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The Bias That Divides Us: The Science and Politics of Myside Thinking
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Why we don't live in a post-truth society but rather a myside society: what science tells us about the bias that poisons our politics. In The Bias That Divides Us, psychologist Keith Stanovich argues provocatively that we don't live in a post-truth society, as has been claimed, but rather a myside society. Our problem is not that we are unable to value and respect truth and facts, but that we are unable to agree on commonly accepted truth and facts. We believe that our side knows the truth. Post-truth? That describes the other side. The inevitable result is political polarization. Stanovich shows what science can tell us about myside bias: how common it is, how to avoid it, and what purposes it serves. Stanovich explains that although myside bias is ubiquitous, it is an outlier among cognitive biases. It is unpredictable. Intelligence does not inoculate against it, and myside bias in one domain is not a good indicator of bias shown in any other domain. Stanovich argues that because of its outlier status, myside bias creates a true blind spot among the cognitive elite—those who are high in intelligence, executive functioning, or other valued psychological dispositions. They may consider themselves unbiased and purely rational in their thinking, but in fact they are just as biased as everyone else. Stanovich investigates how this bias blind spot contributes to our current ideologically polarized politics, connecting it to another recent trend: the decline of trust in university research as a disinterested arbiter.
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“All of these mechanisms, which are sometimes grouped under the general rubric of ‘myside bias’111–113, can contribute to issue polarization, insofar as individuals often become more extreme in their opinions after selectively processing the evidence on specific topics such as capital punishment, immigration, healthcare policy or climate change114,115.”
From Cognitive–motivational mechanisms of political polarization in social-communicative contexts (2022) · cites this paper as [113]
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- Stanovich, Keith E.
- ORCID
- Stanovich, Keith E.
- Venue
- The MIT Press eBooks
- Publisher
- The MIT Press
- Published
- 2021-08-31
- OpenAlex
- W4252880621
- Cited by
- 152
- References
- 561
- Citations by year
- 2026: 39 · 2025: 42 · 2024: 34 · 2023: 21 · 2022: 15 · 2021: 1
- FWCI
- 22.64
- Type
- book
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The MIT Press eBooks (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Keywords
- myside bias, confirmation bias, political polarization, post-truth, cognitive biases, bias blind spot, public trust in science, ideological partisanship, rationality
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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