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slash Lawfair. Also check out Lawfair's other podcast offerings. Rational security chatter. There is a big

a lot fair no bull and the aftermath

There is a big responsibility part here for the people who are making decisions

about putting these systems into the world, for the people who are designing these systems and deploying them in the world

that there is a real human cost for not building the right processes in place,

for protecting the users or the people who are getting affected from these systems

to understand how these decisions are being made and what can they do to be able to contest them and ask the question of why.

I am Eugenia Lohtray,

Luffer's fellow in technology policy and law,

and this is the Lawfer Podcast, April 3rd, 2024.

The use of AI to make decisions about individuals raises the issue of contestability.

When automated systems are used by governments to decide whether to grant or deny benefits or calculate medical needs,

the affected person has a right to know why that decision was made and challenge it. But what does meaningful

contestability of AI systems look like in practice? To discuss this question I

was joined by Jim Dempsey, senior policy advisor at the Stanford Cyber Policy Center, and EJ

Kameh, managing director of the AI Frontiers Lab at Microsoft.

In January, they convened a workshop with stakeholders across disciplines to issue recommendations

that could help governments embrace AI while enabling the contestability required by law.

We talked about the challenges that the use of AI creates for contestability, how the

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