Noise: A Flaw in Human Judgment
Kahneman, Sibony, and Sunstein's 2021 study of inconsistency in expert judgment — co-equal partner to bias
Tradition: Behavioural decision science
Kahneman et al.'s 2021 study of noise — random variability — as the underappreciated partner of bias in judgment
Noise: A Flaw in Human Judgment (2021), co-written by Kahneman with Olivier Sibony and Cass Sunstein, develops the systematic study of "noise" — random, unwanted variability in judgments that should be identical. Where Thinking, Fast and Slow focused on bias (systematic deviation), Noise focuses on noise (random variability) and shows it is as substantial — and as costly — as bias in domains from criminal sentencing to medical diagnosis to insurance claims. Proposes "decision hygiene" measures.
Author
Editions cited
- Noise: A Flaw in Human Judgment (Little, Brown Spark, 2021)
School Embodiments
Mature behavioural-economics statement — noise as the underappreciated counterpart to bias.
"Wherever there is judgment, there is noise — and more than you think." (Noise)
Empirically-grounded statement about systematic features of human judgment.
"Noise is the unwanted variability in judgments that should ideally be identical." (Noise)
Engages philosophical questions about the normative status of judgment.
"The judgment of the experienced expert is supposed to be more accurate than that of the novice; the data suggest experts are mainly more confident." (Noise)
Liberal-institutional implications — noise as an objection to discretionary judgment, support for algorithmic and rule-based decision-making.
"The case for replacing human judgment with rules or algorithms is at least as much about noise as about bias." (Noise)
Naturalises decision-making — noise is an empirical fact about cognitive systems.
"Noise is a fact about cognitive systems, not a moral failing." (Noise)
Major empirical case for noise in legal-judicial judgment.
"The same judge, on different days, sentences identical cases very differently — that is noise." (Noise)
Internal Tensions
The book's policy-prescriptive recommendations have been variously assessed — defenders see them as proper decision-hygiene, critics worry about the displacement of human judgment by algorithmic substitutes.
I. Time
The 2010s research programme; the 2021 contemporary moment of algorithmic-vs-human-judgment debate.
Attributes
II. Space
The institutional decision-making contexts — courtrooms, hospitals, insurance offices — studied.
Attributes
III. Matter
The embodied judgment-making humans whose noise is the topic.
Attributes
IV. Observer
The decision-maker as both subject and observer of noisy judgment.
Attributes
V. Energy
The cognitive energies of effortful expert judgment.
Attributes
VI. Information
The institutional decision-information whose quality noise degrades.
Attributes
Personas with the nearest attribute fingerprint
Historical figures whose own classification on the same six-dimensional grid lands closest to this work's. Computed by attribute-agreement on coordinates both address.
Computed school proximity
The work's attribute fingerprint scored against all schools using the same quiz scorer. Useful as a sanity check on the hand-curated embodiments above.
How Noise: A Flaw in Human Judgment resolves each dilemma
44 resolved positions across 4 dimensions, including 6 distinctive where the majority of schools go the other way · 13 unaligned.
Each dimension is sorted so minority positions come first. Mainstream positions are folded into an expandable list.
Time · 9 dilemmas · 3 distinctive
Persistence, the future, and the direction of becoming.
6 mainstream positions
Matter · 7 dilemmas, all mainstream
Observer · 37 dilemmas · 3 distinctive
Mind, agency, and the knower's relation to the known.