Back to Search Start Over

Toward Democracy Levels for AI

Authors :
Ovadya, Aviv
Thorburn, Luke
Redman, Kyle
Devine, Flynn
Milli, Smitha
Revel, Manon
Konya, Andrew
Kasirzadeh, Atoosa
Publication Year :
2024

Abstract

There is increasing concern about the unilateral power of the organizations involved in the development, alignment, and governance of AI. Recent pilots - such as Meta's Community Forums and Anthropic's Collective Constitutional AI - have illustrated a promising direction, where democratic processes might be used to meaningfully improve public involvement and trust in critical decisions. However, there is no standard framework for evaluating such processes. In this paper, building on insights from the theory and practice of deliberative democracy, we provide a "Democracy Levels" framework for evaluating the degree to which decisions in a given domain are made democratically. The framework can be used (i) to define milestones in a roadmap for the democratic AI, pluralistic AI, and public AI ecosystems, (ii) to guide organizations that need to increase the legitimacy of their decisions on difficult AI governance questions, and (iii) as a rubric by those aiming to evaluate AI organizations and keep them accountable.<br />Comment: 11 pages. Accepted to the Workshop on Pluralistic Alignment at NeurIPS 2024

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2411.09222
Document Type :
Working Paper