Mozart nella macchina, parte 2 Automazione, arte e musica, pagine di "21 lezioni per il XXI secolo" (2018) di Yuval Noah Harari.

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Mozart nella macchina, parte 2 Automazione, arte e musica, pagine di "21 lezioni per il XXI secolo" (2018) di Yuval Noah Harari.

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People might object that algorithms could never make important decisions for us, because important decisions usually involve an ethical dimension, and algorithms don’t understand ethics. Yet there is no reason to assume that algorithms won’t be able to outperform the average human even in ethics. Already today, as devices like smartphones and autonomous vehicles undertake decisions that used to be a human monopoly, they start to grapple with the same kind of ethical problems that have bedevilled humans for millennia.
For example, suppose two kids chasing a ball jump right in front of a self-driving car. Based on its lightning calculations, the algorithm driving the car concludes that the only way to avoid hitting the two kids is to swerve into the opposite lane, and risk colliding with an oncoming truck. The algorithm calculates that in such a case there is a 70 percent chance that the owner of the car - who is fast asleep in the back seat - would be killed. What should the algorithm do?
Philosophers have been arguing about such ‘trolley problems' for millennia (they are called 'trolley problems’ because the textbook examples in modern philosophical debates refer to a runaway trolley car racing down a railway track, rather than to a self-driving car).“ Up until now, these arguments have had embarrassingly little impact on actual behaviour, because in times of crisis humans all too often forget about their philosophical views and follow their emotions and gut instincts instead. One of the nastiest experiments in the history of the social sciences was conducted in December 1970 on a group of Students at the Princeton Theological Seminary, who were training to become ministers in the Presbyterian Church. Each student was asked to hurry to a distant lecture hall, and there give a talk on the Good Samaritan parable, which tells how a Jew travelling from Jerusalem to Jericho was robbed and beaten by criminals, who then left him to die by the side of the road. After some time a priest and a Levite passed nearby, but both ignored the man. In contrast, a Samaritan - a member of a sect much despised by the Jews - stopped when he saw the victim, took care of him, and saved his life. The moral of the parable is that people’s merit should be judged by their actual behaviour, rather than by their religious affiliation.
The eager young seminarians rushed to the lecture hall, contemplating on the way how best to explain the moral of the Good Samaritan parable. But the experimenters planted in their path a shabbily dressed person, who was sitting slumped in a doorway with his head down and his eyes closed. As each unsuspecting seminarian was hurrying past, the 'victim’ coughed and groaned pitifully. Most seminarians did not even stop to inquire what was wrong with the man, let alone offer any help. The emotional stress created by the need to hurry to the lecture hall trumped their moral obligation to help strangers in distress.
Human emotions trump philosophical theories in countless other situations. This makes the ethical and philosophical history of the world a rather depressing rale of wonderful ideals and less than ideal behaviour. How many Christians actually turn the other cheek, how many Buddhists actually rise above egoistic obsessions, and how many Jews actually love their neighbours as themselves? That’s just the way natural selection has shaped Homo sapiens. Like all mammals, Homo sapiens uses emotions to quickly make life and death decisions. We have inherited our anger, our fear and our lust from millions of ancestors, all of whom passed the most rigorous quality control tests of natural selection.
Unfortunately, what was good for survival and reproduction in the African savannah a million years ago does not necessarily make for responsible behaviour on twenty-first-century motorways. Distracted, angry and anxious human drivers kill more than a million people in traffic accidents every year. We can send all our philosophers, prophets and priests to preach ethics to these drivers - but on the road, mammalian emotions and savannah instincts will still take over. Consequently, seminarians in a rush will ignore people in distress, and drivers in a crisis will run over hapless pedestrians.
This disjunction between the seminary and the road is one of the biggest practical problems in ethics. Immanuel Kant, John Swart Mill and John Rawls can sit in some cosy university hall and discuss theoretical problems in ethics for days - but would their conclusions actually be implemented by stressed-out drivers caught in a split-second emergency? Perhaps Michael Schumacher - the Formula One champion who is sometimes hailed as the best driver in history - had the ability to think about philosophy while racing a car; but most of us aren’t Schumacher.
Computer algorithms, however, have not been shaped by natural selection, and they have neither emotions nor gut instincts. Hence in moments of crisis they could follow ethical guidelines much better than humans - provided we find a way to code ethics in precise numbers and statistics. If we teach Kant, Mill and Rawls to write code, they can carefully program the self-driving car in their cosy laboratory, and be certain that the car will follow their commandments on the highway. In effect, every car will be driven by Michael Schumacher and Immanuel Kant rolled into one.
Thus if you program a self-driving car to stop and help strangers in distress, it will do so come hell or high water (unless, of course, you insert an exception clause for infernal or high-water scenarios). Similarly, if your self-driving car is programmed to swerve to the opposite lane in order to save the two kids in its path, you can bet your life this is exactly what it will do. Which means that when designing their self-driving car, Toyota or Tesla will be transforming a theoretical problem in the philosophy of ethics into a practical problem of engineering.
Granted, the philosophical algorithms will never be perfect. Mistakes will still happen, resulting in injuries, deaths and extremely complicated lawsuits. (For the first time in history, you might be able to sue a philosopher for the unfortunate results of his or her theories, because for the first time in history you could prove a direct causal link between philosophical ideas and real-life events.) However, in order to take over from human drivers, the algorithms won’t have to be perfect. They will just have to be better than the humans. Given that human drivers kill more than a million people each year, that isn’t such a tall order. When all is said and done, would you rather the car next to you was driven by a drunk teenager, or by the Schumacher-Kant team?
The same logic is true not just of driving, but of many other situations. Take for example job applications. In the twenty-first century, the decision whether to hire somebody for a job will increasingly be made by algorithms. We cannot rely on the machine to set the relevant ethical standards - humans will still need to do that. But once we decide on an ethical standard in the job market - that it is wrong to discriminate against black people or against women, for example - we can rely on machines to implement and maintain this standard better than humans. A human manager may know and even agree that it is unethical to discriminate against black people and women, but then, when a black woman applies for a job, the manager subconsciously discriminates against her, and decides not to hire her. If we allow a computer to evaluate job applications, and program the computer to completely ignore race and gender, we can be certain that the computer will indeed ignore these factors, because computers don’t have a subconscious. Of course, it won’t be easy to write code for evaluating job applications, and there is always a danger that the engineers will somehow program their own subconscious biases into the software. Yet once we discover such mistakes, it would probably be far easier to debug the software than to rid humans of their racist and misogynist biases.
We saw that the rise of artificial intelligence might push most humans out of the job market - including drivers and traffic police (when rowdy humans are replaced by obedient algorithms, traffic police will be redundant). However, there might be some new openings for philosophers, because their skills - hitherto devoid of much market value - will suddenly be in very high demand. So if you want to study something that will guarantee a good job in the future, maybe philosophy is not such a bad gamble. Of course, philosophers seldom agree on the right course of action. Few 'trolley problems’ have been solved to the satisfaction of all philosophers, and consequentialist thinkers such as John Stuart Mill (who judge actions by consequences) hold quite different opinions to deontologists such as Immanuel Kant (who judge actions by absolute rules). Would Tesla have to actually take a stance on such knotty matters in order to produce a car?
Well, maybeTesla will just leave it to the market. Tesla will produce two models of the self-driving car: the Tesla Altruist and the Tesla Egoist. In an emergency, the Altruist sacrifices its owner to the greater good, whereas the Egoist does everything in its power to save its owner, even if it means killing the two kids. Customers will then be able to buy the car that best fits their favourite philosophical view. If more people buy the Tesla Egoist, you won’t be able to blame Tesla for that. After all. the customer is always right.
This is not a joke. In a pioneering 2015 study people were presented with a hypothetical scenario of a self-driving car about to run over several pedestrians. Most said that in such a case the car should save the pedestrians even at rhe price of killing its owner. When they were then asked whether they personally would buy a car programmed to sacrifice irs owner for the grearet good, most said no. For themselves, they would prefer the Tesla Egoist.
Imagine the situation: you have bought a new car, bur before you can start using it, you must open the settings menu and tick one of several boxes. In case of an accident, do you want the car to sacrifice your life - or to kill the family in the other vehicle? Is this a choice you even want to make? Just think of the arguments you are going to have with your husband about which box to tick.
So maybe the state should intervene to regulate the market, and lay down an ethical code binding all self-driving cars? Some lawmakers will doubtless be thrilled by the opportunity to finally make laws that are always followed to the letter. Other lawmakers may be alarmed by such unprecedented and totalitarian responsibility. After all, throughout history the limitations of law enforcement provided a welcome check on the biases, mistakes and excesses of lawmakers. It was an extremely lucky thing that laws against homosexuality and against blasphemy were only partially enforced. Do we really want a system in which the decisions of fallible politicians become as inexorable as gravity?
- Yuval Noah Harari, The philosophical car in 21 Lessons for the 21st century
Yuval Noah Harari In Conversation with Christine Lagarde
“I do think it’s very important for people to make the effort to get to know themselves better. I know this is the oldest advice in the book. Socrates, Jesus, and Buddha said it: ‘Know thyself.’ But in the age of Socrates, you did not have competition. Now you have.”
21 LESSONS FOR THE 21st CENTURY - YUVAL NOAH HARARI
I was looking for an image that would sit alongside the iconic finger prints on both Sapiens and Homo Deus. The iris is like a fingerprint. It is individual to each of us. I had just come back from a holiday and it struck me as I went through passport control, that it might be a fabulous image for 21 Lessons. We then found this wonderful iris, by artist Marc Quinn, that seemed to stand for all mankind.
21 Lessons is published by Jonathan Cape.
Yuval Noah Harari: The Challenges of The 21st Century

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21 Lessons for the 21st Century (Yuval Noah Harari, 2018)
“According to some measures, Russia is one of the most unequal countries in the world, with 87 per cent of wealth concentrated in the hands of the richest 10 per cent of people.
How many working-class supporters of the Front National want to copy this wealth-distribution pattern in France?
Humans vote with their feet.
In my travels around the world I have met numerous people in many countries who wish to emigrate to the USA, to Germany, to Canada or to Australia.
I have met a few who want to move to China or Japan. But I am yet to meet a single person who dreams of emigrating to Russia.
As for ‘global Islam’, it attracts mainly those who were born in its lap.
While it may appeal to some people in Syria and Iraq, and even to alienated Muslim youths in Germany and Britain, it is hard to see Greece or South Africa – not to mention Canada or South Korea – joining a global caliphate as the remedy to their problems.
In this case, too, people vote with their feet.
For every Muslim youth from Germany who travelled to the Middle East to live under a Muslim theocracy, probably a hundred Middle Eastern youths would have liked to make the opposite journey, and start a new life for themselves in liberal Germany.”
21 Lessons for the 21st Century (Yuval Noah Harari, 2018)
“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.
But Amazon won’t have to be perfect. It will just need to be better on average than us humans.”
(…)
“One student might start law school because she has an inaccurate image of her own skills, and an even more distorted view of what being a lawyer actually involves (you don’t get to give dramatic speeches and shout ‘Objection, Your Honour!’ all day).
Meanwhile her friend decides to fulfil a childhood dream and study professional ballet dancing, even though she doesn’t have the necessary bone structure or discipline.
Years later, both deeply regret their choices. In the future we could rely on Google to make such decisions for us.
Google could tell me that I would be wasting my time in law school or in ballet school – but that I might make an excellent (and very happy) psychologist or plumber.
Once AI makes better decisions than us about careers and perhaps even relationships, our concept of humanity and of life will have to change.
Humans are used to thinking about life as a drama of decision-making.”
21 Lessons for the 21st Century (Yuval Noah Harari, 2018)
“When trying to outline their identity, people often make a grocery list of common traits.
That’s a mistake. They would fare much better if they made a list of common conflicts and dilemmas.
For example, in 1618 Europe didn’t have a single religious identity – it was defined by religious conflict.
To be a European in 1618 meant to obsess about tiny doctrinal differences between Catholics and Protestants or between Calvinists and Lutherans, and to be willing to kill and be killed because of these differences.
If a human being in 1618 did not care about these conflicts, that person was perhaps a Turk or a Hindu, but definitely not a European.
Similarly in 1940 Britain and Germany had very different political values, yet they were both part and parcel of ‘European Civilisation’.
Hitler wasn’t less European than Churchill. Rather, the very struggle between them defined what it meant to be European at that particular juncture in history.
In contrast, a !Kung hunter-gatherer in 1940 wasn’t European because the internal European clash about race and empire would have made little sense to him.”
(…)
“The people we fight most often are our own family members. Identity is defined by conflicts and dilemmas more than by agreements.
What does it mean to be European in 2018? It doesn’t mean to have white skin, to believe in Jesus Christ, or to uphold liberty.
Rather, it means to argue vehemently about immigration, about the EU, and about the limits of capitalism.
It also means to obsessively ask yourself ‘what defines my identity?’ and to worry about an ageing population, about rampant consumerism and about global warming.
In their conflicts and dilemmas, twenty-first-century Europeans are different from their ancestors in 1618 and 1940, but are increasingly similar to their Chinese and Indian trade partners.”