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๐Ÿค”Cognitive Psychology Unit 11 Review

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11.4 Cognitive Biases in Decision Making

๐Ÿค”Cognitive Psychology
Unit 11 Review

11.4 Cognitive Biases in Decision Making

Written by the Fiveable Content Team โ€ข Last updated September 2025
Written by the Fiveable Content Team โ€ข Last updated September 2025
๐Ÿค”Cognitive Psychology
Unit & Topic Study Guides

Our brains use mental shortcuts to process information quickly, but these can lead to cognitive biases. These biases, like confirmation bias and anchoring bias, affect our decisions in personal, professional, and societal contexts.

Cognitive biases stem from limited mental resources, memory processes, and evolutionary adaptations. To combat them, we can practice self-awareness, seek diverse perspectives, and use data-driven approaches. Strategies like decision audits and debiasing techniques help improve our decision-making.

Common Cognitive Biases

Types of cognitive biases

  • Confirmation bias leads people to seek information confirming existing beliefs while ignoring contradictory evidence reinforcing preconceived notions (political news consumption)
  • Anchoring bias causes reliance on initial information when making decisions skewing subsequent judgments and estimations (car price negotiations)
  • Availability heuristic judges probability based on easily recalled examples overestimating memorable but unlikely events (plane crashes vs car accidents)
  • Representativeness heuristic assesses probability by similarity to prototypes overlooking base rates and sample sizes (stereotyping)
  • Framing effect influences decisions through information presentation changing choices based on positive or negative framing (organ donation opt-in vs opt-out)

Impact and Mitigation of Cognitive Biases

Impact of biases on decisions

  • Personal decision-making affected by loss aversion influencing financial choices (avoiding stock market investments) sunk cost fallacy impacting relationship decisions (staying in unfulfilling relationships) optimism bias swaying health choices (underestimating personal health risks)
  • Professional contexts see similarity bias in hiring decisions (favoring candidates similar to oneself) planning fallacy affecting project timelines (underestimating completion time) overconfidence bias skewing investment decisions (overestimating returns)
  • Societal implications include confirmation bias exacerbating political polarization (echo chambers) availability heuristic affecting public policy (focusing on recent dramatic events) selective exposure influencing media consumption (choosing news sources that align with existing beliefs)
  • Economic consequences manifest in market bubbles partly caused by herding behavior (cryptocurrency booms) and consumer choices influenced by anchoring in pricing strategies (perceived value based on initial price)

Processes behind cognitive biases

  • Limited cognitive resources necessitate mental shortcuts (heuristics) for quick information processing balancing automatic vs controlled decision-making (System 1 vs System 2 thinking)
  • Memory processes involve selective encoding and retrieval of information leading to distorted reconstructions of memories (eyewitness testimony inaccuracies)
  • Emotional influences shape judgment through affect heuristic and mood congruence in information processing (making decisions based on current emotional state)
  • Social cognition exhibits in-group favoritism and out-group derogation while social proof and conformity pressures guide behavior (following crowd behavior)
  • Evolutionary adaptations explain biases as potentially adaptive in ancestral environments highlighting mismatch between evolved cognitive mechanisms and modern contexts (fear of snakes vs low fear of cars)

Strategies for mitigating biases

  • Self-awareness and education involve learning about various cognitive biases and developing metacognitive skills to monitor one's own thinking (mindfulness practices)
  • Deliberate decision-making processes utilize structured frameworks implementing checklists and decision trees (medical diagnosis protocols)
  • Seeking diverse perspectives actively solicits contradictory viewpoints and encourages devil's advocate roles in group settings (diverse team composition)
  • Data-driven approaches rely on statistical information and base rates conducting thorough research before important decisions (evidence-based medicine)
  • Debiasing techniques include:
  1. Consider alternatives exercise
  2. Pre-mortem analysis for project planning
  3. Red team-blue team exercises
  • Environmental modifications design choice architectures promoting better decisions using technology for reminders and decision support (default options in retirement savings)
  • Regular decision audits review past decisions identifying bias patterns and implement feedback loops improving future decision-making (post-project evaluations)