Deliberation decreases the likelihood of expressing dominant responses

Deliberation is commonly assumed to be a central characteristic of humans' higher cognitive functions, and the responses following deliberation are attributed to mechanisms that are qualitatively different from lower-level associative or affectively driven responses. In contrast to this perspective, the current article's aim is to draw attention to potential issues with making inferences about mechanisms of deliberation based on characteristics of the observed decision outcomes. We propose that a consequence of deliberation is to simply reduce the likelihood of expressing immediately available (dominant) responses. We illustrate how this consequence of deliberation can provide a parsimonious explanation for a broad range of prior research on decision-making. Furthermore, we discuss how the present perspective on deliberation relates to the question of how the cognitive system implements nondominant responses based on associative learning and affective prioritization rather than voluntary decisions. Beyond the present article's theoretical focus, for illustrative purposes, we provide some empirical evidence (three studies, N = 175) that is in line with our proposal. In sum, our theoretical framework, prior empirical evidence, and the present studies suggest that deliberation reduces the likelihood of expressing dominant responses. Although we do not argue that this is the only consequence or mechanism regarding deliberation, we aim to highlight that it is worthwhile considering this minimal consequence of deliberation as compared with certain higher cognitive functions in the interpretation of deliberation outcomes.

Probability matching does not decrease under cognitive load: A preregistered failure to replicate

Does taxing cognitive resources improve people's choices in repeated binary prediction? Wolford, Newman, Miller, and Wig (2004, Canadian Journal of Experimental Psychology, 58, 221-228) found that a secondary verbal working memory task, which competed for cognitive resources with a repeated binary choice task, steered participants toward adopting the optimal strategy, namely, probability maximizing. By contrast, under single-task conditions, an inferior strategy prevailed, namely, probability matching. We conducted a preregistered direct replication of Experiment 1 in Wolford et al. (2004) with a sample of participants more than 5 times larger than the original sample. We did not find a statistically significant effect of cognitive load on strategy selection in repeated binary choice. Moreover, in many cases, Bayesian analyses, which were performed in addition to conventional methods of null hypothesis significance testing, yielded substantial evidence in favor of the absence of cognitive load effects on choice behavior. Thus, we found no reliable support for the claim that taxing cognitive resources leads to improved decision-making in repeated binary prediction.

Taking the easy way out? Increasing implementation effort reduces probability maximizing under cognitive load

Cognitive load has previously been found to have a positive effect on strategy selection in repeated risky choice. Specifically, whereas inferior probability matching often prevails under single-task conditions, optimal probability maximizing sometimes dominates when a concurrent task competes for cognitive resources. We examined the extent to which this seemingly beneficial effect of increased task demands hinges on the effort required to implement each of the choice strategies. Probability maximizing typically involves a simple repeated response to a single option, whereas probability matching requires choice proportions to be tracked carefully throughout a sequential choice task. Here, we flipped this pattern by introducing a manipulation that made the implementation of maximizing more taxing and, at the same time, allowed decision makers to probability match via a simple repeated response to a single option. The results from two experiments showed that increasing the implementation effort of probability maximizing resulted in decreased adoption rates of this strategy. This was the case both when decision makers simultaneously learned about the outcome probabilities and responded to a dual task (Exp. 1) and when these two aspects were procedurally separated in two distinct stages (Exp. 2). We conclude that the effort involved in implementing a choice strategy is a key factor in shaping repeated choice under uncertainty. Moreover, highlighting the importance of implementation effort casts new light on the sometimes surprising and inconsistent effects of cognitive load that have previously been reported in the literature.

Everyday Consequences of Analytic Thinking

We review recent evidence revealing that the mere willingness to engage analytic reasoning as a means to override intuitive gut feelings is a meaningful predictor of key psychological outcomes in diverse areas of everyday life. For example, those with a more analytic thinking style are more skeptical about religious, paranormal, and conspiratorial concepts. In addition, analytic thinking relates to having less traditional moral values, making less emotional or disgust-based moral judgments, and being less cooperative and more rationally self-interested in social dilemmas. Analytic thinkers are even less likely to offload thinking to smartphone technology and may be more creative. Taken together, these results indicate that the propensity to think analytically has major consequences for individual psychology.

Understanding and shifting drug-related decisions: contributions of automatic decision-making processes

While substance use is common, only a minority of individuals who use drugs or alcohol develop problematic use. An understanding of the factors underlying the transition from substance use to misuse may improve prevention and intervention efforts. A key feature of substance misuse is ongoing decisions to use drugs or alcohol despite escalating negative consequences. Research findings highlight the importance of both relatively automatic, associative cognitive processes and relatively controlled, deliberative, and rational-analytic cognitive processes, for understanding situational decisions to use drugs. In this review, we discuss several cognitive component processes that may contribute to decision-making that promotes substance use and misuse, with a focus on more automatic processes. A growing body of evidence indicates that relative differences in the strength of these component processes can account for individual differences in the transition from substance use to misuse and may offer important avenues for developing novel intervention strategies.