⚖️ FTC removes posts warning of AI risks

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FTC Quietly Removes AI Safety Blog Posts

The Federal Trade Commission (FTC) has taken down three blog posts from the Lina Khan era that discussed open-source AI and consumer risks tied to artificial intelligence. The posts, including “On Open-Weights Foundation Models” (July 2024) and “AI and the Risk of Consumer Harm” (January 2025), highlighted the dangers of AI-enabled fraud, surveillance, and discrimination. Their removal follows a broader Trump administration effort to revise or delete large amounts of federal agency content. Since the inauguration, President Trump’s new FTC Chair, Andrew Ferguson, has redirected the agency toward deregulation and competition-friendly policies, aligning with the administration’s AI Action Plan, which prioritizes open-source innovation over safety and oversight.

Shifting AI Policy Signals a Regulatory Reset

The takedowns are more than housekeeping; they signal a philosophical reset in U.S. AI regulation. Under Khan, the FTC positioned itself as a watchdog over consumer harm in AI applications. Under Ferguson, the agency is pivoting toward loosening restrictions to encourage rapid innovation and global competitiveness, particularly against China. For startups, this shift suggests an environment with fewer enforcement actions and slower regulatory response times, especially regarding consumer protection and antitrust oversight. But that leniency may be temporary, as history shows, deregulatory periods often end with reactive crackdowns following high-profile harms or scandals.

Read the Regulatory Room

Founders building AI products should interpret this as a window of opportunity, but one that demands foresight. While the current FTC leadership may emphasize growth and open access, startups must still bake in transparency, data protection, and user safety from day one. These guardrails are not just compliance tools; they’re brand differentiators that can attract enterprise customers and investors wary of reputational risk. Founders should also document internal decisions around data use and model safety, as future administrations may restore oversight. In short: innovate boldly, but build as if the regulators are coming back.

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