Key challenges for the participatory governance of AI in public administration

Wong, Janis; Morgan, Deborah; Straub, Vincent John; Hashem, Youmna; Bright, Jonathan

doi:10.31235/osf.io/pdcrm

Cited by 2 publications

(1 citation statement)

References 45 publications

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“…Our theory of change is centered on engaging with the reparative role that relational user agreements could play in minimizing sociotechnical harms and risks in AI. Similar to other benefits of participatory AI (Sharp et al, 2022;Wong et al, 2022), the value TwSw dimensions offer is mutual learning and understanding, which we argue can foster more equitable, creative, and reparative futures. Realizing this role requires forging meaningful community participation, and a commitment from technologists to participatory methodologies.…”

Section: Discussionmentioning

confidence: 69%

Terms-we-serve-with: Five dimensions for anticipating and repairing algorithmic harm

Rakova,

Shelby,

2023

Big Data & Society

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Power and information asymmetries between people and digital technology companies are further legitimized through contractual agreements that fail to provide meaningful consent and contestability. In particular, the Terms-of-Service (ToS) agreement, is a contract of adhesion where companies effectively set the terms and conditions of the contract. Whereas, ToS reinforce existing structural inequalities, we seek to enable an intersectional accountability mechanism grounded in the practice of algorithmic reparation. Building on existing critiques of ToS in the context of algorithmic systems, we return to the roots of contract theory by recentering notions of agency and mutual assent. We evolve a multipronged intervention we frame as the Terms-we-Serve-with (TwSw) social, computational, and legal framework. The TwSw is a new social imaginary centered on: (1) co-constitution of user agreements, through participatory mechanisms; (2) addressing friction, leveraging the fields of design justice and critical design in the production and resolution of conflict; (3) enabling refusal mechanisms, reflecting the need for a sufficient level of human oversight and agency including opting out; (4) complaint and algorithmic harms reporting, through a feminist studies lens and open-sourced computational tools; and (5) disclosure-centered mediation, to disclose, acknowledge, and take responsibility for harm, drawing on the field of medical law. We further inform our analysis through an exploratory design workshop with a South African gender-based violence reporting AI startup. We derive practical strategies for communities, technologists, and policy-makers to leverage a relational approach to algorithmic reparation and propose there's a need for a radical restructuring of the “take-it-or-leave-it” ToS agreement.

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Section: Discussionmentioning

confidence: 69%