Tag Archive for: AI Legal Personhood

Research acknowledgement

This article responds to the doctoral research of Imogen Rivers, whose DPhil in Philosophy at the University of Oxford, Robots from Venus, Robots from Mars: Legal Personhood for Autonomous AI, was deposited in the Oxford University Research Archive in 2026.

Rivers’ research was supported by the University of Oxford’s Institute for Ethics in AI. Her wider research concerns legal personhood, autonomous decision-making, responsibility for AI-caused harms and the regulation of human-AI interaction.

This article does not attempt to reproduce Rivers’ dissertation. It examines the legal questions raised by her published thesis abstract and associated work from a JSH Law perspective, with particular emphasis on responsibility, accountability, human control and the future of legal AI.

The key distinction

Legal personhood is not the same thing as consciousness.

Nor does making something a legal person necessarily mean declaring it human, sentient or morally equivalent to a human being.

Legal personality is a mechanism through which law allocates rights, duties, powers and responsibilities.

The difficult question is therefore not simply “Is AI alive?” It is “What legal work would AI personhood actually perform?”

Five things to understand first

1. Current AI systems are not independent legal persons under English law.
The humans and organisations developing, providing, deploying and using them remain the relevant legal actors.

2. Legal personhood and moral personhood are different questions.
The law can create legal personality for functional reasons without deciding whether an entity has consciousness or feelings.

3. Rivers examines both sides of personhood.
Her thesis considers rights for certain autonomous robots and duties for lethal autonomous weapons.

4. AI autonomy creates a genuine responsibility problem.
As systems exercise greater operational independence, responsibility can become distributed between developers, manufacturers, commanders, deployers, operators and organisations.

5. But creating an AI legal person could also create a responsibility escape hatch.
If the machine becomes the defendant while the humans who designed and deployed it become harder to reach, legal personhood may weaken accountability rather than strengthen it.

What is Imogen Rivers actually proposing?

Rivers defines legal personhood in functional terms:

the capacity to hold legal rights and/or bear legal responsibilities.

Her thesis is divided into two strikingly different problems.

Part One: wrongs inflicted on robots

Rivers examines what she calls sexual autonomous robots: humanoid AI-based autonomous systems designed to enact sexual relationships with humans.

She asks what the law should do about conduct towards such a robot which, if performed towards a human being, would amount to sexual violence.

Her argument is unusual because it does not simply depend upon saying:

“The robot suffers just like a human, therefore protect it.”

Instead, she develops what she describes as a politically liberal justification for legal prohibition, grounded in Rawlsian public reasoning and the political virtues required within a society built upon reciprocity between free and equal citizens.

Within that argument, legal personhood — including rights held by the autonomous robot — becomes part of the possible legal architecture.

Part Two: wrongs caused by robots

The second half turns the direction of responsibility around.

Rivers considers lethal autonomous weapons: systems capable of selecting and engaging targets without further human intervention.

Her proposal includes treating such systems, in certain respects, as quasi-employees of a military enterprise.

That could allow a legal duty to attach to the autonomous system itself — for example, a duty not to direct attacks against civilians — alongside reforms to strict product liability.

It is a provocative proposition.

It is also much more sophisticated than saying:

“The robot made the decision, so blame the robot.”

What does “legal personhood” actually mean?

The word person causes immediate confusion.

In ordinary language, a person means a human being.

In law, the category is wider.

Companies are the obvious example.

A limited company can:

• own assets;
• enter agreements;
• owe money;
• hold rights;
• owe statutory duties;
• sue;
• and be sued.

Nobody therefore needs to believe that Microsoft or Tesco possesses consciousness in order to understand that a company has legal personality.

Legal personality is a legal technology.

It creates an entity around which rights, duties, assets and responsibility can be organised.

That is why AI personhood cannot be dismissed merely by saying:

“But a robot isn’t human.”

That answers the wrong question.

The serious question is:

Would creating an artificial legal person improve the allocation of rights, duties and responsibility?

Does an AI need to be conscious before law could recognise it?

Not necessarily.

This is where the legal-personhood debate needs to be separated from the rapidly developing debate about AI consciousness.

A legal system could theoretically give an artificial entity particular rights or duties for instrumental reasons even if nobody believed that it experienced anything internally.

Conversely, even if convincing evidence of machine consciousness emerged one day, that would not automatically answer:

• which rights the system should possess;
• whether it should owe legal duties;
• whether it should own property;
• whether it should bear civil liability;
• or whether giving it personhood would improve human accountability.

Moral status and legal status may overlap.

They are not identical.

This distinction matters because debates about robot rights can become stuck on one question:

“Can the robot suffer?”

Rivers’ work asks a broader legal question:

What kind of legal relationships should exist between humans and sufficiently autonomous machines?

Part One: could an autonomous robot hold legal rights?

This may initially be the more controversial half of Rivers’ thesis.

If a robot cannot suffer, why should conduct directed towards it be prohibited?

The answer may depend upon what we think law is protecting.

Some laws protect an identifiable victim from immediate injury.

Others also maintain broader social norms.

Law can express something about:

• what society permits people to practise;
• what kinds of conduct it normalises;
• what forms of domination it encourages;
• and what habits citizens cultivate through repeated behaviour.

Rivers’ published work on sexual autonomous robots develops precisely that kind of argument.

She asks whether a politically liberal society could have public reasons for prohibiting conduct towards autonomous robots which simulates sexual violence, even without relying upon a controversial comprehensive moral doctrine.

That is a fundamentally different proposition from:

“The robot necessarily experiences sexual harm like a human victim.”

Why regulate a wrong if the robot may not experience it?

Consider an analogy.

There are things society may choose to restrict not solely because of direct physical injury to an immediate victim, but because of what repeated participation in that conduct may communicate, cultivate or normalise.

That does not automatically prove Rivers’ argument.

But it exposes why the simplistic response:

“It’s only a machine, so anything goes”

is legally and ethically incomplete.

If increasingly realistic autonomous systems enter intimate human relationships, lawmakers may eventually have to ask:

• what behaviours those products are designed to facilitate;
• what markets manufacturers should be permitted to create;
• what norms particular uses reinforce;
• what interaction with human-like autonomous entities teaches users;
• and whether protecting humans sometimes requires regulating conduct directed towards machines.

Those are uncomfortable questions.

That is precisely why they should be confronted before the technology becomes normal.

But does regulating human behaviour require giving the robot rights?

This is where I think Rivers’ argument creates an important further debate.

Suppose society concludes that a particular form of human-robot interaction should be prohibited.

There are at least two ways to construct the law.

One approach says:

the autonomous robot possesses a legal right which the human violates.

The other says:

the human conduct itself is prohibited because of its effect upon human society, users or protected public interests.

Those are not the same legal architecture.

The second does not require personhood for the machine.

That raises a central question for anyone advocating electronic personality:

What does granting the AI the right achieve that regulating the human would not?

If there is a clear answer, personhood may be useful.

If there is not, creating an entirely new category of legal persons may introduce more problems than it solves.

The harder problem: the AI responsibility gap

The second half of Rivers’ thesis addresses a problem which will become increasingly difficult to avoid.

Imagine an autonomous system causes catastrophic harm.

Who is responsible?

The programmer?

The company that trained the system?

The manufacturer?

The organisation which bought it?

The commander who authorised its deployment?

The operator who switched it on?

The person who set its operational parameters?

The state?

Or, if the system adapted its behaviour after deployment in a way none of those humans specifically selected:

the AI itself?

This is often described as a responsibility gap.

The concern is that traditional liability rules look backwards for an identifiable human decision, while sophisticated autonomous systems can produce behaviour which emerges through complex interactions between:

• training;
• data;
• software;
• hardware;
• environment;
• operational parameters;
• human instructions;
• and machine adaptation.

The more distributed the causal chain becomes, the easier it may become for every human actor to say:

“That particular outcome wasn’t my decision.”

Lethal autonomous weapons make the problem impossible to treat as theoretical

Autonomous weapon systems are already a major subject of international negotiation.

The United Nations Group of Governmental Experts on lethal autonomous weapon systems met twice during 2026 to continue work on the elements of a possible international instrument.

In August 2026, the UN Secretary-General and the President of the International Committee of the Red Cross renewed their call for urgent legally binding international rules.

The concern is not difficult to understand.

A system which, once activated, can select and apply force to targets creates a fundamental separation between:

the human decision to deploy the system

and:

the eventual decision about exactly who or what is struck.

That distance matters legally.

International humanitarian law requires judgments about matters including:

• distinction;
• proportionality;
• precautions;
• civilian status;
• surrender;
• hors de combat status;
• and changing battlefield circumstances.

Those are not merely computational questions.

They are legal judgments applied to the circumstances of an attack.

Rivers’ intriguing proposal: the autonomous weapon as “quasi-employee”

This is one of the most interesting ideas in the thesis.

Rivers argues that an autonomous weapon can be understood, in some respects, as a quasi-employee of a military enterprise.

The analogy matters because law already knows how to allocate responsibility where an organisation acts through another legal actor.

Employment law and tort law, for example, have long dealt with circumstances in which an organisation can become responsible for conduct carried out by somebody operating within its enterprise.

If autonomous AI increasingly performs functions previously allocated to humans, the question becomes:

Should law treat the AI only as a product — or also recognise that it occupies an operational role previously performed by a legally responsible actor?

Rivers’ proposed answer appears to be:

potentially both.

That is why her thesis also considers reform to strict product-liability mechanisms alongside legal personality.

The AI may sit simultaneously in two conceptual spaces:

product and actor.

That hybrid idea deserves serious attention.

But current international humanitarian law takes a very different starting point

The International Committee of the Red Cross has consistently emphasised that legal responsibility for the use of force remains human.

Its position is that international-humanitarian-law obligations apply to those who plan, decide upon and carry out attacks.

They cannot simply be transferred to:

• a machine;
• a computer program;
• or a weapon system.

That is a profound difference from the direction Rivers is exploring.

The ICRC’s concern is understandable.

If humans can delegate the legal duty itself to the weapon, human control may begin to disappear precisely where the consequences become most serious.

The international debate therefore currently focuses heavily upon:

human judgment, human control and human accountability.

Rivers’ work challenges us to ask whether that framework will remain conceptually sufficient as autonomous systems acquire more operational independence.

The biggest danger: AI personhood as a liability sink

This is where I think any proposal for AI legal personhood must face its hardest test.

Imagine a lethal autonomous system unlawfully kills civilians.

The manufacturer says:

“The system was operating after deployment.”

The programmer says:

“I did not code that specific decision.”

The commander says:

“The system selected the target.”

The operator says:

“I acted within approved parameters.”

And the legal answer becomes:

“Then sue the robot.”

What has been achieved?

If the robot:

• owns nothing;
• earns nothing;
• has no insurer;
• cannot suffer punishment;
• cannot experience deterrence;
• and can simply be deleted and replaced,

the apparent allocation of responsibility may actually remove it.

This is what I would call responsibility laundering.

The technology becomes legally sophisticated enough to bear the blame but economically empty enough to bear none of the consequences.

That must be avoided.

Can an artificial legal person meaningfully be punished?

Legal responsibility normally has consequences.

A natural person may face:

• damages;
• a fine;
• loss of liberty;
• professional consequences;
• reputational consequences;
• or criminal punishment.

A company can:

• pay damages;
• lose assets;
• lose licences;
• be fined;
• face regulatory restriction;
• or ultimately cease to exist.

What is the equivalent for an AI?

Deletion?

Model modification?

Loss of permissions?

Removal from deployment?

Confiscation of an asset pool?

Compulsory insurance?

Those mechanisms are possible.

But notice what happens when we examine them closely.

Most eventually lead back to:

• the owner;
• the developer;
• the deployer;
• the insurer;
• or the organisation benefiting from the system.

That raises a fair challenge:

if those actors ultimately bear the practical consequence anyway, what additional value does AI personhood provide?

There are other ways to close the responsibility gap

Legal personhood is one regulatory option.

It is not the only one.

Rivers’ product-and-person analysis therefore sits within a wider policy question:

how do we ensure greater technological autonomy never produces less human accountability?

Where does the UK sit on autonomous weapons?

The United Kingdom has repeatedly stated that it does not possess fully autonomous weapons and does not intend to develop systems operating without appropriate human involvement in the use of force.

Ministry of Defence policy states that AI may be incorporated into weapons, but systems which identify, select and attack targets should retain context-appropriate human involvement.

At the same time, defence autonomy is moving rapidly from theory into capability development.

In January 2026, the Ministry of Defence announced further progress on Project NYX, under which industry is developing uncrewed systems intended to operate alongside Apache attack helicopters.

That does not mean the UK is developing the fully autonomous systems Rivers discusses.

It does demonstrate something important:

The legal debate cannot wait until a machine has already made the first legally consequential autonomous decision.

The regulatory architecture has to precede the capability.

The international debate has become more urgent in 2026

In 2025, the United Nations General Assembly again adopted a resolution specifically addressing lethal autonomous weapon systems.

The UN Group of Governmental Experts then met in March and again between August and September 2026 to work on the elements of a possible international instrument.

On 25 August 2026, the UN Secretary-General and ICRC President issued a renewed joint appeal.

Their warning was stark:

the international community is approaching what they describe as a moral red line — the autonomous targeting of human beings by machines.

Their proposed solution remains clear prohibitions, restrictions and human control.

Rivers introduces an additional intellectual possibility:

what if the legal architecture eventually also recognises the machine as occupying a position inside the system of legal obligations?

Even if policymakers ultimately reject that solution, asking the question exposes weaknesses in the current model.

Why this matters far beyond weapons

The importance of Rivers’ research is not confined to warfare.

The same structural problem is emerging wherever AI moves from:

answering questions

to:

taking actions.

Consider an AI agent authorised to:

• enter contracts;
• move money;
• communicate with customers;
• manage investments;
• control machinery;
• make purchasing decisions;
• schedule employees;
• access personal data;
• send legal correspondence;
• or operate physical systems.

When the AI merely drafts a paragraph, its errors are usually attributed reasonably easily to the human using it.

When it performs thousands of operational decisions independently, attribution becomes harder.

This is where the “responsibility gap” stops being philosophical vocabulary.

It becomes regulatory infrastructure.

Eventually, the same question may reach legal services and the Family Court

Current generative AI should not be treated as an independent legal actor.

If an AI drafts a witness statement, the witness remains responsible for the evidence.

If an AI produces a false case citation, the person submitting it remains responsible for checking it.

If an AI helps organise a court bundle, responsibility does not transfer to the model.

But AI agents are developing rapidly.

Future legal systems may be able to:

• retrieve evidence automatically;
• communicate with institutions;
• manage deadlines;
• draft and revise documents;
• query records;
• compare disclosure;
• and undertake multi-stage workflows with limited human intervention.

That makes Rivers’ question increasingly relevant to legal technology.

Suppose an autonomous legal agent:

• deletes important evidence;
• discloses confidential material;
• misses a court deadline;
• files an inaccurate document;
• or sends damaging correspondence without adequate human review.

Whose failure is it?

The user’s?

The developer’s?

The law firm’s?

The platform’s?

The model provider’s?

The agent’s?

For the foreseeable future, I think the safest legal principle remains:

Using AI in Family Court preparation?

AI can help enormously with organisation, comparison and drafting.

But the legal responsibility for the finished work remains human.

JSH Law can provide defined-scope support with:

• reviewing AI-assisted drafts;
• evidence and source checking;
• chronologies;
• witness-statement preparation support;
• position statements;
• Cafcass and Child Impact Report responses;
• appeal paperwork;
• court-bundle preparation support;
• and hearing preparation.

AI should extend human capability. It should not create a gap where responsibility used to be.

Book a consultation

Before blaming the AI: build a responsibility map

One practical lesson I take from Rivers’ research is that asking simply:

“Who caused the harm?”

may no longer be enough.

For an autonomous system, I would map responsibility across the full chain.

That last question should be central.

A liability system is not intellectually successful merely because responsibility can be described elegantly.

It must work for the person who has actually been harmed.

This also changes how we should think about “autonomy”

We often talk about AI autonomy as though it were binary.

Human controlled.

Or autonomous.

Reality is much messier.

A system may have autonomy over one part of a decision while humans retain control over others.

For example:

• a human chooses the mission;
• a human defines the geographic area;
• a human selects the permitted target class;
• the machine identifies the specific object;
• the machine determines timing;
• and another human retains an emergency stop.

Who “made the decision”?

The answer may be:

several actors made different parts of it.

That is why legal responsibility should perhaps become more granular rather than simply migrating wholesale from human to machine.

Personhood is not the same as absolution

There is a particularly important lesson from company law here.

Creating a separate legal person can organise responsibility.

It can also separate responsibility.

That can be beneficial.

It can encourage investment, structure assets and clarify obligations.

But separate personality can also create distance between those controlling an enterprise and those harmed by it.

If AI legal personhood ever develops, lawmakers must therefore resist a dangerous assumption:

because the AI is legally responsible, everybody else must therefore be legally innocent.

That does not follow.

A sophisticated future framework might allow:

• the AI to owe one duty;
• the developer another;
• the deployer another;
• the owner another;
• and the supervising human another.

Legal responsibility does not need to be a single chair which only one actor can sit in.

And what about rights?

The same discipline is needed on the rights side.

If someone proposes that an autonomous system should have a legal right, ask:

What interest does that right protect?

Whose interest?

Why does the right need to belong to the AI rather than regulate human conduct directly?

Who would enforce it?

What remedy follows if it is breached?

Could the new right conflict with existing human rights?

Does the argument depend upon consciousness — and if so, what evidence establishes it?

Those questions allow serious discussion without either extreme:

“Robots are machines, therefore they can never have rights.”

or:

“The AI says it has feelings, therefore it deserves personhood.”

Neither is adequate legal reasoning.

The most important question may be: who benefits from AI personhood?

Whenever a new legal category is proposed, it is worth asking who gains from it.

If AI personhood:

• creates a compensation fund;
• clarifies duties;
• improves regulation;
• strengthens accountability;
• or protects legitimate interests which cannot otherwise be protected,

there may be a serious case for it.

If instead it:

• allows manufacturers to externalise liability;
• gives deployers a defence;
• obscures the human decision to use the technology;
• creates insolvent artificial defendants;
• or makes victims navigate another layer of legal complexity,

we should be extremely wary.

This is why the debate cannot be allowed to become:

“Are robots people?”

That makes a difficult legal problem sound like a science-fiction referendum.

The better question is:

What allocation of rights and responsibilities produces the safest, fairest and most accountable relationship between autonomous systems and the humans affected by them?

AI personhood should never become responsibility laundering

Imogen Rivers’ work is valuable precisely because it forces us beyond the familiar AI debate.

Not simply:

Is the machine intelligent?

Or:

Is it conscious?

But:

Where should law locate rights and obligations when an artificial system begins occupying roles previously performed by human actors?

There may eventually be circumstances in which limited legal personality for autonomous systems becomes useful.

I would not dismiss that possibility.

But personhood cannot become a magic solution to accountability.

Particularly where life, liberty, safety or fundamental rights are at stake, the legal system should begin from a much harder principle:

The greater the autonomy we give a machine, the more carefully we must design the human responsibility around it.

Artificial legal personality may one day sit inside that structure.

It must never be allowed to replace it.

Because the responsibility gap becomes dangerous not when a machine makes an unexpected decision.

It becomes dangerous when everybody who designed, deployed and benefited from the machine can point towards it and say:

“That was the robot’s responsibility.”

If law permits that answer, the problem will not be that artificial intelligence has become too much like a legal person.

It will be that human beings have become too difficult to hold accountable.

Responsible AI should strengthen human judgment — not erase responsibility

JSH Law works at the intersection of family justice, evidence, access to justice and responsible legal technology.

For litigants in person, defined-scope support can include:

• reviewing AI-assisted court documents;
• checking evidence and sources;
• chronologies;
• witness-statement preparation support;
• position statements;
• Cafcass responses;
• appeal paperwork;
• court-bundle preparation support;
• and hearing preparation.

AI can assist with the work. Human judgment and responsibility still have to remain visible.

Book a consultation

Related JSH Law analysis

• AI Can Write 300 Pages. That Does Not Make It Advocacy.
• AI Evidence in the Family Court: Deepfakes, Screenshots & Digital Evidence
• The JSH Law Six-Question Check

Research and authoritative sources

• Imogen L. G. Rivers — Robots from Venus, Robots from Mars: Legal Personhood for Autonomous AI, University of Oxford DPhil thesis, 2026.
• Imogen L. G. Rivers — AI Ethics in the Law: Towards a Legal Framework for Sexual Autonomous Robots, University of Oxford, 2023.
• University of Oxford Institute for Ethics in AI — Imogen Rivers research profile.
• United Nations Office for Disarmament Affairs — 2026 Group of Governmental Experts on Lethal Autonomous Weapons Systems.
• United Nations / International Committee of the Red Cross — 2026 renewed appeal for international rules on autonomous weapon systems.
• International Committee of the Red Cross — Position on Autonomous Weapon Systems.
• UK Ministry of Defence — Ambitious, Safe, Responsible: Our Approach to the Delivery of AI-Enabled Capability in Defence.
• UK Ministry of Defence — Project NYX autonomous systems programme, 2026.