About Me
I study the human supply chain of Artificial Intelligence.
AI relies on invisible human labor. My research examines crowdwork platforms—the digital assembly lines where workers label data and train algorithms. I use econometric methods to understand fairness, task estimation, and worker retention in these marketplaces.
Before joining UCLA, I was the Head of Advanced Analytics at ACHS in Chile and a management consultant at Oliver Wyman. I hold an MBA from MIT Sloan.
Publications
Fairness in Crowdwork: Making the Human AI Supply Chain More Humane
Business Horizons (2025), Vol. 68, No. 5
AI relies on manual data annotation, often sourced through unregulated crowdwork platforms. Surveying workers in the AI supply chain, we find significant variability in perceived fairness and identify how platform design affects welfare. Drawing on physical supply chain management, we offer guidance for responsibly sourcing AI technologies.
Working Papers
The Impact of Information Systems on Experts' Decisions: Evidence from Physicians
Submitted
How do professionals respond to computerized guidance? We analyze a system in a workers’ compensation program that flagged diagnoses with historically low coverage. While physicians denied coverage more often when alerted, they also evaded alerts by recoding diagnoses. The results suggest the system acted through persuasion rather than by providing new information.
Searching for Serendipity
Submitted to Strategic Management Journal
Does purposeful search kill serendipity? Using an NK modeling framework, we find that searchers with clear hypotheses who move in incremental steps are best at converting luck into value. The model demonstrates how intent and information distinctively drive novel discovery, even in rugged search terrains.