AI Slop, Costs and Litigants in Person: Should Courts Sanction Bad AI Use?

The JSH Law position

The problem is not AI-generated text.

The problem is unverified, disproportionate or irrelevant material being transferred from the machine to the court without sufficient human judgment.

If you file it, you remain responsible for it. But sanctions should respond to unreasonable conduct — not merely to the fact that an unrepresented person used technology to help them participate.

Seven things to know first

1. “AI slop” is a real procedural problem.
Generative AI can produce huge quantities of fluent, repetitive and apparently sophisticated legal material almost instantly.

2. Cheap production does not mean zero cost.
The burden may simply move to the other party, their lawyers, court staff, judges and the taxpayer.

3. The person filing the document remains responsible.
“The AI wrote it” does not excuse fabricated authorities, inaccurate evidence, irrelevance or failure to comply with a court order.

4. Sir Robert Buckland is not proposing automatic punishment for AI-using litigants in person.
He expressly distinguishes uninformed use from persistent or irresponsible conduct.

5. The Family Court is not the ordinary civil costs regime.
Children proceedings have a longstanding general practice against costs orders, subject to the court’s discretion in exceptional cases involving unreasonable or reprehensible conduct.

6. The Civil Justice Council is already looking closely at litigants in person.
Its June 2026 update identifies litigants in person, witness statements and expert evidence as areas requiring further consideration.

7. Good use of AI should often produce less material, not more.
The best legal use of AI is often subtraction: finding the central issue, removing duplication and making the evidence easier to understand.

What exactly is “AI slop”?

The phrase is inelegant.

But the problem it describes is real.

In his September 2026 address to the Costs Lawyers Conference, Sir Robert Buckland used the expression to describe the production of large quantities of superficially impressive but unnecessary legal material using generative AI.

That might include:

• overlong pleadings;
• repetitive witness statements;
• generic legal submissions;
• dozens of weak grounds of challenge;
• irrelevant authorities;
• multiple documents covering the same issue;
• fabricated case citations;
• quotations which the cited judgment does not contain;
• or lengthy arguments which have no material bearing on what the court must decide.

But the important point is this:

the defining feature is not that AI was involved.

A concise, accurate and relevant position statement does not become “slop” simply because AI assisted with its structure.

Equally, a 40-page repetitive submission is not transformed into good advocacy merely because a human typed every word.

The real failure occurs when generation replaces judgment.

What Sir Robert Buckland actually said

The full speech is considerably more nuanced than the shorthand appearing on social media.

Buckland’s starting point is that AI itself is not the enemy.

He expressly recognises that it can:

• help a litigant understand procedural rules;
• assist with research;
• identify patterns across large bodies of material;
• help lawyers organise information;
• and potentially reduce the cost of some legal services.

His distinction is between:

using AI to assist judgment

and:

using AI instead of exercising judgment.

That is an important distinction.

He also proposes a straightforward principle:

If you put material before the court, responsibility for that material remains yours.

AI does not become an intermediary which absorbs responsibility.

If a submission contains an authority which does not exist, the problem remains.

If the facts have been misstated, the problem remains.

If the document ignores a page limit, the problem remains.

If somebody files 100 pages to make a point which reasonably required five, the burden imposed on everyone else does not disappear merely because a machine generated the excess.

AI has changed the economics of litigation

This is, in my view, the strongest part of Buckland’s analysis.

Historically, legal prolixity had a natural brake.

Someone had to produce the words.

A lawyer’s time cost money.

Even a litigant in person had to spend hours producing a lengthy document manually.

Generative AI changes that calculation.

A person can now generate in minutes:

• a pleading;
• a witness statement;
• a chronology;
• a skeleton argument;
• a list of authorities;
• a response;
• a reply;
• and then a reply to the reply.

The marginal cost of production may be almost nothing.

But the consumption cost remains.

Another party may have to pay a lawyer to read it.

Every authority may need checking.

The court must establish whether factual propositions are supported.

Judicial time is consumed identifying the few points which actually matter.

Court staff process the material.

Hearings become longer.

Bundles become larger.

Deadlines become harder to manage.

The cost has not disappeared.

It has been externalised.

Hancox: when 132,000 words obscure rather than assist

The September 2026 Employment Appeal Tribunal decision in Hancox v Sutherland & Others [2026] EAT 139 provides an extraordinary example.

The appellant, acting in person, filed a skeleton argument created using ChatGPT.

It was approximately:

300 pages and almost 132,000 words.

The EAT said the document served to obscure rather than illuminate the case.

It did not comply with the applicable Practice Direction.

The appellant himself accepted at the hearing that much of it lacked credibility, and ultimately it was not relied upon.

With assistance from counsel, the actual argument before the EAT was reduced to a focused ground.

That contrast is instructive.

The machine was capable of producing 132,000 words.

The case did not require 132,000 words.

The EAT emphasised that anyone using generative AI must take personal responsibility for ensuring that court documents:

• comply with applicable procedural rules;
• are checked as thoroughly as reasonably possible for factual, evidential and legal accuracy;
• do not mislead the court;
• contain only relevant points;
• focus on the central or strongest arguments;
• and avoid undue repetition.

That is not anti-AI.

It is ordinary litigation discipline applied to a new tool.

Read the fuller JSH Law analysis: AI Can Write 300 Pages. That Does Not Make It Advocacy.

Could irresponsible AI use lead to a civil costs order?

Potentially, yes.

Buckland’s point is that the ordinary civil courts do not necessarily need a special new rule labelled:

“Costs caused by artificial intelligence.”

CPR Part 44 already permits the court to consider the conduct of the parties when deciding costs.

Relevant conduct includes:

• whether it was reasonable to raise, pursue or contest a particular allegation or issue; and
• the manner in which a party pursued or defended the case or a particular issue.

AI-generated conduct is still conduct.

The relevant question therefore remains:

Was it reasonable?

Imagine a litigant is told:

• a cited case does not exist;
• their argument falls outside the issues ordered for determination;
• their skeleton must not exceed 20 pages;
• and repeated material should not be filed.

If they then deliberately use AI to generate another 80 pages containing the same rejected material, the issue is not really whether ChatGPT was involved.

The issue is procedural conduct after warning.

Could the same thing happen in the Family Court?

Yes — but this is where the distinction between civil litigation and family proceedings becomes essential.

Under FPR 28.1:

the court may at any time make such order as to costs as it thinks just.

FPR 28.2 also applies substantial parts of CPR Parts 44, 46 and 47 to family proceedings, subject to specified modifications and the special regime for financial remedy proceedings.

But children proceedings have an important and longstanding approach of their own.

In Re E (Children: Costs) [2025] EWCA Civ 183, the Court of Appeal restated that there is a general practice of not awarding costs against a party in family proceedings concerning children.

The court nevertheless retains discretion in exceptional circumstances.

Those circumstances can include unreasonable or reprehensible litigation conduct.

The principle applies in both public and private law children proceedings.

That distinction matters enormously.

A parent should not think:

“If I lose an allegation, I will automatically have to pay the other parent’s legal costs.”

That is not the position.

Nor should parents be discouraged from raising genuine safeguarding concerns because they fear an adverse costs order simply because a court ultimately reaches a different conclusion.

But there is equally no rule saying:

“Anything goes because this is a children case.”

Where litigation conduct becomes objectively unreasonable or reprehensible, costs remain within the court’s armoury.

There is, as yet, no need to invent an “AI costs doctrine” for children proceedings.

The existing principles are capable of responding to conduct if and when the facts justify it.

Litigants in person need a different conversation

This is the part of Buckland’s speech I think deserves particular emphasis.

He expressly rejects the equation:

“Litigant in person + AI = costs sanction.”

That would be both unfair and counterproductive.

People frequently represent themselves because:

• they cannot afford solicitors and counsel;
• they do not qualify for legal aid;
• they have exhausted available funds;
• they cannot find representation;
• or the economics of the case simply make full representation impossible.

In the Family Court they may also be trying to prepare documents while:

• separated from a child;
• experiencing domestic abuse or post-separation abuse;
• managing disability or neurodivergence;
• dealing with trauma;
• working around childcare;
• or facing a hearing they barely understand.

Generative AI can be genuinely useful in that situation.

It can explain unfamiliar terminology.

It can help organise hundreds of messages by date.

It can identify duplicated paragraphs.

It can convert a chaotic notebook into a provisional chronology.

It can suggest headings for a statement.

It can explain what a court order appears to require.

It can help someone formulate questions for professional advice.

That has genuine access-to-justice value.

So we need to distinguish between:

a person who does not yet understand the limits of the technology

and:

a person who knowingly persists in unreasonable litigation conduct after the problem has been identified.

Buckland’s example is useful.

A litigant who genuinely thinks an AI-generated authority is correct may need education and an opportunity to correct it.

A litigant who has been told the authority is fictitious and continues to rely upon it presents a different issue.

That distinction is fair.

There is another danger: “AI slop” could itself become a litigation weapon

Once a phrase enters legal culture, parties start using it against each other.

I can easily imagine future correspondence saying:

“The applicant’s statement is plainly AI slop and should be disregarded.”

Or:

“The respondent has apparently used ChatGPT to manufacture safeguarding allegations.”

That cannot become a substitute for answering the material.

In a high-conflict Family Court case, accusations about the other party’s AI use could easily become another layer of procedural warfare.

The proper questions are more disciplined:

• Is the factual assertion supported by evidence?
• Can its source be identified?
• Has an allegation been converted into a fact?
• Is the authority genuine?
• Does it actually support the proposition for which it is cited?
• Does the document comply with the court’s directions?
• Is the point relevant?
• Is the material proportionate?
• Is it repetitive?
• Has the author adopted and checked it?

If the answer to those questions is satisfactory, whether AI assisted with punctuation or structure may be of very little importance.

Focus on the defect.

Not the software.

The Civil Justice Council is already wrestling with exactly this distinction

In June 2026, the Civil Justice Council published an update on its work concerning AI in the preparation of court documents.

There was a strong degree of agreement that, for professional lawyers preparing pleadings, advocacy documents and skeleton arguments, additional AI-specific formal requirements are not currently necessary.

The reasoning is significant:

existing professional responsibility frameworks should generally be sufficient.

But the Working Group identified three areas requiring further attention:

• witness statements;
• expert evidence; and
• litigants in person.

Witness statements raise particular concerns because AI may reshape, embellish or subtly alter personal recollection.

Experts raise questions about methodology and transparency.

Litigants in person create a different problem:

how do you protect the integrity of court proceedings without depriving the people with least access to legal support of one of the tools which may help them participate?

That is the access-to-justice question at the heart of this debate.

Has AI made your Family Court document longer rather than clearer?

You may not need another 20 pages.

You may need somebody to identify which three pages actually matter.

JSH Law provides defined-scope support with:

• reviewing and reducing AI-assisted drafts;
• evidence organisation;
• chronologies;
• witness-statement preparation support;
• position statements;
• schedules of issues or allegations;
• Cafcass and Child Impact Report responses;
• appeal paperwork;
• court-bundle preparation support;
• source and authority checking;
• and hearing preparation.

The purpose is not to replace your evidence with AI. It is to make your real case easier for the court to understand.

Get help with your court documents

Good AI use and bad AI use can look completely different

Compare two workflows.

Workflow A: generation without judgment

A litigant types:

“Give me every legal argument I can make against the other parent.”

The model generates 30 arguments.

The litigant asks it to make each one stronger.

Then asks for case law.

Then asks it to expand the statement.

Then copies the result into Word.

Then files it.

Workflow B: AI-assisted human judgment

The litigant identifies the order and the issues the court must decide.

AI helps organise documents by date.

The litigant checks every date against the original record.

The model identifies repetitive sections.

The litigant removes them.

Possible legal authorities are checked against legislation, judgments or official procedural sources.

The final document is reduced to the strongest relevant points.

Every word is read.

The litigant understands it.

The litigant accepts responsibility for it.

Those are not remotely the same use of technology.

The first delegates judgment.

The second augments it.

The JSH Law responsible-AI filing standard

“Be careful with AI” is not practical guidance.

Before filing any AI-assisted court document, I would apply these eight checks.

If the answer to one of those questions is no, the problem is not that AI has failed to finish the job.

The human has not finished theirs.

The Family Procedure Rules already provide the right direction

Family procedure does not need the expression “AI slop” to explain what proportionate litigation looks like.

The overriding objective in FPR Part 1 requires cases to be dealt with justly, having regard to welfare issues.

That includes:

• dealing with cases expeditiously and fairly;
• acting proportionately to the nature, importance and complexity of the issues;
• keeping parties on an equal footing;
• saving expense;
• and allocating each case an appropriate share of finite court resources.

Parties are required to help the court further that objective.

Active case management expressly includes considering whether the likely benefit of a particular step justifies its cost and making use of technology.

That combination is important.

The rules do not say:

“Technology is dangerous.”

They effectively say:

Use court resources proportionately.

That is a technology-neutral principle which works remarkably well for generative AI.

What should courts do before reaching for costs?

For litigants in person especially, notice and clarity matter.

Someone who does not understand what is required is not necessarily in the same position as somebody who deliberately ignores repeated directions.

I would favour an escalating response.

This preserves a critical distinction:

lack of knowledge can sometimes be remedied by explanation.

Persistent unreasonable conduct after explanation is something else.

A Family Court example: when more allegations do not create a stronger case

Imagine a parent preparing for a child arrangements hearing.

The central issue is whether a particular communication arrangement is safe and workable.

The parent uploads three years of messages to an AI model and asks:

“Find every example showing that the other parent is coercively controlling.”

The system produces 147 alleged examples.

Some are significant.

Some are duplicates.

Some reflect ordinary disagreement.

Some contain no identified source.

Some are interpretations rather than facts.

Several repeat the same underlying incident.

The litigant files all 147.

The other parent responds to all 147.

Cafcass receives all 147.

The judge must work through all 147.

The central welfare issue becomes harder to see.

Now compare the alternative.

The AI is used to:

• identify dates;
• group repeated incidents;
• locate the original source;
• remove duplicates;
• separate objective event from interpretation;
• identify the handful of examples which genuinely demonstrate the alleged pattern;
• and organise those examples around the welfare issue the court must decide.

The technology is the same.

The difference is the human instruction and the human judgment applied afterwards.

AI should help the court see the pattern. It should not bury the court underneath every event which might conceivably fit it.

The irony: good legal AI should often make documents shorter

This is the point I think much of the discussion misses.

If AI is being used well, one of its great strengths should be reduction.

It can identify duplication.

It can group related evidence.

It can compress a chronology.

It can find passages which repeat the same proposition.

It can ask which paragraph does not connect to the issues.

It can turn 4,000 messages into a usable index before a human decides which matter.

It can help someone locate the six documents which actually prove the point.

And AI is not the only source of legal “slop”

There is another point worth making.

Overlong, unfocused and repetitive legal documents existed before generative AI.

Lawyers produce them too.

So do represented parties.

Humans have always:

• over-argued weak points;
• cited excessive authorities;
• repeated evidence;
• produced bloated correspondence;
• and mistaken volume for persuasion.

AI has not invented poor judgment.

It has made poor judgment dramatically easier to scale.

That means courts should resist an unhelpful divide in which:

human prolixity is advocacy

while:

AI-assisted prolixity is misconduct.

The procedural standard should be the same.

Is it accurate?

Is it relevant?

Is it proportionate?

Does it comply?

Does it assist the court?

Where should this debate go next?

I do not think the justice system needs a war on AI-assisted litigants.

Nor can it ignore what generative AI has done to the economics of litigation.

The right direction is technology-neutral responsibility.

If a solicitor files a fictitious authority, that is a problem.

If a litigant in person files the same fictitious authority after using AI, that is still a problem.

If a lawyer submits 80 pages contrary to a 20-page limit, the court can respond.

If an AI-assisted litigant does the same, the rule does not vanish.

But neither should responsible AI assistance be stigmatised.

That is the distinction any future guidance should preserve.

The answer to AI slop is not less access to justice

Sir Robert Buckland is right about the underlying economic change.

The court cannot operate on the fiction that an additional 50 pages creates no cost merely because generating them cost the litigant nothing.

But costs sanctions are only one part of the answer.

Particularly in family justice, we must preserve something equally important:

the ability of ordinary people to participate meaningfully in proceedings which may determine their relationship with their children.

AI can help with that.

Sometimes enormously.

The challenge is to teach people to use it as:

• an organiser;
• an editor;
• a comparison tool;
• a research assistant;
• and a way of reducing procedural overwhelm.

Not as an inexhaustible advocate which assumes every conceivable argument deserves to be made.

AI should lower the cost of understanding a case. It should not raise the cost of everyone else having to understand what the AI produced.

That is the line I think the courts should hold.

Used AI to help prepare your Family Court documents?

If the draft is becoming longer rather than clearer, stop adding.

JSH Law can provide defined-scope support with:

• reviewing and reducing AI-assisted documents;
• chronologies;
• witness-statement preparation support;
• position statements;
• schedules and evidence maps;
• Cafcass responses;
• appeal paperwork;
• court bundles;
• source checking;
• and hearing preparation.

The aim is simple: keep what assists the court. Remove what does not.

Book a consultation

Related JSH Law analysis

• AI Can Write 300 Pages. That Does Not Make It Advocacy.
• AI Can State Facts. Can It Tell the Truth? Why the Difference Matters in Law
• Can AI Feel Pain? What the “Pain Axis” Study Really Means for Human Safety and Legal AI
• AI Evidence in the Family Court: Deepfakes, Screenshots & Digital Evidence
• The JSH Law Six-Question Check

Primary and authoritative sources

• Sir Robert Buckland KC — The Price of Justice: Civil Costs, Litigation Funding and the AI Problem, 24 September 2026
• Hancox v Sutherland & Others [2026] EAT 139
• Civil Justice Council — Use of AI in Preparing Court Documents
• Family Procedure Rules Part 28 — Costs
• Family Procedure Rules Part 1 — Overriding Objective
• Re E (Children: Costs) [2025] EWCA Civ 183