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Cut out the noise for a more equitable world

Nobel Prize-winning economist Daniel Kahneman and his co-authors show us ways to reduce ‘noise’ in decision-making in their new book

Noise can be triggered by something as bizarre as the environment, mood swings, or the weather.
Noise can be triggered by something as bizarre as the environment, mood swings, or the weather. (iStock)

If there’s a single factor that has remained constant since the outbreak of the pandemic (apart from the trail of deaths and suffering), it’s the disagreements in the global medical community regarding the best treatment of covid-19. The latter is a relatively new malady, but physicians continue to differ even on the right course of treatment of some of the familiar ones as well. The result is confusion for patients and their caregivers and a system that’s riddled with “noise”—random and unpredictable divergences.

Nobel Prize-winning economist Daniel Kahneman teams up with management expert Olivier Sibony and behavioural economist Cass Sunstein to take a deep dive into such “noise”—its causes and remedies—in their new book Noise: A Flaw In Human Judgment (HarperCollins, 699). From judges presiding over hearings to committees responsible for college admissions to people assigned to approve or underwrite insurance coverage, noise can affect key decision making, causing upheavals in the lives of individuals and organisations.

Front cover of 'Noise'.
Front cover of 'Noise'.

Worse, it can be triggered by something as bizarre as the environment, mood swings, or the weather (“occasional noise”). Studies show that judges are likely to give lenient sentences when the sun is out, and doctors are prone to prescribing opioids to patients who see them at the end of a long day. Even fingerprint experts tend to revise their view when they are shown the same set of samples after an interval of several days.

Noise is not to be confused with bias, which is a systemic deviation rather than arbitrary scatter. The authors use elegant examples, with statistical graphs and mathematical models (these can be a bit jarring, at times, to be frank), to establish this thesis. By analysing case studies, they make an argument for conducting “noise audits” in organisations and across professions, including through the appointment of “decision observers”, who can minimise intuitive moves in favour of sounder judgements. To err is human—but to aspire for a fairer world is far more humane.

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