Cathy O'Neil Quotes

We can't just throw something out there and assume it works just because it has math in it.

There's less of a connection for a lot of people between the technical decisions we make and the ethical ramifications we are responsible for.

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

I think what's happened is that the general public has become much more aware of the destructive power of Wall Street.

When people are not given an option by some secret scoring system, it's very hard to complain, so they often don't even know that they've been victimized.

That's what we do when we work in Silicon Valley tech startups: We think about who's going to benefit from this. That's almost the only thing we think about.

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.

The NSA buys data from private companies, so the private companies are the source of all this stuff.

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.

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

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.

Occupy provided me a lens through which to see systemic discrimination.

I think big data companies only like good news. So I think they're just hoping that they don't get sued, essentially.

I set up a company, an algorithmic auditing company myself. I have no clients.

You'll never be able to really measure anything, right? Including teachers.

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."

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.

Micro-targeting is the ability for a campaign to profile you, to know much more about you than you know about it, and then to choose exactly what to show you.

Evidence of harm is hard to come by.

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.

For whatever reason, I have never separated the technical from the ethical.

I know how models are built, because I build them myself, so I know that I'm embedding my values into every single algorithm I create and I am projecting my agenda onto those algorithms.

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.

Every system using data separates humanity into winners and losers.

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.

The privileged, we’ll see time and again, are processed more by people, the masses by machines.