I set up a company, an algorithmic auditing company myself. I have no clients.

With recidivism algorithms, for example, I worry about racist outcomes. With personality tests [for hiring], I worry about filtering out people with mental health problems from jobs. And with a teacher value-added model algorithm [used in New York City to score teachers], I worry literally that it's not meaningful. That it's almost a random number generator.

People felt like they were friends with Google, and they believed in the "Do No Evil" thing that Google said. They trusted Google more than they trusted the government, and I never understood that.

Especially from my experience as a quant in a hedge fund - I naively went in there thinking that I would be making the market more efficient and then was like, oh my God, I'm part of this terrible system that is blowing up the world's economy, and I don't want to be a part of that.

We've learned our lesson with finance because they made a huge goddamn explosion that almost shut down the world. But the thing I realized is that there might never be an explosion on the scale of the financial crisis happening with big data.

Because of my experience in Occupy, instead of asking the question, "Who will benefit from this system I'm implementing with the data?" I started to ask the question, "What will happen to the most vulnerable?" Or "Who is going to lose under this system? How will this affect the worst-off person?" Which is a very different question from "How does this improve certain people's lives?"

You'll never be able to really measure anything, right? Including teachers.