We are pleased to have Brent Mittelstadt, Senior Research Fellow in data ethics at the Oxford Internet Institute, University of Oxford, join us for this ART-AI seminar, entitled ‘Governance and Professional Ethics in AI’
AI Ethics is now a global topic of discussion. Many initiatives have proposed frameworks of high-level principles, values, and other tenets to guide the ethical development, deployment, and governance of AI. The impact of such frameworks on AI development and governance remains unproven. In this talk I will examine potential difficulties faced in creating ethical AI in practice. In particular, I will examine the relative lack in AI development of (1) common aims and fiduciary duties, (2) professional history and norms, (3) proven methods to translate principles into practice, and (4) robust legal and professional accountability mechanisms. These differences suggest much ethical and political disagreement remains to be resolved when putting principles into practice. To demonstrate these challenges in practice, I will examine in particular the case of designing AI to be ‘fair’ through compliance with differing theories of equality and non-discrimination law.
Brent Mittelstadt is a Senior Research Fellow in data ethics at the Oxford Internet Institute, University of Oxford. He is an ethicist focusing on auditing, interpretability, and ethical governance of complex algorithmic systems. Brent coordinates the Governance of Emerging Technologies (GET) research programme at the OII, which investigates ethical, legal, and technical aspects of AI, machine learning, and other emerging technologies. His current research examines the feasibility of ethical auditing of decision-making algorithms, and the development of standards and methods to ensure fairness, accountability, transparency, interpretability and group privacy in ‘black box’ algorithmic systems. In his recent work he has examined the implications of the EU General Data Protection Regulation and non-discrimination law on the governance of AI and automated decision-making systems.