Evidence of harm is hard to come by.

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.

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

So much of our society as a whole is gearing us to maximize our salary or bonus. Basically, we just think in terms of money. Or, if not money, then, if you're in academia, it's prestige. It's a different kind of currency. And there's this unmeasured dimension of all jobs, which is whether it's improving the world.

I wanted to prevent people from giving them too much power. I see that as a pattern. I wanted that to come to an end as soon as possible.

Evidence of harm is hard to come by.