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Rule of the Robots: How Artificial Intelligence Will Transform Everything

Rule of the Robots: How Artificial Intelligence Will Transform Everything PDF

Author: Martin Ford

Publisher: Basic Books


Publish Date: September 30, 2021

ISBN-10: 1529345987

Pages: 257

File Type: PDF

Language: English

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Book Preface

ON NOVEMBER 30, 2020, DEEPMIND, A LONDON-BASED ARTIFICIAL intelligence company owned by Google parent Alphabet, announced a stunning, and likely historic, breakthrough in computational biology, an innovation with the potential to genuinely transform science and medicine. The company had succeeded in using deep neural networks to predict how a protein molecule will fold into its final shape based on the genetic code from which the molecule is constructed in cells. It was a milestone that culminated a fifty-year scientific quest and marked the advent of a new technology that was poised to usher in an unprecedented understanding of the very fabric of life—as well as a new age of medical and pharmaceutical innovation.1

Protein molecules are long chains in which each link consists of one of twenty different amino acids. The genes encoded in DNA lay out the precise sequence, or essentially the recipe, of the amino acids that make up the protein molecule. This genetic recipe, however, does not specify the shape of the molecule, which is critical to its function. Instead, the shape results from the way the molecule automatically folds into a highly complex three-dimensional structure within milliseconds of its fabrication in the cell.2
Predicting the exact configuration into which a protein molecule will fold is one of the most daunting challenges in science. The number of possible shapes is virtually infinite. Scientists have devoted entire careers to the problem, but have collectively achieved only modest success. DeepMind’s system uses AI techniques that the company pioneered in the AlphaGo and AlphaZero systems that had famously triumphed over the world’s best human competitors at board games like Go and chess. But the era of AI being primarily associated with adeptness at games is clearly drawing to a close. AlphaFold’s ability to predict the shape of protein molecules with an accuracy that rivals expensive and time-consuming laboratory measurement using techniques like X-ray crystallography offers irrefutable evidence that research at the very frontier of artificial intelligence has produced a practical and indispensable scientific tool with the potential to transform the world.

Arriving at a moment when nearly everyone on earth had likely encountered illustrations featuring the most notorious example of how a protein molecule’s three-dimensional shape defines its function—the coronavirus spike protein, a kind of molecular docking mechanism that allows the virus to attach to and infect its host—the breakthrough offered hope that we will be far better prepared for the next pandemic. One important use of the system might be to rapidly screen existing medications to find the ones likely to be most effective against a newly emergent virus, putting powerful treatments in the hands of doctors in the earliest stages of an outbreak. Beyond this, DeepMind’s technology is poised to lead to a variety of advances, including the design of entirely new drugs and a better understanding of the ways in which proteins can misfold—something that has been associated with illnesses like diabetes as well as Alzheimer’s and Parkinson’s diseases. The technology might someday be employed in a range of applications outside medicine, for example, to help engineer microbes that can secrete proteins capable of degrading waste such as plastic or oil.3 In other words, it is an innovation with the potential to accelerate progress in virtually every sphere of biochemical science and medicine.

Over roughly the past decade, the field of artificial intelligence has taken a revolutionary leap forward and is beginning to deliver an ever-increasing number of practical applications that are already transforming the world around us. The primary accelerant of this progress has been “deep learning”—a machine learning technique based on the use of multilayered artificial neural networks of the kind employed by DeepMind. The basic principles of deep neural networks have been understood for decades, but recent dramatic advances have been enabled by the confluence of two relentless trends in information technology: First, the arrival of vastly more powerful computers has, for the first time, allowed neural networks to transition into truly capable tools. And, second, the enormous troves of data now being generated and collected across the information economy provide a resource crucial to training these networks to perform useful tasks. Indeed, the availability of data at a scale that would have once been unimaginable is arguably the single most important factor underlying the startling progress we have seen. Deep neural networks hoover up and leverage data much in the way that a massive blue whale feeds on tiny krill, scooping up vast numbers of individually insignificant organisms and then using their collective energy to animate a creature of magnificent size and power.

As artificial intelligence is successfully applied to more and more areas, it is becoming clear that it is evolving into a uniquely consequential technology. In some specific areas of medicine, for example, diagnostic AI applications are already beginning to match or even exceed the performance of the best doctors. The true power of such an innovation does not lie just in its ability to potentially outperform a single world-class physician, but rather in the ease with which the intelligence encapsulated in the technology can be scaled. Someday soon, elite diagnostic expertise will be affordably broadcast across the globe, making it available even in regions where people barely have access to any doctor or nurse—let alone to one of the world’s best medical specialists.

Now imagine taking a single, extremely specific innovation—an AI-based diagnostic tool or perhaps DeepMind’s breakthrough in protein folding—and multiplying it by a virtually limitless number of possibilities in other areas from medicine to science, industry, transportation, energy, government and every other sphere of human activity. What you end up with is a new, and uniquely powerful, utility. In essence, an “electricity of intelligence.” A flexible resource that can—perhaps someday with almost a flick of a switch—apply cognitive capability to virtually any problem we face. Ultimately, this new utility will deliver the ability not just to analyze and make decisions but to solve complex problems and even exhibit creativity.

The purpose of this book will be to explore the future implications of artificial intelligence by viewing it not as a specific innovation, but rather as a uniquely scalable and potentially disruptive technology—a powerful new utility poised to deliver a transformation that will someday rival the impact of electricity. The arguments and explanations I will put forth here draw heavily on three of my own professional experiences.

First, since the publication of my book Rise of the Robots: Technology and the Threat of a Jobless Future in 2015, I have been invited to speak about the impact of artificial intelligence and robotics at dozens of technology conferences, regional summits and corporate and academic events. I’ve traveled to more than thirty countries and have had an opportunity to visit research labs, to see demonstrations of leading-edge technology and to discuss and debate the implications of the unfolding AI revolution with technical experts, economists, business executives, investors and politicians, as well as average people who are seeing—and beginning to worry about—the changes happening around them.

Second, in 2017 I began working with a team at the French bank Société Générale to create a proprietary stock market index that would offer investors a way to benefit directly from the artificial intelligence and robotics revolution. In my role as the consulting thematic expert, I helped formulate a strategy informed by the view that AI is becoming a powerful new utility and that it will therefore generate value and transform businesses in a wide range of industries. The result was Société Générale’s “Rise of the Robots” index and subsequently the Lyxor Robotics and AI ETF4 (exchange traded fund), which is based on the index.

Finally, throughout 2018, I had an opportunity to sit down and have wide-ranging discussions with twenty-three of the world’s foremost artificial intelligence research scientists and entrepreneurs. These men and women are truly the “Einsteins” of the field, and indeed, four of the people I spoke with have won the Turing award, computer science’s equivalent of the Nobel prize. These conversations, which delved into the future of artificial intelligence as well as the risks and opportunities that progress will bring, are recorded in my 2018 book Architects of Intelligence: The Truth about AI from the People Building It. I have drawn extensively from this unique opportunity to get inside some of the absolute brightest minds working in the field of AI, and their insights and predictions directly inform much of the material in this book.

Viewing artificial intelligence as the new electricity offers a useful model for thinking about how the technology will evolve and ultimately touch nearly every sphere of the economy, society and culture. However, there is one important caveat. Electricity is universally viewed as an unambiguously positive force. Setting aside the most dedicated hermit, it would probably be hard to find anyone living in a developed country who has reason to regret electrification. AI is different: it has a dark side, and it comes coupled with genuine risks both to individuals and to society as a whole.

As artificial intelligence continues to advance, it has the potential to upend both the job market and the overall economy to a degree that is likely unprecedented. Virtually any job that is fundamentally routine and predictable in nature—or in other words, nearly any role where a worker faces similar challenges again and again—has the potential to be automated in full or in part. Studies have found that as much as half of the American workforce is engaged in such predictable activities, and that tens of millions of jobs could eventually evaporate in the United States alone.5 And the impact will not be limited to lower-wage, unskilled workers. Many people in white collar and professional roles likewise perform relatively routine tasks. Predictable intellectual work is at especially high risk of automation because it can be performed by software. Manual labor, in contrast, requires an expensive robot.

There continues to be a vibrant debate over the impact of automation on the future workforce. Will sufficient new, non-automatable jobs be created to absorb the workers who lose more routine work? And,

if so, will these workers have the necessary skills, capabilities and personality traits to successfully transition into these newly created roles? We probably should not assume that most former truck drivers or fast food workers can become robotics engineers—or, for that matter, personal care assistants for the elderly. My own view, as I argued in Rise of the Robots, is that a large fraction of our workforce is eventually at risk of being left behind as AI and robotics continue to advance. And, as we’ll see, there are very good reasons to believe that the coronavirus pandemic and the associated economic downturn will accelerate the impact of artificial intelligence on the job market.

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