We don't let a car company just throw out a car and start driving it around without checking that the wheels are fastened on. We know that would result in death; but for some reason we have no hesitation at throwing out some algorithms untested and unmonitored even when they're making very important life-and-death decisions.

The training one receives when one becomes a technician, like a data scientist - we get trained in mathematics or computer science or statistics - is entirely separated from a discussion of ethics.

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 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.

I would argue that one of the major problems with our blind trust in algorithms is that we can propagate discriminatory patterns without acknowledging any kind of intent.

My fantasy is that there is a new regulatory body that is in charge of algorithmic auditing.

The public trusts big data way too much.