Criminal Liability in Offenses Involving Autonomous Systems Driven by Artificial Intelligence

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Criminal Liability in Offenses Involving Autonomous Systems Driven by Artificial Intelligence

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Produktdetails

The outputs of AI-driven robots are inherently unpredictable and difficult to explain due to opacity. It complicates the attribution of criminal liability, which is based on individual culpability. In particular, the scope of negligent liability and the duty of care owed by developers, producers, users, and others remain contested issues in legal discourse. This study addresses these questions through German criminal law dogmatics, offering concrete suggestions. It also examines individual responsibility in product liability cases involving multiple actors within the production chain. The author has long been engaged in research at the intersection of technology and criminal law, with numerous publications. This Title is also Available as Open Access.

Infotabelle

Produktspezifikationen

Autor
Baran Kızılırmak
Format
gebundene Ausgabe
Sprachfassung
Englisch
Seiten
490
Erscheinungsdatum
2025-11-25
Verlag
Nomos

Produktkennung

Artikelnummer m0000R6WLW
EAN 9783756034871
GTIN 09783756034871

Zusatzinfo und Downloads

The outputs of AI-driven robots are inherently unpredictable and difficult to explain due to opacity. It complicates the attribution of criminal liability, which is based on individual culpability. In particular, the scope of negligent liability and the duty of care owed by developers, producers, users, and others remain contested issues in legal discourse. This study addresses these questions through German criminal law dogmatics, offering concrete suggestions. It also examines individual responsibility in product liability cases involving multiple actors within the production chain. The author has long been engaged in research at the intersection of technology and criminal law, with numerous publications. This Title is also Available as Open Access.

Produktspezifikationen

Autor
Baran Kızılırmak
Format
gebundene Ausgabe
Sprachfassung
Englisch
Seiten
490
Erscheinungsdatum
2025-11-25
Verlag
Nomos

Produktkennung

Artikelnummer m0000R6WLW
EAN 9783756034871
GTIN 09783756034871

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