The Illinois Department of Human Rights has drafted rules for the implementation of the new amendments. Below is a list of questions employers should be able to answer before integrating any new AI tool into their business in order to avoid costly penalties for violations of the new rules.
Businesses and investors are increasingly including AI-specific representations and warranties in commercial contracts and agreements, reassessing longstanding data strategies and sharpening their focus on protecting the rights in data that parties provide to one another.
Mass web-scraping for AI training, authorship of AI-generated works, and the scope of fair use in data-hungry systems are reshaping what “copyright risk” even means for a business. Companies that treat copyright as a mere box-checking exercise, or that assume long-standing internal practices are low-risk, increasingly find themselves out of step with how courts and regulators are thinking about AI-driven uses of content.
Together, EO 14365 and the National Policy Framework for Artificial Intelligence raise questions about the future of state and local laws governing employers’ use of AI, many of which are intended to protect against discrimination in connection with the use of AI.
After more than a hundred conversations with general counsel, chief legal officers, and legal operations leaders over the past seven months, I expected to hear complaints about AI accuracy or capability. The same five barriers appeared in conversation after conversation. Here’s what’s actually stopping deployment, and how to diagnose which barriers are blocking your team.
The use of AI does not alter fundamental obligations of accuracy, reasonableness and accountability. The legal risk lies not in the existence of hallucinations but in the failure to govern and verify them.
The Court held that intent is required and that mere awareness of infringement does not establish secondary liability.
The cyber insurance industry has long been dominated by conversations around security threats. Privacy concerns were often treated as an afterthought. But recently, there has been a critical shift: privacy risks that arise outside of traditional breaches are now front and center.
State app store age verification regimes do more than reallocate responsibility between platforms and developers. They create a new data supply chain for age knowledge, one that can move COPPA questions from “do we ask age?” to “what do we do when the platform tells us?” The teams that handle this best will treat platform age signals as sensitive compliance inputs: minimize them, tightly control where they flow, and design product behavior so that minors do not trigger unnecessary collection or disclosure.
A recent decision from the U.S. District Court for the Southern District of New York (SDNY), United States v. Heppner, has generated outsized commentary suggesting that the use of generative AI tools may jeopardize attorney-client privilege. A closer reading shows something far less dramatic.
