Implicit social cognition: from measures to mechanisms
Open accessAbstract
Most human cognition occurs outside conscious awareness or conscious control. Some of these implicit processes influence social perception, judgment and action. The past 15 years of research in implicit social cognition can be characterized as the Age of Measurement because of a proliferation of measurement methods and research evidence demonstrating their practical value for predicting human behavior. Implicit measures assess constructs that are distinct, but related, to self-report assessments, and predict variation in behavior that is not accounted for by those explicit measures. The present state of knowledge provides a foundation for the next age of implicit social cognition: clarification of the mechanisms underlying implicit measurement and how the measured constructs influence behavior.
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Humans are generally unaware of their implicit cognitions or attitudes and therefore not able to adequately report on them.
“Humans are generally unaware of their implicit cognitions or attitudes, and therefore not be able to adequately report on them.”
From Human- versus Artificial Intelligence (2021) · cites this paper as Nosek et al. (2011)
In “The Mind Beyond What Is Self-Reported” (page not provided), Nosek says some mental content may be inaccessible to introspection and that self-report accuracy is uncertain. The paper does not say people are generally unaware of their implicit attitudes or therefore unable to report them adequately; it explicitly allows that self-report can be accurate and identifies other limits on reporting. (LLM, conf=0.87)
Experimental — accuracy not yet measuredLike our own brains, artificial neural networks are fundamentally intransparent.
“Like our own brains, artificial neural networks are fundamentally intransparant (Nosek et al., 2011; Feldman-Barret, 2017).”
From Human- versus Artificial Intelligence (2021) · cites this paper as Nosek et al., 2011
In “The Mind Beyond What Is Self-Reported” (page not provided), the paper says that only a small portion of brain activity is available to consciousness, supporting the point about limited insight into our own minds. It does not address whether artificial neural networks are intransparent, so it does not support the comparison. (LLM, conf=0.87)
Experimental — accuracy not yet measured
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Percentages, sums and reported differences re-computed from the paper’s own numbers.
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- Authors
- Nosek, B. A., Hawkins, C. B., & Frazier, R. S.
- Affiliations
- University of Virginia (US)
- Corresponding author
- Nosek, Brian A.
- Venue
- Trends in Cognitive Sciences
- Publisher
- Elsevier BV
- Published
- 2011-04
- Volume
- 15
- Issue
- 4
- Pages
- 152-159
- ISSN
- 1364-6613 (ISSN-L)
- PMC
- PMC3073696
- OpenAlex
- W2088840132
- Cited by
- 578
- References
- 128
- Citations by year
- 2026: 20 · 2025: 25 · 2024: 34 · 2023: 44 · 2022: 25 · 2021: 52 · 2020: 46 · 2019: 57 · 2018: 50 · 2017: 31 · 2016: 53 · 2015: 45 · 2014: 26 · 2013: 32 · 2012: 34
- FWCI
- 16.80
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Trends in Cognitive Sciences (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (R21AG033862)
- Topics
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Psychology › Applied Psychology › Psychological Testing and Assessment
- Social Sciences › Psychology › Social Psychology › Deception detection and forensic psychology
- Keywords
- implicit social cognition, implicit measures, implicit processing, social perception, social judgment, behavior prediction, self-report measures, measurement mechanism
- MeSH terms
- Awareness, Cognition, Consciousness, Humans, Models, Psychological, Neuropsychological Tests, Social Behavior, Weights and Measures, Self Report
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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