By Kai-Fu Lee | 12 October 2018
While I was undergoing chemotherapy for my cancer in Taiwan, an old friend of mine who is a serial entrepreneur came to me with a problem at his latest startup. He had already founded and sold off several successful consumer technology companies, but as he grew older he wanted to do something more meaningful, that is, he wanted to build a product that would serve the people that technology startups had often ignored. Both my friend and I were entering the age at which our parents needed more help going about their daily lives, and he decided to design a product that would make life easier for the elderly.
What he came up with was a large touchscreen mounted on a stand that could be placed next to an elderly person’s bed. On the screen were a few simple and practical apps connected to services that elderly people could use: ordering food delivery, playing their favorite soap operas on the TV, calling their doctor, and more. Older people often struggle to navigate the complexities of the internet or to manipulate the small buttons of a smartphone, so my friend made everything as simple as possible. All the apps required just a couple of clicks, and he even included a button that let the elderly users directly call up a customer-service agent to guide them through using their device.
It sounded like a wonderful product, one that would have a real market right now. Sadly, there are many adult children in China and elsewhere who are too busy with work to devote time to taking care of their aging parents. They may experience a sense of guilt about the importance of filial piety, but when it comes down to it, they just don’t feel they can find the time to care for their parents in an adequate way. The touchscreen would make for a nice substitute.
But after deploying a trial version of his product, my friend discovered he had a problem. Of all the functions available on the device, the one that received by far the most use wasn’t the food delivery, TV controls, or doctor’s consultation. It was the customer-service button. The company’s customer-service representatives found themselves overwhelmed by a flood of incoming calls from the elderly. What was going on here? My friend had made the device as simple as possible to use — were his users still unable to navigate the one-click process onscreen?
Not at all. After consulting with the customer-service representatives, he found that people weren’t calling in because they couldn’t navigate the device. They were calling simply because they were lonely and wanted someone to talk to. Many of the elderly users had children who worked to ensure that all of their material needs were met: meals were delivered, doctors’ appointments were arranged, and prescriptions were picked up. But once those material needs were taken care of, what these people wanted more than anything was true human contact, another person to trade stories with and relate to.
My friend relayed this “problem” to me just as I was waking up to my own realizations about the centrality of love to the human experience. If he had come to me just a few years earlier, I likely would have recommended some technical fix, maybe something like an AI chat bot that could simulate a basic conversation well enough to fool the human on the other end. But as I recovered from my illness and awakened to the looming AI crises of jobs and meaning, I began to see things differently.
In that touchscreen device and that unmet desire for human contact, I saw the first sketches of a blueprint for coexistence between people and artificial intelligence. Yes, intelligent machines will increasingly be able to do our jobs and meet our material needs, disrupting industries and displacing workers in the process. But there remains one thing that only human beings are able to create and share with one another: love.
With all of the advances in machine learning, the truth remains that we are still nowhere near creating AI machines that feel any emotions at all. Can you imagine the elation that comes from beating a world champion at the game you’ve devoted your whole life to mastering? AlphaGo did just that, but it took no pleasure in its success, felt no happiness from winning, and had no desire to hug a loved one after its victory. Despite what science-fiction films like Her — in which a man and his artificially intelligent computer operating system fall in love — portray, AI has no ability or desire to love or be loved.
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, humans will bring the personal, creative, and compassionate touch.
— Kai-Fu Lee (@kaifulee) March 12, 2019
It is in this uniquely human potential for growth, compassion, and love where I see hope. I firmly believe we must forge a new synergy between artificial intelligence and the human heart, and look for ways to use the forthcoming material abundance generated by artificial intelligence to foster love and compassion in our societies.
The challenges before us remain immense. Within fifteen years, I predict that we will technically be able to automate 40 to 50 percent of all jobs in the United States. That does not mean all of those jobs will disappear overnight, but if the markets are left to their own devices, we will begin to see massive pressure on working people.
Techno-optimists will point to history, citing the Industrial Revolution and the nineteenth-century textile industry as “proof” that things always work out for the best. But as we’ve seen, this argument stands on increasingly shaky ground. The coming scale, pace, and skill-bias of the AI revolution mean that we face a new and historically unique challenge.
We are already witnessing the way that stagnant wages and growing inequality can lead to political instability and even violence. As AI rolls out across our economies and societies, we risk aggravating and quickening these trends.
Building societies that thrive in the age of AI will require substantial changes to our economy but also a shift in culture and values. Centuries of living within the industrial economy have conditioned many of us to believe that our primary role in society (and even our identity) is found in productive, wage-earning work. Take that away and you have broken one of the strongest bonds between a person and his or her community. As we transition from the industrial age to the AI age, we will need to move away from a mindset that equates work with life or treats humans as variables in a grand productivity optimization algorithm. Instead, we must move toward a new culture that values human love, service, and compassion more than ever before.
No economic or social policy can “brute force” a change in our hearts. But in choosing different policies, we can reward different behaviors and start to nudge our culture in different directions. We can choose a purely technocratic approach — one that sees each of us as a set of financial and material needs to be satisfied — and simply transfer enough cash to all people so that they don’t starve or go homeless. In fact, this notion of universal basic income seems to be becoming more and more popular these days.
But in making that choice I believe we would both devalue our own humanity and miss out on an unparalleled opportunity.
I propose we explore the creation not of a universal basic income but of what I call a social investment stipend. The stipend would be a decent government salary given to those who invest their time and energy in those activities that promote a kind, compassionate, and creative society. These would include three broad categories: care work, community service, and education.
These would form the pillars of a new social contract, one that valued and rewarded socially beneficial activities in the same way we currently reward economically productive activities. The stipend would not substitute for a social safety net — the traditional welfare, healthcare, or unemployment benefits to meet basic needs — but would offer a respectable income to those who choose to invest energy in these socially productive activities. Today, social status is still largely tied to income and career advancement. Endowing these professions with respect will require paying them a respectable salary and offering the opportunity for advancement like a normal career. If executed well, the social investment stipend would nudge our culture in a more compassionate direction. It would put the economic bounty of AI to work in building a better society, rather than just numbing the pain of AI-induced job losses.
Each of the three recognized categories — care, service, and education — would encompass a wide range of activities, with different levels of compensation for full- and part-time participation. Care work could include parenting of young children, attending to an aging parent, assisting a friend or family member dealing with illness, or helping someone with mental or physical disabilities live life to the fullest. Service work would be similarly broadly defined, and tasks could include performing environmental remediation, leading afterschool programs, guiding tours at national parks, or collecting oral histories from elders in our communities. Education could range from professional training for the jobs of the AI age to taking classes that could transform a hobby into a career.
Providing a stipend in exchange for participation in prosocial activities reinforces a clear message: It took efforts from people all across society to help us reach this point of economic abundance. We are now collectively using that abundance to recommit ourselves to one another, reinforcing the bonds of compassion and love that make us human.
In an age in which intelligent machines have supplanted us as the cogs and gears in the engine of our economy, I hope that we will value all of these pursuits — care, service, and personal cultivation — as part of our collective social project of building a more human society.
Kai-Fu Lee is the author of AI SUPERPOWERS: China, Silicon Valley, and the New World Order, from which this article is excerpted.
Reprinted with permission from the author.
— Machine Learning FLX (@machinelearnflx) March 8, 2019
A Conversation With Kai-Fu Lee – Edge
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