This collection brings together selected projects and writing at the intersection of AI accountability, policy analysis, and public communications. The work spans clinical AI governance, education policy, independent research, and public interest writing, with a consistent focus on what happens when AI systems meet real communities, and who is accountable when things go wrong. Each project reflects a different facet of that work, from policy memos and governance frameworks to data analysis and public explainers, but the through line is the same: making complex systems legible to the people most affected by them.