Understanding and predicting the relevant risky choices of modern life is a key goal of the behavioral sciences and cognitive decision research specifically. However, do researchers study those choices that people actually face in their lives, or choices that at least capture the same cognitive processes? To address these open questions, we compare 214 risky choices from three perspectives (research, layperson, life outcomes) and use semantic embeddings extracted from a LLM to assess the similarity of choices between perspectives. Furthermore, by means of a Bayesian mixed effects model we examine the potential overlaps and gaps between the three perspectives regarding which cognitive mechanisms may be at play when people make the various choices. Our research informs theories of risk taking by revealing discrepancies of behavioral research with real-life choices, both regarding the choices that are considered timely as well as the cognitive underpinnings that influence these choices.

Which are the psychological mechanisms shaping people's risky choices? While the behavioral sciences have produced many theories to address this question, attempts to integrate their different assumptions are sparse: Verbal theories may explain real life decisions with high face validity but lack precisely testable predictions. Conversely, formal theories allow for clear mathematical predictions but often focus on artificial lab tasks. We aim to bridge this gap and harness each approach's respective advantages. To this end, we created a taxonomy of the most important psychological mechanisms involved in risk taking spanning different aspects of cognition, including attentional, affective, motivational, and psycho-social mechanisms proposed in the literature. As such, this taxonomy is the basis for an integrative process model quantifying the psychological mechanisms involved in decisions under risk and uncertainty, and may help researchers to identify similarities and discrepancies between different theories of choice.