Hariri Institute Distinguished Speaker Arvind Narayanan, Princeton University

Friday, Nov. 3, 2023
11:00am – 12:00pm ET
Location: Zoom only.
Register here

Arvind Narayanan, Professor of Computer Science, Director CITP, Princeton University

Talk Title: The Reproducibility Crisis in Machine Learning-based Science

Abstract: Many scientific fields have rapidly adopted machine learning. While an exciting development, it has led to a spate of reproducibility failures. We compile evidence of strikingly similar flaws in disparate fields such as medicine and political science. Some are simple to fix while others are open research questions. We introduce REFORMS, a 32-item checklist to guide researchers on reproducibility and avoid common pitfalls.

This talk is based on two papers: 

Sayash Kapoor & Arvind Narayanan. Leakage and the Reproducibility Crisis in Machine-Learning-Based Science. Patterns 2023.

Kapoor et al. REFORMS: Reporting Standards for Machine-Learning-Based Science. arXiv 2023.

Bio: Arvind Narayanan is a Professor of Computer Science at Princeton University, and the Director of the Center for Information Technology Policy (CITP). He co-authored a textbook on fairness and machine learning and is currently co-authoring a book on AI snake oil. He led the Princeton Web Transparency and Accountability Project to uncover how companies collect and use our personal information. His work was among the first to show how machine learning reflects cultural stereotypes, and his doctoral research showed the fundamental limits of de-identification. Narayanan is a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE), twice a recipient of the Privacy Enhancing Technologies Award, and thrice a recipient of the Privacy Papers for Policy Makers Award. 

BU Host: Tesary Lin, Isabel Anderson Career Development Assistant Professor of Marketing at Questrom School of Business and Hariri Institute Junior Faculty Fellow