2 citations · 3 across the 4 of their papers we have counts for
6 papers
When Representative Samples Produce Worse Outcomes: Scale-up Decisions and Testing in Small-Budget RCTs
Hannah Li, Hongseok Namkoong, Isaac Scheinfeld
Small randomized controlled trials are often used to screen interventions before running larger follow-up studies. This is a critical phase of experimentation, as missing effective…
Dropping Standardized Testing for Admissions Trades Off Information and Access
Nikhil Garg, Hannah Li, Faidra Monachou
We study the role of information and access in capacity-constrained selection problems with fairness concerns. We develop a statistical discrimination framework, where each applica…
Digital Twins as Funhouse Mirrors: Five Key Distortions
Tianyi Peng, George Gui, Melanie Brucks +20
Scientists and practitioners are increasingly moving to deploy digital twins--LLM-based models of real individuals--across social science and policy research. We conduct 19 pre-reg…
Deployment of AI-Assisted Interventions: Capacity Constraints and Noisy Compliance
Carri W. Chan, Yi Han, Hannah Li +1
AI tools increasingly guide targeted interventions in healthcare, education, and recruiting. Algorithms score individuals, trigger outreach to those above a threshold (e.g., high-r…
Operational Dosage: Implications of Capacity Constraints for the Design and Interpretation of Experiments
Justin Boutilier, Jonas Oddur Jonasson, Hannah Li +1
We study RCTs that evaluate the impact of service interventions, for example, teachers or advisors conducting proactive outreach to at-risk students, medical providers giving medic…
When Does Interference Matter? Decision-Making in Platform Experiments
Ramesh Johari, Hannah Li, Anushka Murthy +1
This paper investigates decision-making in A/B experiments for online platforms and marketplaces. In such settings, due to constraints on inventory, A/B experiments typically lead…