Pushkin.

From Pushkin Industries, this is Deep Background, the show where we explore the stories behind the stories in the news.

I'm Noah Feldman.

How did you find this podcast?

Did you see an ad for it on your phone?

If so, that ad might have shown up for you because based on information about you that's

out there on the internet, a computer algorithm decided that this show might be the kind

of thing that you would like.

Algorithms like that are all around us.

Some are far more consequential than others.

I'm glad you're listening to the show, but hey, if you're applying for credit, an algorithm

could actually evaluate your creditworthiness, and the stakes are a little higher there than

whether you're listening to this podcast or to Trevor Noah's.

If I'm looking for a job, an algorithm could go through all of the job applicants to try to

do a first cut before the employer decides who they're going to interview.

In some cities, algorithms are even being used by the police to try to predict the probability that there's going to be a crime in a particular place and to decide where they're going to focus the police efforts and actually send the cops.

Nicole Turner Lee is a fellow at Brookings Center for Technology Innovation. they're going to focus the police efforts and actually send the cops.

Nicole Turner-Lee is a fellow at Brookings Center for Technology Innovation.

She's been studying how algorithms like this work and how they fail. She recently co-wrote a report for Brookings about algorithmic bias, or in other words,

how computers can be racist.

So if we look at an algorithm like a black box, it starts with an input and it ends with an output.

When it comes to the input, you know, big data has made it very easy to actually harness volumes of data that are about us, these reference points about individuals, and to create,

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