Is There a Description–Experience Gap in Choices Between a Described and an Experienced Option?

Decision makers seem to evaluate risky options differently depending on the learning mode—that is, whether they learn about the options’ payoff distributions from a summary description (decisions from description) or by drawing samples from them (decisions from experience). Are there also discrepancies when people choose between a described and an experienced option? In two experiments, we compared people’s behavior in a condition with mixed learning modes (i.e., one option described, the other experienced with the sampling paradigm) to that in conditions where both options were either described or experienced. Using cumulative prospect theory’s value and probability weighting functions to characterize how observed outcome and probability information was subjectively distorted in people’s choices, we found clear differences between the pure description and pure experience conditions. In the mixed-mode condition, however, the value and probability weighting functions did not differ between the described and the experienced options, suggesting that people evaluated them based on a joint representation despite the different learning modes. Participants’ choices were not biased toward the described or the experienced option. Finally, per-option search effort for an experienced option tended to be higher in the mixed-mode condition than in the purely experience-based condition. Our findings demonstrate that how people evaluate described and experienced options depends on the learning mode of the other option in the choice set, highlighting a previously overlooked boundary condition of discrepancies between description- and experience-based choice.