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It's possible for a powerful player to in theory make something open, but not actually be doing it in a way that's supposed to serve the end goal of like collaborative deliberative public input into

how something is designed for the public benefit and instead is doing it more in a

way that it benefits themselves. It's the Law Fair Podcast.

I'm Kevin Frazier, a Tarbell fellow at Law Fair with Chini Sharma, associate professor at

Fordham Law School, and Janiton Arbel, co-director of the Center for Law and AI Risk, an associate professor at Alabama

law.

If we take these concerns seriously, there is a reason to worry about the free dissemination of models to every person on the planet,

no matter their set of values, their commitments, and, you know, their goals.

Today we're talking about open source AI, its meaning, its costs and benefits, and its future

amid an uncertain regulatory environment.

A tale as old as tech is a struggle to democratize access to the latest innovations

while also making sure that access to technology is sufficiently regulated. A new chapter in that

tale has unfolded. Depending on who you ask, open source AI might be increasing the

odds of catastrophic risk, a praise-worthy example of the democratization increasing the to try to get to the root of what open source AI means, the legal and policy ramifications

of open source AI, and some predictions about where AI development and deployment may be

headed.

Jenny, let's start with you.

Can you speak to the idea of what open source means generally?

...