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Journal Articles:

Reinforcement, rationality, and intentions: How robust is automatic reinforcement learning in economic decision making?
Anja Achtziger and Sabine Hügelschäfer.
Journal of Behavioral Decision Making, forthcoming.

Abstract: Reinforcement learning is often observed in economic decision making and may lead to detrimental decisions. Due to its automaticity, it is difficult to avoid. In three experimental studies we investigated whether this process could be controlled by goal intentions and implementation intentions. Participants’ decisions were investigated in a probability-updating task in which the normative rule to maximize expected payoff (Bayes’ rule) conflicted with the reinforcement heuristic as a simple decision rule. Some participants were asked to set goal intentions designated to foster the optimization of rational decision making, while other participants were asked to furnish these goal intentions with implementation intentions. Results showed that controlling automatic processes of reinforcement learning is possible by means of goal intentions or implementation intentions that focus decision makers on the analysis of decision feedback. Importantly, such beneficial effects were not achieved by simply instructing participants to analyze the feedback, without defining a goal as the desired end state from a first-person perspective. Regarding intentions supposed to shut down reinforcement processes by controlling negative affect, effects were more complex and depended on the specified goal-directed behavior. The goal intention to suppress the disappointment elicited by negative feedback was not effective in controlling reinforcement processes. Furnishing this goal with an implementation intention even backfired and strengthened unwanted reinforcement processes. In contrast, asking participants to keep cool in response to negative decision outcomes through the use of goal intentions or implementation intentions increased decisions in line with Bayes' rule.

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Detecting gender before you know it: How implementation intentions control early gender categorization
Sabine Hügelschäfer, Alexander Jaudas, Anja Achtziger.
Brain Research, Vol. 1649, October 2016, pp. 9-22.

Abstract: Gender categorization is highly automatic. Studies measuring ERPs during the presentation of male and female faces in a categorization task showed that this categorization is extremely quick (around 130 ms, indicated by the N170). We tested whether this automatic process can be controlled by goal intentions and implementation intentions. First, we replicated the N170 modulation on gender-incongruent faces as reported in previous research. This effect was only observed in a task in which faces had to be categorized according to gender, but not in a task that required responding to a visual feature added to the face stimuli (the color of a dot) while gender was irrelevant. Second, it turned out that the N170 modulation on gender-incongruent faces was altered if a goal intention was set that aimed at controlling a gender bias. We interpret this finding as an indicator of nonconscious goal pursuit. The N170 modulation was completely absent when this goal intention was furnished with an implementation intention. In contrast, intentions did not alter brain activity at a later time window (P300), which is associated with more complex and rather conscious processes. In line with previous research, the P300 was modulated by gender incongruency even if individuals were strongly involved in another task, demonstrating the automaticity of gender detection. We interpret our findings as evidence that automatic gender categorization that occurs at a very early processing stage can be effectively controlled by intentions.

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On Confident Men and Rational Women: It’s All on Your Mind(set)
Sabine Hügelschäfer, Anja Achtziger.
Journal of Economic Psychology, Vol. 41, April 2014, pp. 31-44.

Abstract: We tested the hypothesis that inducing the deliberative and the implemental mindset differently affects judgment and decision making. More specifically, we explored mindset effects on decision makers’ confidence ratings, risk preferences, and susceptibility to anchoring effects. As earlier research on mindsets showed that individual differences sometimes moderate mindset effects, we also tested for interaction effects of mindset and gender. For confidence ratings, we found a main effect of mindset and a main effect of gender. For risk preferences and anchoring effects, mindset interacted with gender. When being in an implemental mindset, the judgments of female decision makers came closer to their actual performance compared to being in a deliberative mindset where they were observed as underconfident. Male decision makers were already overconfident in the deliberative mindset and showed even more overconfidence when being in an implemental mindset. Concerning risk attitudes it was found that female decision makers were more prone to choose the less risky, but also less profitable option (in terms of expected payoffs) when they were in the deliberative compared to the implemental mindset. For men the opposite effects were observed. When investigating anchoring effects, male but not female participants’ judgments were influenced by mindset: In an implemental mindset, male participants followed an irrelevant anchor more strongly (i.e., made more anchor-consistent judgments) compared to being in a deliberative mindset.

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