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Leading legal disruption : artificial intelligence and a toolkit for lawyers and the law / Giuseppina (Pina) D'Agostino, Aviv Gaon, Carole Piovesan.
D'Agostino, Giuseppina, 1973- author.; Gaon, Aviv, author.; Piovesan, Carole, author.
2021
K564.C6 D34 2021 (Map It)
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Author
D'Agostino, Giuseppina, 1973- author.
Title
Leading legal disruption : artificial intelligence and a toolkit for lawyers and the law / Giuseppina (Pina) D'Agostino, Aviv Gaon, Carole Piovesan.
Published
Toronto, Ontario : Thomson Reuters, [2021]
Copyright
©2021
Call Number
K564.C6 D34 2021
ISBN
0779898710 (softcover)
9780779898718 (softcover)
Description
xxi, 401 pages : illustrations ; 23 cm
System Control No.
(OCoLC)1257403507
Summary
Establishing liability for damages caused by AI used to be rather straightforward when only one or few stakeholders are involved, or when the AI could only take a limited range of pre-defined decisions in accordance with specific parameters defined by a human programmer. However, AI usually involves several stakeholders and components (e.g. sensors and hardware, softwares and applications, data itself and data services, connectivity features) and recent forms of AI are increasingly able to learn without human supervision which makes it difficult to allocate liability between all stakeholders. This contributions maps various possibilities, identify their challenges and explore lines of thought to develop new solutions or close the gaps, the whole from a global perspective. Existing liability regimes already offer basic protection of victims, to the extent that specific characteristics of emerging technologies are taken into account. Consequently, instead of considering new liability principles (solutions that require certain amendments of the current liability regimes), one should consider simply adapting current fault-based liability regimes with enhanced duties of care and precisions regarding shared liability and solidarity between tortfeasors, which could potentially be done through case-law in most jurisdictions. When it comes to the calculation of damages, given the difficulties in calculating the damage and to take into account the specificities of IPR or privacy rights, economic methods may be considered to calculate the damages in general, such as the Discounted Cash Flow Method (DCF) and the Financial Indicative Running Royalty Model (FIRRM), as well as the Royalty Rate Method and case-law about Fair, Reasonable and Non-Discriminatory license terms (FRAND). This path will lead to a certain "flat-rating"damages ("barémisation" or "forfaitisation"), at least when IPR and personal data are illegally used by AI-tools and mostly not visible, hence barely quantifiable in terms of damages. -- Provided by publisher.
Bibliography, etc. Note
Includes bibliographical references and index.
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Added Author
Gaon, Aviv, author.
Piovesan, Carole, author.
About the authors
Acknowledgements
Table of contents
Foreword / Justice Marshall Rothstein
Leading legal disruption editorial: a vision for the future of Artificial Intelligence / Giuseppina (Pina) D'Agostino, Aviv Gaon, and Carole Piovesan
1. Artificial Intelligence and (the lack of) security / Oleg Brodt, Michael Khavkin, Lior Rokach, Asaf Shabtai, and Yuval Elovici
2. AI and legal scholarship: reflections on evolution and influences / Jonathon W. Penney
3. Intellectual property strategy for AI technology in Canada / Maya Medeiros, William Chalmers, and Jordana Sanft
4. Inventive machines and obvious(ness) legal disruptions / Ryan Abbott
5. Legal issues around data scraping as a source of data for AI innovation / Teresa Scassa
6. Ethical lawyering and Artificial Intelligence / Ian Stedman
7. Artificial Intelligence and damages: assessing liability and calculating damages / Yaniv Benhamou and Justine Ferland
8. When AI Systems Are Negligent / Kami Chagal-Feferkorn
9. Smarter contracts: AI and smart contracts / Gregory R. Hagen
10. The meeting of the new minds: contract law, intent and Artificial Intelligence / Salil K. Mehra
11. The introduction of medical algorithms into the reimbursement process: incentivizing industry-payer collaboration / Maya Peleg, Shai Yom-Tov, Dor Nahshoni, and Dov Greenbaum
12. The rise of fintech: promises, perils, and challenges / Moran Ofir and Ido Sadeh
13. Identifying the potential and risks of AI integration to taxation: the case of general anti-avoidance rule / Błażej Kuźniacki and Kamil Tylinski
14. Artificial Intelligence and regulation / Anthony Niblett
15. Regulating Artificial Intelligence in the European Union / Jan De Bruyne and Brahim Bénichou
16. Artificial Intelligence governance and policy: a practical guide to identifying, understanding, and mitigating legal risks associated with AI integration / Anjanette H. Raymond, Chris Draper, and Dakota Coates
17. Artificial Intelligence and human rights: a contested relationship / Vivek Krishnamurthy
Table of cases.

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