Beyond intuition: using mathematical models to shape behavior

18 May, 2025
Beyond intuition: using mathematical models to shape behavior

A new study introduces choice engineering—a powerful new way to guide decisions using math instead of guesswork. By applying carefully designed mathematical models, researchers found they could influence people’s choices more effectively than relying on gut instincts or even traditional psychology. This discovery could pave the way for smarter, more ethical tools to improve decision-making in areas like education, health, and everyday life.


 

A new study published in Nature Communications demonstrates that mathematical models can be more effective than psychological intuition when it comes to influencing human decisions. Led by Prof. Yonatan Loewenstein from Safra Center for Brain Sciences (ELSC) at Hebrew University, in collaboration with Dr. Ohad Dan from Yale University and Dr. Ori Plonsky from the Technion, the research introduces a novel concept: choice engineering.

The study draws a distinction between two approaches to influencing behavior. The first, known as choice architecture, has gained widespread popularity since one of its pioneers, Richard Thaler, was awarded the Nobel Prize in Economics in 2017—with behavioral insights (“nudge”) teams emerging in governments around the world. Choice architecture relies on psychological principles—such as primacy, anchoring, or intuitive heuristics—to subtly steer decisions. The second approach, proposed by the researchers, is choice engineering: a method that uses computational models and optimization techniques to systematically shape behavior with precision.

To put these approaches to the test, the team launched an academic competition where international academic teams were tasked with designing an incentivization mechanism (“reward schedule”) that would get people to choose one of two objectively equal-value options. More than 3,000 participants took part in the experiment, each exposed to one of several reward strategies. Some were built on intuition and psychological insights, while others were crafted using computational models.

The most effective schedule was based on a computational model called CATIE (Contingent Average, Trend, Inertia, and Exploration), designed by Dr. Ori Plonsky together with Prof. Ido Erev from the Technion. The model integrates multiple behavioral tendencies into a unified predictive framework. This CATIE-based strategy significantly outperformed those based on the widely used machine-learning model Q-learning, and those informed by qualitative intuition alone.

“Our study shows that just as engineers use mathematical models to build bridges or design aircraft, we can use models of learning and decision-making to influence behavior—reliably and efficiently,” said Prof. Loewenstein.

The findings demonstrate that behavior can be engineered with surprising accuracy when guided by well-calibrated models. Moreover, the study offers a new method for evaluating cognitive models—not only by their explanatory power, but also by their effectiveness in shaping real-world decisions.

The implications are far-reaching. In fields ranging from education and public health to digital design and policy-making, choice engineering could enable the development of empirically optimized, scalable interventions. At the same time, the researchers note that ethical frameworks will be essential to guide the responsible application of these tools.

As a proof of concept, this study underscores the emerging potential of mathematical modeling in the cognitive sciences—not just for understanding behavior, but for actively guiding it.

The research paper titled “Behavior engineering using quantitative reinforcement learning models” is now available in Nature Communications and can be accessed at https://doi.org/10.1038/s41467-025-58888-y

Researchers:
Ohad Dan1, Ori Plonsky2, Yonatan Loewenstein3,4,5,6

Institutions:
1)    Department of Comparative Medicine, Yale University, New Haven, CT, USA
2)    Faculty of Data and Decision Sciences, Technion – Israel Institute of Technology, Haifa, Israel
3)    The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel
4)    Department of Cognitive and Brain Sciences, The Hebrew University, Jerusalem, Israel
5)    The Alexander Silberman Institute of Life Sciences, The Hebrew University, Jerusalem, Israel
6)    The Federmann Center for the Study of Rationality, The Hebrew University, Jerusalem, Israel

For a century, the Hebrew University of Jerusalem has been a beacon for visionary minds who challenge norms and shape the future. Founded by luminaries like Albert Einstein, who entrusted his intellectual legacy to the university, it is dedicated to advancing knowledge, fostering leadership, and promoting diversity. Home to over 23,000 students from 90 countries, the Hebrew University drives much of Israel’s civilian scientific research, with over 11,000 patents and groundbreaking contributions recognized by nine Nobel Prizes, two Turing Awards, and a Fields Medal. Ranked 81st globally by the Shanghai Ranking (2024), it celebrates a century of excellence in research, education, and innovation. To learn more about the university’s academic programs, research, and achievements, visit the official website at http://new.huji.ac.il/en.