
Sign up to save your podcasts
Or


In this episode, Jeremy Bearer-Friend, Associate Professor of Law at George Washington University Law School, and Sarah Polcz, Acting Professor of Law at UC Davis School of Law, discuss their article "Sharing the Algorithm: The Tax Solution to Generative AI," which is published in the Columbia Journal of Tax Law. Bearer-Friend and Polcz begin by outlining some of the social problems associated with generative AI and explaining why existing proposals to address those problems are inadequate. They then propose an alternative model, consisting of an equity tax on AI companies, and explain why it would be both effective and preferable to alternative approaches. Bearer-Friend is on Twitter and Bluesky. Polcz is also on Twitter and Bluesky.
This episode was hosted by Brian L. Frye, Spears-Gilbert Professor of Law at the University of Kentucky College of Law. Frye is on Twitter at @brianlfrye and on Bluesky at @brianlfrye.bsky.social.
Hosted on Acast. See acast.com/privacy for more information.
By CC0/Public Domain4.9
9999 ratings
In this episode, Jeremy Bearer-Friend, Associate Professor of Law at George Washington University Law School, and Sarah Polcz, Acting Professor of Law at UC Davis School of Law, discuss their article "Sharing the Algorithm: The Tax Solution to Generative AI," which is published in the Columbia Journal of Tax Law. Bearer-Friend and Polcz begin by outlining some of the social problems associated with generative AI and explaining why existing proposals to address those problems are inadequate. They then propose an alternative model, consisting of an equity tax on AI companies, and explain why it would be both effective and preferable to alternative approaches. Bearer-Friend is on Twitter and Bluesky. Polcz is also on Twitter and Bluesky.
This episode was hosted by Brian L. Frye, Spears-Gilbert Professor of Law at the University of Kentucky College of Law. Frye is on Twitter at @brianlfrye and on Bluesky at @brianlfrye.bsky.social.
Hosted on Acast. See acast.com/privacy for more information.

9,238 Listeners

3,530 Listeners

379 Listeners

1,110 Listeners

6,304 Listeners

5,867 Listeners

15,684 Listeners

5,832 Listeners

3,946 Listeners

1,445 Listeners

3,541 Listeners

65 Listeners

399 Listeners

746 Listeners

2,282 Listeners