AI Ethics – Too Principled to Fail?

15 Pages Posted: 13 Jun 2019

See all articles by Brent Mittelstadt

Brent Mittelstadt

University of Oxford - Oxford Internet Institute

Date Written: May 20, 2019


AI Ethics is now a global topic of discussion in academic and policy circles. At least 63 public-private initiatives have produced statements describing high-level principles, values, and other tenets to guide the ethical development, deployment, and governance of AI. According to recent meta-analyses, AI Ethics has seemingly converged on a set of principles that closely resemble the four classic principles of medical ethics. Despite the initial credibility granted to a principled approach to AI Ethics by the connection to principles in medical ethics, there are reasons to be concerned about its future impact on AI development and governance. Significant differences exist between medicine and AI development that suggest a principled approach in the latter may not enjoy success comparable to the former. Compared to medicine, AI development lacks (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 we should not yet celebrate consensus around high-level principles that hide deep political and normative disagreement.

Keywords: artificial intelligence, ethics, governance, regulation, principilism, principles, value-sensitive design, machine learning

Suggested Citation

Mittelstadt, Brent, AI Ethics – Too Principled to Fail? (May 20, 2019). Available at SSRN: or

Brent Mittelstadt (Contact Author)

University of Oxford - Oxford Internet Institute ( email )

1 St. Giles
University of Oxford
Oxford OX1 3PG Oxfordshire, Oxfordshire OX1 3JS
United Kingdom

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