Policy Memo by Anna Lenhart: “AI systems are regularly used to make decisions that directly impact individuals, from who gets a housing voucher to who gets a job, to bail—contexts with a long history of social disparities, facilitating encoded discrimination. The designs of these consequential AI decision systems are shaped by corporations and increasingly overseen by governments with little input from the public, specifically from users and individuals impacted by these decisions.
Executive branch agencies frequently engage the public in policy decisions via requests for comment and town halls. For decades, the Food and Drug Administration (FDA) has gone beyond traditional agency engagement processes via the Patient Representative Program (PRP), which recruits, trains, and embeds patients into oversight of the pharmaceutical industry, including decisions regarding clinical trial design, endpoints (evaluation metrics), risk/benefit analysis, product labeling, etc. This memo proposes creating a Decision Subject Representative Program inspired by the FDA’s Patient Representative Program.
While pharmaceutical drugs and consequential AI decision systems vary in scope and impact, both technologies need to be safe and effective to be trusted by the public and consumers. Public engagement has long been a tool for building trust and legitimacy in governance decisions while providing a complement to expertise associated with elite institutions. Three decades of FDA experience in systematizing patient engagement offer valuable inspiration for AI governance. Specifically, the General Services Administration (GSA) should pilot embedding Decision Subject Representatives into the procurement process for consequential AI decision systems, the National Institute of Standards and Technology (NIST) should pilot engaging Decision Subject Representatives in efforts to shape standards, and Congress could add a flexible Decision Subject Representatives Program (DSRP) to new regulatory proposals…(More)”.
