Toward Democracy Levels for AI

• URL: http://arxiv.org/abs/2411.09222v1
• Date: Thu, 14 Nov 2024 06:37:45 GMT
• Title: Toward Democracy Levels for AI
• Authors: Aviv Ovadya, Luke Thorburn, Kyle Redman, Flynn Devine, Smitha Milli, Manon Revel, Andrew Konya, Atoosa Kasirzadeh,
• Abstract summary: 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 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.
• Score: 4.048639768405042
• License:
• 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.

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