Portrait of Ignacio Cofone

Ignacio Cofone

Affiliate Member
Associate Professor, University of Oxford
Research Topics
AI Ethics
AI Legal Issues
AI4Humanity
Law
Privacy
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Biography

Ignacio Cofone is the Professor of Law and Regulation of AI at Oxford, working jointly at the Faculty of Law and the Institute for Ethics in AI. He is also a Fellow of Reuben College and an Affiliated Fellow of the Yale Law School Information Society Project. Before joining Oxford, he was the Canada Research Chair in AI Law and Data Governance at McGill University.

Ignacio’s research examines how the law can and should adapt to AI-driven social and economic changes. His book, The Privacy Fallacy: Harm and Power in the Information Economy, argues that AI requires restructuring privacy and data protection law based on the duties that we owe one another as members of a society—typically captured by extracontractual obligations—because basing these bodies of law on individual consent and control has become ineffective. His current research project focuses on how to prevent and redress nonmaterial AI harms and on fostering human-centred AI innovation.

Publications

The Cost of Arbitrariness for Individuals: Examining the Legal and Technical Challenges of Model Multiplicity
Prakhar Ganesh
Ihsan Ibrahim Daldaban
Ignacio Cofone
Golnoosh Farnadi
Model multiplicity, the phenomenon where multiple models achieve similar performance despite different underlying learned functions, introdu… (see more)ces arbitrariness in model selection. While this arbitrariness may seem inconsequential in expectation, its impact on individuals can be severe. This paper explores various individual concerns stemming from multiplicity, including the effects of arbitrariness beyond final predictions, disparate arbitrariness for individuals belonging to protected groups, and the challenges associated with the arbitrariness of a single algorithmic system creating a monopoly across various contexts. It provides both an empirical examination of these concerns and a comprehensive analysis from the legal standpoint, addressing how these issues are perceived in the anti-discrimination law in Canada. We conclude the discussion with technical challenges in the current landscape of model multiplicity to meet legal requirements and the legal gap between current law and the implications of arbitrariness in model selection, highlighting relevant future research directions for both disciplines.
2024-05-28
ArXiv (preprint)
doi.org
arxiv.org