Welcome to a tech policy podcast. I'm Ashken Kazarian. On today's show, we're going to talk about preventing algorithmic discrimination.

Joining me is one of experts and academic Dr. Ignacio Cofone, assistant professor at McGill University's Faculty of Law.

Ignacio, welcome to a show.

Hi, thanks so much for having me here.

So your topic is obviously a very serious and complicated topic, and you've written multiple

papers about this, which we will all link in notes to.

So if our lessons want to do a deeper dive in them, they can go there. But let's try

to break it down in 20 minutes or under. Can you give us, just like a brief overview, we're going

to focus on two of your papers and how they connect to each other and what they cover. So the papers

focus on a function that the law has sometimes, which is that the law

in some occasions blocks demographic information to prevent people from being discriminated

against. So for example, people may be familiar with the fact that employers are banned by

employment law to ask job candidates whether they intend to

take a parental leave in the near future, whether they intend to have a baby.

They also prevent from asking about HIV status or other genetic information.

And that is because by not having that information, the law is preventing employers to discriminate

against people that have the status.

Now, once we develop a better understanding

of how information flows regarding privacy,

which is this blocking demographic information

and discrimination works, this will allow us to

apply this method to other dimensions and have further protection for people that would

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