How experts' own inconsistency relates to their confidence and between-expert disagreement
Aleksandra Litvinova1, Ralf H J M Kurvers1, Ralph Hertwig1
1Center for Adaptive Rationality, Max Planck Institute for Human Development, 14195, Berlin, Germany.
Abstract:
People routinely rely on experts' advice to guide their decisions. However, experts are known to make inconsistent judgments when judging the same case twice. Previous research on expert inconsistency has largely focused on individual or situational factors; here we focus directly on the cases themselves. First, using a theoretical model, we study how within-expert inconsistency and confidence are related to how strongly experts agree on a case. Second, we empirically test the model's predictions in two real-world datasets with a diagnostic ground truth from follow-up research: diagnosticians rating the same mammograms or images of the lower spine twice. Our modeling and empirical analyses converge on the same novel results: The more experts disagree in their initial decisions about a case (i.e., as consensus decreases), the less confident individual experts are in their initial decision-despite not knowing the level of consensus-and the more likely they are to judge that same case differently when facing it again months later, regardless of whether the expert consensus is correct. Our results suggest the following advice when faced with two conflicting decisions from a single expert: In the absence of more predictive cues, choose the more confident decision.
Related Concept Videos
Theory of Attribution II: Kelley's Covariation Theory
Causes of Similarity-Dissimilarity Effect
Self-Discrepancy Theory
Uncertainty in Measurement: Accuracy and Precision
Interpretation of Confidence Intervals
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
Uncertainty: Confidence Intervals


