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The role of causal structure in implicit cognition

Causal relationships, unlike mere co-occurrence, allow humans to obtain rewards and avoid punishments by intervening on their environment. Accordingly, explicit (controlled) cognition is known to represent causal relationships above and beyond mere co-occurrence. In this project, we conduct stringent tests of whether implicit (automatic) cognition is also sensitive to causal relationships and begin to probe the representational mechanisms underlying such sensitivity. Participants (N = 4836) observed causal events during which two stimuli were equally contingent with positive or negative outcomes but only one of them was causally responsible for these outcomes. Across 6 studies, varying in design and amount of verbal scaffolding provided, differences in causal status consistently guided not only explicit measures of evaluation (Likert and slider scales; Cohen’s d = .28, BF10 > 10^46) but also their implicit counterparts (Implicit Association Tests; Cohen’s d = .22, BF10 > 10^29). However, unlike explicit evaluations, implicit evaluations were not sensitive to causal relationships that had to be derived by combining disparate past experiences via causal principles. Taken together, these studies suggest that implicit evaluations encode causal information, but through compressed value representations influenced by causal knowledge rather than online computations over a causal model.