Hanlon’s razor: never attribute to malice that which is adequately explained by carelessness.

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The third story, most respectful interpretation, and Hanlon’s razor are all attempts to overcome what psychologists call the fundamental attribution error, where you frequently make errors by attributing others’ behaviors to their internal, or fundamental, motivations rather than external factors. You are guilty of the fundamental attribution error whenever you think someone was mean because she is mean rather than thinking she was just having a bad day.

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The problem with the just world hypothesis and victim-blaming is that they make broad judgments about why things are happening to people that are often inaccurate at the individual level.

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Learned helplessness describes the tendency to stop trying to escape difficult situations because we have gotten used to difficult conditions over time. Someone learns that they are helpless to control their circumstances, so they give up trying to change them.

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For many years, targets were given in physical terms—so many yards of cloth or tons of nails—but that led to obvious difficulties. If cloth was rewarded by the yard, it was woven loosely to make the yarn yield more yards. If the output of nails was determined by their number, factories produced huge numbers of pinlike nails; if by weight, smaller numbers of very heavy nails. The satiric magazine Krokodil once ran a cartoon of a factory manager proudly displaying his record output, a single gigantic nail suspended from a crane. Goodhart’s law summarizes the issue: When a measure becomes a target, it ceases to be a good measure

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Both describe the same basic phenomenon: When you try to incentivize behavior by setting a measurable target, people focus primarily on achieving that measure, often in ways you didn’t intend. Most importantly, their focus on the measure may not correlate to the behavior you hoped to promote.

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[…] seemingly small changes in incentive structures can really matter. You should align the outcome you desire as closely as possible with the incentives you provide. You should expect people generally to act in their own perceived self-interest, and so you want to be sure this perceived self-interest directly supports your goals.

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One model that can help you figure out how to strike this balance in certain situations is the precautionary principle: when an action could possibly create harm of an unknown magnitude, you should proceed with extreme caution before enacting the policy. It’s like the medical principle of “First, do no harm.” For example, if there is reason to believe a substance might cause cancer, the precautionary principle advises that it is better to control it tightly now while the scientific community figures out the degree of harm, rather than risk people getting cancer unnecessarily because the substance has not been controlled.

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Parkinson’s law (yes, another law by the same Parkinson of Parkinson’s law of triviality) states that “work expands so as to fill the time available for its completion.” Does that ring true for you? It certainly does for us.

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Tom Cargill was credited (in the September 1985 Communications of the ACM) for the similar ninety-ninety rule from his time programming at Bell Labs in the 1980s: The first 90 percent of the code accounts for the first 90 percent of the development time. The remaining 10 percent of the code accounts for the other 90 percent of the development time.

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[…] if you can identify the center of gravity of an idea, market, or process—anything—then you might effect change faster by acting on that specific point. For example, you might convince a central influencer, someone other people or organizations look to for direction, that an idea is worthwhile.

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