# Book Review - Noise: A Flaw in Human Judgement

/ Published March 23, 2024

**Editor's Note: March is National Reading Month. Everyday reading increases knowledge and develops personal and professional skills. Throughout the month, DLA Disposition Services Pathways to Career Excellence program participants are sharing insights from books* they recently finished.**

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Imagine you and your team have an important decision to make that will impact your entire organization. You gathered all the relevant information, compiled extensive research, and are ready to come to a decision. However, depending on who speaks first, what the weather is like, or if it’s close to lunch time, your decision will be impacted, and you wouldn’t even be aware of it. For every decision we make, there will be an unwanted variability that affects our judgment. This is called noise.   

*Noise: A Flaw in Human Judgment*, by D. Kahneman, O. Sibony, and C. Sunstein, explains the concept of noise and how it has a profound impact on our decision-making abilities. Unlike bias, which produces systematic and consistent errors in judgment, noise refers to the variability and inconsistencies in our decisions. For instance, when one judge is more lenient than another when it comes to sentencing, that is a form of bias; however, when the same judge is presented the same case and hands down a drastically different sentence, that is an example of noise. We should come to the same conclusion when presented with identical information, but we often have variability because of noise. 

In this book, the authors present several real-world case studies of the implications noise has on fields like medicine, law, forensic science, and personnel selection. They describe the impact noise has and how to minimize its effects on decision making. 

I would recommend this book to anyone who is interested in how to make more accurate decisions, especially to those in positions where their decisions can impact another person. The amount of academic attention noise receives compared to bias is minimal. However, both contribute equally to errors in decision making. 

One example given in the book that is applicable to our organization is the interview process. When deciding on the best candidate to select for the job, if the senior person voiced their opinion first, the other panel members would rarely challenge that decision and change their top choice. Or if the first panel member spoke confidently about their choice, the rest of the members would start to question their own selection. A “noise audit” was developed by the authors to combat this from happening. Essentially, each panel member will immediately score the candidate after each section (resume, interview, reference checks, etc.) independently. Only after everyone gives their score will they come together at the end of the process and discuss their options. When discussing their options, they now have more accurate data that better represents their decisions.

This is just one example of how noise affects decision making and how to reduce its effects. Every decision we make will be affected in some way by random variability. Yet, I don’t think we should stress out every time we need to make a decision. However, if whatever we are deciding has major implications, I think it is wise to at least recognize that our decisions are likely being influenced by noise.