Towards Protecting the Injured Party from Errors and Hallucinations of Artificial Intelligence: A Contemporary Legal Perspective
Identification
- Public canonical key
- doi:10.12688/f1000research.179603.1
- Authors
- Nagwa Abouhaiba · Saed Ahmed Khouli · Maya Khater
- Reported year
- 2026
- Reported language
- en
- Source type
- article
- First detected
- 2026-11-09T19:04:47.728023+00:00
- Last metadata observation
- 2026-11-09T19:04:47.728023+00:00
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Institutions reported by the source
Abu Dhabi University · United Arab Emirates University
Reported affiliation countries
AE
Documentary abstract — original language
The world has been witnessing a growing and accelerating expansion in the use of artificial intelligence (AI) systems, as leading worldwide technology businesses compete to develop systems and software that can simulate the human mind, produce technological solutions, and accomplish activities that previously needed human mental effort. This has given rise to a host of new and unfamiliar legal challenges, including those connected to errors and 'hallucinations' that may produce inaccurate or misleading outputs. This paper examines the technical and practical risks associated with the use of AI, with a focus on the phenomenon of hallucinations that has recently become widely discussed, and its potential effects on users and third parties. This study adopts a comparative, analytical legal approach by analyzing the current legal framework to determine the extent to which the law protects the injured party, assessing the adequacy of existing civil-liability rules, and emphasizing the difficulties associated with proving fault and causation, as well as identifying the responsible party within the complex smart-transactions ecosystems. Accordingly, the objective of this paper is to determine how civil liability arising from the use of AI systems in numerous fields may be attributed, and to identify the future legal implications of such systems in light of the general rules of the UAE Civil Transactions Law and the substance of the EU regulation. Accordingly, the study presents a contemporary legal perspective on conventional culpability to safeguard the harmed person against AI faults and hallucinations. It concludes by proposing innovative legal mechanisms, such as strict (objective) liability, transparency obligations, and compulsory insurance, to compensate the injured party for 'digital harm' caused by AI technologies. The research indicates that legal responsibility and technical innovation must be balanced to safeguard the damaged party.
Identifiers
- OPENALEX
- W7155561573
- DOI
- 10.12688/f1000research.179603.1
Documentary context
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- article
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OpenAlex · Record 1 · Record 2
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- openalex:w7143516040 · CITES
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Cite this reference
Nagwa Abouhaiba; Saed Ahmed Khouli; Maya Khater. Towards Protecting the Injured Party from Errors and Hallucinations of Artificial Intelligence: A Contemporary Legal Perspective. 2026. https://doi.org/10.12688/f1000research.179603.1
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- APA
- Nagwa Abouhaiba; Saed Ahmed Khouli; Maya Khater. (2026). Towards Protecting the Injured Party from Errors and Hallucinations of Artificial Intelligence: A Contemporary Legal Perspective. https://doi.org/10.12688/f1000research.179603.1
- Chicago
- Nagwa Abouhaiba; Saed Ahmed Khouli; Maya Khater. Towards Protecting the Injured Party from Errors and Hallucinations of Artificial Intelligence: A Contemporary Legal Perspective. 2026. https://doi.org/10.12688/f1000research.179603.1
- ISO 690
- Nagwa Abouhaiba; Saed Ahmed Khouli; Maya Khater. Towards Protecting the Injured Party from Errors and Hallucinations of Artificial Intelligence: A Contemporary Legal Perspective. 2026. https://doi.org/10.12688/f1000research.179603.1
UDTR Global Rights of Nature Legal Library. Towards Protecting the Injured Party from Errors and Hallucinations of Artificial Intelligence: A Contemporary Legal Perspective. Documentary record: https://www.declarationuniverselledesdroitsdelarbre.org/global-rights-of-nature-radar/reference/r-c305cf05bc626251ca1bbb2397966bc5/ · Last HTTP verification: not performed
Field provenance and record version
Version 2e66c07b41387647 · udtr-reference-1.1.2
- Title
- OpenAlex · source · 2026-11-09T19:04:47.728023+00:00
- Authors
- OpenAlex · source · 2026-11-09T19:04:47.728023+00:00
- Year
- OpenAlex · source · 2026-11-09T19:04:47.728023+00:00
- Identifiers
- OpenAlex · source · 2026-11-09T19:04:47.728023+00:00
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- OpenAlex · source · 2026-11-09T19:04:47.728023+00:00
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10bb978efe60959e · 2026-11-09T19:04:47.728023+00:00
d3234ef1a08da56b · 2026-11-09T19:04:47.728023+00:00
b9d473761ff82c56 · 2026-11-09T19:04:47.728023+00:00
2e66c07b41387647 · 2026-11-09T19:04:47.728023+00:00
Research dossiers and documentary relations
United Arab Emirates University
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Discovery source · https://doi.org/10.12688/f1000research.179603.1
Discovery source · https://openalex.org/W7155561573
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