Our work explores how rational goals related to decision making (seeking to favor one option over others) can create polarization and extreme views even in absence of any bias. We build cognitive models of information sampling and how it relates to different goals (choose between options, evaluate options separately, compare options), using simulations to explore and generate quantitative hypotheses about how they create polarization. We then use these models to generate novel interventions that reduce polarization and promote more thorough information search when making judgments -- such as manipulating the type of response we elicit (decision, separate scale ratings, relative evaluation scale). We also explore the spread of polarization and information between individuals or through social networks using agent-based modeling.

College of Arts and Sciences profile ↗

Select Publications

Alaukik, A., & Kvam, P. D. (2025). Goal-driven information search biases create polarization and extremism during the accumulation of qualitative evidence. Preprint.

Kvam, P. D. (2024). The Tweedledum and Tweedledee of dynamic decisions: Discriminating between diffusion decision and accumulator models. Psychonomic Bulletin & Review, 1-26. DOI.

Kvam, P. D., Alaukik, A., Mims, C. E., Martemyanova, A., & Baldwin, M. (2022). Rational inference strategies and the genesis of polarization and extremism. Scientific reports, 12(1), 7344. DOI.