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

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.

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.

By construction, the world of big data is siloed and segmented and segregated so that successful people, like myself - technologists, well-educated white people, for the most part - benefit from big data, and it's the people on the other side of the economic spectrum, especially people of color, who suffer from it. They suffer from it individually, at different times, at different moments. They never get a clear explanation of what actually happened to them because all these scores are secret and sometimes they don't even know they're being scored.

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.

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.

When I think about whether I want to take a job, I don't just think about whether it's technically interesting, although I do consider that. I also consider the question of whether it's good for the world.