Envisioning Contestability Loops: Evaluating the Agonistic Arena as a Generative Metaphor for Public AI

Public sector organizations increasingly use artificial intelligence to augment, support, and automate decision-making. Such public AI can infringe on citizens’ right to autonomy. Contestability is a system quality that protects against this by ensuring systems are open and responsive to dispute throughout their life cycle. A growing body of work is investigating contestable AI by design. However, little of this knowledge has so far been evaluated with practitioners. To make explicit the guiding ideas underpinning contestable AI research, we construct the generative metaphor of the Agonistic Arena from the political theory of agonistic pluralism. We combine this metaphor and current contestable AI guidelines into an infographic supporting the early-stage concept design of public AI system contestability mechanisms. We evaluate this infographic in five workshops paired with focus groups with a total of 18 practitioners, yielding ten concept designs. Our findings describe mechanisms for contestability proposed by these concept designs. Building on these findings, we subsequently evaluate the efficacy of the Agonistic Arena as a generative metaphor for the design of public AI and identify two competing metaphors at play in this space: the Black Box and the Sovereign.