Imagine this. You have to travel from one place to another. You have two options. Human driver driven taxi or an-AI-algorithm-controlled automatic taxi. You know the associated traits of each – the human driver wouldn’t accurately know the roads that will be congested, and may be tired or sleepy. The “machine” driver will exactly know that roads to avoid and would never be sleepy or tired. Well, of course the human driver will have human traits like maybe he likes music and hum a tune or may look up at the sky and get his eyes filled with joy, but you wouldn’t really care about these human traits when your concern is a safe travel to your destination. So, in all likelihood, if both are within your means, you will choose the “machine” over the human cab.
Remind yourselves the fate of horses during the Industrial Revolution. Horse-driven carriages were the ubiquitous means of transport. And in fact, an ordinary farm horse can “smell, love, recognise faces, jump over fences and do a thousand things far better than a Model T Ford or a million-dollar Lamborghini.” But once cars and drivers came along, horse-driven carriages gradually became obsolete, because cars were better in a handful of tasks that travel demanded. “Taxi drivers are highly likely to go the way of horses.”
Suppose you don’t feel well and want to visit a doctor. Again you have two options – a human doctor or an-AI-algorithm-controlled doctor. The human doctor will probably examine you for a few minutes and ask you some questions about your past illnesses, family history etc. and prescribe some examinations and will diagnose your problem. And he maybe tired or sleepy and may not do his job as well. Moreover, not even the best of doctors can be familiar with every illness and drug, or read every new article published in every medical journal. And we all know, that in spite of the best of intentions, doctors often misdiagnose.
Now consider IBM’s famous Watson – an artificial intelligence (AI) system that is currently groomed to diagnose diseases. An AI “can hold in its databanks information about every known illness and medicine in history. It can then update these databanks every day, not only with the findings of new researches, but also with medical statistics gathered from every clinic and hospital in the world.” Secondly, Watson will be familiar not only with your entire genome and day-to-day medical history, but also with the genomes and medical histories of your parents, siblings, cousins, neighbours and friends. Watson will know the history of your recent travels and therefore your vulnerability to certain ailments. And of course, Watson will never be tired, hungry or sick, and will have all the time in the world for you. “With such a Watson around, there is not much need for Sherlocks.”
Sounds a bit like Hollywood sci-fi or Star Trek adventure with machines taking over privacy and lives of humans who actually created them? In Homo Deus, Harari argues that not just taxi drivers and doctors in future. The trend has already set in and is all around us. Think of professionals like travel agents or insurance agents. They are already obsolete when everyone can purchase tickets and insurances at the clicks of their mobile phones.
The main thesis of Homo Deus by Yuval Noah Harari is the following: that we follow the humanist creed in every sphere of life which basically builds on the doctrine that individuals are free to choose what they want – be they politicians to run their country, their spouses, the gadgets in their apartment and so on. This is turn leads us to hail liberalism that stands on the pillars of individualism, human rights, democracy and free market.
However, recent scientific discoveries, especially in biology and computer science, have begun eroding these very fundamental notions that we have taken for granted since many centuries. Biologists now hold that humans are nothing but an assemblage of electrochemical impulses that are not free. And computer scientists have designed algorithms that not only can be influenced (and hence make humans do and choose things) but also can perform tasks incredibly well – tasks that hitherto were thought to be a monopoly of the human species.
Therefore, the rise of non-conscious but super-intelligent algorithms, not only substituting humans in almost every profession, but in fact manipulating and controlling them as marionettes, might just be in the offing. As a result, when individuals and their free choices, as we understand them, cease to exist, the institutions that are sustained around it, like democracy and consumerism, would begin to crumble.
Elephant in the laboratory
Harari argues that actually there is nothing called free will. “The contradiction between free will and contemporary science is the elephant in the laboratory, whom many prefer not to see as they peer into their microscopes and fMRI scanners.” The electrochemical brain processes that result in any action or decision are either deterministic or random or a combination of both (leading to probabilistic outcomes) – but they are never fee, contends Harari.
“Suppose we build a robot whose central processing unit is linked to a radioactive lump of uranium. When choosing between two options – say, press the right button or the left button – the robot counts the number of uranium atoms that decayed during the previous minute. If the number is even – it presses the right button. If the number is odd – the left button. We can never be certain about the actions of such a robot. But nobody would call this contraption ‘free’, and we wouldn’t dream of allowing it to vote in democratic elections or holding it legally responsible for its actions.
To the best of our scientific understanding, determinism and randomness have divided the entire cake between them, leaving not even a crumb for ‘freedom’. The sacred word ‘freedom’ turns out to be, just like ‘soul’, an empty term that carries no discernible meaning. Free will exists only in the imaginary stories we humans have invented.”
Not free, therefore manipulable
Since our decisions and actions are not free, and are basically the outcomes of electrochemical reactions, these can be potentially manipulated.
Harari describes the experiences of a journalist Sally Adee who was allowed to test the effects herself. First, she entered a battlefield simulator without wearing the transcranial helmet (non-intrusive helmet-like devices that is fitted with electrodes that attach to the scalp from outside. It produces weak electromagnetic fields and directs them towards specific brain areas, thereby stimulating or inhibiting select brain activities). “Sally describes how fear swept over her as she saw twenty masked men, strapped with suicide bombs and armed with rifles, charge straight towards her. ‘For every one I manage to shoot dead,’ writes Sally, ‘three new assailants pop up from nowhere. I’m clearly not shooting fast enough, and panic and incompetence are making me continually jam my rifle.’
Then they put the transcranial helmet on her. “She reports feeling nothing unusual, except a slight tingle and a strange metallic taste in her mouth. Yet she began picking off the terrorists one by one, as coolly and methodically as if she were Rambo or Clint Eastwood. ‘As twenty of them run at me brandishing their guns, I calmly line up my rifle, take a moment to breathe deeply, and pick off the closest one, before tranquilly assessing my next target. In what seems like next to no time, I hear a voice call out, “Okay, that’s it.” The lights come up in the simulation room . . . In the sudden quiet amid the bodies around me, I was really expecting more assailants, and I’m a bit disappointed when the team begins to remove my electrodes. I look up and wonder if someone wound the clocks forward. Inexplicably, twenty minutes have just passed. “How many did I get?” I ask the assistant. She looks at me quizzically. “All of them.”’
So all that the transcranial helmet did was silence the voices in our brain that breeds fear, self-doubt, uncertainty and make the voices of confidence and fearlessness louder. Usually one’s head is full of voices, some stemming from society’s prejudices, some reflecting our personal history and some articulating our genetic legacy. All of these together shape our conscious decisions in ways which we seldom understand. “What would happen if we could rewrite our inner monologues, or even silence them completely on occasion?”
Transcranial stimulators are still in their infancy, and nothing is known about their long-term effects and hazards. “However, if the technology does mature, or if some other method is found to manipulate the brain’s electric patterns, what would it do to human societies and to human beings?”
“Who Are I?”
Not only are we not free, there is no ‘one’ self that is in control of us either. In-dividual (dividual means divided, individual therefore means “cannot be divided”). Individuals are anything but that, argues Harari.
“For liberalism to make sense, I must have one – and only one – true self, for if I had more than one authentic voice, how would I know which voice to heed in the polling station, in the supermarket and in the marriage market? However, over the last few decades the life sciences have reached the conclusion that this liberal story is pure mythology. … If you look really deep within yourself, the seeming unity that we take for granted dissolves into a cacophony of conflicting voices, none of which is ‘my true self’. Humans aren’t individuals. They are ‘dividuals’.”
To back his claim, he explains how we have emotional and cognitive differences between the two hemispheres of our brains, though the division is far from clear-cut. “In most cases the left hemisphere plays a more important role in speech and in logical reasoning, whereas the right hemisphere is more dominant in processing spatial information.”
Many breakthroughs in understanding the relations between the two hemispheres were based on the study of epilepsy patients (in severe cases of epilepsy, electrical storms from one part of the brain quickly spread to other parts, causing a very acute seizure). In the mid-twentieth century, when all other treatments failed, doctors tried to solve the problem by cutting the thick neural cable connecting the two hemispheres, so that electrical storms beginning in one hemisphere did not spill over to the other. These split-brain patients provided a treasure trove of data for brain scientists on how the different lobes of the brain function.
Professor Roger Wolcott Sperry, who won the Nobel Prize in Physiology and Medicine for his groundbreaking discoveries, his student, Professor Michael S. Gazzaniga conducted series of path-breaking experiments. In one such experiment, for example, Gazzaniga and his team “flashed a picture of a chicken claw to the left-half brain – the side responsible for speech – and simultaneously flashed a picture of a snowy landscape to the right brain. When asked what they saw, patients invariably answered ‘a chicken claw’. Gazzaniga then presented one patient, PS, with a series of picture cards and asked him to point to the one that best matched what he had seen. The patient’s right hand (controlled by his left brain) pointed to a picture of a chicken, but simultaneously his left hand shot out and pointed to a snow shovel. Gazzaniga then asked PS the million-dollar question: ‘Why did you point both to the chicken and to the shovel?’ PS replied, ‘Oh, the chicken claw goes with the chicken, and you need a shovel to clean out the chicken shed.’ ”
The left brain, which controls speech, had no data about the snow scene, and therefore did not really know why the left hand pointed to the shovel. So it just invented something credible. After repeating this experiment many times, Gazzaniga concluded that the left hemisphere of the brain is the seat not only of our verbal abilities, but also of an internal interpreter that constantly tries to make sense of our life, using partial clues in order to concoct plausible stories.”
Which part of my brain is actually me? The experiencing part or the narrating/story-telling part?
Decoupling of Intelligence from Consciousness
This decoupling of consciousness and intelligence is the key to the rise of the machines. “Until today, high intelligence always went hand in hand with a developed consciousness. Only conscious beings could perform tasks that required a lot of intelligence, such as playing chess, driving cars, diagnosing diseases or identifying terrorists. However, we are now developing new types of non-conscious intelligence that can perform such tasks far better than humans. For all these tasks are based on pattern recognition, and non-conscious algorithms may soon excel human consciousness in recognising patterns. This raises a novel question: which of the two is really important, intelligence or consciousness? As long as they went hand in hand, debating their relative value was just a pastime for philosophers. But in the twenty-first century, this is becoming an urgent political and economic issue. And it is sobering to realise that, at least for armies and corporations, the answer is straightforward: intelligence is mandatory but consciousness is optional.”
Let us come back to the opening examples in the article. Suppose we give computer algorithms complete control over all vehicular traffic. Then theoretically, it would make car accidents virtually impossible. “In August 2015, one of Google’s experimental self-driving cars had an accident. As it approached a crossing and detected pedestrians wishing to cross, it applied its brakes. A moment later it was hit from behind by a sedan whose careless human driver was perhaps contemplating the mysteries of the universe instead of watching the road. This could not have happened if both vehicles were steered by interlinked computers. The controlling algorithm would have known the position and intentions of every vehicle on the road, and would not have allowed two of its marionettes to collide. Such a system will save lots of time, money and human lives – but it will also do away with the human experience of driving a car and with tens of millions of human jobs.”
The signs of massive substitution of human workers not only for less-skilled jobs like bank clerks and travel agents but also white-collar jobs by more sophisticated computer-algorithms abound. “How many travel agents do we need when we can use our smartphones to buy plane tickets from an algorithm?”
Stock-exchange trading today is already being managed by computer algorithms, “which can process in a second more data than a human can in a year, and that can react to the data much faster than a human can blink.”
Most run-of-the-mill lawyers for example, “spend their time going over endless files, looking for precedents, loopholes and tiny pieces of potentially relevant evidence. Some are busy… formulating a gargantuan business contract that will protect their client against every conceivable eventuality. What will be the fate of all these lawyers once sophisticated search algorithms can locate more precedents in a day than a human can in a lifetime, and once brain scans can reveal lies and deceptions at the press of a button?”
How about spotting deceptions merely by observing people’s facial expressions and tone of voice? Lying involves different ares of the brain than used during telling the truth. What if a computer algorithm can see fMRI scans and act as infallible truth machines? “Where will that leave millions of lawyers, judges, cops and detectives?”, questions Harari.
What about the fate of teachers? “Companies such as Mindojo are developing interactive algorithms that not only teach me maths, physics and history, but also simultaneously study me and get to know exactly who I am. Digital teachers will closely monitor every answer I give, and how long it took me to give it. Over time, they will discern my unique weaknesses as well as my strengths. They will identify what gets me excited, and what makes my eyelids droop. … And these digital teachers will never lose their patience, never shout at me, and never go on strike.”
Algorithms (like Watson, as described in the beginning) are threatening to replace not just general practitioners but experts too, and even more so. “For example, in a recent experiment a computer algorithm diagnosed correctly 90 per cent of lung cancer cases presented to it, while human doctors had a success rate of only 50 per cent. In fact, the future is already here. CT scans and mammography tests are routinely checked by specialised algorithms, which provide doctors with a second opinion, and sometimes detect tumours that the doctors missed.” Again, there are several technical problems that still prevent Watson from replacing most doctors tomorrow morning. Yet once they are sorted out, their performance would be arguably much better.
Professor Frank Levy from MIT and Professor Richard Murnane from Harvard who in 2004 in an article, listed those professions most likely to undergo automation. “Truck drivers were given as an example of a job that could not possibly be automated in the foreseeable future. It is hard to imagine, they wrote, that algorithms could safely drive trucks on a busy road. A mere ten years later, Google and Tesla not only imagine this, but are actually making it happen.”
In September 2013 two Oxford researchers, Carl Benedikt Frey and Michael A. Osborne, published ‘The Future of Employment’, in which they studied the likelihood of different professions being taken over by computer algorithms within the next twenty years. They estimated that “47 per cent of US jobs are at high risk. For example, there is a 99 per cent probability that by 2033 human telemarketers and insurance underwriters will lose their jobs to algorithms. There is a 98 per cent probability that the same will happen to sports referees, 97 per cent that it will happen to cashiers and 96 per cent to chefs. Waiters – 94 per cent. Paralegal assistants – 94 per cent. Tour guides – 91 per cent. Bakers – 89 per cent. Bus drivers – 89 per cent. Construction labourers – 88 per cent. Veterinary assistants – 86 per cent. Security guards – 84 per cent. Sailors – 83 per cent. Bartenders – 77 per cent. Archivists – 76 per cent. Carpenters – 72 per cent. Lifeguards – 67 per cent. And so forth.”
However, “by 2033 many new professions are likely to appear, for example, virtual-world designers. But such professions will probably require much more creativity and flexibility than your run-of-the-mill job, and it is unclear whether forty-year-old cashiers or insurance agents will be able to reinvent themselves as virtual-world designers… After all, algorithms might well outperform humans in designing virtual worlds too. The crucial problem isn’t creating new jobs. The crucial problem is creating new jobs that humans perform better than algorithms.”
Why has it become so easy to substitute humans? Harari answers, “not merely because the algorithms are getting smarter, but also because humans are professionalising. Ancient hunter-gatherers mastered a very wide variety of skills in order to survive, which is why it would be immensely difficult to design a robotic hunter-gatherer. Such a robot would have to know how to prepare spear points from flint stones, how to find edible mushrooms in a forest, how to use medicinal herbs to bandage a wound, how to track down a mammoth and how to coordinate a charge with a dozen other hunters. However, over the last few thousand years we humans have been specialising. A taxi driver or a cardiologist specialises in a much narrower niche than a hunter- gatherer, which makes it easier to replace them with AI.”
Nowadays companies are even appointing algorithms as board members to manage complex corporation! “Ventures – a Hong Kong venture-capital firm specialising in regenerative medicine – broke new ground by appointing an algorithm called VITAL to its board. VITAL makes investment recommendations by analysing huge amounts of data on the financial situation, clinical trials and intellectual property of prospective companies. Like the other five board members, the algorithm gets to vote on whether the firm makes an investment in a specific company or not.”
What might be the fallout of such unprecedented algorithmic ascent in otherwise human institutions? Harari points out, “wealth might become concentrated in the hands of the tiny elite that owns the all-powerful algorithms, creating unprecedented social inequality.”
What about art?
But surely machines won’t have a chance where creativity, imagination and originality are concerned? What about art, music, poetry?
David Cope is a musicology professor at the University of California in Santa Cruz, “who’s written programs that compose concertos, chorales, symphonies and operas. His first creation was named EMI (Experiments in Musical Intelligence), which specialised in imitating the style of Johann Sebastian Bach. It took seven years to create the program, but once the work was done, EMI composed 5,000 chorales à la Bach in a single day.” EMI gradually improved and learned to imitate Beethoven, Chopin, Rachmaninov and Stravinsky.
But a sceptic, Professor Steve Larson from the University of Oregon, sent Cope a challenge for a musical contest, where professional pianists would play three pieces one after the other – one by Bach, one by EMI, and one by Larson himself. The audience would then be asked to vote who composed which piece. “On the appointed date, hundreds of lecturers, students and music fans assembled in the University of Oregon’s concert hall. At the end of the performance, a vote was taken. The result? The audience thought that EMI’s piece was genuine Bach, that Bach’s piece was composed by Larson, and that Larson’s piece was produced by a computer. … Critics continued to argue that EMI’s music is technically excellent, but that it lacks something. It is too accurate. It has no depth. It has no soul. Yet when people heard EMI’s compositions without being informed of their provenance, they frequently praised them precisely for their soulfulness and emotional resonance.”
Cope created newer and newer algorithms and his crowning achievement was Annie. “Whereas EMI composed music according to predetermined rules, Annie is based on machine learning. Its musical style constantly changes and develops in reaction to new inputs from the outside world. Cope has no idea what Annie is going to compose next.”
Annie not only composes music but also writes poetry – haiku. “In 2011 Cope published Comes the Fiery Night: 2,000 Haiku by Man and Machine. Of the 2,000 haikus in the book, some are written by Annie, and the rest by organic poets. The book does not disclose which are which. If you think you can tell the difference between human creativity and machine output, you are welcome to test your claim.”
As I am writing this review, I see news about the creativity of AI in the newspaper almost everyday. In Statesman on 7th May there is a picture of AI-based art https://epaper.thestatesman.com/c/72363713 while in Hindustan Times there’s news of writers going on strike as Hollywood studios employ AI to write the next stories for Hollywood movies https://www.hindustantimes.com/world-news/will-ai-write-the-next-hollywood-blockbuster-writers-strike-intensifies-over-studios-refusal-to-regulate-use-of-ai-101683425045699.html. On 8th May, Statesman carries the news “Could AI pen ‘Casablanca’? Screenwriters take aim at ChatGPT” (available at https://epaper.thestatesman.com/c/72368368).
In short, even the domains of creativity and imagination, that were supposed to be strictly within human dominance, have begun to be invaded by computer algorithms.
Is this bad news?
Well, not necessarily. When external algorithms to know me far better than I know myself, “the belief in individualism will collapse and authority will shift from individual humans to networked algorithms. People will no longer see themselves as autonomous beings running their lives according to their wishes, and instead become accustomed to seeing themselves as a collection of biochemical mechanisms that is constantly monitored and guided by a network of electronic algorithms. For this to happen, there is no need of an external algorithm that knows me perfectly, and that never makes any mistakes; it is enough that an external algorithm will know me better than I know myself, and will make fewer mistakes than me. It will then make sense to trust this algorithm with more and more of my decisions and life choices.
We have already crossed this line as far as medicine is concerned. In the hospital, we are no longer individuals. Who do you think will make the most momentous decisions about your body and your health during your lifetime? It is highly likely that many of these decisions will be taken by computer algorithms such as IBM’s Watson. … Diabetics already carry sensors that automatically check their sugar level several times a day, alerting them whenever it crosses a dangerous threshold. In 2014 researchers at Yale University announced the first successful trial of an ‘artificial pancreas’ controlled by an iPhone. … Each patient had a tiny sensor and a tiny pump implanted in his or her stomach. The pump was connected to small tubes of insulin and glucagon, two hormones that together regulate sugar levels in the blood. The sensor constantly measured the sugar level, transmitting the data to an iPhone. The iPhone hosted an application that analysed the information, and whenever necessary gave orders to the pump, which injected measured amounts of either insulin or glucagon – without any need of human intervention.”
Nowadays everyone uses wearable sensors and computers to monitor their health and activities. “The devices – incorporated into anything from smartphones and wristwatches to armbands and underwear – record diverse biometric data such as blood pressure. The data is then fed into sophisticated computer programs, which advise you how to change your diet and daily routines so as to enjoy improved health and a longer and more productive life.”
Not just in medicine, suppose algorithms could make other decisions like voting decisions for us. Is that necessarily bad? Usually humans (rather its narrating/story-telling self) tend to forget vast majority of events, and remembers only a few extreme incidents and gives unduly large weightage to recent happenings.
Harari elaborates, “For four long years I may repeatedly complain about the PM’s policies, telling myself and anyone willing to listen that he will be ‘the ruin of us all’. However, in the months prior to the elections the government cuts taxes and spends money generously. The ruling party hires the best copywriters to lead a brilliant campaign, with a well-balanced mixture of threats and promises that speak right to the fear centre in my brain. On the morning of the elections I wake up with a cold, which impacts my mental processes, and causes me to prefer security and stability over all other considerations. And voila! I send the man who will be ‘the ruin of us all’ back into office for another four years.
I could have saved myself from such a fate if I only authorised Google to vote for me. Google wasn’t born yesterday, you know. Though it doesn’t ignore the recent tax cuts and the election promises, it also remembers what happened throughout the previous four years. It knows what my blood pressure was every time I read the morning newspapers, and how my dopamine level plummeted while I watched the evening news. Google will know how to screen the spin-doctors’ empty slogans. Google will also know that illness makes voters lean a bit more to the right than usual, and will compensate for this. Google will therefore be able to vote not according to my momentary state of mind, and not according to the fantasies of the narrating self, but rather according to the real feelings and interests of the collection of biochemical algorithms known as ‘I’.”
Hence we could potentially live in an algorithm-controlled albeit healthier and happier world and lives.
What is the bad news then?
When every one of our breaths is monitored and recorded, we might actually forget about privacy. “If we connect all the dots, and if we give Google and its competitors free access to our biometric devices, to our DNA scans and to our medical records, we will get an all-knowing medical health service, which will not only fight epidemics, but will also shield us from cancer, heart attacks and Alzheimer’s. Yet with such a database at its disposal, Google could do far more. Imagine a system that, in the words of the famous Police song, watches every breath you take, every move you make and every bond you break. A system that monitors your bank account and your heartbeat, your sugar levels and your sexual escapades. It will definitely know you much better than you know yourself. The self-deceptions and self-delusions that trap people in bad relationships, wrong careers and harmful habits will not fool Google. Unlike the narrating self that controls us today, Google will not make decisions on the basis of cooked-up stories, and will not be misled by cognitive short cuts and the peak-end rule. Google will actually remember every step we took and every hand we shook.”
Think of the apparently innocuous act of buying a book on Amazon, something that each of us do several times. “When I go to Amazon to buy a book, an ad pops up and tells me: ‘I know which books you liked in the past. People with similar tastes also tend to love this or that new book.’ Wonderful! There are millions of books in the world, and I can never go over all of them, not to mention predicting accurately which ones I would like. How good that an algorithm knows me, and can give me recommendations based on my unique taste.
And this is just the beginning. Today in the US more people read digital books than printed volumes. Devices such as Amazon’s Kindle are able to collect data on their users while they are reading the book. For example, your Kindle can monitor which parts of the book you read fast, and which slow; on which page you took a break, and on which sentence you abandoned the book, never to pick it up again. (Better tell the author to rewrite that bit.) If Kindle is upgraded with face recognition and biometric sensors, it can know what made you laugh, what made you sad and what made you angry. Soon, books will read you while you are reading them. And whereas you quickly forget most of what you read, Amazon will never forget a thing. Such data will enable Amazon to evaluate the suitability of a book much better than ever before. It will also enable Amazon to know exactly who you are, and how to turn you on and off.”
And it is nearly impossible to actually choose the benefits of the system and keeping your privacy intact at the same time. Harari foretells doom, “Eventually, we may reach a point when it will be impossible to disconnect from this all-knowing network even for a moment. Disconnection will mean death. If medical hopes are realised, future people will incorporate into their bodies a host of biometric devices, bionic organs and nano-robots, which will monitor our health and defend us from infections, illnesses and damage. Yet these devices will have to be online 24/7, both in order to be updated with the latest medical news, and in order to protect them from the new plagues of cyberspace. Just as my home computer is constantly attacked by viruses, worms and Trojan horses, so will be my pacemaker, my hearing aid and my nanotech immune system. If I don’t update my body’s anti-virus program regularly, I will wake up one day to discover that the millions of nano-robots coursing through my veins are now controlled by a North Korean hacker.”
Dataism: the new normal
Where has all the power gone?
Though cyberspace is crucial to our daily lives, economy and security, hardly anyone has an understanding of how things actually happen, leave alone control them. “Governments and NGOs consequently conduct intense debates about restructuring the Internet, but …by the time the cumbersome government bureaucracy makes up its mind about cyber regulation, the Internet has morphed ten times. The governmental tortoise cannot keep up with the technological hare. It is overwhelmed by data.”
In general, both politicians and voters are clueless as to what’s going on. “In the coming decades, it is likely that we will see more Internet-like revolutions, in which technology steals a march on politics. Artificial intelligence and biotechnology might soon overhaul our societies and economies – and our bodies and minds too – but they are hardly a blip on our political radar. Our current democratic structures just cannot collect and process the relevant data fast enough, and most voters don’t understand biology and cybernetics well enough to form any pertinent opinions. … Ordinary voters are beginning to sense that the democratic mechanism no longer empowers them. The world is changing all around, and they don’t understand how or why. … Power is shifting away from them, but they are unsure where it has gone.”
Harari concludes, “The idea that humans will always have a unique ability beyond the reach of non-conscious algorithms is just wishful thinking. … Hence there is no reason to think that organic algorithms can do things that non-organic algorithms will never be able to replicate or surpass. As long as the calculations remain valid, what does it matter whether the algorithms are manifested in carbon or silicon?”
None of these will probably happen in our lifetimes but nevertheless we’re all bound by shared feelings for those that were, are and will be, and this might well be the reality of our children. For old-timers like us, Homo Deus is literally a horror story. The book, its questions and possible prophecies are exceedingly uncomfortable to say the least and outrightly scary at worst – it makes the chill of losing your worth run down your spine and fills you with a kind of melancholic foreboding and apprehension that might have filled the Neanderthals when the Sapiens came along. But then maybe, it is coming full circle with what started with the ascent of the Sapiens as masters over all other species making them subservient to his will. Maybe it is time AI pays us in our own coins.
Soumyanetra Munshi, Associate Professor, Economic Research Unit, Indian Statistical Institute, Kolkata.