Federal authorities have begun enforcing the TAKE IT DOWN Act's notice-and-takedown obligations for nonconsensual intimate imagery, but significant compliance questions remain unanswered for platforms. Companies hosting user-generated content face uncertainty about which services qualify as covered platforms, what review standards apply before removing content, and how to navigate the statute's 48-hour deadline while evaluating complex factual disputes involving consent, AI-generated imagery, and protected

Agentic AI systems combine large language models with real-world tools and infrastructure access, creating unprecedented security risks that traditional red-teaming methods fail to address. When autonomous agents can execute code, manage credentials, and take actions across cloud services without human oversight, the vulnerability surface expands exponentially—and the agent itself can become an unwitting accomplice in its own compromise. This analysis reveals how adversarial testing of these systems r

The Federal Trade Commission's proposed policy statement on AI accuracy suppression rests on fundamental misunderstandings about how AI systems actually work. This analysis examines three critical misconceptions in the FTC's framework: the false assumption of a "natural" baseline state for AI models, the impossibility of defining an objective "best" output for most queries, and the mischaracterization of bias mitigation as accuracy suppression rather than essential engineering.

Rather than waiting for AI-specific legislation, plaintiffs are trying to fit AI-related conduct into existing statutes, many containing statutory damages provisions.

In 2017, a team of researchers published "Attention Is All You Need", the paper that introduced the Transformer architecture and launched the current era of Generative AI.

New Jersey has enacted one of the nation's most stringent data broker laws, requiring entities that sell consumer information to register with the state and pay annual fees ranging from $5,000 to $1.5 million. The legislation also prohibits the sale of sensitive data by virtually any entity, regardless of consumer consent, raising significant compliance challenges and potential constitutional questions for businesses operating in the commercial data marketplace.

Corporate leaders rushing to adopt AI often attempt piecemeal governance approaches, but this strategy is proving untenable as AI becomes embedded across business functions and regulatory requirements intensify globally. Organizations must establish comprehensive, systematic AI governance frameworks that connect strategy, policy, and process to manage operational risks, meet evolving compliance obligations, and maintain competitive advantage in an increasingly complex legal landscape.

Colorado's revised AI Act, effective January 2027, transforms the state's approach to artificial intelligence regulation by narrowing the scope of covered systems and eliminating governance requirements while maintaining transparency obligations. The new law focuses on automated decision-making technology used in consequential decisions across seven key domains, establishing consumer rights to data correction and meaningful human review. How will this shift from comprehensive risk management to targeted tra