Event Date/Time:

Thursday May 18th 9:00 PST/ 12:00 PM EST (45 min talk + Q&A)

Generative AI presents a significant opportunity for technology, innovation, and connection, yet its dramatic growth has raised questions about how to use this innovation in ethical and legal ways that require careful consideration by industry, policymakers, and regulators. This MUSA webinar explored whether the growing demand for datasets to be used to feed generative AI model training has contributed to the rise of unauthorized scraping and whether this gives rise to questions around privacy risks and the need for transparency. Experts from civil society, academic and industry fields came together to discuss the benefits, risks, and challenges of generative AI and its relationship to unauthorized scraping.

The Mitigating Unauthorized Scraping Alliance (MUSA) brings together industry members and experts to address challenges and establish a unified front against unauthorized scraping and data misuse. It is working with member companies and experts to publish industry-aligned practices to mitigate unauthorized scraping across member platforms, reduce the attack vector for unauthorized scraping threat actors, and serve as a resource for media and policymaker engagement.

Speakers and Moderator:

Daniel Gervais, Professor, Vanderbilt University

David Patariu, Associate, Venable LLP; Privacy Law Specialist (PLS); International Association of Privacy Professionals Fellow of Information Privacy, CIPP/US, CIPP/E, CIPM; ISC² CCSP, CISSP

Brandi Guerkink, Senior Policy Fellow, Mozilla Foundation

A.J. Zottola, Moderator, Partner, Venable LLP