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EPRS BRI(2023)739342 EN · Table (p.11)

From EPRS_BRI(2023)739342_EN.pdf · page 11

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01
AI Liability Directive, Legislative Observatory (OEIL), European Parliament.
ENDNOTES
1While there is no exact definition of AI, it is generally acknowledged that AI technologies are a combined range of
technologies including machine-learning techniques, robotics and automated decision-making systems used to
improving prediction, for optimising operations and resource allocation, and for personalising service. See European
Commission, Proposal for a regulation of the European Parliament and of the Council laying down harmonised rules
on artificial intelligence (artificial intelligence act) 2021/0106 (COD), Explanatory memorandum. See OECD, Artificial
Intelligence in Society, 2022. See also: McKinsey Global Survey on AI in 2021.
2See European Commission, Report on the safety and liability implications of Artificial Intelligence, the Internet of
Things and robotics, 2020.
3See European Commission, Directorate-General for Justice and Consumers, M. Mosoreanu, D. Ulicna, S.,Paetz, and
al., Behavioural study on the link between challenges of artificial intelligence for Member States’ civil liability rules and
consumer attitudes towards AI-enabled products and services : final report, 2022.
4See European Commission, Impact assessment accompanying the document Proposal for a Directive of the European
Parliament and of the Council on adapting non-contractual civil liability rules to artificial intelligence, SWD(2022) 319,
2022 (hereinafter, the AI liability directive impact assessment'). See also: European Commission, Inception impact
assessment, Adapting liability rules to the digital age and circular economy, 2021.
5See European Commission, Impact assessment accompanying the document: Proposal for a Directive of the European
Parliament and of the Council on adapting non-contractual civil liability rules to artificial intelligence, above.
6Ibid. The PLD does not cover damage caused to property intended for professional use, damage caused during the
provision of a service, damage to victims other than natural persons or claims based on the wrongful use of a product.
In all these cases, victims can only get compensation according to national liability rules.
7See European Commission, Report on the safety and liability implications of AI, above. See also the AI liability directive
impact assessment, above.
8Ibid.
9See European Commission, impact assessment at p.20. Academics have also stressed a number of gaps exist in current
EU consumer law on addressing AI liability issues. While some support the harmonisation of liability regimes
concerning AI-related harm, the right approach is subject to debate (see B. Schütte, L. Majewski; K. Havu, Damage s
Liability for Harm Caused by Artificial Intelligence – EU Law in Flux, 2021; G. Wagner, Liability for Artificial Intelligence:
A Proposal of the European Parliament, 14 July 2021.
10See S. De Luca, EPRS, New Product Liability Directive, January 2023.
11European Commission, Proposal for a directive of the European Parliament and of the Council on liability for defective
products, COM(2022) 495. See European Commission, New liability rules on products and AI to protect consumers
and foster innovation, 2022. See also: S. De Luca, above.
12See European Commission, Comparative law study on civil liability for artificial intelligence, 2021. See also: European
Commission, Liability for Artificial Intelligence and other emerging technologies, report of the New Technologies
formation of the Expert Group on Liability and New Technologies, 2019.
13See European Parliament, A study on Artificial Intelligence and Civil Liability, 2020.
14See T. Evas, Civil liability regime for artificial intelligence, EPRS study, 2020. See EPRS implementation appraisal
briefing, Aligning the Product Liability Directive with the circular economy and emerging technologies – Revision of
Directive 85/374/EEC, 2022.
15See Explanatory memorandum at p.2.
16Ibid.
17AI systems are defined in the draft AI act as software developed with certain techniques and approaches (machine
learning, logic- and knowledge-based approaches, statistical approaches etc.) that can, for a given set of human-
defined objectives, generate outputs such as content, predictions, recommendations, or decisions influencing the
environments with which these systems interact.
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EPRS_BRI(2023)739342_EN.pdf
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pdfs_from_pdf_links
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pdf
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camelot_stream
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