Homo Deus

by Yuval Noah Harari

  —

  By equating the human experience with data patterns, Dataism undermines our main source of authority and meaning, and heralds a tremendous religious revolution, the like of which has not been seen since the eighteenth century. In the days of Locke, Hume and Voltaire humanists argued that ‘God is a product of the human imagination’. Dataism now gives humanists a taste of their own medicine, and tells them: ‘Yes, God is a product of the human imagination, but human imagination in turn is the product of biochemical algorithms.’ In the eighteenth century, humanism sidelined God by shifting from a deo-centric to a homo-centric world view. In the twenty-first century, Dataism may sideline humans by shifting from a homo-centric to a data-centric view.

  The Dataist revolution will probably take a few decades, if not a century or two. But then the humanist revolution too did not happen overnight. At first, humans kept on believing in God, and argued that humans are sacred because they were created by God for some divine purpose. Only much later did some people dare say that humans are sacred in their own right, and that God doesn’t exist at all. Similarly, today most Dataists say that the Internet-of-All-Things is sacred because humans are creating it to serve human needs. But eventually, the Internet-of-All-Things may become sacred in its own right.

  The shift from a homo-centric to a data-centric world view won’t be merely a philosophical revolution. It will be a practical revolution. All truly important revolutions are practical. The humanist idea that ‘humans invented God’ was significant because it had far-reaching practical implications. Similarly, the Dataist idea that ‘organisms are algorithms’ is significant due to its day-to-day practical consequences. Ideas change the world only when they change our behaviour.

  In ancient Babylon, when people faced a difficult dilemma they climbed to the top of the local temple in the darkness of night and observed the sky. The Babylonians believed that the stars control our fate and predict our future. By watching the stars the Babylonians decided whether to get married, plough the field and go to war. Their philosophical beliefs were translated into very practical procedures.

  Scriptural religions such as Judaism and Christianity told a different story: ‘The stars are lying. God, who created the stars, revealed the entire truth in the Bible. So stop observing the stars – read the Bible instead!’ This too was a practical recommendation. When people didn’t know whom to marry, what career to choose and whether to start a war, they read the Bible and followed its counsel.

  Next came the humanists, with an altogether new story: ‘Humans invented God, wrote the Bible and then interpreted it in a thousand different ways. So humans themselves are the source of all truth. You may read the Bible as an inspiring human creation, but you don’t have to. If you are facing any dilemma, just listen to yourself and follow your inner voice.’ Humanism then gave detailed practical instructions on how to listen to yourself, recommending things such as watching sunsets, reading Goethe, keeping a private diary, having heart-to-heart talks with a good friend and holding democratic elections.

  For centuries scientists too accepted these humanist guidelines. When physicists wondered whether to get married or not, they too watched sunsets and tried to get in touch with themselves. When chemists contemplated whether to accept a problematic job offer, they too wrote diaries and had heart-to-heart talks with a good friend. When biologists debated whether to wage war or sign a peace treaty, they too voted in democratic elections. When brain scientists wrote books about their startling discoveries, they often put an inspiring Goethe quote on the first page. This was the basis for the modern alliance between science and humanism, which kept the delicate balance between the modern yang and the modern yin – between reason and emotion, between the laboratory and the museum, between the production line and the supermarket.

  The scientists not only sanctified human feelings, but also found an excellent evolutionary reason to do so. After Darwin, biologists began explaining that feelings are complex algorithms honed by evolution to help animals make the right decisions. Our love, our fear and our passion aren’t some nebulous spiritual phenomena good only for composing poetry. Rather, they encapsulate millions of years of practical wisdom. When you read the Bible, you get advice from a few priests and rabbis who lived in ancient Jerusalem. In contrast, when you listen to your feelings, you follow an algorithm that evolution has developed for millions of years, and that withstood the harshest quality tests of natural selection. Your feelings are the voice of millions of ancestors, each of whom managed to survive and reproduce in an unforgiving environment. Your feelings are not infallible, of course, but they are better than most alternatives. For millions upon millions of years, feelings were the best algorithms in the world. Hence in the days of Confucius, of Muhammad or of Stalin, people should have listened to their feelings rather than to the teachings of Confucianism, Islam or communism.

  Yet in the twenty-first century, feelings are no longer the best algorithms in the world. We are developing superior algorithms which utilise unprecedented computing power and giant databases. The Google and Facebook algorithms not only know exactly how you feel, they also know a million other things about you that you hardly suspect. Consequently you should now stop listening to your feelings, and start listening to these external algorithms instead. What’s the use of having democratic elections when the algorithms know how each person is going to vote, and when they also know the exact neurological reasons why one person votes Democrat while another votes Republican? Whereas humanism commanded: ‘Listen to your feelings!’ Dataism now commands: ‘Listen to the algorithms! They know how you feel.’

  When you contemplate whom to marry, which career to pursue and whether to start a war, Dataism tells you it would be a total waste of time to climb a high mountain and watch the sun setting on the waves. It would be equally pointless to go to a museum, write a private diary or have a heart-to-heart talk with a friend. Yes, in order to make the right decisions you must get to know yourself better. But if you want to know yourself in the twenty-first century, there are much better methods than climbing mountains, going to museums or writing diaries. Here are some practical Dataist guidelines for you:

  ‘You want to know who you really are?’ asks Dataism. ‘Then forget about mountains and museums. Have you had your DNA sequenced? No?! What are you waiting for? Go and do it today. And convince your grandparents, parents and siblings to have their DNA sequenced too – their data is very valuable for you. And have you heard about these wearable biometric devices that measure your blood pressure and heart rate twenty-four hours a day? Good – so buy one of those, put it on and connect it to your smartphone. And while you are shopping, buy a mobile camera and microphone, record everything you do, and put in online. And allow Google and Facebook to read all your emails, monitor all your chats and messages, and keep a record of all your Likes and clicks. If you do all that, then the great algorithms of the Internet-of-All-Things will tell you whom to marry, which career to pursue and whether to start a war.’

  But where do these great algorithms come from? This is the mystery of Dataism. Just as according to Christianity we humans cannot understand God and His plan, so Dataism says the human brain cannot embrace the new master algorithms. At present, of course, the algorithms are mostly written by human hackers. Yet the really important algorithms – such as the Google search algorithm – are developed by huge teams. Each member understands just one part of the puzzle, and nobody really understands the algorithm as a whole. Moreover, with the rise of machine learning and artificial neural networks, more and more algorithms evolve independently, improving themselves and learning from their own mistakes. They analyse astronomical amounts of data, which no human can possibly encompass, and learn to recognise patterns and adopt strategies that escape the human mind. The seed algorithm may initially be developed by humans, but as it grows, it follows its own path, going where no human has gone before – and where no human can follow.

  A Ripple in the Data
Flow

  Dataism naturally has its critics and heretics. As we saw in Chapter 3, it’s doubtful whether life can really be reduced to data flows. In particular, at present we have no idea how or why data flows could produce consciousness and subjective experiences. Maybe we’ll have a good explanation in twenty years. But maybe we’ll discover that organisms aren’t algorithms after all.

  It is equally doubtful whether life boils down to decision-making. Under Dataist influence, both the life sciences and the social sciences have become obsessed with decision-making processes, as if that’s all there is to life. But is it so? Sensations, emotions and thoughts certainly play an important part in making decisions, but is that their sole meaning? Dataism gains a better and better understanding of decision-making processes, but it might be adopting an increasingly skewed view of life.

  A critical examination of the Dataist dogma is likely to be not only the greatest scientific challenge of the twenty-first century, but also the most urgent political and economic project. Scholars in the life sciences and social sciences should ask themselves whether we miss anything when we understand life as data processing and decision-making. Is there perhaps something in the universe that cannot be reduced to data? Suppose non-conscious algorithms could eventually outperform conscious intelligence in all known data-processing tasks – what, if anything, would be lost by replacing conscious intelligence with superior non-conscious algorithms?

  Of course, even if Dataism is wrong and organisms aren’t just algorithms, it won’t necessarily prevent Dataism from taking over the world. Many previous religions gained enormous popularity and power despite their factual mistakes. If Christianity and communism could do it, why not Dataism? Dataism has especially good prospects, because it is currently spreading across all scientific disciplines. A unified scientific paradigm may easily become an unassailable dogma. It is very difficult to contest a scientific paradigm, but up till now, no single paradigm was adopted by the entire scientific establishment. Hence scholars in one field could always import heretical views from outside. But if everyone from musicologists to biologists uses the same Dataist paradigm, interdisciplinary excursions will serve only to strengthen the paradigm further. Consequently even if the paradigm is flawed, it would be extremely difficult to resist it.

  If Dataism succeeds in conquering the world, what will happen to us humans? In the beginning, it will probably accelerate the humanist pursuit of health, happiness and power. Dataism spreads itself by promising to fulfil these humanist aspirations. In order to gain immortality, bliss and divine powers of creation, we need to process immense amounts of data, far beyond the capacity of the human brain. So the algorithms will do it for us. Yet once authority shifts from humans to algorithms, the humanist projects may become irrelevant. Once we abandon the homo-centric world view in favour of a data-centric world view, human health and happiness may seem far less important. Why bother so much about obsolete data-processing machines when much better models are already in existence? We are striving to engineer the Internet-of-All-Things in the hope that it will make us healthy, happy and powerful. Yet once the Internet-of-All-Things is up and running, we might be reduced from engineers to chips, then to data, and eventually we might dissolve within the data torrent like a clump of earth within a gushing river.

  Dataism thereby threatens to do to Homo sapiens what Homo sapiens has done to all other animals. In the course of history humans have created a global network, and evaluated everything according to its function within the network. For thousands of years, this boosted human pride and prejudices. Since humans fulfilled the most important functions in the network, it was easy for us to take credit for the network’s achievements, and to see ourselves as the apex of creation. The lives and experiences of all other animals were undervalued, because they fulfilled far less important functions, and whenever an animal ceased to fulfil any function at all, it went extinct. However, once humans lose their functional importance to the network, we will discover that we are not the apex of creation after all. The yardsticks that we ourselves have enshrined will condemn us to join the mammoths and the Chinese river dolphins in oblivion. Looking back, humanity will turn out to be just a ripple within the cosmic data flow.

  —

  We cannot really predict the future. All the scenarios outlined in this book should be understood as possibilities rather than prophecies. When we think about the future, our horizons are usually constrained by present-day ideologies and social systems. Democracy encourages us to believe in a democratic future; capitalism doesn’t allow us to envisage a non-capitalist alternative; and humanism makes it difficult for us to imagine a post-human destiny. At most, we sometimes recycle past events and think about them as alternative futures. For example, twentieth-century Nazism and communism serve as a blueprint for many dystopian fantasies; and science-fiction authors use medieval and ancient legacies to imagine Jedi knights and galactic emperors fighting it out with spaceships and laser guns.

  This book traces the origins of our present-day conditioning in order to loosen its grip and enable us to think in far more imaginative ways about our future. Instead of narrowing our horizons by forecasting a single definitive scenario, the book aims to broaden our horizons and make us aware of a much wider spectrum of options. As I have repeatedly emphasised, nobody really knows what the job market, the family or the ecology will look like in 2050, or what religions, economic systems or political structures will dominate the world.

  Yet broadening our horizons can backfire by making us more confused and inactive than before. With so many scenarios and possibilities, what should we pay attention to? The world is changing faster than ever before, and we are flooded by impossible amounts of data, of ideas, of promises and of threats. Humans relinquish authority to the free market, to crowd wisdom and to external algorithms partly because they cannot deal with the deluge of data. In the past, censorship worked by blocking the flow of information. In the twenty-first century, censorship works by flooding people with irrelevant information. People just don’t know what to pay attention to, and they often spend their time investigating and debating side issues. In ancient times having power meant having access to data. Today having power means knowing what to ignore. So of everything that happens in our chaotic world, what should we focus on?

  If we think in term of months, we had probably focus on immediate problems such as the turmoil in the Middle East, the refugee crisis in Europe and the slowing of the Chinese economy. If we think in terms of decades, then global warming, growing inequality and the disruption of the job market loom large. Yet if we take the really grand view of life, all other problems and developments are overshadowed by three interlinked processes:

  1. Science is converging on an all-encompassing dogma, which says that organisms are algorithms, and life is data processing.

  2. Intelligence is decoupling from consciousness.

  3. Non-conscious but highly intelligent algorithms may soon know us better than we know ourselves.

  These three processes raise three key questions, which I hope will stick in your mind long after you have finished this book:

  1. Are organisms really just algorithms, and is life really just data processing?

  2. What’s more valuable – intelligence or consciousness?

  3. What will happen to society, politics and daily life when non-conscious but highly intelligent algorithms know us better than we know ourselves?

  Notes

  1 The New Human Agenda

  1. Tim Blanning, The Pursuit of Glory (New York: Penguin Books, 2008), 52.

  2. Ibid., 53. See also: J. Neumann and S. Lindgrén, ‘Great Historical Events That Were Significantly Affected by the Weather: 4, The Great Famines in Finland and Estonia, 1695–97’, Bulletin of the American Meteorological Society 60 (1979), 775–87; Andrew B. Appleby, ‘Epidemics and Famine in the Little Ice Age’, Journal of Interdisciplinary History 10:4 (1980), 643–63; Cormac Ó Gráda and Jean-Michel Chevet, ‘Fam
ine and Market in Ancien Régime France’, Journal of Economic History 62:3 (2002), 706–73.

  3. Nicole Darmon et al., ‘L’insécurité alimentaire pour raisons financières en France’, Observatoire National de la Pauvreté et de l’Exclusion Sociale, https://www.​onpes.​gouv.​fr/​IMG/​pdf/​Darmon.​pdf, accessed 3 March 2015; Rapport Annuel 2013, Banques Alimetaires, http://en.​calameo.​com/​read/​001358178ec47d2018425, accessed 4 March 2015.

  4. Richard Dobbs et al., ‘How the World Could Better Fight Obesity’, McKinseys & Company, November 2014, accessed 11 December 2014, http://www.​mckinsey.​com/​insights/​economic_​studies/​how_the_world_​could_​better_fight_​obesity.

  5. ‘Global Burden of Disease, Injuries and Risk Factors Study 2013’, Lancet, 18 December 2014, accessed 18 December 2014, http://www.​thelancet.​com/​themed/​global-burden-of-disease; Stephen Adams, ‘Obesity Killing Three Times As Many As Malnutrition’, Telegraph, 13 December 2012, accessed 18 December 2014, http://www.​telegraph.​co.​uk/​health/​healthnews/​9742960/​Obesity-killing-three-times-as-many-as-malnutrition.​html.

  6. Robert S. Lopez, The Birth of Europe [in Hebrew] (Tel Aviv: Dvir, 1990), 427.

  7. Alfred W. Crosby, The Columbian Exchange: Biological and Cultural Consequences of 1492 (Westport: Greenwood Press, 1972); William H. McNeill, Plagues and Peoples (Oxford: Basil Blackwell, 1977).

  8. Hugh Thomas, Conquest: Cortes, Montezuma and the Fall of Old Mexico (New York: Simon & Schuster, 1993), 443–6; Rodolfo Acuna-Soto et al., ‘Megadrought and Megadeath in 16th Century Mexico’, Historical Review 8:4 (2002), 360–2; Sherburne F. Cook and Lesley Byrd Simpson, The Population of Central Mexico in the Sixteenth Century (Berkeley: University of California Press, 1948).