Anomalies in the detection of change: When changes in sample size are mistaken for changes in proportions

Abstract

Detecting changes, in performance, sales, markets, risks, social relations, or public opinions, constitutes an important adaptive function. In a sequential paradigm devised to investigate detection of change, every trial provides a sample of binary outcomes (e.g., correct vs. incorrect student responses). Participants have to decide whether the proportion of a focal feature (e.g., correct responses) in the population from which the sample is drawn has decreased, remained constant, or increased. Strong and persistent anomalies in change detection arise when changes in proportional quantities vary orthogonally to changes in absolute sample size. Proportional increases are readily detected and nonchanges are erroneously perceived as increases when absolute sample size increases. Conversely, decreasing sample size facilitates the correct detection of proportional decreases and the erroneous perception of nonchanges as decreases. These anomalies are however confined to experienced samples of elementary raw events from which proportions have to be inferred inductively. They disappear when sample proportions are described as percentages in a normalized probability format. To explain these challenging findings, it is essential to understand the inductivelearning constraints imposed on decisions from experience.

Metacognitive Myopia in Hidden-Profile Tasks: The Failure to Control for Repetition Biases

“…The present findings strongly suggest that metacognitive myopia prevents homo sapiens from this kind of critical assessment, adding convergent evidence to existing findings on metacognitive myopia ( Fiedler, 2000 , 2012 ; Fiedler et al, 2016 ).…”

“…It can only be diagnosed and corrected at the metacognitive level. However, a host of convergent evidence suggests that metacognitive myopia prevents homo sapiens from critical assessment and correction ( Fiedler, 2000 , 2012 ; Fiedler et al, 2016 ). Even explicit reminders not to be misled by selective repetition and lopsided sampling do not prevent people from adopting the more frequently presented arguments.…”

“…The present approach relates an ordinary learning account to the intriguing notion of metacognitive myopia ( Fiedler, 2000 , 2012 ). Numerous findings demonstrate that sampling biases and repetition biases remain undetected and uncorrected at the metacognitive level ( Fiedler et al, 2000 , 2002 , 2016 ; Unkelbach et al, 2007 ; Fiedler, 2012 ; Powell et al, 2017 ). For instance, Unkelbach et al (2007) asked participants to assess how often 10 different shares were among the daily winners in a stock-market game.…”

“…One cannot tell one’s cognitive system to stop learning from repetitions (cf. Koriat, 1997 ; Fiedler et al, 2016 ; Powell et al, 2017 ), just as one cannot instruct oneself to stop learning from repeated CS-US pairings in Pavlovian conditioning.…”

The Power of the Truth Bias: False Information Affects Memory and Judgment Even in the Absence of Distraction

“…We assessed the truth bias via two inter-correlated measures, judgments and memory, each of which is likely to reflect a separate mechanism. The judgment-based truth bias seems to be a clear instance of metacognitive myopia (Fiedler, 2012;Fiedler et al, 2015), understood as the tendency to use large amounts of stimulus information, while being "naive and almost blind regarding the history and validity of the stimulus data" (Fiedler, 2012, p. 2). In this line tested whether participants' judgments about a person are affected by questions they are asked, independently of the answers they give.…”