Futureproof 9 rules for humans in the age of automation

Kevin Roose

Book - 2021

"The machines are here. After decades of sci-fi doomsaying and marketing hype, advanced A.I. and automation technologies have leapt out of research labs and Silicon Valley engineering departments and into the center of our lives. Robots once primarily threatened blue-collar manufacturing jobs, but today's machines are being trained to do the work of lawyers, doctors, investment bankers, and other white-collar jobs previously considered safe from automation's reach. The world's biggest corporations are racing to automate jobs, and some experts predict that A.I could put millions of people out of work. Meanwhile, runaway algorithms have already changed the news we see, the politicians we elect, and the ways we interact wit...h each other. But all is not lost. With a little effort, we can become futureproof. In Futureproof: 9 Rules for Machine-Age Humans, New York Times technology columnist Kevin Roose lays out an optimistic vision of how people can thrive in the machine age by rethinking their relationship with technology, and making themselves irreplaceably human. In nine pragmatic, accessible lessons, Roose draws on interviews with leading technologists, trips to the A.I. frontier, and centuries' worth of history to prepare readers to live, work, and thrive in the coming age of intelligent machines. He shares the secrets of people and organizations that have successfully survived technological change, including a 19th-century rope-maker and a Japanese auto worker, and explains how people, organizations, and communities can apply their lessons to safeguard their own futures. The lessons include : Do work that is surprising, social, and scarce (the types of work machines can't do), break your phone addiction with the help of a rubber band, work in an office, treat A.I. like the office gorilla, resist "hustle porn" and efficiency culture and do less, slower Roose's examination of the future rejects the conventional wisdom that in order to compete with machines, we have to become more like them -- hyper-efficient, data-driven, code-writing workhorses. Instead, he says, we should let machines be machines, and focus on doing the kinds of creative, inspiring, and meaningful work only humans can do"--

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Subjects
Published
New York : Random House [2021]
Language
English
Main Author
Kevin Roose (author)
Edition
First edition
Physical Description
xxix, 217 pages : illustration ; 22 cm
Bibliography
Includes bibliographical references (pages [201]-217).
Includes bibliographical references (pages 197-200) and index.
ISBN
9780593133347
  • Introduction
  • Part I. The Machines
  • 1. Birth of a Snboptimist
  • 2. The Myth of the Robot-Proof Job
  • 3. How Machines Really Replace Us
  • 4. The Algorithmic Manager
  • 5. Beware of Boring Bots
  • Part II. The Rules
  • Rule 1. Be Surprising, Social, and Scarce
  • Rule 2. Resist Machine Drift
  • Rule 3. Demote Your Devices
  • Rule 4. Leave Handprints
  • Rule 5. Don't Be an Endpoint
  • Rule 6. Treat AI Like a Chimp Army
  • Rule 7. Build Big Nets and Small Webs
  • Rule 8. Learn Machine-Age Humanities
  • Rule 9. Arm the Rebels
  • Acknowledgments
  • Appendix Making a Futureproof Plan
  • Reading List
  • Notes
Review by Kirkus Book Review

A technology journalist proposes future-oriented skills to prepare people for a new machine age. To counter worry that artificial intelligence will make human workers obsolete, New York Times tech columnist Roose offers an upbeat, practical guide for dealing with "a world that is increasingly arranged by and for machines." Rather than competing with machines by trying to work longer hours and beefing up technological knowledge, the author advises that humans should optimize skills that machines cannot emulate: "handling the unexpected," for examp meeting "social and emotional needs"; and doing jobs "that involve novel circumstances, low-probability events, and rare combinations of skills." AI is programmed to address "big data sets, large numbers of users, or huge quantities of inputs or outputs" but not to transfer knowledge from one problem to another. If people want to make themselves harder to replace, they should hone their ability to do things that require creativity, flexibility, and "human accountability." Among the nine rules that Roose suggests for the future are a few that deliberately distance humans from technology: Wrest your attention from constantly checking your pho curb "hustle tendencies" to overfill your schedule and drown yourself in work obligations; increase interaction with others by physical proximity, collaborative projects, and social videoconferences even if you work remotely; and speak up about "the potential stakes" of implementing AI and automation in your workplace. It's crucial, Roose asserts, to keep humans involved in critical processes. Essential skills for the future include the ability to pay sustained attention (a skill undermined by the distractions of the internet); being able to hone emotional intelligence and empathy; media literacy; "treating other people well" and "acting ethically"; and becoming a "consequentialist," applying critical thinking to evaluate the success or failure of AI processes and tools and "to analyze new products and imagine all the ways they could go wrong." Helpful advice to quell workers' anxiety. Copyright (c) Kirkus Reviews, used with permission.

Copyright (c) Kirkus Reviews, used with permission.

One Birth of a Suboptimist The machine's danger to society is not from the machine itself but from what man makes of it. --Norbert Wiener When I told people I was writing a book about AI and automation, I got two types of reactions. My more tech-skeptical friends and colleagues generally approved. They'd been hearing the gloomy predictions about job-killing robots, and it worried them. They wanted me to confirm their fears of a looming automation crisis, and their suspicions that even if AI didn't cause mass unemployment, it would bring new harms--creepy surveillance, runaway self-driving cars, brain-melting social media apps--that would outweigh its benefits. Among people in Silicon Valley, though, more typical was the reaction I got from Aaron Levie, the CEO of the enterprise software company Box. "Oh God," he said. "Please tell me you're not writing one of those books that make everyone terrified and depressed." Levie is one of the optimists who believe we're all worrying over nothing. He's annoyed by what he sees as alarmist media coverage of AI, and he doesn't see automation as a major threat that requires an urgent solution. As I said, this is not a book about whether or not robots will destroy jobs. But that question is the place the AI discussion typically starts, and it's where people tend to get stuck. So I wanted to consider arguments like Levie's and develop my own mental model, grounded in evidence, that could help me figure out which AI fears were reasonable and which were probably overstated. First, I talked with a number of AI optimists and distilled what they told me into three big claims. 1. "We've been here before, and it turned out fine." First, the optimists argue, there are hundreds of years' worth of evidence that new technology helps us, rather than hurting us. We didn't suffer mass unemployment after the introduction of the assembly line, the invention of the lightbulb, or the creation of the internet because those technologies created new jobs to replace the ones they destroyed. And if you look at today's economic data, they say, there's no evidence that AI and automation are having a catastrophic effect. (In fact, the U.S. unemployment rate is near historic lows, and productivity growth has actually slowed over the past several decades, which isn't what you'd expect to see if mass automation were happening.) 2. "Automation doesn't destroy jobs. It makes them better." Second, the optimists say, automation doesn't replace workers; it assists them, by taking care of their mundane drudgery and allowing them to focus on more creative tasks. Nobody becomes a lawyer because they like doing legal research and logging their billable hours--and if those tasks can be done by AI, it will free lawyers up to spend more time doing the parts of their job they actually enjoy. The same goes for doctors who hate filling out medical history charts, real estate agents who hate creating listings, and teachers who hate grading papers. All of these people's lives improve when such tasks get automated. 3. "Robots won't cause mass unemployment because human needs are limitless. In the future, we'll come up with new jobs we can't even imagine today." The third argument the optimists make is that the pessimists are, essentially, failing to use their imaginations. Just a few decades ago, the vast majority of the biggest companies in the world--including Facebook, Google, and Amazon--didn't exist. Until recently, there was no such thing as a YouTube marketer, a VR film editor, or a professional esports coach. We've always been good at coming up with new, interesting tasks for ourselves as technology makes new things possible. And the optimists think our bottomless desires will keep us employed for a very long time. After months of research and reporting, the position I landed on was neither total optimism nor total skepticism. It's more like "suboptimism"--a word I made up to convey my belief that while our worst fears about AI and automation may not play out, there are real, urgent threats that require our attention. If I had to rank myself on a 1-to-10 worry scale, with 1 being "AI will cause no problems whatsoever" and 10 being "AI will destroy us and everything we hold dear," I'd probably hover around a 7. I am much more optimistic--maybe a 2 or a 3--when it comes to the technology itself. I think that well-designed AI and automation could radically improve many people's lives. Self-driving cars and trucks alone could save hundreds of thousands of lives a year from fatal accidents, which would be a good thing even if it resulted in truckers and taxi drivers losing their jobs. Precision medicine--an AI-assisted approach to disease treatment and prevention--could help us find new, life-saving treatments. There are a million more ways AI could improve our lives, from the mundane (more accurate credit card fraud detection) to the fun (new forms of adaptive, AI-powered videogames). I am much more worried, though--maybe an 8.5 or a 9--about the humans who are designing and implementing this technology. I've seen that AI is being eagerly embraced by profit-hungry executives and starry-eyed entrepreneurs, many of whom are deliberately underselling the risks of harm and displacement resulting from their products. I know that many bosses are using AI and automation to micromanage and surveil their employees and that, as a result, many workers' jobs are getting worse and more precarious instead of better and more secure. I worry that flawed and biased data sets will result in flawed and biased AI, and that the rush to adopt these systems will disproportionately hurt marginalized groups, including women and racial minorities. I think that AI is, and will continue to be, used by authoritarian regimes to commit human rights abuses. I don't have a ton of faith in the tech industry's ability to self-regulate, and I'm concerned that politicians won't show up until it's too late. I'll admit that part of my suboptimism is a gut reaction, informed by my years of covering the technology industry and watching it fall short of its ideals. But it's also based on what I found out about the case for AI optimism--and why it might be weaker than the optimists think. "We've been here before, and it turned out fine." The first thing I learned is that many optimists have not done their history homework. Because while many of them are eager to claim that the Fourth Industrial Revolution will be great for humankind, they rarely note that, for many people, the first three weren't that great. In the eighteenth and nineteenth centuries, as the United States and Britain industrialized, workers routinely faced brutal conditions in overcrowded and unsanitary factories, and were often subjected to long hours and horrendous exploitation. Some of the harshest conditions were faced by child laborers, who were paid pitifully small wages, packed into squalid boardinghouses, and abused when they failed to meet their bosses' standards. Local newspapers were filled with hellish descriptions of life in the working class, like this 1839 report from a Boston newspaper about a boardinghouse for girls who worked at a textile factory: The young girls are compelled to work in unhealthy confinement for too many hours everyday . . . ​their food is both unhealthy and scanty . . . ​they are not allowed sufficient time to eat . . . ​they are crowded together in ill-ventilated apartments in the boarding-houses of the corporations . . . ​in consequence they become pale, feeble, and finally broken in constitution. The Second and Third Industrial Revolutions went more smoothly for workers, in part because of the labor protections that emerged out of the First Industrial Revolution. But they still had plenty of problems. The Second Industrial Revolution created the Gilded Age, a period of American history during the late nineteenth century that was marked by staggering corruption, bloody labor clashes, bitter racial animus, and soaring income inequality. The advances in digital technology during the Third Industrial Revolution made it possible for multinational companies to offshore and outsource jobs to countries with lower labor costs--a great thing if you're an executive or a shareholder, but less helpful if you're a manufacturing worker in the Midwest. Capital owners generally do well during periods of technological change. But the benefits of progress often take longer to materialize for workers. Gregory Clark, an economic historian at the University of California, Davis, estimates that British workers' real wages didn't rise until more than fifty years after the beginning of industrialization--meaning that by the time the Industrial Revolution paid off for the workers who actually lived through it, most of them were already retired or dead. Excerpted from Futureproof: 9 Rules for Humans in the Age of Automation by Kevin Roose All rights reserved by the original copyright owners. Excerpts are provided for display purposes only and may not be reproduced, reprinted or distributed without the written permission of the publisher.