21 Lessons for the 21st Century

At present, humankind is far from reaching any consensus on these questions. We are still in the nihilist moment of disillusionment and anger, after people have lost faith in the old stories but before they have embraced a new one. So what next? The first step is to tone down the prophecies of doom, and switch from panic mode to bewilderment. Panic is a form of hubris. It comes from the smug feeling that I know exactly where the world is heading – down. Bewilderment is more humble, and therefore more clear-sighted. If you feel like running down the street crying ‘The apocalypse is upon us!’, try telling yourself ‘No, it’s not that. Truth is, I just don’t understand what’s going on in the world.’

The following chapters will try to clarify some of the bewildering new possibilities we face, and how we might proceed from here. But before exploring potential solutions to humanity’s predicaments we need a better grasp of the challenge technology poses. The revolutions in information technology and biotechnology are still in their infancy, and it is debatable to what extent they are really responsible for the current crisis of liberalism. Most people in Birmingham, Istanbul, St Petersburg and Mumbai are only dimly aware, if at all, of the rise of artificial intelligence and its potential impact on their lives. It is undoubtable, however, that the technological revolutions will gather momentum in the next few decades, and will confront humankind with the hardest trials we have ever encountered. Any story that seeks to gain humanity’s allegiance will be tested above all in its ability to deal with the twin revolutions in infotech and biotech. If liberalism, nationalism, Islam or some novel creed wishes to shape the world of the year 2050, it will need not only to make sense of artificial intelligence, Big Data algorithms and bioengineering – it will also need to incorporate them into a new meaningful narrative.

To understand the nature of this technological challenge, perhaps it would be best to start with the job market. Since 2015 I have been travelling around the world talking with government officials, business people, social activists and schoolkids about the human predicament. Whenever they become impatient or bored by all the talk of artificial intelligence, Big Data algorithms and bioengineering, I usually need to mention just one magic word to snap them back to attention: jobs. The technological revolution might soon push billions of humans out of the job market, and create a massive new useless class, leading to social and political upheavals that no existing ideology knows how to handle. All the talk about technology and ideology might sound abstract and remote, but the very real prospect of mass unemployment – or personal unemployment – leaves nobody indifferent.





2


WORK


When you grow up, you might not have a job


We have no idea what the job market will look like in 2050. It is generally agreed that machine learning and robotics will change almost every line of work – from producing yoghurt to teaching yoga. However, there are conflicting views about the nature of the change and its imminence. Some believe that within a mere decade or two, billions of people will become economically redundant. Others maintain that even in the long run automation will keep generating new jobs and greater prosperity for all.

So are we on a verge of a terrifying upheaval, or are such forecasts yet another example of ill-founded Luddite hysteria? It is hard to say. Fears that automation will create massive unemployment go back to the nineteenth century, and so far they have never materialised. Since the beginning of the Industrial Revolution, for every job lost to a machine at least one new job was created, and the average standard of living has increased dramatically.1 Yet there are good reasons to think that this time it is different, and that machine learning will be a real game changer.

Humans have two types of abilities – physical and cognitive. In the past, machines competed with humans mainly in raw physical abilities, while humans retained an immense edge over machines in cognition. Hence as manual jobs in agriculture and industry were automated, new service jobs emerged that required the kind of cognitive skills only humans possessed: learning, analysing, communicating and above all understanding human emotions. However, AI is now beginning to outperform humans in more and more of these skills, including in the understanding of human emotions.2 We don’t know of any third field of activity – beyond the physical and the cognitive – where humans will always retain a secure edge.

It is crucial to realise that the AI revolution is not just about computers getting faster and smarter. It is fuelled by breakthroughs in the life sciences and the social sciences as well. The better we understand the biochemical mechanisms that underpin human emotions, desires and choices, the better computers can become in analysing human behaviour, predicting human decisions, and replacing human drivers, bankers and lawyers.

In the last few decades research in areas such as neuroscience and behavioural economics allowed scientists to hack humans, and in particular to gain a much better understanding of how humans make decisions. It turned out that our choices of everything from food to mates result not from some mysterious free will, but rather from billions of neurons calculating probabilities within a split second. Vaunted ‘human intuition’ is in reality ‘pattern recognition’.3 Good drivers, bankers and lawyers don’t have magical intuitions about traffic, investment or negotiation – rather, by recognising recurring patterns, they spot and try to avoid careless pedestrians, inept borrowers and dishonest crooks. It also turned out that the biochemical algorithms of the human brain are far from perfect. They rely on heuristics, shortcuts and outdated circuits adapted to the African savannah rather than to the urban jungle. No wonder that even good drivers, bankers and lawyers sometimes make stupid mistakes.

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