Whose Voice Counts? Mapping Stakeholder Perspectives on AI Through Public Submissions to the U.S. Government
Researchers analyzed thousands of public comments submitted to the Trump Administration's AI Action Plan, revealing a stark gap between citizen concerns and policy priorities. While individuals flagged risks around employment, privacy, and social harm, academia and industry submissions emphasized innovation and competitiveness. The study surfaces a critical tension in AI governance: whose voice shapes regulation when stakeholder interests diverge sharply. For policy insiders and AI leaders, this maps the legitimacy challenge facing top-down AI frameworks that may not reflect public anxiety.
Modelwire context
Analyst takeThe study's most underreported finding is methodological: by systematically categorizing thousands of submissions, researchers have produced a durable dataset that can benchmark future comment periods, making it possible to track whether public voice actually shifts policy outcomes over time rather than just entering the record.
The legitimacy gap this paper surfaces runs directly through several threads in recent Modelwire coverage. The 'Reducing Political Manipulation with Consistency Training' piece documented how LLMs can appear balanced while subtly privileging one framing, and the same structural problem appears here at the policy layer: a process that looks participatory can still systematically weight industry input over citizen concern. The 'Evaluating Commercial AI Chatbots as News Intermediaries' work is also relevant context, because if AI systems increasingly mediate how people access information about AI governance itself, the feedback loop between public understanding and public comment quality becomes a real governance risk. Together these stories sketch a pattern where surface-level openness in AI processes masks deeper asymmetries in who shapes outcomes.
Watch whether the Trump Administration's final AI Action Plan document cites or responds to any public-comment themes around employment and privacy risk. If those concerns are absent from the final framework despite their volume in submissions, this paper's legitimacy critique will have a concrete, citable confirmation.
This analysis is generated by Modelwire’s editorial layer from our archive and the summary above. It is not a substitute for the original reporting. How we write it.
MentionsTrump Administration · U.S. Government · AI Action Plan
Modelwire Editorial
This synthesis and analysis was prepared by the Modelwire editorial team. We use advanced language models to read, ground, and connect the day’s most significant AI developments, providing original strategic context that helps practitioners and leaders stay ahead of the frontier.
Modelwire summarizes, we don’t republish. The full content lives on arxiv.org. If you’re a publisher and want a different summarization policy for your work, see our takedown page.