Journal article
The US Algorithmic Accountability Act of 2022 vs. The EU Artificial Intelligence Act: what can they learn from each other?
- Abstract:
- The rapid advancement and integration of Artificial Intelligence (AI) technologies in various disciplines have brought significant changes to the world, including Nigeria. However, the expansion of AI systems raises critical concerns regarding the potential negligence and responsibility for any harm caused by these intelligent machines and the Nigerian Legal System has not addressed AI-related negligence and vicarious liability. It is against this backdrop that this work examined the negligence of artificial intelligence and the application of the doctrine of vicarious liability in Nigeria. The work revealed that the application of AI technology is expanding across sectors such as healthcare, transportation, finance, law and medical professions. Negligence in the context of AI can arise from several factors, including design flaws, programming errors, inadequate training data, biased algorithms, or insufficient testing and the doctrine of vicarious liability becomes crucial in determining who should bear responsibility for AI-related harm. The work concluded that due to the dearth of a legal framework for AI in Nigeria, most of these breaches have remained unresolved. To address this, this work made a number of recommendations which include the need for a legal framework to address the liability of AI, There is need for Standards and Guidelines: Industry-specific standards and guidelines should be developed for AI systems to ensure their safe and responsible deployment, need for training and awareness for medical practitioners, legal practitioners, judges, policymakers, and other stakeholders to enhance their understanding of AI technologies and their implications for negligence and vicarious liability, among others Keywords: Artificial Intelligence, Vicarious Liability, Negligence, Doctrine and Legal framewor
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 749.1KB, Terms of use)
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- Publisher copy:
- 10.1007/s11023-022-09612-y
Authors
- Publisher:
- Springer
- Journal:
- Minds and Machines More from this journal
- Volume:
- 32
- Issue:
- 4
- Pages:
- 751-758
- Publication date:
- 2022-08-18
- DOI:
- EISSN:
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1572-8641
- ISSN:
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0924-6495
- Language:
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English
- Keywords:
- Pubs id:
-
1276549
- Local pid:
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pubs:1276549
- Source identifiers:
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W4292223708
- Deposit date:
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2026-04-28
- ARK identifier:
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Terms of use
- Copyright date:
- 2022
- Licence:
- CC Attribution (CC BY)
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