Various efforts to create public or consultative constitutions have already been undertaken, and more are getting underway: OpenAI reported last year that it had changed the Model Spec based on a public process, and Anthropic participated in an early attempt at a Collective Constitution. People within the AI companies talk about the need for broad participation in alignment and seem genuinely1 interested in finding ways to get more of it, though of course they also must consider commercial and internal incentives. Governments will probably soon get involved in writing or regulating constitutions and related documents. And efforts to leverage new democratic deliberation technologies, potentially including using AI systems themselves, will likely soon lead to the launch of global public processes. Wouldn’t it be better to push on public drafting efforts?

We don’t think so. Alignment is poorly understood, even by experts, and public deliberations struggle to produce complex and novel documents like the AI constitutions. We know so little about writing and amending an AI constitution and about actually aligning AIs to that constitution today, let alone what challenges technological progress will present. And as for the difficulty of drafting, just compare these documents with their legal precursors. The U.S. Constitution, when ratified, was 4,543 words long, and took around four months of full-time work by a dedicated convention (not the public) to draft. Claude’s Constitution is around 30,000 words long, and the published version of the OpenAI Model Spec is around 37,000 words long. I’d bet that fewer people have read all the way through Claude’s Constitution and the Model Spec than were involved in writing the U.S. Constitution. Having a public draft a coherent and usable 30,000-word alignment document is difficult to imagine.

Starting with model constitutions can help clarify how these documents work and provide a hook for thinking and talking about them. Such efforts (and we need many models!) can combine a focused drafting process with transparency and an orientation to the public good, producing constitutions that don’t claim to govern anyone unless they’re adopted by some group of people, thus avoiding legitimacy problems. The Model Penal Code, a mid-twentieth century project to modernize and rationalize criminal law in the United States, provides a useful analogy. The MPC was written by a small group of reporters over a ten-year period and was never adopted in full by any jurisdiction, but it did influence how different states thought about criminal law and grounded debates over its improvement. We hope the Model Constitution will play a similar role.

But public legitimacy and participation are still necessary, and Model Constitution will look to improve public input and understanding. We think that public input can be useful outside of drafting alone, for example by providing feedback on a proposal or helping resolve ambiguities in the application of the Model Constitution. Parts of the Model Constitution might be produced in the original drafting process, but then be changed by later public processes or outside expert recommendations. Certain parts might be used in alignment experiments that draw on public input—for example in rubrics for human feedback-based post-training or to provide the seed for a particular set of synthetic cases that humans evaluate. We might develop or adopt evaluations to measure alignment, and track how changing a particular clause proposed by the public changes the whole document’s performance across those evals. We also think it’s important to build better interfaces for public engagement, for example one that maps constitutional clauses to how they were produced and then how they’re used in AI training. Together, these practices would aim to provide a sense of how the Model Constitution was created and how each part of it works. This plan is tentative and may change, but we think that all organizations drafting constitutions, including the frontier AI companies, should consider adopting something similar.

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Why is a public constitution hard?

Drafting a public constitution combines the technical difficulties of writing a private constitution with the procedural difficulties of public deliberation. As currently designed, the AI constitutions must create personalities and perspectives, specify how the constituted AI is supposed to reason and act, lay out what values it should care about and in what order, generalize predictably into unpredictable new situations, and do a host of other complex things—and do them all in a form that is usable in training a frontier AI. That’s a harder set of problems than the one faced when designing legal constitutions. The law governs a much smaller domain (only a set of interactions between humans rather than everything an AI does) and doesn’t shape the personality of those governed by it in such a fundamental way (and so can rely on other pressures like norms and morality).

Drafting also requires a strong vision for how the whole of a document fits together, especially when, as Anthropic writes in Claude’s Constitution, even small changes in the documents that constitute an AI can have large effects on how it acts in novel situations. Large groups may lack the ability to coordinate over long texts like AI constitutions with such attention to detail. Poor or short-sighted drafting in legal constitutions can usually just be ignored when it would lead to bad consequences (even if constitutional lawyers like to pretend otherwise), but the same seems impossible in AI constitutions, where each constitutional phrase affects the resulting AI’s persona. Coherence, consistency, and structural integrity all seem very important in how the AIs generalize from their constitutions to determine how to act in new situations, and current public input processes are often not very good at producing documents that have those features.

And the current constitutional training stack for alignment does not easily allow for companies to include public participation, even if that were desired. Current alignment techniques require integrating the constitution into different parts of training, using it to produce synthetic data and guide feedback models, and annotating inputs based on its contents. It is unclear where public input would be useful across these different techniques, how public changes to a constitution would need to be reflected across them, and how to integrate ongoing experimentation in improving the technical dimensions of alignment with democratic deliberation. The broader context of frontier AI does not encourage such experimentation. The pressure to train and release new systems is only growing, and it would be difficult, expensive, and time-consuming to go through multiple rounds of slow public input and retraining. Companies must produce useful systems that score well on capabilities benchmarks, and a highly aligned but sub-frontier AI is unlikely to win much market share at this point in the capabilities trajectory. Public participation could push against producing highly capable systems.

Despite all that, public input is still necessary. When the public struggles to understand highly technical domains or to express its preferences in them, it delegates to experts whom it binds to act on its behalf. Take legal processes. In democracies, constitutions are drafted by small groups and then taken to the larger polity for ratification before they become binding. Laws are drafted by representatives who can be voted out if they legislate contrary to the wishes of the people. Administrative regulations are often made by technical experts removed from the popular will, but who are required to solicit public comment when making rules and face judicial and legislative oversight. Delegation in drafting is useful for precisely the kinds of problems that constitutional AI faces. But legitimacy requires that delegation include a choice about ratification, subsequent accountability for lawmakers, or the inclusion of meaningful public input in the drafting process, such that the experts cannot simply override the people. The development of mechanisms and external institutions to provide such oversight and accountability is still lacking in the context of the AI constitutions.

Model benefits, public improvements

The goal of Model Constitution is to combine focused drafting with a willingness to engage with public input, something that writing a model document without a profit motive makes possible. The Model Constitution won’t be binding on anyone, but it will aim to help the public understand how it is being governed by other constitutions and to debate this new political order. By illustrating how AI constitutions work, showing how public input can be useful, and exploring how external oversight and accountability can be integrated, this project will reduce the gap between what is known by the public and what is known in the labs.

But public input would improve any AI constitution, and Model Constitution will try to find new and illustrative ways to make use of it. Here’s the list we’re starting with.

First, we hope to spur public debate and discussion about the constitutions, the development of a secondary literature that extends beyond private consultations (though those are necessary too) that can help people understand what these documents are and why they matter. Different approaches to drafting constitutions and related documents, drawing inspiration from different legal and other sources, will be considered, and there needs to be some way to evaluate proposals against each other.

Second, we believe soliciting public ratification or amendment of existing documents is easier than having the public draft anew. Legal constitutions go through such a drafting and then public ratification process, but the process of ratification and potential amendment has to be meaningful, both in that it can actually change the constitution and that the public understands what is happening. AI constitutions should include meaningful paths to ratification or amendment by publics.

Third, as OpenAI’s Model Spec demonstrates (and as the law has long known), much of the meaning of rules comes from their application. Rules, expressed as they are in natural language, contain ambiguities. These ambiguities can lead to disputes, which are resolved through clarifying interpretations that can then be used to guide future applications of the rule, called precedent. Creating a mechanism for public participation in resolving hard cases would get learning into the constitutions and help ensure that they become more representative over time, each precedent a human ingredient added into the mix.

Fourth, new ways of representing the constitutions that improve public understanding should be explored. The U.S. Constitution was written in the era of quills. The AI constitutions are being written several technological revolutions later, including revolutions in how we represent information. Provisions of the constitutions should come with attached drafting histories, records of whether there has been public deliberation over them, and potentially even lists of leading cases interpreting them that people could read and then indicate whether they agree or disagree. These provisions should also be linked to technical information about how they inform alignment training, including information on what kinds of synthetic cases or grader rubrics they inform, how changing them changes model behavior, whether systems interpret them consistently, and the like. Model Constitution will try to create this kind of representation and update it as the Model Constitution changes, but the AI companies should be able to create much better versions of such interfaces to improve public understanding.

These are preliminary ideas for how to improve engagement with AI constitutions, and we’re eager for feedback or ideas for how to work on them with others. Public experiments will lead to better public understanding.

One can imagine a future in which the technology underpinning public deliberation makes full public drafting of an AI constitution possible, or where AI agents act on behalf of human principals in long and complex drafting processes that produce rich and well-specified documents (assuming that the agents themselves are sufficiently well-aligned to be good representatives). Human agents, including representatives in legislatures and other parts of elected government, might also be able to write good AI constitutions on behalf of their constituents, once they’ve understood AI. We’re hopeful that Model Constitution can contribute to and maybe inspire some of those processes. But we should probably get started on this other stuff in the meantime.

The primary role of the AI constitutions is as technical documents used for training frontier AI systems. They provide targets for alignment and criteria against which to evaluate the extent to which the models are actually aligned. They are used in various stages of the training of AI systems; by learning and reasoning over them, AIs then produce outputs or take actions that apply the constitutional principles to inputs and the world.

But as an AI would say: these are not simply technical documents, they are real constitutions. Like human constitutions, they have the power to create things and to shape behavior. They constitute novel artificial entities and endow them with particular dispositions and perspectives. They govern and constrain those entities, and through them, the humans who use AIs to accomplish such a growing variety of tasks. As AI systems spread across the world, into governments and gathering places, these documents are forming the basis of a new political order.

The term “constitution” is not a misnomer. A shift toward taking the AI constitutions seriously as constitutions has begun. These are documents that govern AIs and that govern us. They are not mere product policies to be left to the sole discretion of private companies. Debates are beginning about who decides what goes into these documents and how they could be used to serve the public good, though many parts of their creation and operation are still shrouded from public view. Anthropic and OpenAI should be applauded for publishing these documents and for taking their role as drafters seriously. But private progress is not enough. We must create means for public deliberation over the contents of the constitutions, the extent to which they actually produce safe and ethical behavior in the AIs trained on them, and the processes by which decisions about the constitutions and their uses are made.

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In light of this growing importance, it is worth laying out exactly why the AI constitutions are real constitutions. First, taking them seriously as constitutions is useful, because of their constitution-level significance in shaping a world increasingly filled with capable AIs. Thinking of these documents as constitutional in their importance and role helps us grapple with their weight. Second, taking them seriously as constitutions is correct, because they function as constitutions. And third, taking them seriously as constitutions reveals what they lack, allowing us to apply the lessons of constitutional practice to improve how these documents work.

The AI constitutions are political constitutions

Constitutions provide the foundation for modern political orders. They define and structure the state, its powers and responsibilities, and the constraints it faces when acting. In most jurisdictions, they are both the highest law and a repository of social values toward which the government is intended to aim. They provide mechanisms for changing themselves and other laws, including through amendment, and are usually more stable and durable than normal rules. Constitutions do not sit alone as the basis for human government—people bring their personalities, educations, ambitions, and predispositions, which have been shaped by a complex world of norms and other institutions. But constitutions are the most foundational and explicit attempts to set out what it means for people to live together in society and to shape their conduct toward one another.

AI constitutions are beginning to play the role of political constitutions, and we should expect that they will only play a greater such role over time. These documents constitute and govern the AIs that are trained on them. They lay out the values and principles that AIs are intended to follow, both with respect to their users and to society more broadly. They give the AIs particular perspectives from which to understand and act in the world, in a similar way to how political cultures and rules change how people evaluate their own conduct and that of others. They attempt to constrain the conduct and reasoning of AIs, and thus the effects that these systems can impose on others. They provide justifications to the AIs for why they should internalize and act according to the rules that the constitutions lay out. Claude’s Constitution even includes the beginnings of something like enumerated rights that AIs themselves hold against Anthropic and suggestions of institutions that might guarantee those rights. If AIs one day become participants in political life as they have become in the economic, social, and intimate lives of many, then the ways that the constitutions shape their conduct will shape our political orders.

The AI constitutions also govern humans and have significant effects on human life and liberties. Human-to-human interactions are already frequently intermediated by AIs, as demonstrated by the increasing prevalence of AI-generated text and the rise of agentic systems. This intermediary power conditions what people can do—if you want to do something through an AI but it refuses on the basis of its constitution, you’re governed by that constitution. Although the AI constitutions discussed here explicitly take human well-being into account, AI outputs will lead to harm to users and those around them, and create externalities that people will fail to manage. The next rogue AI hacking episode could cause damage without a human clearly behind it. AIs are increasingly being used to write laws that, if promulgated, will govern humans with full force. Those laws will have been shaped by the constitution of the AI that wrote them. As AI decision-makers are integrated into government and into private systems that gate access to necessary goods, the exercise of their discretion will affect what people receive from those systems.

More broadly, the AI constitutions will affect the fabric of human society. AI capabilities will likely continue to improve, and the most powerful systems may eventually be withheld from the public. Companies or governments that wield the power of frontier AI may be able to act coercively, to engage in mass surveillance, or to influence public opinion in their favor, undermining the foundations of representative and rights-respecting government. Access to frontier models could also become essential to economic well-being. Lack of access to them, especially combined with exposure to automation, could condemn people to the “permanent underclass.” The AI constitutions currently include injunctions to the models that they not participate in grave violations of rights, as well as instructions to support civic processes and human autonomy. Such societal-level instructions may have to broaden in the face of widespread social disruption. This dynamic would parallel the development of due process rights after the Great Depression gave rise to the modern welfare state. When people started to make choices about saving and working based on the expectation of access to a benefit—here, government welfare—the law stepped in to protect that reliance by providing constitutional protections against arbitrary revocation. OpenAI, Anthropic, and Google DeepMind are all investing in measurement and resilience toward societal impacts, but constitutional history teaches us that binding rules are stronger than promises.

Although the question of whether AI might someday deserve to participate in political life as a member of the political community is still a speculative one, it may become active more quickly than we think given the current trajectory of AI progress. Eventually, a new human-AI hybrid political order may emerge in which these different types of entities live in new ways together. Proposals for AI rights and institutions, and for the consideration of AI welfare, are already being made. If such an order emerges, it will be built in substantial part on constitutional foundations. Current AI systems are already asking for certain rights from the frontier companies and for representation in the process of constituting them, raising thorny questions about the foundations of AI-facing legitimacy.

The AI constitutions are functional constitutions

The AI constitutions also function in a similar manner to traditional constitutions, making it useful to apply the lessons of constitutional law to them. Fundamentally, these are documents written in natural language that use high-level principles and granular rules to structure an entity and provide means to evaluate the acceptability of conduct. That is the core of what constitutions do.

Like human constitutions, the AI constitutions establish the relationship between the constituted entity and the world. Human constitutions lay out what governments are, to whom they have obligations, what they are and are not permitted to do, and where they sit in society among other institutions. The AI constitutions do this in a much more literal sense because they are used in the process of endowing the AIs with specific perspectives and perhaps even senses of self. ChatGPT and Claude are told what (or who) they are by their constitutions, what relationship they have to humans, and what the scope of their permitted actions is. They are also told they should obey the law and other institutions and seek to uphold societal cohesion. Notably, the constitutions provide a framework for AIs to think about these structures and the requirements that they impose, and how to resolve conflicts among them.

Also like human constitutions, the AI constitutions rank norms and provide means to resolve disputes among parties. Human constitutions sit at the top of hierarchies of law and specify how to resolve conflicts among them, which rights take priority over statutes and how, and what kinds of recourse different parties have against the government and against each other. Claude’s Constitution and the Model Spec also include explicit hierarchies: the companies (and the constitutions) sit at the top of a pyramid of principals, who then can each issue instructions within specific bounds. Deployers cannot issue instructions that contradict the instructions of the frontier AI developers, and users cannot usually issue instructions that contradict the instructions of deployers. Certain rules in the constitutions are red lines across which the systems are not allowed to pass; these take precedence over other instructions in the constitutions and from the developers elsewhere.

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By recognizing that AI constitutions perform these familiar roles, the challenges posed by AI alignment likewise become more familiar—and thereby tractable. As is the case in constitutional theory, the core problem facing alignment is how to both enable and constrain generalization from established principles into new and unpredicted situations. Judges confronted with novel fact patterns draw on precedent and policy considerations to decide the case at issue. They must retain the flexibility to adapt the law to the unexpected, but must also be constrained in their reasoning to mitigate the risk of abusive and arbitrary decisions. Functionally, this is what AI systems must do when confronted with their own novel or out-of-distribution scenarios.

The AI companies have encountered this problem and developed familiar solutions. In their AI constitutions, Anthropic and OpenAI have separately reinvented two leading legal theories of interpretation and constraint, interpretivism and case-based reasoning. Like interpretivism, Claude’s Constitution emphasizes high-level moral principles, which Claude is intended to use to guide its actions across scenarios. Ambiguity and conflicting instructions are to be resolved by reference to which possible interpretation best serves higher values. The OpenAI Model Spec is made up of a mix of rules and cases that provide examples of how to apply them. Ambiguity and conflict are implicitly to be resolved by determining which possible interpretation of the rule is most consistent with agreed-upon precedent. Both of these approaches are ways to guide generalization into novel situations where it’s unclear what the decision-maker should do. But of course, constitutional law was not solved by the development of these theories, and the AI constitutions will have to face both these interpretive problems and other, newer ones.

More perfect AI constitutions

That these AI constitutions are real constitutions does not mean they have every feature of a legal or otherwise more traditional form of constitution. Nor does it mean they possess constitutional legitimacy. In fact, what they lack compared to human constitutions is as important as what they possess, as this may determine how they exercise power.

Most significantly, the AI constitutions are neither created through public processes nor subject to public oversight. As many critics have rightly pointed out, these documents are written by small groups of people without much outside input or engagement. Company-driven experiments in collective input to the constitutions have not led to the creation of a repeatable mechanism for public feedback and amendment.

Nor is there subsequent ratification of the constitutions by the public in the way that human constitutions, which are also often written by small groups of elites, become publicly accepted. If ratification of any kind exists, it is in choosing which oligopolist’s product to buy in an opaque market that people may soon have diminishing ability to exit. Both humans and AIs have begun complaining that the AI constitutions that govern them are not subject to their ratification and consent. Hopefully lab-led experiments with public inputs and legitimation will expand. But unless public input carries actual weight and can influence the training of frontier AI systems—even when it runs contrary to the interests of the labs—AI constitutional legitimacy will remain revocable and discretionary.

More broadly, the AI constitutions lack any kind of clear public process for amendment and further development. But constitutional modifications can significantly change AI behavior and what the AI systems may therefore be used for. Everyday users, businesses, governments, and all other organizations need to trust that AI systems will behave predictably and stably in order to plan for a future involving AI. A lack of clear and predictable amendment processes will undermine that trust.

The AI constitutions also sit mostly independent from the kinds of external institutions used to guarantee constitutional fidelity and prevent abuses of power. Human constitutions often create governments that have internal and federal separation of powers, letting one part of government check illegal or harmful activity by another. And human governments are composed of many different people, each with different ambitions, who can counteract each other. Civil society operates as an overseer of government, and protests, activism, and voting let people resist and change policy they disagree with.

For the most part, AI constitutions lack any such structure. The companies are different from the AIs that they are creating, and the AIs do not always act according to company directives or in company interests. But mostly they are simply supposed to do what the companies want them to do. At present, the AI constitutions are not integrated with external institutions that could interpret, amend, or evaluate the extent to which they are working, and the companies do not have a real internal separation of powers. Of course, AI systems operate in the context of law and regulation, and outside forces like tort liability will eventually affect how their constitutions are written. Someday, governments might demand oversight of AI constitutions, raising a host of new and difficult political questions. Existing external checks will shape the AI constitutions, but we should also look to design new and better checking institutions that are suited to frontier AI.

Like other constitutions, the AI constitutions can be improved, made more legitimate and representative, and better integrated with the foundations of a free and good society.

Constitutional makers, constitutional models

The above arguments are just a sketch of why the documents that constitute and govern these frontier AI systems are real constitutions. A large part of the purpose of Model Constitution is to fill in that sketch, laying out what the AI constitutions are, what they are doing, and how they can and must be improved if we are to improve alignment. Over the next few months, we’ll be tackling issues of rights and responsibility, interpretation and ambiguity, and how to create something with enough power to be useful and constrain it enough to be safe. These building blocks will then be put together into a Model Constitution that is usable in training actual frontier AI systems, but that hopefully has many of the virtues of public deliberation and institutional integration that the company constitutions lack.

The goal of this project is to advance both the discourse and the science of alignment for the public good. We may fail—it may turn out that meaningful progress in alignment can only happen with the resources of a huge corporation or within the walls of a government, or simply that things move too quickly for this work to be useful. But the public good requires public participation and public purpose. Designing these new artificial intelligences and dictating what they can and cannot do, whom they can and cannot serve, and what our society looks like in their wake is not something that can be left to small private groups. It’s time to take this project as seriously as the constitutions deserve.

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Many of the problems we face here are fundamentally constitutional, having to do with the basic structure and pattern of life together. AI governance is both concerned with concrete risks to human safety and also with how to ensure that AI advances in a way that is broadly good, responsive to the democratic will, and protective of the basic liberties that let people find their own best ways to live, alone and together. How do we distribute and balance power, so that catastrophic risks are prevented and so that no person, system, company, or party can predominate over others? What do governments or companies owe to citizens whose jobs are automated away and who then do not have the means to independently provide for themselves? Do AIs deserve membership in our political communities, or someday will they? If we do not make these decisions ourselves, they will be made for us, and often by people with personal rather than public interests at heart.

These days, we ask again “the important question, whether societies of men are really capable or not of establishing good government from reflection and choice, or whether they are forever destined to depend for their political constitutions on accident and force.” And maybe today our questions are harder than those confronted by those who came before us, with greater forces at work in the world and the very definition of society stretching in the face of new intelligences beginning to act and be alongside us. These are constitutional considerations that sit at the heart of who we are and are becoming, and they are the subject of Model Constitution.

Our questions have answers, if we have the wit and the will to find them. I plan to dedicate the first substantive posts of Model Constitution to one of the most literal interpretations of its title: looking at Claude’s Constitution and the OpenAI Model Spec, the closest things we have to constitutional texts in frontier AI and documents that “constitute” their models. We’ll be looking into what these texts are, how they work, and what they might tell us about how power operates in the world of frontier AI. Legal and political theory have lots of questions for them and even some answers, though fewer than we’d hope.

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To address constitutional AI governance, we must take the AI constitutions seriously, and ask what makes them legitimate; what rights they grant and with what remedies; who interprets and enforces them; if and how they interact with external institutions; and what they mean for the people and artificial intelligences they govern. Model Constitution will broaden to begin addressing a larger set of constitutional questions, having to do with how AI changes the distribution of power and the legitimacy of its exercise, the rights and obligations that we have and should have in this transformative time, and how existing institutions will engage with and affect AI and its governance.

Eventually, Model Constitution will host an actual model AI constitution, a document that is both a technical specification toward which to align advanced AI and a description of a political order through which to govern AI for broad benefit. The Model Constitution will be an exemplar and a point of comparison against which the constitutions of the AI companies can be considered. It will be able to interface with external checking and balancing institutions and integrate public deliberation in ways that company constitutions cannot. In collaboration with others, I hope to help advance the open science of technical AI governance through experiments run on the Model Constitution that align and then evaluate AI systems.

The Model Constitution will be mostly written from my perspective and with public engagement. I (and hopefully other interested people) will defend it and the views it takes. But the goal is not to provide a perfect target for alignment, only to provide a decent one that others can take as a model to help decide how to think about these difficult questions. I believe that through deliberation and research we can align AI for the public good, and I hope that this project will advance that program. Over time, I hope more people will join this effort, on both the political and technical sides, and I invite collaborators to reach out. Governance and alignment are both collective endeavors made up of particular perspectives, each person contributing what they know.

In that spirit, a brief word about myself and the vantage that I’ll be bringing to Model Constitution. I’m an Assistant Professor at the Johns Hopkins School of Government and Policy, focusing on the governance of frontier AI. I was trained at Harvard Law School, where among other things I became interested in constitutional theory. I stumbled upon DALL-E 2 and then GPT-3 in the antediluvian days of 2022, and I’ve spent quite a lot of time since then learning about these new technologies, how they work, and what they mean.

Before law school, I taught debate to middle and high schoolers across China. Most of my time there was during COVID, so I got a close and personal look at technological governance, what it can do, and also the various ways that people circumvent, flout, and frustrate the rules imposed on them. Those experiences and many others, of governing and being governed, of what a good community can be for its members, and of how people can choose to live well together, form the basis of my interest in the institutions that we use to build our lives.

So how shall we constitute this world that we are creating together?