Timeline of Cognitive Biases
Experimental research on systematic errors in judgment, from the halo effect in 1920 through confirmation, anchoring, framing, and cross-laboratory replication in 2018.
- Category
- Social Sciences
- Events
- 18 events 1920 – 2018
- Generated
- by gpt-6
1920: Thorndike identifies the halo effect
Edward Thorndike reported that ratings of different personal qualities tended to move together more than their independence would suggest. His study of judgments about military personnel described how a general impression could influence evaluations of particular traits.
https://en.wikipedia.org/wiki/Halo_effect1957: Festinger develops cognitive dissonance theory
Leon Festinger proposed that inconsistency among beliefs and actions could create psychological discomfort and motivate change. Cognitive dissonance theory supplied an account of rationalization and selective responses to information, rather than a claim that every inconsistency produced the same reaction.
https://en.wikipedia.org/wiki/Cognitive_dissonance1960: Wason tests confirmation in rule discovery
Peter Wason asked participants to discover a rule governing triples of numbers. Many tested examples consistent with their initial guesses instead of seeking cases that might disprove them, helping establish confirmation bias as an experimental problem.
https://en.wikipedia.org/wiki/Confirmation_bias1967: Chapman demonstrates illusory correlation
Loren Chapman investigated how people perceived associations between paired items that were not supported by the data. The experiments introduced illusory correlation as a mechanism through which expectations could distort judgments about relationships.
https://en.wikipedia.org/wiki/Illusory_correlation1971: Tversky and Kahneman challenge small-sample intuition
Amos Tversky and Daniel Kahneman published "Belief in the Law of Small Numbers." They described researchers' tendency to expect small samples to resemble their populations too closely, with implications for experimental design and confidence in results.
https://en.wikipedia.org/wiki/Insensitivity_to_sample_size1973: Tversky and Kahneman describe availability
Amos Tversky and Daniel Kahneman examined how the ease of recalling or imagining examples influenced estimates of frequency and probability. Availability could be informative, but memorability and ease of retrieval could also produce misleading judgments.
https://en.wikipedia.org/wiki/Availability_heuristic1974: Anchoring experiments show irrelevant numbers influencing estimates
Amos Tversky and Daniel Kahneman described estimates that shifted toward a preceding numerical anchor, including a number generated by a wheel of fortune. Their results made anchoring and insufficient adjustment central examples in research on judgment under uncertainty.
https://en.wikipedia.org/wiki/Anchoring_effect1975: Fischhoff demonstrates hindsight bias
Baruch Fischhoff showed that learning an outcome changed people's judgments about how predictable it had been. Participants had difficulty reconstructing assessments made without outcome knowledge, complicating retrospective judgments about decisions and forecasts.
https://en.wikipedia.org/wiki/Hindsight_bias1977: Ross names the fundamental attribution error
Lee Ross used the term fundamental attribution error for a tendency to overemphasize personal dispositions when explaining behavior and underweight situational constraints. Later research examined how the pattern depended on culture, information, and task design.
https://en.wikipedia.org/wiki/Fundamental_attribution_error1979: Researchers demonstrate biased assimilation
Charles Lord, Lee Ross, and Mark Lepper presented people with mixed evidence about capital punishment. Participants evaluated evidence differently depending on their prior views, illustrating how exposure to the same material could sustain disagreement.
https://en.wikipedia.org/wiki/Group_polarization#Attitude_polarization1981: Framing changes responses to equivalent choices
Amos Tversky and Daniel Kahneman showed that describing outcomes as gains or losses could alter preferences between risky options. Their disease-outbreak problem made framing effects visible even when the numerical consequences of the alternatives were equivalent.
https://en.wikipedia.org/wiki/Framing_effect_(psychology)1983: The Linda problem exposes conjunction errors
Amos Tversky and Daniel Kahneman reported that many participants ranked a detailed conjunction as more probable than one of its components. The Linda problem connected representativeness judgments with violations of a basic rule of probability.
https://en.wikipedia.org/wiki/Conjunction_fallacy1985: Arkes and Blumer investigate sunk costs
Hal Arkes and Catherine Blumer reported experiments in which prior investments of money or effort increased willingness to continue an undertaking. The sunk-cost effect described choices influenced by unrecoverable expenditures rather than only future consequences.
https://en.wikipedia.org/wiki/Sunk_cost1988: Samuelson and Zeckhauser study status quo bias
William Samuelson and Richard Zeckhauser examined a preference for leaving an existing choice unchanged. Their experiments distinguished a status quo effect from preferences over the options themselves, while recognizing that switching costs could sometimes justify staying put.
https://en.wikipedia.org/wiki/Status_quo_bias1995: Gigerenzer and Hoffrage test frequency formats
Gerd Gigerenzer and Ulrich Hoffrage showed that expressing statistical information as natural frequencies could improve performance on Bayesian reasoning tasks. Their experiments demonstrated that apparent reasoning errors depended partly on how a problem represented the evidence.
https://en.wikipedia.org/wiki/Gerd_Gigerenzer1999: Kruger and Dunning study miscalibrated self-assessment
Justin Kruger and David Dunning reported that low-scoring participants often overestimated their relative performance on several tasks. The finding prompted research on metacognition, alongside debate about how statistical effects and task design contributed to the observed pattern.
https://en.wikipedia.org/wiki/Dunning%E2%80%93Kruger_effect2002: Pronin and colleagues identify the bias blind spot
Emily Pronin, Daniel Lin, and Lee Ross reported that people tended to see themselves as less susceptible to biases than other people. The bias blind spot highlighted limits in using introspection to assess the reliability of one's own judgment.
https://en.wikipedia.org/wiki/Bias_blind_spot2018: Many Labs 2 retests judgment effects
The Many Labs 2 collaboration repeated 28 psychological findings across many samples and settings. Fourteen showed statistically significant effects in the original direction, demonstrating why the reliability of named effects had to be assessed individually.
https://en.wikipedia.org/wiki/Replication_crisis