“Why would anyone visit a publisher’s website ever again?”
Penske Media Corp. (PMC) and its subsidiaries have sued Google LLC and Alphabet Inc., alleging Google has used its monopoly in General Search Services to coerce publishers into providing content for free, which Google uses for its generative AI products (Penske v. Google, No. 1:25-cv-03192, D.D.C.)
PMC is a media and publishing company with a portfolio of brands spanning music, entertainment, fashion, art, sports, and lifestyle. The plaintiffs include Rolling Stone, Billboard, Variety, The Hollywood Reporter, Deadline, ARTFORUM, ARTnews, SheMedia (including sheknows.com and stylecaster.com), Gold Derby, IndieWire, Sourcing Journal, Sportico, VIBE, and WWD (Women’s Wear Daily).
Filed in U.S. District Court for the District of Columbia, the complaint alleges:
Misappropriation of Content. PMC claims that Google republishes its content without permission in AI-generated answers, such as AI Overviews and Featured Snippets, which appear prominently on Google’s search engine results page (SERP). This practice allegedly reduces traffic to PMC’s websites, depriving them of advertising, affiliate, and subscription revenue.
AI Training Without Consent. Google is accused of using PMC’s content to train its large language models (LLMs), such as Bard and Gemini, without compensating PMC. These models generate derivative content that competes directly with PMC’s original works.
Threat to Online Publishing. PMC argues that Google’s practices undermine the business model of online publishers, reducing incentives to produce high-quality content. The company quotes New York Times writer Kevin Roose: “If A.I. search engines can reliably summarize what’s happening in Gaza, or tell users which toaster to buy, why would anyone visit a publisher’s website ever again? Why would journalists, bloggers and product reviewers continue to put their work online if an A.I. search engine is just going to gobble it up and regurgitate it?”
Decline in Search Referral Traffic. Studies cited in the complaint show that Google’s AI Overviews have led to significant declines in click-through rates for publishers. Bain & Company found that 60% of searches now terminate without the user clicking through to another website.
Antitrust and Unjust Enrichment
PMC’s complaint outlines six legal counts against Google:
1) Reciprocal Dealing in Violation of Section 1 of the Sherman Act. Google allegedly ties the sale of search referral traffic to publishers’ forced provision of content for republishing, AI training, and retrieval-augmented generation (RAG).
2) Reciprocal Dealing in Violation of Section 2 of the Sherman Act. Google is accused of using its monopoly power in General Search Services to coerce publishers into providing content for free, maintaining its monopoly and harming competition.
3) Unlawful Monopoly Leveraging in Violation of Section 2 of the Sherman Act. Google allegedly leveraged its monopoly in General Search Services to gain an unfair advantage in the online publishing market.
4) Unlawful Monopolization in Violation of Section 2 of the Sherman Act. Google is accused of willfully maintaining its monopoly in General Search Services through anticompetitive practices.
5) Unlawful Attempted Monopolization in Violation of Section 2 of the Sherman Act. Google allegedly engaged in anticompetitive conduct with the intent to monopolize the online publishing market.
6) Common Law Unjust Enrichment. Google is accused of unjustly benefiting from PMC’s content without compensation, using it for AI training, grounding, and republishing.
Threat to Competitive Markets
The case highlights the tension between tech companies and content creators in the era of generative AI. As Google transitions from a search engine to an “answer engine,” its practices raise questions about the sustainability of independent journalism and the future of the open web. PMC’s publications continue to deliver content, but the company is fighting to ensure its business model remains viable. The advent of the internet already challenged the publishing model, and many publishers have adapted to online publishing. But if major companies can use data to generate content without paying for it, publishers and any original content creators are at risk. The plaintiffs quote celebrity.land reporter Oliver Darcy, who wrote, “Users will soon no longer have to click on the links displayed in search results to find the information they are seeking.”
Along with its many advantages and enormous potential, AI puts competitive markets at risk, particularly as its development and deployment become increasingly concentrated among a few dominant firms.
As we’ve reported in the Mogin Law Blog, an immediate concern is the potential for algorithmic collusion. AI-powered pricing tools, especially when used across competing firms, can learn to avoid price wars and stabilize prices at artificially high levels—without any explicit agreement between companies. This kind of tacit coordination, facilitated by machine learning algorithms, can mimic cartel behavior and harm consumers by reducing price competition. Numerous antitrust suits are pending over algorithmic pricing.
Another issue is market concentration. Building advanced AI models requires massive amounts of data, computing power, and specialized talent. When a handful of companies dominate access to these resources, such as proprietary datasets or high-performance cloud infrastructure, they can effectively block new entrants. This entrenches the market power of incumbents. Platform dominance also plays a role. Companies that operate major platforms, e.g., search engines, app stores, or e-commerce sites, can use AI to favor their own products or services in rankings and recommendations. Strategic partnerships and acquisitions in the AI space are also under scrutiny. Deals between tech giants and leading AI startups, such as Microsoft’s investment in OpenAI or Google’s ties to Anthropic, raise concerns about exclusive access to cutting-edge technologies. These arrangements may give dominant firms an unfair advantage and reduce the incentive for independent innovation.
Finally, the complexity and opacity of AI systems make enforcement difficult. Regulators often struggle to detect anticompetitive behavior when it’s driven by algorithms, and it can be challenging to assign liability for decisions made by autonomous systems. This regulatory gap allows harmful conduct to go unchecked and makes it harder to maintain a level playing field.
‘ The preceding article may include information circulated by third parties ’
‘ Some details of this article were extracted from the following source www.jdsupra.com ’
