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Prediction Errors: Using ML For Measurement

Say you want to measure how often people visit pornographic domains over some period. To measure that, you build a model to predict whether or not a domain hosts pornography. And let’s assume that for the chosen classification threshold, the False Positive rate (FP) is 10\% and the False

Technical Leadership: Building Great Teams and Products

Companies bet on people. They bet that the people they have hired will figure out the problems and their solutions. To make the bet credible, the golden rule is to hire competent people. Other virtues matter, but competence generally matters the most in technical roles. Once you have made the

Comparing Ad Targeting Regimes

Ad targeting is often useful when you have multiple things to sell (opportunity cost), when the cost of running an ad is non-trivial, when an irrelevant ad reduces your ability to reach the user later, or any combination of the above. (For a more formal treatment, see below.) targetingtargeting.pdf133

What's Relevant? Learning from Organic Growth

Say that we want to find people to whom a product is relevant. One way to do that is to launch a small campaign advertising the product and learn from people who click on the ad, or better yet, learn from people who not just click on the ad but

Sometimes Scientists Spread Misinformation

To err is human. Good scientists are aware of that, painfully so. The model scientist obsessively checks everything twice over and still keeps eyes peeled for loose ends. So it is a shock to learn that some of us are culpable for spreading misinformation. Ken and I find that articles

The New Unit of Scientific Production

One fundamental principle of science is that there is no privileged observer. You get to question what people did. But to question, you first must know what people did. So part of good scientific practice is to make it easy for people to understand how the sausage was made—how

Quality Data: Plumbing ML Data Pipelines

What’s the difference between a scientist and a data scientist? Scientists often collect their own data, and data scientists often use data collected by other people. That is part jest but speaks to an important point. Good scientists know their data. Good data scientists must know their data, too.

Operating Efficiently: Thumb Rules for Increasing Operational Efficiency

ABC ships cereal to people. ABC has a large operations team that handles customer complaints, e.g., “I got the wrong kind of cereal,” “the cereal was too old,” “the cereal arrived too late,” etc., and custom requests, e.g., “I would like seventy custom boxes shipped to a company

Optimal Sequence in Which to Service Orders

What is the optimal order in which to service orders assuming a fixed budget? Let's assume that we have to service orders $o_1,…,…o_n$, with the n orders iterated by $i$. Let's also assume that for each service order, we know how the costs

Pride and Prejudice

It is ‘so obvious’ that policy A >> policy B that only those who don’t want to know or who want inferior things would support policy B. Does this conversation remind you of any that you have had? We don’t just have such conversations about policies. We