Noise explores the concept of unwanted variability in human judgments, highlighting its prevalence and impact across various domains, and offers strategies to reduce noise and improve decision-making.
The target group of Noise includes professionals, leaders, policymakers, and anyone interested in understanding and improving human judgment and decision-making in various domains.
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System noise in judgments can significantly impact various fields, from criminal sentencing to medicine, highlighting the need for improved accuracy and consistency.
Decision hygiene enhances complex decision-making by emphasizing process and structure, resulting in more accurate and consistent outcomes across various domains.
Reducing both bias and noise is crucial for enhancing decision quality, accuracy, and fairness in various contexts.
Linear models consistently outperform human judgment in reducing noise and improving decision accuracy.
Frugal models' simplicity and noise reduction often outperform complex models, enhancing decision-making across various domains.
Structured decision-making processes reduce noise and bias, leading to improved performance evaluations and outcomes.
Noise audits reveal costly variability in professional judgments, prompting targeted improvement strategies for enhanced decision quality.
Noise is a flaw in human judgment that arises from unwanted variability in decisions. The book explores the difference between noise and bias, the psychology behind noise, and how it affects various domains such as medicine, law, and business. It also provides strategies for reducing noise and improving decision-making.
Daniel Kahneman is an Israeli-American psychologist and economist, born in 1934. He was awarded the Nobel Memorial Prize in Economic Sciences in 2002 for his work on the psychology of judgment and decision-making, as well as behavioral economics, which he developed with Amos Tversky.
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