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arXiv:2411.09222cs.CY

Democratic AI is Possible. The Democracy Levels Framework Shows How It Might Work

Aviv Ovadya, Kyle Redman, Luke Thorburn, Quan Ze Chen, Oliver Smith, Flynn Devine, Andrew Konya, Smitha Milli, Manon Revel, K. J. Kevin Feng, Amy X. Zhang, Bilva Chandra, Michiel A. Bakker, Atoosa Kasirzadeh

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Abstract

This position paper argues that effectively "democratizing AI" requires democratic governance and alignment of AI, and that this is particularly valuable for decisions with systemic societal impacts. Initial steps -- such as Meta's Community Forums and Anthropic's Collective Constitutional AI -- have illustrated a promising direction, where democratic processes could be used to meaningfully improve public involvement and trust in critical decisions. To more concretely explore what increasingly democratic AI might look like, we provide a "Democracy Levels" framework and associated tools that: (i) define milestones toward meaningfully democratic AI, which is also crucial for substantively pluralistic, human-centered, participatory, and public-interest AI, (ii) can help guide organizations seeking to increase the legitimacy of their decisions on difficult AI governance and alignment questions, and (iii) support the evaluation of such efforts.

arXiv comments
31 pages. Accepted to the position paper track at ICML 2025. A previous version was presented at the Pluralistic Alignment Workshop at NeurIPS 2024. For ongoing work, see: https://democracylevels.org
Journal reference
DOI
Subjects
cs.CYComputers and Society

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    • There is a lot of potential in this. Not just for government democracy, but for also introducing democratic elements into tech/AI policy, when that tech has impact comparable to many governments. I worked in tech, and after some formative experiences, shifted to working on…

      avivoView on HNParent context

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