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What Academics Can Learn From Industry

At its best, industry focuses people. It demands that people use everything at their disposal to solve a problem. It puts a premium on being lean, humble, agnostic, creative, and rigorous. Industry data scientists use qualitative methods, e.g., directly observe processes and people, do lean experimentation, build novel instrumentation,

Unsighted: Why Some Important Findings Remain Uncited

Poring over the first 500 citations of the over 900 citations for Fear and Loathing across Party Lines on Google Scholar (7/31/2020), I could not find a single study citing the paper for racial discrimination. You may think the reason is obvious—the paper is about partisan prejudice,

Gaming Measurement: Using Economic Games to Measure Discrimination

Prejudice is the bane of humanity. Measurement of prejudice, in turn, is a bane of social scientists. Self-reports are unsatisfactory. Like talk, they are cheap and thus biased and noisy. Implicit measures don’t even pass the basic hurdle of measurement—reliability. Against this grim background, economic games as measures

Predicting Reliable Respondents

Setting aside concerns about sampling, the quality of survey responses on popular survey platforms is abysmal (see here and here). Both insincere and inattentive respondents are at issue. A common strategy for identifying inattentive respondents is to use attention checks. However, many of these attention checks stick out like sore

Interacting With Human Decisions

In sport, as in life, luck plays a role. For instance, in cricket, there is a toss at the start of the game. And the team that wins the toss wins the game 3% more often. The estimate of the advantage from winning the toss, however, is likely an underestimate

Solving Problem Solving: Meta Skills For Problem Solving

Each problem is new in different ways. And mechanically applying specialized tools often doesn’t take you far. So, beyond specialized tools, you need meta-skills. The top meta-skill is learning. Immersing yourself in the area you are thinking about will help you solve problems better and quicker. Learning more broadly

99 Problems: How to Solve Problems

“Data is the new oil,” according to Clive Humby. But we have yet to build an engine that uses the oil efficiently and doesn’t produce a ton of soot. Using data to discover and triage problems is especially polluting. Working with data for well over a decade, I have

Trading On Overconfidence

In Thinking Fast and Slow, Kahneman recounts a time when Thaler, Amos, and he met a senior investment manager in 1984. Kahneman asked, “When you sell a stock, who buys it?” “[The investor] answered with a wave in the vague direction of the window, indicating that he expected the buyer