TL;DR: Effectively "democratizing AI" requires democratic governance and alignment of AI; we propose a Democracy Levels framework for evaluating the degree to which such efforts are democratic.
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.
Lay Summary: The power to make decisions about AI is becoming increasingly important as AI systems become more ubiquitous and capable. This has led to talk about "democratizing" AI, but that often just means making AI accessible. We argue that it is also important to have democratic decision-making about how AI is built and used.
To make this more concrete, we introduce the Democracy Levels Framework, which defines milestones (L0-L5) for transferring decision-making power to democratic systems. Building on this framework, we provide tools for helping identify when it makes sense to make decisions more democratic, and to evaluate the quality of a democratic system. We also address concerns about why this matters, and how to make it feasible. Ultimately, truly democratic AI could prevent unprecedented power concentration as AI capabilities increase.
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Primary Area: Research Priorities, Methodology, and Evaluation
Keywords: democratic AI, participatory AI, pluralistic AI, public AI, human-centered AI
Submission Number: 173
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