Anchoring and Judgment Bias:

Disregarding Under Uncertainty

Berg and Moss (2022)

GOAL: Examined cognitive processing consequences after exposure to extraneous information followed by explicit instruction to disregard it; aimed to more fully understand biases that factor into decision-making behavior

EXPERIMENTAL QUESTION: Will participants exhibit classic anchoring effects even when instructions tell them to ignore the biasing information?

CONCLUSION: Even when instructions are explicit to ignore biasing information, observed effects on numerical estimates are evidence of failure to disregard

TAKEAWAY: Effects of anchoring and judgment bias have direct, concrete implications for UX design patterns (such as price anchoring in e-commerce, default pre-selections in onboarding flows, and form field priming); must be considered from earliest stages in design process

Insights

  • Support for the notion that participants, even when explicitly instructed to do so, do not disregard biasing anchors when making subsequent numerical estimates

    • High-magnitude anchors are resilient

    • Low-magnitude anchors are suppressible

    • Disregard instructions are asymmetrical

    • System 2 requires active engagement

  • Effects of anchoring and judgment bias have direct, concrete implications for UX design patterns:

    • Decision-making in high-stakes systems

    • Optimization of pricing strategies and e-commerce

    • Form defaults and survey design (on pricing tables, form placeholders, survey rating scales, error messages, and more)

  • Effects of anchoring and judgment bias have direct, concrete implications for UX research:

    • Leveraging "consider-the-opposite" strategies

    • The asymmetrical mitigation of "high-ceiling" bias

    • Ethical anchoring and the avoidance of deceptive patterns

  • For more on these insights, see my related case study (coming soon!)

Table 1 (Berg & Moss, 2022)
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Case Study: Wegners