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Ai Snake Oil: What artificial Intelligence Can Do, What It Canâ¿¿T, and How To Tell the Difference
[Hardback - 2024]
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Category: Business
Publisher: Princeton University Press | ISBN: 9780691249131 | Pages: 360
Shipping Weight: .590 | Dimensions: null

From two of TIME’s 100 Most Influential People in AI, what you need to know about AI―and how to defend yourself against bogus AI claims and products

Confused about AI and worried about what it means for your future and the future of the world? You’re not alone. AI is everywhere―and few things are surrounded by so much hype, misinformation, and misunderstanding. In AI Snake Oil, computer scientists Arvind Narayanan and Sayash Kapoor cut through the confusion to give you an essential understanding of how AI works and why it often doesn’t, where it might be useful or harmful, and when you should suspect that companies are using AI hype to sell AI snake oil―products that don’t work, and probably never will.

While acknowledging the potential of some AI, such as ChatGPT, AI Snake Oil uncovers rampant misleading claims about the capabilities of AI and describes the serious harms AI is already causing in how it’s being built, marketed, and used in areas such as education, medicine, hiring, banking, insurance, and criminal justice. The book explains the crucial differences between types of AI, why organizations are falling for AI snake oil, why AI can’t fix social media, why AI isn’t an existential risk, and why we should be far more worried about what people will do with AI than about anything AI will do on its own. The book also warns of the dangers of a world where AI continues to be controlled by largely unaccountable big tech companies.

By revealing AI’s limits and real risks, AI Snake Oil will help you make better decisions about whether and how to use AI at work and home.

Arvind Narayanan is professor of computer science at Princeton University and director of its Center for Information Technology Policy. He is the coauthor of Bitcoin and Cryptocurrency Technologies (Princeton) and Fairness and Machine Learning. Sayash Kapoor is a PhD candidate in computer science at Princeton. He previously worked as a software engineer at Facebook, where he helped create AI for content moderation.

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