Futureproof: 9 Rules for Humans in the Age of Automation - Couverture souple

Roose, Kevin

Couverture souple

ISBN 10 : 0593133366 ISBN 13 : 9780593133361

Editeur : Random House Publishing Group, 2022

Synopsis

A practical, deeply reported survival guide for the age of AI, written by the New York Times tech columnist who has introduced millions to the promise and pitfalls of artificial intelligence—now featuring a new afterword.
 
“Artificial intelligence can be terrifying, but Kevin Roose provides a clear, compelling strategy for surviving the next wave of technology with our jobs—and souls—intact.”—Charles Duhigg, author of The Power of Habit

It’s time to get real about AI.
 
After decades of hype and sci-fi fantasies, AI—artificial intelligence—is leaping out of research labs and into the center of our lives. Millions of people now use tools like ChatGPT and DALL-E 2 to write essays, create art and finish coding projects. AI programs are already beating humans in fields like law, medicine and entertainment, and they’re getting better every day.
 
But AI doesn’t just threaten our jobs. It shapes our entire human experience, steering our behavior and influencing our choices about which TV shows to watch, which clothes to buy, and which politicians to vote for.
 
And while many experts argue about whether a robot apocalypse is near, one critical question has gone unanswered:
 
In a world where AI is ascendant, how can humans survive and thrive?
 
In Futureproof: 9 Rules for Surviving in the Age of AI, New York Times technology columnist Kevin Roose shares the secrets of people and organizations that have successfully navigated waves of technological change, and explains what skills are necessary to stay ahead of the curve today, with lessons like
 
• Be surprising, social, and scarce
• Resist machine drift
• Leave handprints
• Demote your devices
• Treat AI like a chimp army
 
Roose rejects the conventional wisdom that in order to compete with AI, we have to become more like robots ourselves—hyper-efficient, data-driven workhorses. Instead, he says, we should focus on being more human, and doing the kinds of creative, inspiring, and meaningful things even the most advanced algorithms can’t do.

A propos du livre

À propos de l?auteur

Kevin Roose is a technology columnist for The New York Times. He is the host of the Rabbit Hole podcast and a regular guest on The Daily. He writes and speaks frequently about topics including automation and AI, social media, disinformation and cybersecurity, and digital wellness. Previously, he was a writer at New York magazine and the co–executive producer of Real Future, a documentary TV series about technology. He is the New York Times bestselling author of two previous books, Young Money and The Unlikely Disciple. He lives in Oakland, California.

Extrait. © Reproduit sur autorisation. Tous droits réservés.

Recently, I was at a party in San Francisco when a man approached me and introduced himself as the founder of a small AI start-up. As soon as the founder figured out that I was a technology writer for The New York Times, he launched into a pitch for his company, which he said was trying to revolutionize the manufacturing sector using a new AI technique called “deep reinforcement learning.” Modern factories, he explained, were struggling with what is called “production planning”—the complex art of calculating which machines should be making which things on which days. Today, he said, most factories employ humans to look at thick piles of data and customer orders to figure out whether the plastic-molding machines should be making X-Men figurines on Tuesdays and TV remotes on Thursdays, or vice versa. It’s one of those dull-but-essential tasks without which modern capitalism would probably grind to a halt, and companies spend billions of dollars a year trying to get it right. The founder explained that his company’s AI could run millions of virtual simulations for any given factory, eventually arriving at the exact sequence of processes that would allow it to produce goods most efficiently. This AI, he said, would allow factories to replace entire teams of human production planners, along with most of the outdated software those people relied on. “We call it the Boomer Remover,” he said. “The . . . Boomer . . . Remover?” I asked. “Yeah,” he said. “I mean, that’s not the official name. But our clients have way too many old, overpaid middle-managers who aren’t really necessary anymore. Our platform lets them replace those people.” The founder, who appeared to be a few drinks deep, then told a story about a client who had been looking for a way to get rid of one particular production planner for years, but could never figure out how to fully automate his job away. But mere days after installing his company’s software, the client had been able to eliminate the planner’s position with no loss of efficiency. Slightly stunned, I asked the founder if he knew what had happened to the production planner. Was he reassigned within the company? Was he just laid off unceremoniously? Did he know that his bosses had been scheming to replace him with a robot? The founder chuckled. “That’s not my problem,” he said, and headed to the bar for another drink.

Détails de l'édition

• Éditeur: Random House Publishing Group
• Date d'édition: 2022
• ISBN 10: 0593133366
• ISBN 13: 9780593133361
• Reliure: Broché
• Langue: anglais
• Nombre de pages: 272
• Coordonnées du fabricant: non disponible