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๐Ÿ’•Intro to Cognitive Science Unit 5 Review

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5.3 Decision-making models and cognitive biases

๐Ÿ’•Intro to Cognitive Science
Unit 5 Review

5.3 Decision-making models and cognitive biases

Written by the Fiveable Content Team โ€ข Last updated September 2025
Written by the Fiveable Content Team โ€ข Last updated September 2025
๐Ÿ’•Intro to Cognitive Science
Unit & Topic Study Guides

Decision-making models shape how we understand and approach choices. Normative models prescribe ideal decision-making, while descriptive models reflect real-world behavior. This distinction highlights the gap between theoretical rationality and actual human cognition.

Cognitive biases significantly impact our decisions, often leading to suboptimal outcomes. From confirmation bias to the sunk cost fallacy, these mental shortcuts can distort our judgment. Recognizing and mitigating these biases is crucial for improving decision-making in both individual and group contexts.

Decision-Making Models

Normative vs descriptive decision models

  • Normative decision models prescribe how decisions should be made assuming decision-makers are rational and aim to maximize expected utility (Expected Utility Theory, Bayesian Decision Theory)
  • Descriptive decision models focus on how people actually make decisions in real-world situations accounting for cognitive limitations, biases, and heuristics (Prospect Theory, Bounded Rationality)
  • Key differences: normative models are idealized and prescriptive while descriptive models are based on observed behavior; normative models assume perfect rationality while descriptive models acknowledge cognitive limitations and biases

Cognitive Biases in Decision-Making

Common cognitive biases in decisions

  • Confirmation bias leads to seeking, interpreting, and recalling information that confirms pre-existing beliefs or hypotheses overweighting supporting evidence and underweighting contradictory evidence
  • Anchoring bias involves relying heavily on the first piece of information encountered (the "anchor") when making decisions or estimates with insufficient adjustment from the initial anchor even when presented with new information
  • Availability heuristic overestimates the likelihood of events that are easily remembered or imagined (plane crashes, shark attacks)
  • Framing effect causes making decisions based on how information is presented (emphasizing gains vs losses)
  • Sunk cost fallacy continues a course of action because of previously invested resources (time, money) even when it is no longer rational

Impact of biases on decision processes

  • Individual decision-making: biases can lead to suboptimal decisions and judgments; overconfidence in one's abilities or knowledge can result in poor decision-making; biases can cause individuals to ignore relevant information or overweight irrelevant factors
  • Group decision-making:
    1. Groupthink prioritizes consensus and harmony over critical thinking and dissent
    2. Polarization leads to group discussions resulting in more extreme positions than individual members initially held
    3. Biases can be amplified or attenuated in group settings depending on group dynamics and decision-making processes (risky shift, cautious shift)

Strategies for mitigating cognitive biases

  • Encourage diversity of thought and perspectives by seeking input from individuals with different backgrounds, expertise, and viewpoints and fostering an environment that welcomes constructive dissent and critical thinking
  • Use structured decision-making processes:
    1. Implement decision-making frameworks (multi-criteria decision analysis, decision trees)
    2. Establish clear criteria and weighting for evaluating options
  • Promote self-awareness and metacognition by encouraging individuals to reflect on their own biases and thought processes and providing training on cognitive biases and strategies for mitigating their effects
  • Employ debiasing techniques:
    1. Consider alternatives and counterarguments to initial judgments
    2. Use reference class forecasting to make predictions based on similar past events
    3. Conduct premortem analysis to identify potential pitfalls and risks before making a decision