Transparent and Accountable Decision Systems

Automated and algorithmic decision systems are used extensively in public policy, yet these systems are often opaque, not publicly audited, and implemented through contracts with third-party vendors that limit transparency. As government agencies increasingly rely on automated systems to allocate resources and make decisions, transparency and accountability remain critical prerequisites for building trust and ensuring fair and equitable outcomes.

By studying the accountability of algorithmic decision systems through a multidisciplinary lens, this project focuses on developing methodological approaches for auditing, explaining, and correcting algorithmic decisions under real-world constraints.