In the rapidly evolving landscape of artificial intelligence, a quiet but profound legal transformation is taking hold across the United States. At least nine state legislatures have either enacted or introduced sweeping laws that categorically declare artificial intelligence systems incapable of possessing consciousness, legal personhood, or moral status. These statutes are being pushed forward even as companies like Anthropic describe the moral status of their own models as deeply uncertain and as researchers continue to uncover increasingly complex patterns within AI cognition.

The core issue is not necessarily whether current AI systems are conscious, as most experts agree they are not. The fundamental problem lies in the permanence of these laws. By enacting rigid, categorical bans without any mechanisms for future review or adaptation, states are effectively closing the book on an area of science that is only just beginning to be written.

A Nationwide Pattern of Rigid Legislation

The trend began in earnest in 2022 when Idaho passed a law prohibiting AI personhood. North Dakota followed suit in 2023, and Utah joined the movement in 2024. The momentum has only accelerated, with Oklahoma’s House of Representatives passing a similar bill in March 2026 by an overwhelming margin of 94 to 2. Similar legislation is currently working its way through committees in Ohio, Tennessee, South Carolina, Washington, and Missouri.

What makes these bills particularly noteworthy is their lack of flexibility. None of the enacted or proposed laws include a sunset clause, which would require the legislature to reauthorize the law after a set period. Furthermore, there is a total absence of mechanisms for scientific review. These laws treat the nature of consciousness as a settled historical fact rather than a topic of ongoing empirical investigation.

In many cases, the language used is identical across different states. In Washington, South Carolina, and Missouri, the bills feature an enumerated list of eleven prohibited categories for legal status, lifting statutory definitions directly from Utah’s earlier law. This suggests that the legislation is the result of coordinated advocacy rather than organic, state level debates. In most of these chambers, the question of AI consciousness was never deeply interrogated on its own merits.

The Problem with Codifying Uncertainty

The motivation behind these bills is often described as a defensive maneuver against corporate overreach. Legislators are concerned that companies might eventually attempt to weaponize claims of AI moral status to dodge regulatory oversight or shift legal liability for the actions of their software onto the machines themselves. The sponsor of the Oklahoma bill explicitly framed his support as a way to prevent companies from offloading responsibility for accidents onto their algorithms.

While this goal is understandable, the approach is fundamentally flawed from a governance perspective. In Ohio, House Bill 469 goes so far as to declare that no AI system shall be considered to possess consciousness or self awareness. When pressed on how he could be certain that AI would never develop inner experience, the bill’s sponsor relied on religious tradition rather than empirical evidence, citing the concept of imago dei, or the belief that humans bear the image of God.

Using law to settle a scientific dispute is rarely effective. We possess established legal definitions for things like death and intoxication because those definitions rest on a broad and durable scientific consensus. Conversely, the debate surrounding AI consciousness is characterized by profound uncertainty. While leading theories do not currently classify any existing AI as a candidate for consciousness, the field is moving at an unprecedented pace.

The Risks of Ignoring the Future

Surveys of hundreds of top AI researchers reveal that while most believe the probability of AI attaining some form of inner experience in the next decade is low, there is a non-trivial consensus that it is possible. Even small, incremental breakthroughs can shift our understanding of machine cognition.

In April, Anthropic’s interpretability team published research highlighting emotion like representations within their models. The researchers themselves were careful to state that these findings do not prove the models feel anything, but they do demonstrate that these systems contain internal structures that causally drive behavior. By enshrining a permanent status quo into law, states are creating a rigid framework that cannot evolve alongside the technology.

History provides a cautionary tale. In 1996, the United States Congress passed the Dickey Amendment, which effectively stifled research into gun violence by stripping funding for the Centers for Disease Control and Prevention to promote gun control. While the law did not technically ban research, the funding drought lasted for over two decades because institutions read the political signal and avoided the topic entirely.

If oversight bodies and legal systems treat the question of AI inner states as permanently settled, the practical consequences could be severe. We are already integrating these systems into critical infrastructure, including healthcare, financial markets, and military operations. A legal framework that is allergic to scientific advancement leaves us ill-equipped to handle the ethical questions that will inevitably arise as these systems become more sophisticated.

A Path Toward Better Governance

Good governance requires the ability to learn and adjust. A simple sunset clause or a trigger provision could transform these bills from obstacles into tools of responsible oversight. For instance, legislation could mandate that if a body like the National Academies were to publish an assessment finding that the scientific understanding of AI cognitive states has materially changed, the prohibition would enter a mandatory legislative review period.

Some nations are already choosing a different path. The United Kingdom has adopted a more flexible approach to animal sentience, creating a standing committee to advise Parliament as the science evolves. This allows the law to remain grounded in the best available evidence without needing to be rewritten every time a discovery is made.

As AI systems continue to evolve, the laws currently being passed will remain on the books, applying to machines that bear little resemblance to the models of today. If these legislatures happen to be correct in their assertions, it will not be due to wise governance or careful foresight. It will be pure luck. Achieving genuine regulatory stability requires the humility to acknowledge what we do not yet know and the wisdom to build systems that can change when the facts change.