21 Lessons for the 21st Century(19)
Even if you do, and even if you keep hiding from yourself and your classmates, you won’t be able to hide from Amazon, Alibaba or the secret police. As you surf the Web, watch YouTube or read your social media feed, the algorithms will discreetly monitor you, analyse you, and tell Coca-Cola that if it wants to sell you some fizzy drink, it had better use the advertisement with the shirtless guy rather than the shirtless girl. You won’t even know. But they will know, and such information will be worth billions.
Then again, maybe it will all be out in the open, and people will gladly share their information in order to get better recommendations – and eventually in order to get the algorithm to make decisions for them. It starts with simple things, like deciding which movie to watch. As you sit down with a group of friends to spend a cozy evening in front of the TV, you first have to choose what to see. Fifty years ago you had no choice, but today – with the rise of view-on-demand services – there are thousands of titles available. Reaching an agreement can be quite difficult, because while you personally like science-fiction thrillers, Jack prefers romantic comedies, and Jill votes for artsy French films. You may well end up compromising on some mediocre B-movie that disappoints all of you.
An algorithm might help. You can tell it which previous movies each of you really liked, and based on its massive statistical database, the algorithm can then find the perfect match for the group. Unfortunately, such a crude algorithm is easily misled, particularly because self-reporting is a notoriously unreliable gauge for people’s true preferences. It often happens that we hear lots of people praise some movie as a masterpiece, feel compelled to watch it, and even though we fall asleep midway through, we don’t want to look like philistines, so we tell everyone it was an amazing experience.7
Such problems, however, can be solved if we just allow the algorithm to collect real-time data on us as we actually watch movies, instead of relying on our own dubious self-reports. For starters, the algorithm can monitor which movies we completed, and which we stopped watching halfway through. Even if we tell the whole world that Gone With the Wind is the best movie ever made, the algorithm will know we never made it past the first half-hour, and we never really saw Atlanta burning.
Yet the algorithm can go much deeper than that. Engineers are currently developing software that can detect human emotions based on the movements of our eyes and facial muscles.8 Add a good camera to the television, and such software will know which scenes made us laugh, which scenes made us sad, and which scenes bored us. Next, connect the algorithm to biometric sensors, and the algorithm will know how each frame has influenced our heart rate, our blood pressure, and our brain activity. As we watch, say, Tarantino’s Pulp Fiction, the algorithm may note that the rape scene caused us an almost imperceptible tinge of sexual arousal, that when Vincent accidentally shot Marvin in the face it made us laugh guiltily, and that we didn’t get the joke about the Big Kahuna Burger – but we laughed anyway, so as not to look stupid. When you force yourself to laugh, you use different brain circuits and muscles than when you laugh because something is really funny. Humans cannot usually detect the difference. But a biometric sensor could.9
The word television comes from Greek ‘tele’, which means ‘far’, and Latin ‘visio’, sight. It was originally conceived as a device that allows us to see from afar. But soon, it might allow us to be seen from afar. As George Orwell envisioned in Nineteen Eighty-Four, the television will watch us while we are watching it. After we’ve finished watching Tarantino’s entire filmography, we may have forgotten most of it. But Netflix, or Amazon, or whoever owns the TV algorithm, will know our personality type, and how to press our emotional buttons. Such data could enable Netflix and Amazon to choose movies for us with uncanny precision, but it could also enable them to make for us the most important decisions in life – such as what to study, where to work, and who to marry.
Of course Amazon won’t be correct all the time. That’s impossible. Algorithms will repeatedly make mistakes due to insufficient data, faulty programming, muddled goal definitions and the chaotic nature of life.10 But Amazon won’t have to be perfect. It will just need to be better on average than us humans. And that is not so difficult, because most people don’t know themselves very well, and most people often make terrible mistakes in the most important decisions of their lives. Even more than algorithms, humans suffer from insufficient data, from faulty programming (genetic and cultural), from muddled definitions, and from the chaos of life.
You may well list the many problems that beset algorithms, and conclude that people will never trust them. But this is a bit like cataloguing all the drawbacks of democracy and concluding that no sane person would ever choose to support such a system. Winston Churchill famously said that democracy is the worst political system in the world, except for all the others. Rightly or wrongly, people might reach the same conclusions about Big Data algorithms: they have lots of hitches, but we have no better alternative.
As scientists gain a deeper understanding of the way humans make decisions, the temptation to rely on algorithms is likely to increase. Hacking human decision-making will not only make Big Data algorithms more reliable, it will simultaneously make human feelings less reliable. As governments and corporations succeed in hacking the human operating system, we will be exposed to a barrage of precision-guided manipulation, advertisement and propaganda. It might become so easy to manipulate our opinions and emotions that we will be forced to rely on algorithms in the same way that a pilot suffering an attack of vertigo must ignore what his own senses are telling him and put all his trust in the machinery.