2 citations · 6 across the 8 of their papers we have counts for
9 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…
Deployment of AI-Assisted Interventions: Capacity Constraints and Noisy Compliance
Carri W. Chan, Yi Han, Hannah Li +1
AI tools increasingly drive targeted interventions in various service settings, including healthcare, education, and public services. Algorithms score individuals, trigger outreach…
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…
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…
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…
Interference, Bias, and Variance in Two-Sided Marketplace Experimentation: Guidance for Platforms
Hannah Li, Geng Zhao, Ramesh Johari +1
Two-sided marketplace platforms often run experiments to test the effect of an intervention before launching it platform-wide. A typical approach is to randomize individuals into t…
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…
Experimental Design in Two-Sided Platforms: An Analysis of Bias
Ramesh Johari, Hannah Li, Inessa Liskovich +1
We develop an analytical framework to study experimental design in two-sided marketplaces. Many of these experiments exhibit interference, where an intervention applied to one mark…
Exploration vs. Exploitation in Team Formation
Ramesh Johari, Vijay Kamble, Anilesh K. Krishnaswamy +1
An online labor platform faces an online learning problem in matching workers with jobs and using the performance on these jobs to create better future matches. This learning probl…