To help us think seriously about data ethics, we need case studies that we can discuss, argue about, and come to terms with as we engage with the real world. Good case studies give us the opportunity to think through problems before facing them in real life. And case studies show us that ethical problems aren't simple. They are multi-faceted, and frequently there's no single right answer. And they help us to recognize there are few situations that don't raise ethical questions.

In this co-written piece, senior fellow D.J. Patil outlines and recommends several strategies for improving our ethical lives in a digital age.

What does it take to build a good data product or service? Not just a product or service that’s useful, or one that’s commercially viable, but one that uses data ethically and responsibly.

Over the past year, there has been a great discussion of data ethics, motivated in part by discomfort over “fake news,” targeted advertising, algorithmic bias, and the effect that data products have on individuals and on society. Concern about data ethics is hardly new; the ACM, IEEE, and the American Statistical Association all have ethical codes that address data. But the intensity with which we’ve discussed ethics shows that something significant is happening: data science is coming of age and realizing its responsibilities. A better world won’t come about simply because we use data; data has its dark underside.

The hard thing about being an ethical data scientist isn’t understanding ethics. It’s the junction between ethical ideas and practice. It’s doing good data science.