Human confidence judgments reflect reliability-based hierarchical integration of contextual information

Schustek, Philipp; Moreno-Bote, Rubén

doi:10.1101/425462

Cited by 2 publications

(2 citation statements)

References 55 publications

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“…estimates of block statistics is biased towards earlier trials in the block (primacy). Schustek et al (2018) likewise asked subjects to track information across trials in a cognitive task more analogous to our HSLC condition, and report close to flat weighting of evidence across trials Schustek and Moreno-bote (2018).…”

Section: Discussionmentioning

confidence: 99%

A confirmation bias in perceptual decision-making due to hierarchical approximate inference

Lange

Chattoraj

Beck

et al. 2018

Preprint

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1Human decisions are known to be systematically biased. A prominent example of such a bias 2 occurs when integrating a sequence of sensory evidence over time. Previous empirical studies di↵er 3 in the nature of the bias they observe, ranging from favoring early evidence (primacy), to favoring 4 late evidence (recency). Here, we present a unifying framework that explains these biases and 5 makes novel psychophysical and neurophysiological predictions. By explicitly modeling both the 6 approximate and the hierarchical nature of inference in the brain, we show that temporal biases 7 depend on the balance between "sensory information" and "category information" in the stimulus. 8Finally, we present new data from a human psychophysics task that confirm that temporal biases 9 can be robustly changed within subjects as predicted by our models. 10Imagine a doctor trying to infer the cause of a patient's symptoms from an x-ray image. Unsure 12 about the evidence in the image, she asks a radiologist for a second opinion. If she tells the 13 radiologist her suspicion, she may bias his report. If she does not, he may not detect a faint 14 diagnostic pattern. As a result, if the evidence in the image is hard to detect or ambiguous, 15 the radiologist's second opinion, and hence the final diagnosis, may be swayed by the doctor's 16 initial hypothesis. The problem faced by these doctors exemplifies the di culty of hierarchical 17 inference: each doctor's suspicion both informs and is informed by their collective diagnosis. If 18 they are not careful, their diagnosis may fall prey to circular reasoning. The brain faces a similar 19 problem during perceptual decision-making: any decision-making area combines sequential signals 20 from sensory brain areas, not directly from sensory input, just as the doctors' consensus is based 21 on their individual diagnoses rather than on the evidence per se. If sensory signals in the brain 22 themselves reflect inferences that combine both prior expectations and sensory evidence, we suggest 23 that this can then lead to an observable perceptual confirmation bias (Nickerson, 1998). 24 We formalize this idea in the context of approximate Bayesian inference and classic evidence-25 integration tasks in which a range of biases has been observed and for which a unifying explanation 26 1 is currently lacking. Evidence-integration tasks require subjects to categorize a sequence of inde-27 pendent and identically distributed (iid) draws of stimuli (Gold and Shadlen, 2007; Bogacz et al., 28 2006). Previous normative models of evidence integration hinge on two quantities: the amount of 29 information available on a single stimulus draw and the total number of draws. One might expect, 30 then, that temporal biases should have some canonical form in tasks where these quantities are 31 matched. However, existing studies are heterogeneous, reporting one of three distinct motifs: some 32 find that early evidence is weighted more strongly (a primacy e↵ect) (Kiani et al., 2008; Nienborg 33 and Cu...

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Section: Discussionmentioning

confidence: 99%

A confirmation bias in perceptual decision-making due to hierarchical approximate inference

Lange

Chattoraj

Beck

et al. 2018

Preprint

View full text Add to dashboard Cite

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“…In sum, interventions relying on critical thinking display robust effects if addressing the issue of pseudoscience upfront. This maybe because cognitive biases and reasoning errors vanish when problems (information) are contextualized (Schustek et al, 2019; see also Gigerenzer & Gaissmaier, 2011). Hence, "contextualizing" critical thinking in the domain of pseudoscience could facilitate pseudoscientific beliefs change.…”

Section: The Psychological Foundations Of Unfounded Beliefsmentioning

confidence: 99%

Reducing teachers' unfounded beliefs through critical‐thinking education: A non‐randomized controlled trial

Caroti

Arciszewski

2022

Applied Cognitive Psychology

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The prevalence of unfounded beliefs (e.g., supernatural or conspiracy beliefs) remains an important issue due to their negative consequences in various domains. Interventions were shown to reduce supernatural beliefs only when addressing pseudoscientific ones. Based on these findings, we designed a single session intervention aiming to teach participants the epistemological distinction between science and pseudoscience. We then assessed the effectiveness of this intervention. Secondary school teachers (N = 130) were assigned to one of two groups focusing on critical thinking with or without the intervention content related to pseudoscience. Supernatural beliefs, conspiracy mentality, and pattern perception were measured using computerized surveys pre-and one moth post-intervention. Mixed-model analyses revealed the expected decrease in conspiracy mentality, d = .60, supernatural beliefs, d = 1.01 and illusory pattern perception, d = .34 among teachers in the pseudosciencefocused group. Our intervention constitutes a novel cost-effective tool for critical thinking promotion among education professionals.

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Human confidence judgments reflect reliability-based hierarchical integration of contextual information

Cited by 2 publications

References 55 publications

A confirmation bias in perceptual decision-making due to hierarchical approximate inference

A confirmation bias in perceptual decision-making due to hierarchical approximate inference

Reducing teachers' unfounded beliefs through critical‐thinking education: A non‐randomized controlled trial

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