Making Evidence Visible: Data Visualization and AI Workflows for Health Policy Impact (Intermediate; Added Fee)

We live in an era of unprecedented data volume and velocity — while our attention is shrinking, the public's trust is dwindling, and funders are asking more with less. For health policy professionals, the challenge is no longer access to evidence but the ability to distill it: to find the signal in the noise, match the message to the audience, and make the numbers land. In a crowded information environment, a well-made data visual is not a nicety — it is a competitive advantage.This 2-hour hands-on workshop equips health policy professionals, researchers, and analysts with practical frameworks to improve the clarity, credibility, and impact of their data visuals. Building on an invited skill lab presented at the American Association for the Advancement of Science (AAAS), this session addresses a well-documented gap: despite the central role of data in health policy, few practitioners receive formal training in visual communication, and research consistently shows deficits in both knowledge and skills in this critically important area.Participants will be introduced to principles and concepts through lightning lectures, then work through guided exercises in visual anatomy, art-critique methods, and AI-assisted brainstorming and coding using structured requirement frameworks — collaborating throughout to improve quality. Whether building tables and figures for publication, dashboards for program monitoring, or visuals for policy briefs and testimony, attendees will leave with pragmatic tools and techniques they can apply immediately.Target Audience: Health policy researchers, biostatisticians, epidemiologists, program evaluators, and analysts working at the intersection of data, evidence, and public health decision-making.