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Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Enhancing models of social and strategic decision making with process tracing and neural data
Organization Unit
Authors
  • Arkady Konovalov
  • Christian Ruff
Item Subtype Further Contribution (e.g. review article, editorial)
Refereed No
Status Published in final form
Language
  • English
Journal Title Wiley Interdisciplinary Reviews: Cognitive Science
Publisher Wiley-Blackwell Publishing, Inc.
Geographical Reach international
ISSN 1939-5078
Volume 13
Number 1
Page Range e1559
Date 2022
Abstract Text Every decision we take is accompanied by a characteristic pattern of response delay, gaze position, pupil dilation, and neural activity. Nevertheless, many models of social decision making neglect the corresponding process tracing data and focus exclusively on the final choice outcome. Here, we argue that this is a mistake, as the use of process data can help to build better models of human behavior, create better experiments, and improve policy interventions. Specifically, such data allow us to unlock the “black box” of the decision process and evaluate the mechanisms underlying our social choices. Using these data, we can directly validate latent model variables, arbitrate between competing personal motives, and capture information processing strategies. These benefits are especially valuable in social science, where models must predict multi‐faceted decisions that are taken in varying contexts and are based on many different types of information.
Digital Object Identifier 10.1002/wcs.1559
Other Identification Number merlin-id:21074
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Keywords Economics, interactive decision‐making, neuroscience, cognition, psychology, reasoning and decision making