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<p>Artificial intelligence governance is evolving faster than traditional policy analysis tools. Policymakers face a growing volume of bills, executive actions, and regulatory proposals across fragmented jurisdictions, often without a standardized way to compare their objectives, assumptions, or trade-offs. We respond to that gap with a transparent instrument for evaluating AI governance: a framework for assessing how a policy aligns with selected AI governance priorities. The framework draws on traditional policy analysis and computational text analysis.</p><p> </p><p>This seminar will be given Paulo Carvão, M-RCBG Research Fellow, and will be moderated by M-RCBG Co-Director John Haigh. It will take place in Wexner 434AB for those with an HUID who wish to attend in person. Others may join us remotely via Zoom. Refreshments will be served.</p><p> </p><p>M-RCBG welcomes individuals with disabilities to participate in its programs. To request accommodations or ask questions about access provided, please email mrcbg@hks.harvard.edu.</p>
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