Ethics and Data Science

Data is frequently collected, used, and sold without consent.

Trust requires consistency over time. You can’t trust someone who is unpredictable.

Any code of data ethics will tell you that you shouldn’t collect data from experimental subjects without informed consent.

It’s easy to argue that Strava shouldn’t have produced this product, or that AOL shouldn’t have released their search data, but that ignores the data’s potential for good. In both cases, well-intentioned data scientists were looking to help others. The problem is that they didn’t think through the consequences and the potential risks.

An individual needs to be empowered to stop the process before damage is done.

how should an application inform users about how their data will be used, and get their consent?

“Growth hacking” focuses on getting people to sign up for services through viral mechanisms. We’ve seen few product teams that try to develop a user experience that balances immediate experience with long-term values.

Anyone should be able to escalate issues for remediation without fear of retaliation.

It’s easy to say that applications shouldn’t collect data about race, gender, disabilities, or other protected classes. But if you don’t gather that data, you will have trouble testing whether your applications are fair