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Generative AI and Law (GenLaw)
Katherine Lee · A. Feder Cooper · FatemehSadat Mireshghallah · Madiha Zahrah · James Grimmelmann · David Mimno · Deep Ganguli · Ludwig Schubert

Sat Jul 29 12:00 PM -- 08:00 PM (PDT) @ Ballroom B
Event URL: https://genlaw.github.io »

Progress in generative AI depends not only on better model architectures, but on terabytes of scraped Flickr images, Wikipedia pages, Stack Overflow answers, and websites. But generative models ingest vast quantities of intellectual property (IP), which they can memorize and regurgitate verbatim. Several recently-filed lawsuits relate such memorization to copyright infringement. These lawsuits will lead to policies and legal rulings that define our ability, as ML researchers and practitioners, to acquire training data, and our responsibilities towards data owners and curators.

AI researchers will increasingly operate in a legal environment that is keenly interested in their work — an environment that may require future research into model architectures that conform to legal requirements. Understanding the law and contributing to its development will enable us to create safer, better, and practically useful models.

We’re excited to share a series of tutorials from renowned experts in both ML and law and panel discussions, where researchers in both disciplines can engage in semi-moderated conversation.

Our workshop will begin to build a comprehensive and precise synthesis of the legal issues at play. Beyond IP, the workshop will also address privacy and liability for dangerous, discriminatory, or misleading and manipulative outputs. It will take place on 29 July 2023, in Ballroom B.

Author Information

Katherine Lee (Google DeepMind)
A. Feder Cooper (Cornell University)
FatemehSadat Mireshghallah (University of California San Diego)
Madiha Zahrah (Cornell Tech)

Madiha is a Ph.D. student at Cornell Tech. Her research interests are at the intersection of technology, law and privacy. Specifically, she is investigating the ways that communities use technical and legal affordances to express and enact their shared values, with a particular emphasis on privacy and openness.

James Grimmelmann (Cornell)
James Grimmelmann

I’m a professor at Cornell Law School and Cornell Tech, where I direct CTRL-ALT, the Cornell Tech Research Lab in Applied Law and Technology. I study how laws regulating software affect freedom, wealth, and power. I try to help lawyers and technologists understand each other. My research interests include search engines, digital copyright, online governance, content moderation, and other topics in computer and Internet law.

David Mimno (Cornell University)
Deep Ganguli (Anthropic)
Ludwig Schubert
Ludwig Schubert

Formerly researching mechanistic interpretability with Chris Olah at Google Brain, OpenAI; supporting clear explanations of machine learning at Distill.pub. Currently unaffiliated on sabbatical while supporting friends' research.

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