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When we make a mistake, we attribute it to circumstances that pushed us into doing it. But when others make a mistake, we tend to see it as a character flaw, as something that flowed from their imperfect personality. This is known as the attribution bias. You must work against this. With an empathic attitude, you consider first the circumstances that might have made a person do what they did, giving them the same benefit of the doubt as you give yourself.
The Laws of Human Nature
Robert Greene
Equal-weight models do well because they are not susceptible to accidents of sampling. The immediate implication of Dawes’s work deserves to be widely known: you can make valid statistical predictions without prior data about the outcome that you are trying to predict. All you need is a collection of predictors that you can trust to be correlated with the outcome.
Noise
Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein
1. Structure and clarity: Are goals, roles, and execution plans on our team clear? 2. Psychological safety: Can we take risks on this team without feeling insecure or embarrassed? 3. Meaning of work: Are we working on something that is personally important for each of us? 4. Dependability: Can we count on each other to do high-quality work on time? 5. Impact of work: Do we fundamentally believe that the work we’re doing matters?
Measure What Matters
John Doerr
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