Metacognitive Myopia in Change Detection: A Collective Approach to Overcome a Persistent Anomaly

Going beyond the origins of cognitive biases, which have been the focus of continued research, the notion of metacognitive myopia refers to the failure to monitor, control, and correct for biased inferences at the metacognitive level. Judgments often follow the given information uncritically, even when it is easy to find out or explicitly explained that information samples are misleading or invalid. The present research is concerned with metacognitive myopia in judgments of change. Participants had to decide whether pairs of binomial samples were drawn from populations with decreasing, equal, or increasing proportions p of a critical feature. Judgments of p changes were strongly affected by changes in absolute sample size n, such that only increases (decreases) in p that came along with increasing (decreasing) n were readily detected. Across 4 experiments these anomalies persisted even though the distinction of p and n was strongly emphasized through outcome feedback and full debriefing (Experiment 1-4), simultaneous presentation (Experiments 2-4), and recoding of experienced samples into descriptive percentages (Experiment 3-4). In Experiment 4, a joint attempt was made by 10 scientists working in 7 different institutions to develop an effective debiasing training, suggesting how multilab-collaboration might improve the quality of science in the early stage of operational research designing. Despite significant improvements in change judgments, debiasing treatments did not eliminate the anomalies. Possible ways of dealing with the metacognitive deficit are discussed.