On the link between cognitive control and heuristic processes

On the Link between Cognitive Control and Heuristic Processes Edward T. Cokely (cokely@mpib-berlin.mpg.de) Paula Parpart (parpart@mpib-berlin.mpg.de) Lael J. Schooler (schooler@mpib-berlin.mpg.de) Max Planck Institute for Human Development, Lentzallee 94, 14195 Berlin, Germany Abstract In several experiments, we demonstrate that controlled cognition (e.g., “System 2,” as measured by the cognitive reflection test) can give rise to seemingly intuitive judgments (e.g., “System 1”). Experiment 2 examined a bias that occurs when price estimates are made in the presence of unfamiliar (disfluent) money. Paradoxically, more controlled cognition was related to a greater reliance on disfluency as a basis for judgment, which led to a large devaluation bias. Experiment 3 examined how the ease of company name pronunciation (fluency) influenced company profit estimation. Paradoxically, more controlled cognition was related to a greater reliance on the ease of company name pronunciation as a basis for stock profit estimations. Effects were independent of basic working memory capacities and did not interact with age. Results highlight the often neglected relations between cognitive control and heuristic processes. Results also provide some new evidence on the potential influence of an early selection mode of cognitive control. Keywords: judgment; decision making; aging; bias; fluency; dual process; cognitive reflection; heuristic; working memory Dual System Theories Drawing on various dual process theories, researchers have posited a general theoretical framework describing the interplay of two fundamental cognitive systems (Evans, 2008; Sloman, 1996; Stanovich and West, 2000). The intuitive “System 1”—sometimes referred to as “the heuristic system”—is said to involve automatic, contextualized, heuristic, affective, and associative processes, which rapidly give rise to impressions (Kahneman, 2003). In contrast, “System 2” is said to rely on effortful, decontextualized, abstract, serial processes, that either use rule-based mechanisms (such as logic) to compute responses or otherwise monitor and adjust the output of “System 1” (for a review see Evans 2008). 1 Although this general framework has met with strong criticism (e.g., arguments that the framework is internally inconsistent and too imprecise to make meaningful predictions; see Gigerenzer & Regier, 1996), the interplay of the two systems has been widely used to organize and explain findings in the judgment and decision making literature (Evans, 2008; Kahneman, 2003). The exact nature of the interplay of the systems is debated. Dynamics are commonly taken as default-interventionist (i.e., one process monitors and corrects the other) or parallel-competitive (i.e., both processes compute independent outputs) (Evans, 2008). Cognitive Abilities and Decision Making Key evidence used in support of a general dual systems theory is the correlation between cognitive abilities and superior reasoning, judgment, and decision making (Stanovich & West, 2000). Theoretically, it is often assumed that the link between abilities and decision making results from the fact that more able individuals have more cognitive resources available, enabling the computation of more normative decisions via logical and normative processes (“System 2”). Indeed, “the notion that System 2 is in some sense rule- based is compatible with the proposals of most dual process theorists” (p. 261, Evans 2008). For example, Stanovich and West (2000) have noted that “high analytic intelligence may lead to task construals that track normative rationality” (p. 662) and that “normative responses are computationally more complex, and only those people with the requisite computational power are able to compute them” (p. 706). Specifically, “System 2” is said to be constrained by limited working memory resources wherein larger working memory capacities are necessary for the inhibition of inappropriate heuristics (“System 1”) and/or the representation of more abstract, normative decision processes (“System 2”). Elaborative heuristic search Recent research indicates that the relationships between decision making (i.e., risky choices) and cognitive abilities (e.g., working memory, numeracy, cognitive reflection) can result from differences in heuristic-type exploration and representation of the problem space, rather than the use of more normative decision strategies. Specifically, protocol analysis revealed that normative decisions were strongly related to participants’ more elaborative heuristic search processes 2 (e.g., verbalized considerations of more diverse aspects of differences in lotteries), which fully mediated the relationships between cognitive ability measures and normative choices (Cokely & Kelley, 2009). Indeed, fewer than 5% of the participants verbalized processes consistent with normative computations although most of the participants made normative choices. These results echo well established findings relating heuristic search processes to deliberative cognition in expertise. For example, superior move selection in chess results, in part, from increased rates In this paper, Heuristic search refers specifically to Herbert Simon’s notion of heuristics as problem solving processes that rely on selective (i.e., non-exhaustive) problem space search.