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- Autorius: Maximilian Kiener
- Leidėjas: Hart Publishing
- ISBN-10: 1509956840
- ISBN-13: 9781509956845
- Formatas: 15.6 x 23.4 x 1.1 cm, kieti viršeliai
- Kalba: Anglų
Moral Responsibility and Artificial Intelligence (el. knyga) (skaityta knyga) | knygos.lt
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Aprašymas
This book uses the 'Lorry Driver Paradox', a novel puzzle, to explore and clarify our understanding of moral responsibility, to break new ground in the ethics of artificial intelligence (AI), and to connect moral philosophy, legal theory, and AI ethics. It supports a 'legal turn', i.e. the idea that an inquiry into legal responsibility can guide an inquiry into moral responsibility, and not just the other way around.
It presents a novel conception of strict answerability, as opposed to strict liability, and argues that taking responsibility is a genuine normative power, like consenting or promising. It elaborates on the moral significance of apologies in our social and legal practices. The book presents a paradox-driven methodology, through a combination of legal and philosophical perspectives, and provides solutions to challenges around 'responsibility gaps' and trustworthy AI.
- Autorius: Maximilian Kiener
- Leidėjas: Hart Publishing
- ISBN-10: 1509956840
- ISBN-13: 9781509956845
- Formatas: 15.6 x 23.4 x 1.1 cm, kieti viršeliai
- Kalba: Anglų
This book uses the 'Lorry Driver Paradox', a novel puzzle, to explore and clarify our understanding of moral responsibility, to break new ground in the ethics of artificial intelligence (AI), and to connect moral philosophy, legal theory, and AI ethics. It supports a 'legal turn', i.e. the idea that an inquiry into legal responsibility can guide an inquiry into moral responsibility, and not just the other way around.
It presents a novel conception of strict answerability, as opposed to strict liability, and argues that taking responsibility is a genuine normative power, like consenting or promising. It elaborates on the moral significance of apologies in our social and legal practices. The book presents a paradox-driven methodology, through a combination of legal and philosophical perspectives, and provides solutions to challenges around 'responsibility gaps' and trustworthy AI.
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