Google is so big you have no idea what a given person does.

People are starting to be very skeptical of the Facebook algorithm and all kinds of data surveillance.

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.

Google is so big you have no idea what a given person does.

With recidivism algorithms, for example, I worry about racist outcomes. With personality tests [for hiring], I worry about filtering out people with mental health problems from jobs. And with a teacher value-added model algorithm [used in New York City to score teachers], I worry literally that it's not meaningful. That it's almost a random number generator.

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.

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.