Even if we could constantly invent new jobs and retrain the workforce, we may wonder whether the average human will have the emotional stamina necessary for a life of such endless upheavals. Change is always stressful, and the hectic world of the early twenty-first century has produced a global epidemic of stress.21 As the volatility of the job market and of individual careers increases, would people be able to cope? We would probably need far more effective stress-reduction techniques – ranging from drugs through neuro-feedback to meditation – to prevent the Sapiens mind from snapping. By 2050 a ‘useless’ class might emerge not merely because of an absolute lack of jobs or lack of relevant education, but also because of insufficient mental stamina.
Obviously, most of this is just speculation. At the time of writing – early 2018 – automation has disrupted many industries but it has not resulted in massive unemployment. In fact, in many countries, such as the USA, unemployment is at a historical low. Nobody can know for sure what sort of impact machine learning and automation will have on different professions in the future, and it is extremely difficult to estimate the timetable of relevant developments, especially as they depend on political decisions and cultural traditions as much as on purely technological breakthroughs. Thus even after self-driving vehicles prove themselves safer and cheaper than human drivers, politicians and consumers might nevertheless block the change for years, perhaps decades.
However, we cannot allow ourselves to be complacent. It is dangerous just to assume that enough new jobs will appear to compensate for any losses. The fact that this has happened during previous waves of automation is absolutely no guarantee that it will happen again under the very different conditions of the twenty-first century. The potential social and political disruptions are so alarming that even if the probability of systemic mass unemployment is low, we should take it very seriously.
In the nineteenth century the Industrial Revolution created new conditions and problems that none of the existing social, economic and political models could cope with. Feudalism, monarchism and traditional religions were not adapted to managing industrial metropolises, millions of uprooted workers, or the constantly changing nature of the modern economy. Consequently humankind had to develop completely new models – liberal democracies, communist dictatorships and fascist regimes – and it took more than a century of terrible wars and revolutions to experiment with these models, separate the wheat from the chaff, and implement the best solutions. Child labour in Dickensian coal mines, the First World War and the Great Ukrainian Famine of 1932–3 constituted just a small part of the tuition fees humankind paid.
The challenge posed to humankind in the twenty-first century by infotech and biotech is arguably much bigger than the challenge posed in the previous era by steam engines, railroads and electricity. And given the immense destructive power of our civilisation, we just cannot afford more failed models, world wars and bloody revolutions. This time around, the failed models might result in nuclear wars, genetically engineered monstrosities, and a complete breakdown of the biosphere. Consequently, we have to do better than we did in confronting the Industrial Revolution.
From exploitation to irrelevance
Potential solutions fall into three main categories: what to do in order to prevent jobs from being lost; what to do in order to create enough new jobs; and what to do if, despite our best efforts, job losses significantly outstrip job creation.
Preventing job losses altogether is an unattractive and probably untenable strategy, because it means giving up the immense positive potential of AI and robotics. Nevertheless, governments might decide to deliberately slow down the pace of automation, in order to lessen the resulting shocks and allow time for readjustments. Technology is never deterministic, and the fact that something can be done does not mean it must be done. Government regulation can successfully block new technologies even if they are commercially viable and economically lucrative. For example, for many decades we have had the technology to create a marketplace for human organs, complete with human ‘body farms’ in underdeveloped countries and an almost insatiable demand from desperate affluent buyers. Such body farms could well be worth hundreds of billions of dollars. Yet regulations have prevented free trade in human body parts, and though there is a black market in organs, it is far smaller and more circumscribed than what one could have expected.22
Slowing down the pace of change may give us time to create enough new jobs to replace most of the losses. Yet as noted earlier, economic entrepreneurship will have to be accompanied by a revolution in education and psychology. Assuming that the new jobs won’t be just government sinecures, they will probably demand high levels of expertise, and as AI continues to improve, human employees will need to repeatedly learn new skills and change their profession. Governments will have to step in, both by subsidising a lifelong education sector, and by providing a safety net for the inevitable periods of transition. If a forty-year-old ex-drone pilot takes three years to reinvent herself as a designer of virtual worlds, she may well need a lot of government help to sustain herself and her family during that time. (This kind of scheme is currently being pioneered in Scandinavia, where governments follow the motto ‘protect workers, not jobs’.)
Yet even if enough government help is forthcoming, it is far from clear whether billions of people could repeatedly reinvent themselves without losing their mental balance. Hence, if despite all our efforts a significant percentage of humankind is pushed out of the job market, we would have to explore new models for post-work societies, post-work economies, and post-work politics. The first step is to honestly acknowledge that the social, economic and political models we have inherited from the past are inadequate for dealing with such a challenge.
Take, for example, communism. As automation threatens to shake the capitalist system to its foundation, one might suppose that communism could make a comeback. But communism was not built to exploit that kind of crisis. Twentieth-century communism assumed that the working class was vital for the economy, and communist thinkers tried to teach the proletariat how to translate its immense economic power into political clout. The communist political plan called for a working-class revolution. How relevant will these teachings be if the masses lose their economic value, and therefore need to struggle against irrelevance rather than against exploitation? How do you start a working-class revolution without a working class?
Some may argue that humans could never become economically irrelevant, because even if they cannot compete with AI in the workplace, they will always be needed as consumers. However, it is far from certain that the future economy will need us even as consumers. Machines and computers could do that too. Theoretically, you can have an economy in which a mining corporation produces and sells iron to a robotics corporation, the robotics corporation produces and sells robots to the mining corporation, which mines more iron, which is used to produce more robots, and so on. These corporations can grow and expand to the far reaches of the galaxy, and all they need are robots and computers – they don’t need humans even to buy their products.
Indeed, already today computers and algorithms are beginning to function as clients in addition to producers. In the stock exchange, for example, algorithms are becoming the most important buyers of bonds, shares and commodities. Similarly in the advertisement business, the most important customer of all is an algorithm: the Google search algorithm. When people design Web pages, they often cater to the taste of the Google search algorithm rather than to the taste of any human being.
Algorithms obviously have no consciousness, so unlike human consumers, they cannot enjoy what they buy, and their decisions are not shaped by sensations and emotions. The Google search algorithm cannot taste ice cream. However, algorithms select things based on their internal calculations and built-in preferences, and these preferences increasingly shape our world. The Google search algorithm has a very sophisticated taste when it comes to ranking the Web pages of ice-cream vendors, and the most suc
cessful ice-cream vendors in the world are those that the Google algorithm ranks first – not those that produce the tastiest ice cream.
I know this from personal experience. When I publish a book, the publishers ask me to write a short description that they use for publicity online. But they have a special expert, who adapts what I write to the taste of the Google algorithm. The expert goes over my text, and says ‘Don’t use this word – use that word instead. Then we will get more attention from the Google algorithm.’ We know that if we can just catch the eye of the algorithm, we can take the humans for granted.
So if humans are needed neither as producers nor as consumers, what will safeguard their physical survival and their psychological well-being? We cannot wait for the crisis to erupt in full force before we start looking for answers. By then it will be too late. In order to cope with the unprecedented technological and economic disruptions of the twenty-first century, we need to develop new social and economic models as soon as possible. These models should be guided by the principle of protecting humans rather than jobs. Many jobs are uninspiring drudgery, not worth saving. Nobody’s life-dream is to be a cashier. What we should focus on is providing for people’s basic needs and protecting their social status and self-worth.
One new model, which is gaining increasing attention, is universal basic income. UBI proposes that governments tax the billionaires and corporations controlling the algorithms and robots, and use the money to provide every person with a generous stipend covering his or her basic needs. This will cushion the poor against job loss and economic dislocation, while protecting the rich from populist rage.23 A related idea proposes to widen the range of human activities that are considered to be ‘jobs’. At present, billions of parents take care of children, neighbours look after one another, and citizens organise communities, without any of these valuable activities being recognised as jobs. Maybe we need to turn a switch in our minds, and realise that taking care of a child is arguably the most important and challenging job in the world. If so, there won’t be a shortage of work even if computers and robots replace all the drivers, bankers and lawyers. The question is, of course, who would evaluate and pay for these newly recognised jobs? Assuming that six-month-old babies will not pay a salary to their mums, the government will probably have to take this upon itself. Assuming, too, that we will like these salaries to cover all of a family’s basic needs, the end result will be something that is not very different from universal basic income.
Alternatively, governments could subsidise universal basic services rather than income. Instead of giving money to people, who then shop around for whatever they want, the government might subsidise free education, free healthcare, free transport and so forth. This is in fact the utopian vision of communism. Though the communist plan to start a working-class revolution might well become outdated, maybe we should still aim to realise the communist goal by other means?
It is debatable whether it is better to provide people with universal basic income (the capitalist paradise) or universal basic services (the communist paradise). Both options have advantages and drawbacks. But no matter which paradise you choose, the real problem is in defining what ‘universal’ and ‘basic’ actually mean.
What is universal?
When people speak about universal basic support – whether in the shape of income or services – they usually mean national basic support. Hitherto, all UBI initiatives have been strictly national or municipal. In January 2017, Finland began a two-year experiment, providing 2,000 unemployed Finns with 560 euros a month, irrespective of whether they find work or not. Similar experiments are under way in the Canadian province of Ontario, in the Italian city of Livorno, and in several Dutch cities.24 (In 2016 Switzerland held a referendum on instituting a national basic income scheme, but voters rejected the idea.25)
The problem with such national and municipal schemes, however, is that the main victims of automation may not live in Finland, Ontario, Livorno or Amsterdam. Globalisation has made people in one country utterly dependent on markets in other countries, but automation might unravel large parts of this global trade network with disastrous consequences for the weakest links. In the twentieth century, developing countries lacking natural resources made economic progress mainly by selling the cheap labour of their unskilled workers. Today millions of Bangladeshis make a living by producing shirts and selling them to customers in the United States, while people in Bangalore earn their keep in call centres dealing with the complaints of American customers.26
Yet with the rise of AI, robots and 3-D printers, cheap unskilled labour would become far less important. Instead of manufacturing a shirt in Dhaka and shipping it all the way to the US, you could buy the shirt’s code online from Amazon, and print it in New York. The Zara and Prada stores on Fifth Avenue could be replaced by 3-D printing centres in Brooklyn, and some people might even have a printer at home. Simultaneously, instead of calling customer services in Bangalore to complain about your printer, you could talk with an AI representative in the Google cloud (whose accent and tone of voice are tailored to your preferences). The newly unemployed workers and call-centre operators in Dhaka and Bangalore don’t have the education necessary to switch to designing fashionable shirts or writing computer code – so how will they survive?
If AI and 3-D printers indeed take over from the Bangladeshis and Bangalorians, the revenues that previously flowed to South Asia will now fill the coffers of a few tech-giants in California. Instead of economic growth improving conditions all over the world, we might see immense new wealth created in hi-tech hubs such as Silicon Valley, while many developing countries collapse.
Of course, some emerging economies – including India and Bangladesh – might advance fast enough to join the winning team. Given enough time, the children or grandchildren of textile workers and call-centre operators might well become the engineers and entrepreneurs who build and own the computers and 3-D printers. But the time to make such a transition is running out. In the past, cheap unskilled labour has served as a secure bridge across the global economic divide, and even if a country advanced slowly, it could expect to reach safety eventually. Taking the right steps was more important than making speedy progress. Yet now the bridge is shaking, and soon it might collapse. Those who have already crossed it – graduating from cheap labour to high-skill industries – will probably be OK. But those lagging behind might find themselves stuck on the wrong side of the chasm, without any means of crossing over. What do you do when nobody needs your cheap unskilled labourers, and you don’t have the resources to build a good education system and teach them new skills?27
What then will be the fate of the stragglers? American voters might conceivably agree that taxes paid by Amazon and Google for their US business could be used to give stipends or free services to unemployed miners in Pennsylvania and jobless taxi-drivers in New York. However, would American voters also agree that these taxes should be sent to support unemployed people in places defined by President Trump as ‘shithole countries’?28 If you believe that, you might just as well believe that Santa Claus and the Easter Bunny will solve the problem.
What is basic?
Universal basic support is meant to take care of basic human needs, but there is no accepted definition for that. From a purely biological perspective, a Sapiens needs just 1,500–2,500 calories per day in order to survive. Anything more is a luxury. Yet over and above this biological poverty line, every culture in history defined additional needs as ‘basic’. In medieval Europe, access to church services was seen as even more important than food, because it took care of your eternal soul rather than of your ephemeral body. In today’s Europe, decent education and healthcare services are considered basic human needs, and some argue that even access to the Internet is now essential for every man, woman and child. If in 2050 the United World Government agrees to tax Google, Amazon, Baidu and Tencent in order to provide basic support for every human being on earth – in Dhaka as well as
in Detroit – how will they define ‘basic’?
For example, what does basic education include: just reading and writing, or also composing computer code and playing the violin? Just six years of elementary school, or everything up to a PhD? And what about healthcare? If by 2050 medical advances make it possible to slow down ageing processes and significantly extend human lifespans, will the new treatments be available to all 10 billion humans on the planet, or just to a few billionaires? If biotechnology enables parents to upgrade their children, would this be considered a basic human need, or would we see humankind splitting into different biological castes, with rich superhumans enjoying abilities that far surpass those of poor Homo sapiens?
Whichever way you choose to define ‘basic human needs’, once you provide them to everyone free of charge, they will be taken for granted, and then fierce social competitions and political struggles will focus on non-basic luxuries – be they fancy self-driving cars, access to virtual-reality parks, or enhanced bioengineered bodies. Yet if the unemployed masses command no economic assets, it is hard to see how they could ever hope to obtain such luxuries. Consequently the gap between the rich (Tencent managers and Google shareholders) and the poor (those dependent on universal basic income) might become not merely bigger, but actually unbridgeable.
Hence even if some universal support scheme provides poor people in 2050 with much better healthcare and education than today, they might still be extremely angry about global inequality and the lack of social mobility. People will feel that the system is rigged against them, that the government serves only the super-rich, and that the future will be even worse for them and their children.29
Homo sapiens is just not built for satisfaction. Human happiness depends less on objective conditions and more on our own expectations. Expectations, however, tend to adapt to conditions, including to the condition of other people. When things improve, expectations balloon, and consequently even dramatic improvements in conditions might leave us as dissatisfied as before. If universal basic support is aimed at improving the objective conditions of the average person in 2050, it has a fair chance of succeeding. But if it is aimed at making people subjectively more satisfied with their lot and preventing social discontent, it is likely to fail.