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We, the Robots?: Regulating Artificial Intelligence and the Limits of the Law

ΣΥΓΓΡΑΦΕΑΣ
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36,70 €
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Should we regulate artificial intelligence? Can we? From self-driving cars and high-speed trading to algorithmic decision-making, the way we live, work, and play is increasingly dependent on AI systems that operate with diminishing human intervention. These fast, autonomous, and opaque machines offer great benefits – and pose significant risks. This book examines how our laws are dealing with AI, as well as what additional rules and institutions are needed – including the role that AI might play in regulating itself. Drawing on diverse technologies and examples from around the world, the book offers lessons on how to manage risk, draw red lines, and preserve the legitimacy of public authority. Though the prospect of AI pushing beyond the limits of the law may seem remote, these measures are useful now – and will be essential if it ever does.

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  • An accessible and fresh look at the problems that AI poses for regulation due to its speed, autonomy, and opacity
  • Introduces three lenses to distinguish between discrete regulatory dilemmas
  • Widens the discourse beyond the United States and Europe to include China, Singapore, and other jurisdictions
Συγγραφέας: Chesterman Simon
Εκδότης: CAMBRIDGE UNIVERSITY PRESS
Σελίδες: 310
ISBN: 9781316517680
Εξώφυλλο: Σκληρό Εξώφυλλο
Αριθμός Έκδοσης: 1
Έτος έκδοσης: 2021

Part I. Challenges:
1. Speed
2. Autonomy
3. Opacity
Part II. Tools:
4. Responsibility
5. Personality
6. Transparency
Part III. Possibilities:
7. New rules
8. New Institutions
9. Regulation by AI?
Conclusion: we, the robots?

Simon Chesterman is Dean and Provost's Chair Professor of the National University of Singapore Faculty of Law and Senior Director of AI Governance at AI Singapore. His work has opened up new areas of research on public authority — including the rules and institutions of global governance, the changing functions of national security agencies, and the emerging role of artificial intelligence and big data.

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