Bültmann & Gerriets
AI Ethics
von Mark Coeckelbergh
Verlag: The MIT Press
Reihe: The MIT Press Essential Knowledge Series
Taschenbuch
ISBN: 978-0-262-53819-0
Erschienen am 07.04.2020
Sprache: Englisch
Format: 175 mm [H] x 125 mm [B] x 18 mm [T]
Gewicht: 222 Gramm
Umfang: 229 Seiten

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Inhaltsverzeichnis
Klappentext

Series Foreword ix
Acknowledgments xi
1 Mirror, Mirror, on the Wall 1
2 Superintelligence, Monsters, and the AI Apocalypse 11
3 All about the Human 31
4 Just Machines? 47
5 The Technology 63
6 Don't Forget the Data (Science) 83
7 Privacy and the Other Usual Suspects 97
8 A-responsible Machines and Unexplainable Decisions 109
9 Bias and the Meaning of Life 125
10 Policy Proposals 145
11 Challenges for Policymakers 167
12 It's the Climate, Stupid! On Priorities, the Anthropocene, and Elon Musk's Car in Space 183
Glossary 203
Notes 207
References 211
Further Reading 221
Index 225



An accessible synthesis of ethical issues raised by artificial intelligence that moves beyond hype and nightmare scenarios to address concrete questions.

Artificial intelligence powers Google's search engine, enables Facebook to target advertising, and allows Alexa and Siri to do their jobs. AI is also behind self-driving cars, predictive policing, and autonomous weapons that can kill without human intervention. These and other AI applications raise complex ethical issues that are the subject of ongoing debate. This volume in the MIT Press Essential Knowledge series offers an accessible synthesis of these issues. Written by a philosopher of technology, AI Ethics goes beyond the usual hype and nightmare scenarios to address concrete questions.

Mark Coeckelbergh describes influential AI narratives, ranging from Frankenstein's monster to transhumanism and the technological singularity. He surveys relevant philosophical discussions: questions about the fundamental differences between humans and machines and debates over the moral status of AI. He explains the technology of AI, describing different approaches and focusing on machine learning and data science. He offers an overview of important ethical issues, including privacy concerns, responsibility and the delegation of decision making, transparency, and bias as it arises at all stages of data science processes. He also considers the future of work in an AI economy. Finally, he analyzes a range of policy proposals and discusses challenges for policymakers. He argues for ethical practices that embed values in design, translate democratic values into practices and include a vision of the good life and the good society.


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