Calibration Certificate No. conservatism-bias
Conservatism Bias
The tendency to revise beliefs too slowly when new evidence arrives, updating in the same direction as Bayesian inference but by insufficient amounts, as if evidence were less diagnostic than it truly is.
documented offset from the normative answer
Early bookbag-and-poker-chip experiments were widely replicated across multiple labs in the 1960s-1970s, establishing conservatism as a robust finding. However, the phenomenon's interpretation has been contested. DuCharme (1970) showed conservatism could be partly explained by response bias. More fundamentally, the 'source skepticism' account (Fischhoff & Beyth-Marom, 1983) argues conservatism may be a rational response to imperfectly reliable information sources rather than a cognitive error. Ambuehl and Li (2015) found conservatism varies substantially across individuals and correlates with out-of-sample updating behavior, suggesting it may be a stable individual trait rather than a universal bias.
Calibration record
Source of systematic error
Edwards (1968) proposed that conservatism arises from misaggregation of accurately perceived evidence: people can correctly assess individual pieces of evidence but struggle to combine them optimally. Slovic and Lichtenstein (1971) elaborated that aggregating multiple sources of information is cognitively demanding. More recently, Fischer and Maier-Konig (2018) proposed a motivated account in which conservatism reflects loss aversion over changing beliefs. The 'participant skepticism' account (Fischhoff & Beyth-Marom, 1983; Koehler, 1996) suggests subjects may rationally discount experimenter-provided evidence because real-world information sources are imperfectly reliable.
The 'misperception' account (Peterson & Beach, 1967) holds that people have inaccurate subjective sampling distributions. The 'source reliability' account argues conservatism is rational skepticism about experimenter-provided data. Recent work by Ambuehl and Li (2015) finds conservatism is individual-specific and not caused by cognitive limitations like statistical knowledge, supporting a motivational account.
Recalibration procedure
Quantify the diagnostic implications of evidence using Bayes' theorem or structured probability estimation. Explicitly compare your intuitive posterior against the Bayesian calculation. For sequential evidence, use decision aids or algorithms that enforce proper aggregation of multiple signals.
Providing Bayesian feedback improved probability estimation in odds-estimation tasks (Donnell & DuCharme, 1975). Decomposition strategies that separate evidence evaluation from belief updating can reduce conservatism by focusing attention on the logical force of each piece of evidence.
Cross-calibrated against
- Base-Rate Neglecteasily-confusedWhile conservatism involves underweighting new evidence relative to priors, base-rate neglect involves underweighting prior probabilities relative to new evidence. They are opposite patterns of deviation from Bayes' theorem.
- Anchoring Effectmechanistically-linkedConservatism may partly reflect anchoring on prior beliefs, with insufficient adjustment toward the implications of new evidence.
- Confirmation BiassiblingBoth biases involve maintaining existing beliefs in the face of new information, but conservatism specifically concerns the magnitude of belief revision while confirmation bias concerns selective search and interpretation.