In the course of everyday life, people encounter numerous situations in which they must make decisions where the available information changes over time. The simple act of changing lanes on a busy highway is an example. While at first, the lane looks clear, the next moment another car may have pulled in from the other side. In order to avoid a collision, the decision maker must be able to analyze and respond to the new information. In the past, much of the research on human decision-making has focused on decision-making when information is constant and unchanging. This project takes a joint experimental and computational modeling approach to study the influence of dynamic information on decisions. The work has relevance in day to day life and offers potential benefits for society. Past research has shown that people's decisions are often sensitive to context (e.g., adding a worse option can make another option look better than before). Advertisers can exploit such effects to promote products that may or may not be good for people. This project investigates how dynamic presentations of information can influence context effects and possibly de-bias these decisions. This project also supports increasing diversity in the quantitative social sciences through the promotion of gender equality in mathematical psychology.
The research goal of this project is to expand our understanding of how people integrate dynamically changing information. Three key questions are addressed: (1) How quickly do people adapt to new information? (2) How is new information integrated into the decision process? (3) Are there commonalities in how decision makers respond to changed information across different paradigms? Or, is adaptation and integration of new information domain specific? To address these key questions, we will examine a range of cognitive models that encode different hypotheses about underlying decision processes. New approximate Bayesian computation methodologies will be developed to integrate these cognitive models with data and compare models encoding different hypotheses. Empirically, the project involves a series of new experiments that will contribute significantly to what is known about how people make decisions under changing information. These experiments span a wide range of paradigms from simple perceptual tasks to high-level preferential choice tasks involving multiple alternatives. Collectively, they will provide valuable insight into how changing information affects decisions across different domains.
