The Liability Shield Play: AI Labs Want the Law Written Before Courts Write It for Them

The move is transparently strategic. Rather than waiting for courts to work through the growing pile of AI-related lawsuits and produce binding precedent, OpenAI is backing Illinois legislation that would set the liability rules in advance. If the bill passes, it would limit the circumstances under which AI companies can be held responsible for harm their models cause. The timing is not accidental.

This is how favorable legal frameworks get established: not through litigation, but by shaping the rules before litigation decides the question. Anyone who watched Section 230 of the Communications Decency Act evolve from a narrow carve-out into the foundational immunity that held up the modern internet has seen this pattern before.

The Section 230 Parallel, and Where It Breaks

Section 230, passed in 1996, immunized online platforms from liability for content their users generated. The 26-word core of the statute, “No provider or user of an interactive computer service shall be treated as the publisher or speaker of any information provided by another information content provider,” enabled every major platform that followed. Without it, hosting user content would have been legally untenable at scale.

The analogy AI companies want you to draw is obvious: just as platforms shouldn’t be liable for what users post, AI labs shouldn’t be liable for what users do with their models. And in that narrow framing, the analogy has some validity. When a user takes a language model and uses it to generate a phishing email, there is a reasonable argument that culpability traces back to the human, not the model.

But the analogy breaks down in a way that matters. Section 230 addressed a situation where harmful content originated from a third party and the platform merely hosted it. The platform was a conduit. With AI systems, the company designs the model, trains it on chosen data, fine-tunes its behavior, defines its outputs, and deploys it with knowledge of its failure modes. When an AI model produces harmful output, the company did not merely host someone else’s content. It built and shipped the thing that did the harm.

Product liability law has a concept for this: a manufacturer can be held strictly liable when a product they designed and sold causes harm, even without proof of negligence. AI labs backing liability shields are trying to preempt exactly that theory. The question is whether legislators in states like Illinois will go along with it before courts have a chance to apply product liability doctrine to AI systems through ordinary litigation.

Why Illinois, and Why Now

Illinois is not a random choice. The state has a history of being an early venue for technology-related privacy and liability disputes. The Biometric Information Privacy Act, passed in 2008, gave Illinois residents private rights of action against companies that collected biometric data without consent. That law produced billions of dollars in settlements, including a $650 million settlement by Facebook over facial recognition and a $228 million settlement by BNSF Railway over thumbprint scanning of employees. Illinois plaintiffs’ attorneys and consumer advocates are well-organized around technology liability, and Illinois courts have been willing to let these cases proceed.

For an AI company, Illinois passing a bill that limits AI liability would have significance beyond its borders. It would signal legislative appetite for such protections, provide a template for lobbying in other states, and potentially preempt some of the most favorable venues for plaintiffs bringing AI harm claims.

The timing is also specific to where OpenAI finds itself legally. The company faces ongoing litigation from the New York Times over copyright infringement, from individual authors over training data, and faces broader scrutiny over whether its products cause harm in educational, medical, and emotional support contexts. Establishing that “model harm” is a legally distinct and limited category of liability would help insulate against several of these theories simultaneously.

What “Model Harm” Is Actually Doing

The phrase “model harm” is doing significant legal work in this framing. It draws a line between harm caused by the model itself, which is what the bill would limit liability for, and harm caused by how a product built on the model is deployed, which would presumably remain actionable.

For anyone building applications on top of AI APIs, this distinction has direct consequences. If a company builds a mental health chatbot on top of a commercial language model and that chatbot gives a suicidal user dangerously bad advice, the question of who bears liability becomes very concrete. A liability shield for the model layer does not eliminate the harm; it redirects legal exposure toward the application developer who deployed the system in a sensitive context.

This is, in some ways, structurally similar to how Section 230 operated in practice. Platform immunity did not reduce internet harm; it shifted the consequences onto users and onto the specific individuals who could be identified as originating the content. The platforms scaled and prospered. The people harmed by content on those platforms had limited legal recourse. Whether that was the right tradeoff for society is still actively debated.

The EU Took the Opposite Position

The contrast with the European Union’s approach is instructive. The EU AI Act, which entered force in 2024, takes a risk-tiered approach that moves in the opposite direction for high-stakes applications. High-risk AI systems, defined to include systems used in employment, education, law enforcement, and critical infrastructure, are subject to strict conformity assessments, documentation requirements, and human oversight mandates. The proposed EU AI Liability Directive would make it easier, not harder, for harmed parties to seek compensation from AI developers, including by creating presumptions of causality when a plaintiff can show a system was defective and the harm is plausibly connected to that defect.

The EU framing treats powerful AI as closer to a regulated product than to a communications platform. Whether that framework proves workable is an open question, but it at least reflects the underlying reality that AI systems are designed artifacts with known failure modes, not neutral conduits.

What the Strategy Reveals

The fact that OpenAI is openly backing state liability legislation reveals something about how the company assesses its legal exposure. If the existing legal framework were clearly favorable to AI labs, there would be no urgency to lobby for new protections. The push for preemptive shields suggests the company expects that, left to evolve through ordinary litigation, the law would be less forgiving.

For developers building on top of commercial AI APIs, the outcome of this legislative push has real implications. Liability exemptions for model providers concentrate legal exposure at the application layer, which is where most independent developers operate. Reading the terms of service for any major AI API, you will find indemnification clauses that require you to defend the provider against third-party claims arising from your use of their API. The liability shield play in the legislature is, in many ways, a continuation of what those contract terms already attempt to accomplish.

Whether Illinois passes the bill or not, the broader effort to establish favorable AI liability law at the state level is underway. The rules being written now, before there is a robust body of case law, will shape who bears the cost when AI systems cause harm. That is worth paying attention to, even if the legislative sausage-making is less exciting than the latest model release.