{"version":"1.0","type":"rich","provider_name":"Acast","provider_url":"https://acast.com","height":250,"width":700,"html":"<iframe src=\"https://embed.acast.com/$/60518a52f69aa815d2dba41c/65bd7091eb7e55001644095d?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":"Riana Pfefferkorn and David Thiel on How to Fight Computer-Generated Child Sexual Abuse Material","description":"<p>One of the dark sides of the rapid development of artificial intelligence and machine learning is the increase in computer-generated child pornography and other child sexual abuse material, or CG-CSAM for short. This material threatens to overwhelm the attempts of online platforms to filter for harmful content—and of prosecutors to bring those who create and disseminate CG-CSAM to justice. But it also raises complex statutory and constitutional legal issues as to what types of CG-CSAM are, and are not, legal.</p><p>To explore these issues, Associate Professor of Law at the University of Minnesota and <em>Lawfare </em>Senior Editor Alan Rozenshtein spoke with Riana Pfefferkorn, a Research Scholar at the Stanford Internet Observatory, who has just published a new <a href=\"https://www.lawfaremedia.org/article/addressing-computer-generated-child-sex-abuse-imagery-legal-framework-and-policy-implications\" rel=\"noopener noreferrer\" target=\"_blank\">white paper</a> in <em>Lawfare</em>'s ongoing Digital Social Contract paper series exploring the legal and policy implications of CG-CSAM. Joining in the discussion was her colleague David Thiel, Stanford Internet Observatory's Chief Technologist, and a co-author of an&nbsp;<a href=\"https://cyber.fsi.stanford.edu/publication/generative-ml-and-csam-implications-and-mitigations\" rel=\"noopener noreferrer\" target=\"_blank\">important technical analysis</a>&nbsp;of the recent increase in CG-CSAM.</p>","author_name":"The Lawfare Institute"}