without any thought to social impact won’t just be morally dubious; it will be downright dangerous.

  Fink referenced automation and job retraining multiple times in his letter. As an investor with interests spanning the full breadth of the global economy, he sees that dealing with AI-induced displacement is not something that can be left entirely up to free markets. Instead, it is imperative that we reimagine and reinvigorate corporate social responsibility, impact investing, and social entrepreneurship.

  In the past, these were the kinds of things that businesspeople merely dabbled in when they had time and money to spare. Sure, they think, why not throw some money into a microfinance startup or buy some corporate carbon offsets so we can put out a happy press release touting it. But in the age of AI, we will need to seriously deepen our commitment to—and broaden our definition of—these activities. Whereas these have previously focused on feel-good philanthropic issues like environmental protection and poverty alleviation, social impact in the age of AI must also take on a new dimension: the creation of large numbers of service jobs for displaced workers.

  As a venture-capital investor, I see a particularly strong role for a new kind of impact investing. I foresee a venture ecosystem emerging that views the creation of humanistic service-sector jobs as a good in and of itself. It will steer money into human-focused service projects that can scale up and hire large numbers of people: lactation consultants for postnatal care, trained coaches for youth sports, gatherers of family oral histories, nature guides at national parks, or conversation partners for the elderly. Jobs like these can be meaningful on both a societal and personal level, and many of them have the potential to generate real revenue—just not the 10,000 percent returns that come from investing in a unicorn technology startup.

  Kick-starting this ecosystem will require a shift in mentality for VCs who participate. The very idea of venture capital has been built around high risks and exponential returns. When an investor puts money into ten startups, they know full well that nine of them most likely will fail. But if that one success story turns into a billion-dollar company, the exponential returns on that one investment make the fund a huge success. Driving those exponential returns are the unique economics of the internet. Digital products can be scaled up infinitely with near-zero marginal costs, meaning the most successful companies achieve astronomical profits.

  Service-focused impact investing, however, will need to be different. It will need to accept linear returns when coupled with meaningful job creation. That’s because human-driven service jobs simply cannot achieve these exponential returns on investment. When someone builds a great company around human care work, they cannot digitally replicate these services and blast them out across the globe. Instead, the business must be built piece by piece, worker by worker. The truth is, traditional VCs wouldn’t bother with these kinds of linear companies, but these companies will be a key pillar in building an AI economy that creates new jobs and fosters human connections.

  There will of course be failures, and returns will never match pure technology VC funds. But that should be fine with those involved. The ecosystem will likely be staffed by older VC executives who are looking to make a difference, or possibly by younger VC types who are taking a “sabbatical” or doing “pro bono” work. They will bring along their keen instincts for picking entrepreneurs and building companies, and will put them to work on these linear service companies. The money behind the funds will likely come from governments looking to efficiently generate new jobs, as well as companies doing corporate social responsibility.

  Together, these players will create a unique ecosystem that is much more jobs-focused than pure philanthropy, much more impact-focused than pure venture capital. If we can pull together these different strands of socially conscious business, I believe we’ll be able to weave a new kind of employment safety net, all while building communities that foster love and compassion.

  BIG CHANGES AND BIG GOVERNMENT

  And yet, for all the power of the private market and the good intentions of social entrepreneurs, many people will still fall through the cracks. We need look no further than the gaping inequality and destitute poverty in so much of the world today to recognize that markets and moral imperatives are not enough. Orchestrating a fundamental change in economic structures often requires the full force of governmental power. If we hope to write a new social contract for the age of AI, we will need to pull on the levers of public policy.

  There are some in Silicon Valley who see this as the point where UBI comes into play. Faced with inadequate job growth, the government must provide a blanket guarantee of economic security, a cash transfer that can save displaced workers from destitution and which will also save the tech elite from having to do anything else about it.

  The unconditiona
l nature of the transfer fits with the highly individualistic, live-and-let-live libertarianism that undergirds much of Silicon Valley. Who is the government, UBI proponents ask, to tell people how to spend their time? Just give them the money and let them figure it out on their own. It’s an approach that matches how the tech elite tend to view society as a whole. Looking outward from Silicon Valley, they often see the world in terms of “users” rather than citizens, customers rather than members of a community.

  I have a different vision. I don’t want to live in a society divided into technological castes, where the AI elite live in a cloistered world of almost unimaginable wealth, relying on minimal handouts to keep the unemployed masses sedate in their place. I want to create a system that provides for all members of society, but one that also uses the wealth generated by AI to build a society that is more compassionate, loving, and ultimately human.

  Achieving this outcome will definitely require creative thinking and complex policymaking, but the inspiration driving that process often comes from unlikely places. For me, it began back at Fo Guang Shan, the monastery in Taiwan that I discussed in the previous chapter.

  THE CHAUFFEUR CEO

  The morning sun had not yet crept over the horizon as I walked across the monastery’s massive grounds to see Master Hsing Yun. It was the morning on which I’d been given a chance to have breakfast with the head monk, and I was hustling my way up a hill when a golf cart pulled up alongside me.