Setting the space for deliberation in decision-making

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6 Citations (Scopus)


Decision-making models in the behavioral, cognitive, and neural sciences typically consist of forced-choice paradigms with two alternatives. While theoretically it is feasible to translate any decision situation to a sequence of binary choices, real-life decision-making is typically more complex and nonlinear, involving choices among multiple items, graded judgments, and deferments of decision-making. Here, we discuss how the complexity of real-life decision-making can be addressed using conventional decision-making models by focusing on the interactive dynamics between criteria settings and the collection of evidence. Decision-makers can engage in multi-stage, parallel decision-making by exploiting the space for deliberation, with non-binary readings of evidence available at any point in time. The interactive dynamics principally adhere to the speed-accuracy tradeoff, such that increasing the space for deliberation enables extended data collection. The setting of space for deliberation reflects a form of meta-decision-making that can, and should be, studied empirically as a value-based exercise that weighs the prior propensities, the economics of information seeking, and the potential outcomes. Importantly, the control of the space for deliberation raises a question of agency. Decision-makers may actively and explicitly set their own decision parameters, but these parameters may also be set by environmental pressures. Thus, decision-makers may be influenced—or nudged in a particular direction—by how decision problems are framed, with a sense of urgency or a binary definition of choice options. We argue that a proper understanding of these mechanisms has important practical implications toward the optimal usage of space for deliberation.

Original languageEnglish
Pages (from-to)743-755
Number of pages13
JournalCognitive Neurodynamics
Issue number5
Publication statusPublished - Oct 2021

All Science Journal Classification (ASJC) codes

  • Cognitive Neuroscience


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