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Teka Komisji Prawniczej PAN Oddział w Lublinie
Article . 2024 . Peer-reviewed
Data sources: Crossref
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Tortious Liability for Using Artificial Intelligence

Authors: Jacek Widło;

Tortious Liability for Using Artificial Intelligence

Abstract

This article discusses the principles of and premises for liability for damage caused by AI systems. It applies to liability models based on the principles of risk and guilt. It indicates that different groups of entities, e.g. programmers, may be responsible for the creation of AI under the principle of guilt, while producers and merchants may put it into circulation under the principle of risk. The liability of AI system users should be tempered and based on the principle of guilt. This article includes a critical view of the AI Act and the relevant directives. It points out that effective liability for damage should be related to the level of harm caused (harm to a person, human death) and not dependent on whether it was inflicted by a high-risk system or any other AI system.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold