Ori Plonsky
Associate Professor, Faculty of Data and Decision Sciences, Technion
Visiting Professor, Rotman School of Management, University of Toronto
I study how people make decisions under uncertainty—both initially and through experience over time—and how we can predict those choices accurately enough to design better interventions and policy. My work combines behavioral decision research with interpretable modeling and machine learning.
Research themes
Decisions from experience
How people learn from repeated choices, especially when outcomes are rare or environments change. A central idea in my work is that people rely on strategies that worked in similar past situations.
Predicting human choice
Developing interpretable models of choice and using prediction as the demanding test of behavioral theories, with the practical goal of designing interventions that work reliably.
Behavioral science × machine learning
Combining behavioral insights with machine learning methods to learn when different decision strategies are likely to be used, improving both prediction and our understanding of choice.
Selected research
PSYCHOLOGICAL REVIEW · 2015
Reliance on small samples, the wavy recency effect, and similarity-based learning
A foundational account of learning from experience. Rather than assuming people simply overweight recent outcomes, we showed how similarity-based learning can explain reliance on small samples and predict a puzzling wavy recency effect of rare events.
NATURE HUMAN BEHAVIOUR · 2025
Predicting human decisions with behavioral theories and machine learning
A large-scale test of hybrid behavioral/ML models. We show that machine learning is most powerful when it combines objective features of the decision environment with interpretable behavioral features summarizing plausible choice strategies (AKA the BEAST-GB paper).
JOURNAL OF APPLIED PSYCHOLOGY · 2023
Motivational drivers for serial position effects: Evidence from high-stakes legal decisions
Using U.S. asylum rulings and 18th-century jury verdicts, we documented robust serial-position effects in high-stakes legal decisions and proposed a similarity-based motivational account. This work led to the 2021 Hillel Einhorn New Investigator Award.
Currently
During the 2026–27 academic year, I am a Visiting Professor in the Marketing Area at the Rotman School of Management, University of Toronto. I’m especially happy to connect with researchers working on related questions while I’m in Toronto.