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All 16 learnings · one per slide
Noise
Daniel Kahneman, Olivier Sibony and Cass R. Sunstein, in bytes
16 key learnings on the unwanted variability in human judgment, and how to reduce it.
16 learnings · ~40 sec eachSwipe →
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Noise, in bytes
16 key learnings from Daniel Kahneman, Olivier Sibony and Cass Sunstein on noise: why different people, or the same person at different times, judge the same case differently. Each takes about 40 seconds to read. Swipe, use the arrows, or your keyboard.
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Learning 1 · Introduction
Bias and Noise
The idea
Bias is consistent error in one direction. Noise is random scatter in judgements that should be the same.
Example
Shots clustered off-centre show bias; shots scattered everywhere show noise.
Takeaway
Both cause error.
Noisebooksinbytes.in
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Learning 2
Judges Who Disagree
The study
Judges given the same cases handed out very different sentences.
Example
Sentences for the same crime could differ by years depending on the judge.
Takeaway
Noise creates injustice.
Noisebooksinbytes.in
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Learning 3
The Noise Audit
The study
An insurance company expected underwriters' quotes to differ by about 10%. The median difference was around 55%.
The lesson
Organisations underestimate noise.
Try this
Give the same case to several colleagues and compare.
Noisebooksinbytes.in
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Learning 4
System Noise
The idea
System noise is variability among people who should agree, like doctors, judges or appraisers.
Example
Two doctors giving different diagnoses for the same patient.
Takeaway
Noise hides in organisations.
Noisebooksinbytes.in
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Learning 5
Level Noise and Pattern Noise
The idea
Level noise: some judges are generally harsher. Pattern noise: individuals react differently to particular cases.
Example
One judge is lenient on young offenders, another on first-timers.
Takeaway
Noise has several sources.
Noisebooksinbytes.in
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Learning 6
Occasion Noise
The idea
The same person can judge differently depending on mood, time of day or weather.
Example
Studies linked judges' decisions to factors like local football losses.
Takeaway
You are noisy too.
Noisebooksinbytes.in
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Learning 7
The Crowd Within
The idea
Averaging independent judgements reduces noise; even your own second guess helps.
Example
Averaging two estimates from the same person after a delay improves accuracy.
Try this
Make a second estimate later and average them.
Noisebooksinbytes.in
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Learning 8
Simple Rules Beat Judgement
The idea
Simple models and algorithms often outperform human judgement because they're consistent.
Example
Mechanical formulas predicting performance better than interviewers.
Takeaway
Consistency beats intuition.
Noisebooksinbytes.in
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Learning 9
Objective Ignorance
The idea
Some outcomes are fundamentally unpredictable, yet experts feel confident.
Example
Predicting long-term job performance from an interview.
Takeaway
Know the limits of prediction.
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Learning 10
Decision Hygiene
The idea
Like handwashing, decision hygiene prevents unknown errors.
Example
Procedures that reduce noise without knowing exactly where it is.
Takeaway
Build good habits into decisions.
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Learning 11
Independent Judgements
The idea
Gather judgements independently before discussion to avoid influence.
Example
Each interviewer scores a candidate before comparing notes.
Try this
Collect views privately before meetings.
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Learning 12
Sequence Information
The idea
Give people only the information they need, in a planned order, to avoid early bias.
Example
Forensic examiners shouldn't see a suspect's confession before analysing fingerprints.
Takeaway
Control what people see first.
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Learning 13
Structured Interviews
The idea
Use the same questions and scoring for every candidate.
Example
Google's hiring practices rely on structured interviews.
Takeaway
Structure reduces noise.
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Learning 14
Break Decisions Down
The idea
Assess separate parts of a decision independently, then combine them.
Example
The 'mediating assessments protocol' scores key factors before an overall judgement.
Try this
List and rate criteria before deciding.
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Learning 15
Rules vs Standards
The idea
Rules reduce noise but can be rigid; standards allow judgement but add noise.
Example
Speed limits versus 'drive reasonably'.
Takeaway
Choose based on the cost of errors.
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Learning 16
Noise in Medicine
The idea
Doctors often disagree in diagnoses, from radiology to psychiatry.
Example
Guidelines and checklists improve agreement.
Reflect
Where could a checklist reduce noise in your work?
Noisebooksinbytes.in
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All 16 learnings complete
That’s all 16 learnings.
Bias is error in one direction; noise is scatter. Where might your organisation's judgments be noisy?
Abhay Kumar JaiswalFCA · PMP® · Workday Financeabhayjaiswal.com
Summaries in my own words. Read the book for the full stories.
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Summaries are written in my own words for learning. Read Noise by Daniel Kahneman, Olivier Sibony and Cass R. Sunstein (2021) for the full stories. More Books in Bytes