Adversarial machine learning (AML) poses significant legal challenges for organizations, particularly regarding privacy compromise attacks in Predictive AI and prompt injection attacks in Generative AI, necessitating careful compliance with regulations like Gramm-Leach-Bliley and HIPAA while managing risks through contractual provisions and internal policy revisions.
The TAKE IT DOWN Act, passed by Congress, establishes federal offenses for the creation and distribution of non-consensual intimate imagery, including AI-generated deepfakes, while mandating prompt removal by online platforms and allowing victims to seek damages, thereby addressing significant gaps in existing legal protections.
Recent research reveals significant risks associated with AI companion chatbots for minors, prompting state-level legislative initiatives across the U.S. aimed at restricting access, enhancing safety measures, and addressing mental health concerns, while the federal government remains inactive on the issue.
The European Commission is enhancing AI literacy among individuals and organizations involved with AI systems, as mandated by the AI Act, to ensure responsible deployment and compliance across all risk tiers in the EU.
In the ongoing case Kadrey v. Meta Platforms Inc, authors claim the company unlawfully used their copyrighted works to train its AI model, raising significant legal questions about fair use and market impact in the context of copyright law.
The White House’s Office of Management and Budget has issued memoranda M-25-21 and M-25-22, establishing new governance and acquisition guidelines for high-impact AI within US federal agencies, emphasizing risk management, transparency, and the prioritization of American-made AI technologies.
