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As of June 9, 2026, New York requires certain advertisements that use artificial intelligence-generated human performers to include a disclosure informing consumers that the advertisement contains a synthetic performer.

What Counts as a Synthetic Performer?

Governor Hochul’s office described the measure as the “first-in-the-nation” law aimed at increasing transparency around the use of AI in advertising. The law applies to commercial advertisements that depict a “synthetic performer,” defined as a digitally created, reproduced, or modified asset generated through artificial intelligence or other software that creates the impression of a human performer, but is not recognizable as any actual person.

Continue Reading New York AI Advertising Disclosure Requirement Now in Effect

What Is RSL Media and Why Does the Human Consent Standard Matter?

On May 12, 2026, RSL Media launched as a public benefit nonprofit co-founded by CEO Nikki Hexum, Cate Blanchett, Doug Leeds, and Eckart Walther. Its mission is to make human consent machine-readable and discoverable to AI systems through the Human Consent Standard, which allows any individual to declare whether AI systems may use their creative works, identity, likeness, voice, characters, or marks. Endorsements from several famous actors and organizations, such as a major talent agency and the Music Artists Coalition, highlight this as one of the entertainment industry’s potential technological answers to unauthorized AI exploitation.

RSL Media builds on the Really Simple Licensing (RSL) standard, an open protocol launched in late 2025, enabling machine-readable AI usage terms for website content, now claiming support from over 1,500 publishers, brands, tech companies, and media organizations. While the original RSL addressed content at a specific URL, the Human Consent Standard applies to “the underlying work, identity, character, or mark itself, wherever it appears.”

Continue Reading A New Framework for AI Permissions in Entertainment: RSL Media’s Human Consent Standard

We’ve all had that moment when we see an ad on social media for a product we were just talking to a friend about. Cox Media Group wanted its customers to believe it was behind this eerily too common phenomenon, but the FTC said otherwise.

On May 21, the Federal Trade Commission (FTC) announced proposed settlements with three companies—CMG Media Corporation, MindSift LLC, and 1010 Digital Works LLC—to resolve charges that they deceived small business customers by selling an advertising service called “Active Listening.”

Continue Reading FTC Settlement Highlights Risks of Deceptive AI Marketing Claims

On March 12, Venable’s Advertising and Marketing Group hosted its 12th Advertising Law Symposium in Washington, DC, bringing together in-house counsel, marketing executives, and industry professionals to examine the legal and regulatory landscape facing advertisers. The panels focused on a range of the latest topics in advertising law, including FTC enforcement priorities, pricing transparency, artificial intelligence, class action trends, and more.

In case you were unable to attend, here are some key themes that emerged from the day’s discussions.

Continue Reading Event in Review | 12th Advertising Law Symposium

In a rare course correction, the Federal Trade Commission (FTC) has reopened and vacated its 2024 consent order against Rytr LLC, a generative AI-powered company. The unusual move reflects a significant strategic reset of how federal regulators will approach AI technology, especially when alleged harms are hypothetical rather than concrete.

In 2024, the FTC filed an administrative complaint against Rytr, a company that sold an AI-powered writing assistant service that could generate testimonials and customer reviews. The FTC alleged that the AI-powered tool could generate reviews and testimonials that were not related to the user’s actual inputs or experience, and such reviews could therefore be deceptive.

The FTC challenged the conduct as unfair under Section 5, and as providing the means and instrumentalities for others to make deceptive statements. The final consent order was entered in December 2024, and it included a categorical ban on Rytr from providing any AI-powered service dedicated to consumer reviews or testimonials. Commissioner, now chairman, Andrew Ferguson, dissented from the votes issuing the complaint and approving the settlement.

Continue Reading The FTC Walks Back Its Rytr Enforcement Action, Signaling a Shift in Federal AI Regulation

Chris Mufarrige, the director of the FTC’s Bureau of Consumer Protection, spoke last week at the National Advertising Division’s Annual Conference in Washington, providing further insight into how the FTC is thinking about key issues.

Mufarrige focused his remarks on privacy and AI. He said he views the basic principles for all consumer protection to be ensuring consumers can make well-informed choices and that companies keep their promises. 

FTC’s Evolving Approach to Privacy Enforcement

Mufarrige noted that individual preferences make abstract rules governing privacy difficult to draft and administer. He criticized the Lina Khan-led FTC for its efforts to use Section 5 of the FTC Act as an omnibus privacy statute. He said the agency should instead focus enforcement on specific privacy statutes such as the Children’s Online Privacy Protection Rule (COPPA) and use Section 5’s unfairness authority only where economic analysis shows consumer harm. 

Continue Reading FTC Bureau of Consumer Protection Director on Privacy Rules and AI Regulation

FTC Commissioner Mark Meador spoke at the National Advertising Division’s Annual Conference this week in Washington and provided some insight into his views on advertising and consumer protection. 

Meador began by noting that he was an antitrust lawyer prior to becoming a commissioner, with limited exposure to consumer protection issues. He noted that many antitrust matters contest subtle issues of market definition and the anticompetitive effects likely to occur in the future. 

On the other hand, Meador described many of the cases brought by the FTC’s Bureau of Consumer Protection as fighting evil and involving conduct that morally shocked him. He threw in a quote from Leviticus 19:35-36 to make his point: “Do not use dishonest standards when measuring length, weight, or volume. Your scales and weights must be accurate. Your containers for measuring dry materials or liquids must be accurate.” 

Continue Reading FTC Commissioner Mark Meador Highlights Consumer Protection Priorities at NAD Conference

In the second landmark decision this week relating to whether use of copyrighted content for training generative AI qualifies as a fair use, Judge Chhabria, in the federal court for the Northern District of California, ordered summary judgment in favor of Meta Platforms Inc. (Meta), finding that Meta’s copying of a group of 13 bestselling authors’ books as training data for use in Meta’s large language training model (LLM) “Llama” was a fair use. Kadrey, et al. v. Meta Platforms, Inc., Case No. 23-cv-0317-VC. This groundbreaking decision out of the NDCA follows Judge Alsup’s ruling earlier this week that Anthropic’s use of legally obtained books for training its LLMs was a fair use, Bartz et al. v. Anthropic PBC, which we covered here.

The orders in both cases determined that the LLM’s use of copyrighted data for training generative AI was “highly transformative” and that the first copyright fair use factor therefore weighed heavily in favor of the AI developers. In both cases, the plaintiffs were unable to demonstrate sufficient market harm to overcome the heavy weight placed on the transformative nature of the AI models. The decisions, however, differed notably as to each judge’s consideration of the source of the copyrighted works and whether the works were obtained through authorized channels or from “pirate websites.”

Continue Reading Back-to-Back Fair Use Decisions: Two NDCA Courts Find Fair Use for AI Training, Emphasizing That the Specific Facts Concerning Alleged Market Harm Will Be Critical in Overcoming AI’s “Highly Transformative” Technology

On June 23, 2025, Judge Alsup in the Northern District of California issued an order in Bartz et al. v. Anthropic PBC, granting in part and denying in part Defendant Anthropic’s motion for summary judgment on the sole issue of whether its use of Plaintiffs’ books as training data for Anthropic’s large language models (LLMs) was “quintessential” fair use.

Central to its mixed holding, the court acknowledged that Anthropic used the works in various ways and for varying purposes, such that each “use” must be identified and assessed separately. Ultimately, the court held that while the use of textual works to train LLMs was “exceedingly transformative” and thereby was protected as fair use when considered against the remaining factors, the separate use of the works to create a central library was only fair use with respect to works purchased or lawfully accessed—i.e., the use of pirated copies to create the central library was not protectible fair use. This decision makes clear that the source of content is a key element in evaluating fair use.

Continue Reading Court Holds That Anthropic’s Training of AI Using Legally Obtained Books Is Fair Use, but Storage of Pirated Books Is Not

This week, the Federal Trade Commission (FTC) issued a proposed order requiring Workado, a company specializing in artificial intelligence (AI) detection tools, to stop advertising the accuracy of its AI detection tools unless it has suitable evidence that the detection tools are as accurate as claimed. The proposed settlement is yet another indication of the FTC’s continued emphasis on tackling deceptive AI technology under a new administration.

The complaint alleged that Workado marketed its AI Content Detector as being “98 percent” accurate when detecting whether text was written by AI or humans, but the complaint alleged that in reality, the accuracy rate was much lower. The complaint also alleges the AI detection tool was trained and built in such a way as to effectively analyze only academic content, rather than all of the various forms of marketing content Workado customers were submitting, thus making the 98% claim impossible. When independent testing was conducted, measuring the tool against various forms of marketing media, the accuracy rate dropped to just 53%.

Continue Reading AI Detection or AI Deception? FTC Says Be Ready to Back It Up