Beyond Bias with Olivier Sibony
If we told you that, all things being equal, black defendants get sentenced to three more years than white defendants, or people of a particular background or a particular gender are treated differently, we would say, “This bias is intolerable,” and we would be right. We would, of course, not tolerate that. Now, when that injustice is triggered simply by the luck of the draw, we somehow don’t pay as much attention to it. Maybe we should. It’s hard to see morally what makes it more justifiable for the personality of the judge to drive as much of the sentencing as these particular studies seem to suggest.
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Intro
In this episode of The Decision Lab podcast, Brooke is joined by Olivier Sibony, co-author of Noise, and experienced consultant and researcher focused on how to improve the quality of decision-making. He is currently a professor at HEC Paris, and Associate Fellow at Saïd Business School at Oxford University. This episode explores the three categories of noise, and how they can affect our decision making in ways that can be incredibly difficult to detect. Olivier draws on real-life examples to illustrate this and proposes several strategies to mitigate and avoid noise when making important decisions. Some topics we discuss include:
- Biases versus noise: how they differ
- How to conceptualize a judgment and judgment error
- What the three different categories of noise look like, and how they can skew decision making
- Why companies that depend on the judgments of many people should conduct a noise audit
- Decision hygiene and preventative strategies to improve decision making
- Practical steps that can be integrated into organizations to optimize judgments and reduce noise
