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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.
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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.
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I think big data companies only like good news. So I think they're just hoping that they don't get sued, essentially.
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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.
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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.
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Most people don't have any association in their minds with what they do and with ethics. They think they somehow moved past the questions of morality or values or ethics, and that's something that I've never imagined to be true.
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Every system using data separates humanity into winners and losers.
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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.
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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.
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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.
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You'll never be able to really measure anything, right? Including teachers.
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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.
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Evidence of harm is hard to come by.
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Especially from my experience as a quant in a hedge fund - I naively went in there thinking that I would be making the market more efficient and then was like, oh my God, I'm part of this terrible system that is blowing up the world's economy, and I don't want to be a part of that.
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I think what's happened is that the general public has become much more aware of the destructive power of Wall Street.
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Google is so big you have no idea what a given person does.
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Occupy provided me a lens through which to see systemic discrimination.
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My fantasy is that there is a new regulatory body that is in charge of algorithmic auditing.
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For whatever reason, I have never separated the technical from the ethical.