SORS/WomenInBSC: algorithm design: the case of school choice

Algorithms play a central role in determining who gets what—and why—in a wide range of allocation problems. In the context of education, school assignment algorithms impact the opportunities and outcomes of millions of students worldwide. As administrative capacity to collect large-scale data and centralize decisions has grown, so has the potential to design better, fairer, and more efficient systems. In this lecture, we will explore school choice as a case study to illustrate how economic theory, behavioral experiments, rich datasets, and computational tools come together to inform the design of real-world matching algorithms. We will discuss how different designs can lead to vastly different outcomes, how evidence can uncover unintended consequences, and how iterative processes combining theory and empirical work can help create systems that are more transparent, equitable, and effective.