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.

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.

Obviously the more transparency we have as auditors, the more we can get, but the main goal is to understand important characteristics about a black box algorithm without necessarily having to understand every single granular detail of the algorithm.

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

There might never be that moment when everyone says, "Oh my God, big data is awful."

An insurance company might say, "Tell us more about yourself so your premiums can go down." When they say that, they're addressing the winners, not the losers.