The DOI matches its Crossref record.
The Law of Implicit Bias
Abstract
Considerable attention has been given to the Implicit Association Test (IA T), which finds that most people have an implicit and unconscious bias against members of traditionally disadvantaged groups. Implicit bias poses a special challenge for antidiscrimination law because it suggests the possibility that people are treating others differently even when they are unaware that they are doing so. Some aspects of current law operate, whether intentionally or not, as controls on implicit bias; it is possible to imagine other efforts in that vein. An underlying suggestion is that implicit bias might be controlled through a general strategy of "debiasing through law."
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Discrimination in the Age of Algorithms
Kleinberg, J., Ludwig, J., Mullainathan, S., & Sunstein, C. R. (2018) · Journal of Legal Analysis · doi:10.1093/jla/laz001 · Cited by 401
Self-citationGerards, J., & Zuiderveen Borgesius, F. (2021) · doi:10.2139/ssrn.3723873 · Cited by 72
Policy Implications of Implicit Social Cognition
Nosek, B. A., & Riskind, R. G. (2012) · Social Issues and Policy Review · doi:10.1111/j.1751-2409.2011.01037.x · Cited by 55
Do Theories of Implicit Race Bias Change Moral Judgments?
Cameron, C. D., Payne, B. K., & Knobe, J. (2010) · Social Justice Research · doi:10.1007/s11211-010-0118-z · Cited by 52
Hissong, R. V., & Wheeler, G. (2019) · Criminal Justice Policy Review · doi:10.1177/0887403417714560 · Cited by 10
Metadata
- Authors
- Jolls, C., & Sunstein, C. R.
- Venue
- California Law Review
- Publisher
- JSTOR
- Published
- 2006-07-01
- Volume
- 94
- Issue
- 4
- Pages
- 969
- ISSN
- 0008-1221 (ISSN-L)
- OpenAlex
- W2105998493
- Cited by
- 177
- References
- 0
- FWCI
- 315.90
- Type
- journal article
- Language
- en
- Open access
- closed
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The Law of Implicit Bias. https://app.cochat.ai/papers/10.2307/20439057
- The paper
- Jolls, C., & Sunstein, C. R. (2006). The Law of Implicit Bias. California Law Review. https://doi.org/10.2307/20439057
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.