On the Efficiency of Ethics as a Governing Tool for Artificial Intelligence

Ethical principles alone are insufficient for governing AI: The paper argues that while organizations have converged on certain ethical principles for AI development, these guidelines are not effective enough to actually regulate the AI industry and its developers without additional enforcement mechanisms.

Current AI ethics lacks teeth compared to other regulated fields: The authors suggest that AI governance should learn from bioethics, which has successfully translated ethical principles into explicit legal requirements—a model that AI ethics has largely failed to adopt.

Professional training and accountability need overhaul: The paper identifies a critical gap in how AI professionals are trained and held accountable, arguing that drastic changes are necessary in education and professional regulation for those developing software and intelligent systems.

Convergence on principles masks implementation problems: While meta-analyses show agreement on ethical principles across different organizations' AI guidelines, this apparent consensus obscures the real problem: these principles are not being meaningfully implemented or enforced in practice.

Legal frameworks must replace voluntary ethics guidelines: The authors contend that responsible AI governance requires moving beyond voluntary ethical frameworks toward binding legal standards, similar to how bioethics principles were formalized into regulatory law.