CONCEPT
Principlist AI Ethics
The dominant framework for contemporary AI ethics — fairness, accountability, transparency, explainability — which MacIntyre's framework diagnoses as empty because principles lack content apart from the traditions that specify them.
Principlism is the approach to AI ethics that proceeds by enumerating abstract principles — typically some combination of fairness, accountability, transparency, explainability, privacy, and human oversight — and then deriving specific guidance from them. The approach has gained widespread institutional acceptance because it appears to offer tradition-independent, universalizable norms. MacIntyre's critique, developed in Whose Justice? Which Rationality?, is that principles without traditions are empty: "fairness" means one thing within a utilitarian framework, another within Kantianism, another within virtue ethics, and another within capabilities theory. The apparent consensus on principlist principles conceals deep disagreement about what the principles require. Principlism is not an alternative to substantive moral traditions; it is a concealing of the traditions that give the principles their content.
In The You On AI Field Guide
Principlism in bioethics was developed by Beauchamp and Childress in the 1970s as a response to the need for practical guidance in medical decision-making that did not require agreement on deeper metaphysical or theological questions.