Mastering AI
A Survival Guide to our Superpowered Future
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- 8,99 €
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- 8,99 €
Publisher Description
An urgent book on generative artificial intelligence exploring the risk and benefits looming in this seminal moment
'Easily the best exploration to date on the perils and promise of AI." —ASHLEE VANCE author of When the Heavens Went on Sale
'Mastering AI is a must-read. It's hard to put down'. —BETHANY McLEAN, coauthor of The Smartest Guys in the Room and The Big Fail
'A timely and urgent exploration of AI's dizzying acceleration' —BRAD STONE, author of The Everything Store
The debut of ChatGPT on November 30th was a watershed moment in the history of technology. We stand on the threshold of a new age — one where content of all kinds, even software itself, will be conjured, seemingly from thin air, with simple conversation.
In a culture fraught with misinformation, Mastering AI pierces through the thicket of exaggerated claims, explaining how we arrived at this moment and mapping the likely long-term impacts on business, economics, culture and society this potent technology will have.
This book will serve as a guide to those dangers — as well as highlighting the technology's transformative potential — and will pinpoint concrete steps that should be taken to regulate generative AI.
PUBLISHERS WEEKLY
Fortune journalist Kahn expounds in his shrewd first book on how AI is likely to change art, education, and the workplace. AI can serve as an educational resource for disadvantaged students who might not otherwise have access to help outside the classroom, Kahn contends, describing how the online education platform Khan Academy built an AI tutor designed to emulate the Socratic method. Kahn is levelheaded in his assessment of AI's abilities and shortcomings, suggesting that while the software might assist artists with generating ideas ("The British crime novelist Ajay Chowdhury uses ChatGPT as a brainstorming partner"), it's designed to conform to examples it has previously encountered and thus can't produce anything novel without extensive human input. Addressing AI's limitations in the design and implementation process is critical, Kahn argues. For instance, he details how algorithms built for identifying crime hot spots reflected racial biases in the data the programs were trained on and asserts that such software "must be engineered to explicitly compensate for past racism by specifying equality as a goal alongside predictive accuracy." Striking a balance between bullishness and caution, Kahn sets out a helpful roadmap for harnessing the promise of AI while navigating its perils. The result is one of the more convincing assessments of how AI will transform society.
