Recent decision making models have explained behaviour using mental sampling mechanisms, but there is still little agreement on the specific sampling process, such as whether sampling rates match true probabilities. Here, we trace the sampling process using random generation: in two experiments using general online samples (total N=103), participants repeatedly produced potential outcomes from pairs of monetary gambles before choosing between them. Results found over-generation of rarer outcomes and under-generation of common outcomes overall but not in initial responses, as well as avoidance of direct repetitions. Participants also tended to select options with higher average utility across their responses, implying generations guided choice. These findings suggest systematic biases in mental sampling that may filter through to choices, constraining models of this behaviour. We thus suggest random generation is a valuable method to access underlying choice processes, offering new assessments of existing theories of decision making.
Spicer et al. (Tue,) studied this question.