21 Lessons for the 21st Century
✒️ Author: Yuval Noah Harari | 📖 Published: 2018 | 🗓 Read: December 4, 2020 | 📄 Pages: 356
Summary
In Sapiens, Yuval Noah Harari explored our past. In Homo Deus, he looked to our future. Now, one of the most innovative thinkers on the planet turns to the present to make sense of today’s most pressing issues. How do computers and robots change the meaning of being human? How do we deal with the epidemic of fake news? Are nations and religions still relevant? What should we teach our children?
Why You Should Read It
Our species, Homo Sapiens, survived and outlived all other homo species for millennia because of the stories we tell ourselves. These stories galvanized the masses to create communities and build up a culture and a belief system that has all put us in lock-step with one another. Our world is only becoming more connected, and issues are arising around technology, climate change, and fake news, demanding new stories to ensure our continued survival. If you are new to Yuval’s work, I suggest you read Sapiens first before diving into this book.
Notable Highlights
A global world puts unprecedented pressure on our personal conduct and morality. Each of us is ensnared within numerous all-encompassing spiderwebs, which on the one hand restrict our movements but on the other transmit our tiniest jiggle to faraway destinations. Our daily routines influence the lives of people and animals halfway across the world, and some personal gestures can unexpectedly set the entire world ablaze, as happened with the self-immolation of Mohamed Bouazizi in Tunisia, which ignited the Arab Spring, and with the women who shared their stories of sexual harassment and sparked the #MeToo movement.
Notes: 1) The macro is easier to influence.
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The merger of infotech and biotech might soon push billions of humans out of the job market and undermine both liberty and equality. Big Data algorithms might create digital dictatorships in which all power is concentrated in the hands of a tiny elite while most people suffer not from exploitation but from something far worse—irrelevance.
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Very soon somebody will have to decide how to use this power—based on some implicit or explicit story about the meaning of life. Philosophers are very patient people, but engineers are far less so, and investors are the least patient of all. If you don’t know what to do with the power to engineer life, market forces will not wait a thousand years for you to come up with an answer. The invisible hand of the market will force upon you its own blind reply. Unless you are happy to entrust the future of life to the mercy of quarterly revenue reports, you need a clear idea what life is all about.
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The year 2016—marked by the Brexit vote in Britain and the rise of Donald Trump in the United States—signified the moment when this tidal wave of disillusionment reached the core liberal states of Western Europe and North America. Whereas a few years ago Americans and Europeans were still trying to liberalize Iraq and Libya at gunpoint, many people in Kentucky and Yorkshire now have come to see the liberal vision as either undesirable or unattainable. Some discovered a liking for the old hierarchical world, and they just don’t want to give up their racial, national, or gendered privileges. Others have concluded (rightly or wrongly) that liberalization and globalization are a huge racket empowering a tiny elite at the expense of the masses.
Notes: 1) The forces behind Donald Trump and why he was elected.
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In 1938 humans were offered three global stories to choose from, in 1968 just two, and in 1998 a single story seemed to prevail. In 2018 we are down to zero.
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Humans were always far better at inventing tools than using them wisely.
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It is easier to manipulate a river by building a dam than it is to predict all the complex consequences this will have for the wider ecological system. Similarly, it will be easier to redirect the flow of our minds than to divine what that will do to our personal psychology or to our social systems.
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In the coming century biotech and infotech will give us the power to manipulate the world inside us and reshape ourselves, but because we don’t understand the complexity of our own minds, the changes we will make might upset our mental system to such an extent that it too might break down.
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In 2018 the common person feels increasingly irrelevant. Lots of mysterious words are bandied around excitedly in TED Talks, government think tanks, and high-tech conferences—globalization, blockchain, genetic engineering, artificial intelligence, machine learning—and common people may well suspect that none of these words are about them. The liberal story was the story of ordinary people. How can it remain relevant to a world of cyborgs and networked algorithms?
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Donald Trump’s main message is that it’s not America’s job to formulate and promote any global vision whatsoever. Similarly, the British Brexiteers barely have a plan for the future of the Disunited Kingdom—the future of Europe and of the world is far beyond their horizon. Most people who voted for Trump and Brexit didn’t reject the liberal package in its entirety—they lost faith mainly in its globalizing part.
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Democracy is based on Abraham Lincoln’s principle that “you can fool all the people some of the time, and some people all of the time, but you cannot fool all the people all the time.” If a government is corrupt and fails to improve people’s lives, enough citizens will eventually realize this and replace the government. But government control of the media undermines Lincoln’s logic, because it prevents citizens from realizing the truth. Through its monopoly over the media, the ruling oligarchy can repeatedly blame all its failures on others and divert attention to external threats, either real or imaginary.
Notes: 1) What is happening in Russia
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When you live under such an oligarchy, there is always some crisis or other that takes priority over boring stuff like healthcare and pollution. If the nation is facing external invasion or diabolical subversion, who has time to worry about overcrowded hospitals and polluted rivers? By manufacturing a never-ending stream of crises, a corrupt oligarchy can prolong its rule indefinitely.
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It is difficult to understand current developments partly because liberalism was never a single thing. Liberalism cherishes liberty, but liberty has different meanings in different contexts. Thus, for one person liberalism implies free elections and democratization. Another person thinks that liberalism means trade agreements and globalization. A third associates liberalism with gay marriage and abortion. Liberalism offers diverse recommendations for behavior in the economic, political, and personal fields, and on both the national and international level.
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But liberalism has no obvious answers to the biggest problems we face: ecological collapse and technological disruption.
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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 very abstract and remote, but the very real prospect of mass unemployment—or personal unemployment—leaves nobody indifferent.
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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.
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AI is now beginning to outperform humans in more and more of these skills, including in the understanding of human emotions.
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It is crucial to realize that the AI revolution is not just about computers getting faster and smarter. It is fueled 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 analyzing human behavior, predicting human decisions, and replacing human drivers, bankers, and lawyers.
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A driver predicting the intentions of a pedestrian, a banker assessing the credibility of a potential borrower, and a lawyer gauging the mood at the negotiating table don’t rely on witchcraft. Rather, unbeknownst to them, their brains are recognizing biochemical patterns by analyzing facial expressions, tones of voice, hand movements, and even body odors. An AI equipped with the right sensors could do all that far more accurately and reliably than a human.
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Two particularly important nonhuman abilities that AI possesses are connectivity and updatability.
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What we are facing is not the replacement of millions of individual human workers by millions of individual robots and computers; rather, individual humans are likely to be replaced by an integrated network. When considering automation, therefore, it is wrong to compare the abilities of a single human driver to that of a single self-driving car, or of a single human doctor to that of a single AI doctor. Rather, we should compare the abilities of a collection of human individuals to the abilities of an integrated network.
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Thanks to learning algorithms and biometric sensors, a poor villager in an underdeveloped country might come to enjoy far better healthcare via her smartphone than the richest person in the world gets today from the most advanced urban hospital.
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In other words, switching to autonomous vehicles is likely to save the lives of one million people every year. It would therefore be madness to block automation in fields such as transport and healthcare just in order to protect human jobs. After all, what we ultimately ought to protect is humans—not jobs.
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In order to enter the art market and displace many human composers and performers, algorithms won’t have to begin by surpassing Tchaikovsky. It would be enough if they outperform Britney Spears.
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Primary care doctors who focus on diagnosing known diseases and administering familiar treatments will probably be replaced by AI doctors. But precisely because of that, there will be much more money to pay human doctors and lab assistants to do groundbreaking research and develop new medicines or surgical procedures.
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AI might help create new human jobs in another way. Instead of humans competing with AI, they could focus on servicing and leveraging AI.
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If so, the job market of 2050 might well be characterized by human-AI cooperation rather than competition. In fields ranging from policing to banking, teams of humans-plus-AIs could outperform both humans and computers. After IBM’s chess program Deep Blue beat Garry Kasparov in 1997, humans did not stop playing chess. Rather, thanks to AI trainers, human chess masters became better than ever, and at least for a while human-AI teams known as “centaurs” outperformed both humans and computers in chess. AI might similarly help groom the best detectives, bankers, and soldiers in history.14
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One new model gaining increasing attention is universal basic income. UBI proposes that governments tax the billionaires and corporations controlling the algorithms and robots, and use that 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.
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Human happiness depends less on objective conditions and more on our own expectations. Expectations, however, tend to adapt to conditions, including the conditions of other people. When things improve, expectations balloon, and so even dramatic improvements in conditions might leave us as dissatisfied as before.
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If we manage to combine a universal economic safety net with strong communities and meaningful pursuits, losing our jobs to algorithms might actually turn out to be a blessing. Losing control over our lives, however, is a much scarier scenario.
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In politics, liberalism believes that the voter knows best. It therefore upholds democratic elections. In economics, liberalism maintains that the customer is always right. It therefore hails free-market principles. In personal matters, liberalism encourages people to listen to themselves, be true to themselves, and follow their hearts—as long as they do not infringe on the liberties of others. This personal freedom is enshrined in human rights.
Notes: 1) Liberty
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Democracy assumes that human feelings reflect a mysterious and profound “free will,” that this “free will” is the ultimate source of authority, and that while some people are more intelligent than others, all humans are equally free.
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To put it succinctly, we can use the following formula: b×c×d = ahh! Biological knowledge multiplied by Computing power multiplied by Data equals Ability to Hack Humans.
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Even more than algorithms, humans suffer from insufficient data, from faulty programming (genetic and cultural), from muddled definitions, and from the chaos of life.
Notes: 1) How will algorithms define better than average if how we feel is subjective ?
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In the late twentieth century democracies usually outperformed dictatorships because democracies were better at data processing. A democracy diffuses the power to process information and make decisions among many people and institutions, whereas a dictatorship concentrates information and power in one place. Given twentieth-century technology, it was inefficient to concentrate too much information and power in one place. Nobody had the ability to process all the information fast enough and make the right decisions.
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AI makes it possible to process enormous amounts of information centrally. In fact, AI might make centralized systems far more efficient than diffused systems, because machine learning works better the more information it can analyze. If you disregard all privacy concerns and concentrate all the information relating to a billion people in one database, you can train much better algorithms than if you respect individual privacy and have in your database only partial information on a million people.
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Intelligence is the ability to solve problems. Consciousness is the ability to feel things such as pain, joy, love, and anger. We tend to confuse the two because in humans and other mammals intelligence goes hand in hand with consciousness. Mammals solve most problems by feeling things. Computers, however, solve problems in a very different way.
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An algorithm does not need to feel joy, anger, or fear in order to recognize the different biochemical patterns of joyful, angry, or frightened apes.
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In the late modern era, however, equality became an ideal in almost all human societies. This was partly due to the rise of the new ideologies of communism and liberalism. But it was also due to the Industrial Revolution, which made the masses more important than ever before. Industrial economies relied on masses of common workers, while industrial armies relied on masses of common soldiers. Governments in both democracies and dictatorships invested heavily in the health, education, and welfare of the masses, because they needed millions of healthy laborers to operate the production lines and millions of loyal soldiers to fight in the trenches.
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The two processes together—bioengineering coupled with the rise of AI—might therefore result in the separation of humankind into a small class of superhumans and a massive underclass of useless Homo sapiens. To make an already ominous situation even worse, as the masses lose their economic importance and political power, the state might lose at least some of the incentive to invest in their health, education, and welfare. It’s very dangerous to be redundant. The future of the masses will then depend on the goodwill of a small elite. Maybe there is goodwill for a few decades. But in a time of crisis—like climate catastrophe—it would be very tempting and easy to toss the superfluous people overboard.
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The race to obtain the data is already on, headed by data giants such as Google, Facebook, Baidu, and Tencent. So far, many of these giants seem to have adopted the business model of “attention merchants.” They capture our attention by providing us with free information, services, and entertainment, and they then resell our attention to advertisers. Yet the data giants probably aim far higher than any previous attention merchant. Their true business isn’t to sell advertisements at all. Rather, by capturing our attention they manage to accumulate immense amounts of data about us, which is worth more than any advertising revenue. We aren’t their customers—we are their product.
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In the medium term, this data hoard opens a path to a radically different business model whose first victim will be the advertising industry itself. The new model is based on transferring authority from humans to algorithms, including the authority to choose and buy things. Once algorithms choose and buy things for us, the traditional advertising industry will go bust.
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War spreads ideas, technologies, and people far more quickly than commerce does.
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War also makes people far more interested in one another. The United States had never been more closely in touch with Russia than during the Cold War, when every cough in a Moscow corridor sent people scrambling up and down Washington staircases. People care far more about their enemies than about their trade partners. For every American film about Taiwan, there are probably fifty about Vietnam.
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Global politics thus follows the Anna Karenina principle: successful states are all alike, but every failed state fails in its own way, by missing this or that ingredient of the dominant political package.
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