97 Things About Ethics Everyone in Data Science Should Know

Chapter 95. Random Selection at Harvard?

Peter Bruce

Founder, Institute for Statistics Education at Statistics.com, an Elder Research company

Ethics in algorithms is a popular topic now. Usually the conversation centers around possible unintentional bias in a statistical or machine learning algorithm and the harm it could do when it is used to select, score, rate, or rank people. For example, a credit-scoring algorithm may include a predictor that is highly correlated with race, which could result in racially biased decisions.

There are contrary cases, though. The use of discretionary human judgment to admit students to highly selective universities is fraught with controversy and allegations of bias. Here’s a proposal for a simple statistical selection technique to assure diversity while avoiding bias. It is best illustrated with Harvard University and a court case that has brought notoriety to the university’s admission process.

“An art collection that could conceivably come our way...”

With 19 rejections for every acceptance, entry to Harvard can seem like a moonshot. The family art collection was one student’s advantage in applying to Harvard. It’s no secret that big donors, or potential donors, have a leg up when it comes to their kids getting into Harvard, Princeton, or any of hundreds of universities. Still, it was unusual to see the plain truth out in the open—the “art ...