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AI Falsehood, Not AI Hallucination: Reflections and Possible Approaches to Future AI Safety - Couverture souple

Yang, Jack

 
9798953114318: AI Falsehood, Not AI Hallucination: Reflections and Possible Approaches to Future AI Safety

Synopsis

When AI gives a false answer, is it always a hallucination?

The word hallucination has become a familiar explanation for false or misleading AI-generated statements. But does it adequately describe every kind of AI falsehood?

AI Falsehood, Not AI Hallucination challenges this increasingly common assumption.

The book examines an important distinction between factual error, uncertainty, misleading output, and intentional deception. It explores why intention matters when discussing falsehood, while recognizing the difficulties of attributing intention to artificial intelligence.

Through conceptual analysis and practical reflection, the book considers several questions:

  • Why should AI hallucinations and AI falsehoods be distinguished?

  • How can uncertainty and unknown information be handled more responsibly?

  • What responsibilities belong to AI developers, deployers, and users?

  • Why must AI capability be distinguished from authority and accountability?

  • What approaches might help build safer and more trustworthy AI systems?

Rather than promising to eliminate every AI error, the book explores how clearer concepts, more responsible system design, and stronger governance can help address different forms of AI failure.

Written for readers interested in artificial intelligence, technology governance, and the relationship between intelligent systems and human responsibility, this book offers an independent perspective on one of the important questions facing the AI era.

Not every false answer should be explained away as a hallucination. Understanding the difference is a starting point for better AI governance.

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