The narrative that AI is becoming sentient and uncontrollable absolves creators of responsibility. A better model is to hold leaders like Sam Altman personally accountable, much like arresting fraternity presidents for noise violations. This creates powerful incentives to build in safeguards.

The argument for new, specific AI regulations overlooks the power of existing legal frameworks. Standard product liability laws already hold companies responsible for harm caused by their products. If an AI company releases a dangerous product, they can be sued under established laws, disincentivizing recklessness without new government bureaucracy.

After advocating for minimal AI regulation, the administration's abrupt action against Anthropic's Fable model signals a chaotic policy reversal. This unpredictable shift from "let it rip" to ad-hoc intervention threatens investment and the future of American AI development by creating an unstable regulatory environment.

Senator Marsha Blackburn's "Trump America AI Act" directly conflicts with the administration's framework by placing a "duty of care" on AI developers. This makes companies legally liable for foreseeable harms, a stark contrast to the White House's proposal to protect developers from liability for how third parties misuse their models.

Federal and state governments are massive customers of technology. Instead of relying solely on legislation, they can use their procurement power to enforce AI safety and ethical standards. By setting strict purchasing requirements, they can compel companies to build more responsible products.

Direct, detailed government regulation of AI in the U.S. is unlikely to be effective. A better model is a self-regulatory organization like FINRA, where the government sets broad risk tolerance levels, and an industry body creates and enforces specific technical rules.

Jonathan Cantor argues that new AI-specific laws aren't immediately necessary. Companies can already be held responsible for their AI's actions under established product liability principles, just as they are for faulty products or employee misconduct.

Without clear government standards for AI safety, there is no "safe harbor" from lawsuits. This makes it likely courts will apply strict liability, where a company is at fault even if not negligent. This legal uncertainty makes risk unquantifiable for insurers, forcing them to exit the market.

The U.S. has a built-in mechanism for AI safety that precedes formal regulation: the court system. The potential for lawsuits (tort law) incentivizes model makers to act responsibly, acting as a form of self-regulation that doesn't require a slow-moving government bureaucracy.