  AI Ethics is now a global topic of discussion in academic and policy circles.
At least 84 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.
