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Infrastructuring Contestability: A Framework for Community-Defined AI Value Pluralism

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abstract

The proliferation of AI-driven systems presents a fundamental challenge to Human-Computer Interaction (HCI) and Computer-Supported Cooperative Work (CSCW), often diminishing user agency and failing to account for value pluralism. Current approaches to value alignment, which rely on centralized, top-down definitions, lack the mechanisms for meaningful contestability. This leaves users and communities unable to challenge or shape the values embedded in the systems that govern their digital lives, creating a crisis of legitimacy and trust. This paper introduces Community-Defined AI Value Pluralism (CDAVP), a socio-technical framework that addresses this gap. It reframes the design problem from achieving a single aligned state to infrastructuring a dynamic ecosystem for value deliberation and application. At its core, CDAVP enables diverse, self-organizing communities to define and maintain explicit value profiles - rich, machine-readable representations that can encompass not only preferences but also community-specific rights and duties. These profiles are then contextually activated by the end-user, who retains ultimate control (agency) over which values guide the AI's behavior. AI applications, in turn, are designed to transparently interpret these profiles and moderate conflicts, adhering to a set of non-negotiable, democratically-legitimated meta-rules. The designer's role shifts from crafting static interfaces to becoming an architect of participatory ecosystems. We argue that infrastructuring for pluralism is a necessary pathway toward achieving robust algorithmic accountability and genuinely contestable, human-centric AI.

fields

cs.AI 1

years

2026 1

verdicts

ACCEPT 1

representative citing papers

A Roadmap to Impactful Pluralistic Alignment Research

cs.AI · 2026-07-24 · accept · novelty 6.0

Pluralistic alignment research has produced no public evidence of adoption in deployed frontier models, so the field should focus on empirical justification, settled goals, and hill-climbable evaluations.

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  • A Roadmap to Impactful Pluralistic Alignment Research cs.AI · 2026-07-24 · accept · none · ref 154 · internal anchor

    Pluralistic alignment research has produced no public evidence of adoption in deployed frontier models, so the field should focus on empirical justification, settled goals, and hill-climbable evaluations.