Regulating for AI legitimacy

Abstract

Artificial intelligence (AI) systems already govern – they rank speech, allocate attention, filter applicants and triage claims. Technical improvements in safety and alignment do not determine whether publics will accept that governance. Legitimacy, on the sociological view used here, turns on recognition: whether power appears rule-bound, justified and situated in institutions that speak for those it governs. Social media demonstrates the problem: distribution improved even as publics questioned who sets the rules, producing recurrent conflicts grounded in missing authorization. As AI embeds upstream of more domains, the risk is repeating that crisis at larger scale – systems that perform yet lack legitimacy, inviting resistance and regulatory backlash. This Article makes legitimacy an explicit regulatory aim for AI. It identifies three persistent deficits: opacity blocks audience-understandable reasons; private actors wield public-facing authority without recognized authorization; and administrative automation strains participation, reason-giving and review. Legal tools can structure recognition. Thin legality supplies visible forms – publicity, stability, consistency – that signal non-arbitrariness. Thick legality adds public authorship, audience-facing reasons and contestation. This Article distills this into three principles: Integration seats AI rule-setting in recognized venues; Familiarity presents rules in locally credible forms; and Contestation guarantees a credible second look. Together, these convert performance into justification and justification into authority publics recognize as rightful.