New Algorithmic Challenges for Ethical Decision-Making

Swati Gupta, MIT.

When someone is denied a job, offered a different price for the same goods or services, or declined a loan, intent to discriminate is often not the case. The decision system applies the same data and rules to all and yet has a disproportionate effect on various groups. The causes of such disparate impact in machine learning and optimization are many, and these create an opportunity for us to develop new algorithms. I will present three such opportunities. The first is motivated by challenges due to bias and errors in evaluation data. I will present new optimization problems using ordinal data, which can create a pathway to solving discrimination in hiring (Management Science, 2023 with Salem, and UC Davis Law Review, 2023 with Salem and Desai). Next, I will discuss the challenge of selecting the “right” notion of fairness. I will present the concept of “portfolios”, that ask to find a small set of approximate solutions that summarize the set (potentially infinite) set of fairness objectives. I will showcase combinatorial techniques to tackle this challenge, and connections to polyhedral structure (EC 2023, SODA 2025, with Singh and Moondra). Finally, motivated by the recent lawsuits on price fluctuations, I will discuss challenges in trajectory-constrained stochastic optimization, which for example, can provide algorithms that monotonically change prices in demand learning (WINE 2022, with Kamble and Salem). This talk is based on joint work with Jad Salem, Deven Desai, Mohit Singh, Jai Moondra, and Vijay Kamble.

Bio: Dr. Swati Gupta is an Associate Professor at the MIT Sloan School of Management in the Operations Research and Statistics Group, and holds the Class of 1947 Career Development Professorship. She received a Ph.D. in Operations Research from MIT, and a dual Bachelors + Masters in Computer Science and Engineering from IIT Delhi. Her research interests include optimization and machine learning, with a focus on algorithmic fairness. Her work is cross-disciplinary and spans various domains such as hiring, admissions, e-commerce, healthcare, districting, power systems, and quantum optimization. She served as the lead of Ethical AI for the NSF AI Institute on Advances in Optimization, from 2021-2023. She has received the NSF CAREER Award in 2023, the JP Morgan Early Career Faculty Recognition in 2021, the NSF CISE Research Initiation Initiative Award in 2019, Simons-Berkeley Research Fellowship in 2017-2018, and the Google Women in Engineering Award (India) in 2011. Dr. Gupta’s research is partially funded by the National Science Foundation (NSF) and Defense Advanced Research Projects Agency (DARPA), as well as Social and Ethical Responsibilities in Computing (SERC) at MIT.