I think there's inherently an issue that models will literally never be able to handle, which is that when somebody comes along with a new way of doing something that's really excellent, the models will not recognize it. They only know how to recognize excellence when they can measure it somehow.

The disconnect I was experiencing was that people hated Wall Street, but they loved tech.

It's a standard thing you hear from startup people - that their product is somehow improving the world. And if you follow the reasoning, you will get somewhere, and I'll tell you where you get: You'll get to the description of what happens to the winners under the system that they're building.

The most important goal I had in mind was to convince people to stop blindly trusting algorithms and assuming that they are inherently fair and objective.

For whatever reason, I have never separated the technical from the ethical.

There are lots of different ways that algorithms can go wrong, and what we have now is a system in which we assume because it's shiny new technology with a mathematical aura that it's perfect and it doesn't require further vetting. Of course, we never have that assumption with other kinds of technology.

I think big data companies only like good news. So I think they're just hoping that they don't get sued, essentially.