News Archives | TheFormTool

ABA Law Technology Today Publishes First Article in Professional Infrastructure Series

The Team at TheFormTool — Fri, 24 Jul 2026 19:59:23 +0000

ABA Law Technology Today Publishes First Article in Professional Infrastructure Series

ABA Law Technology Today has published the first article in a four-part series from TheFormTool on legal technology, professional responsibility, and control.

The article, “Expanding Fault Lines in Legal Technology,” examines a growing tension in legal technology: the profession’s increasing dependence on systems optimized for convenience, scale, and automation, even when those systems may be difficult for lawyers and firms to fully understand, supervise, or control.

The series is not an argument against artificial intelligence, cloud systems, or legal technology modernization. The profession has always evolved with technology, and it should continue to do so.

The question is different:

Are lawyers still meaningfully directing the systems on which they rely, or are they increasingly becoming passengers inside them?

From the article:

“The issue is not whether technology should assist professionals; it’s whether professionals remain capable of meaningfully controlling the systems on which they increasingly rely. That distinction may become one of the defining professional questions of the next decade.”

The first article traces the evolution from heavy enterprise automation systems to cloud-based convenience platforms and now to AI-driven systems that increasingly participate in drafting, summarizing, recommending, and analyzing professional work.

It introduces a distinction between convenience infrastructure and professional infrastructure. Convenience infrastructure is optimized for speed, accessibility, integration, and scale. Professional infrastructure is optimized for accountability, inspectability, reproducibility, manageability, and control.

That distinction matters because not every legal task can tolerate the same level of uncertainty. Marketing copy, scheduling, and general research assistance may tolerate substantial automation variability. Privileged client drafting, court filings, and formal legal analysis may require much more direct professional oversight.

This article was originally published by the American Bar Association’s Law Practice Division’s blog, Law Technology Today.

Read the full article at ABA Law Technology Today: https://www.americanbar.org/groups/law_practice/resources/law-technology-today/2026/expanding-fault-lines-in-legal-technology/

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Large forms suddenly slowed dramatically after recent Microsoft updates

The Team at TheFormTool — Wed, 08 Apr 2026 19:45:15 +0000

Large forms suddenly slowed dramatically after recent Microsoft updates

Here’s how to fix it.

Several customers recently reported significantly slower form processing times following Microsoft updates to Word and Windows.
The affected forms ranged from 12,000 words with 1,500 variables to 90,000 words with more than 2,400 variables. In some cases, processing times increased from 15–20 minutes to over an hour.

Enabling all functions of the Speedy Fill feature included in current versions of our software reduced those times to under five minutes.

Even smaller forms may benefit from a noticeable speed increase. We recommend all users routinely enable all Speedy Fill features.

—

“We use Doxserá daily in our practice, running at least fifteen forms per client, and the decrease in fill time has been phenomenal.”

“What used to take me 2 hours now takes less than 10 minutes.”

—

Doxserá is designed to handle large, complex documents efficiently—without requiring specialized infrastructure or external systems.

If you have any questions or would like help enabling these settings, just let us know. service@theformtool.wp.urdemo.website

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The Lawyer-In-The-Loop (LITL™): The New Professional Standard for AI in Legal Work

The Team at TheFormTool — Mon, 17 Nov 2025 21:52:43 +0000

The Lawyer-In-The-Loop (LITL): The New Professional Standard for AI in Legal Work

Why responsible AI in law requires a lawyer at the center—not the perimeter.

Introduction

For more than a century, every advance in legal technology—from dictation machines to computer-assisted research—has shifted how lawyers work, but never broached the essential question of who is responsible. Artificial intelligence challenges that status in new ways. For the first time, technology is not just storing or transmitting information but generating it, evaluating it, and too-often inventing it.

Across the country, courts are sounding alarms. Lawyers have now filed briefs with nonexistent cases, fabricated citations, and imaginary quotations—each attributed to artificial intelligence. Judges are imposing sanctions, disqualifying counsel, and referring cases to disciplinary authorities. This is not theoretical; it is happening in real courtrooms. Worse, it’s likely happening in some of the millions of legal events outside the courtroom not subject to reviews by opposing counsel and judges? How many of those critically important documents are future land mines for the unsuspecting and unprotected?

At the same time, cloud-based legal drafting platforms are gathering vast troves of client information—names, facts, strategies, disputes—and using them to train systems, shape outputs, and, in some instances, build proprietary data assets.

Against this backdrop, a phrase has begun circulating in bar opinions, legal tech marketing, and industry discussions: lawyer in the loop.

But the term is unfortunately vague. Does it mean a lawyer glances at the final draft? That a human clicks “approve”? That an attorney occasionally reviews AI output?

The legal profession needs more than a slogan, more than relying on judges playing whack a mole to save the profession. It needs a standard.

That standard is LITL — Lawyer-In-The-Loop: a structured, ethically sound framework that preserves professional judgment, protects client confidentiality, and defines where AI fits—and where it doesn’t.

I. What Does “Lawyer-In-The-Loop” Really Mean?

Many AI companies invoke the phrase as a business model:

“We include a lawyer somewhere in the workflow.”

But ethics rules demand more than a workflow checkbox. They demand responsibility, supervision, and ownership.

A genuine Lawyer-In-The-Loop system requires that:

1. A lawyer remains responsible for all legal reasoning

AI may draft, summarize, or surface data—but legal judgment comes from a licensed professional. It is now and will continue to be beyond the ability of any computer model.

2. A lawyer validates all substantive statements

Because hallucinations are not just mistakes; in briefs they become fabrications.
Fabrications are misconduct. To an extent not widely recognized they are not caused by a fault, they are a feature of AI’s relationship with its customers.

3. A lawyer controls the data environment

AI that transmits client information into the cloud creates risks that lawyers cannot disclaim:

- Loss of privilege
- Loss of confidentiality
- Inadvertent disclosure
- Vendor access and data retention
- Future model training on client materials

4. A lawyer supervises the technology under Rule 5.3

Delegation to machines is still delegation. And delegation requires oversight.

LITL is not a marketing claim; it’s an ethical requirement.

II. Why AI in Law Requires LITL

Artificial intelligence excels at speed, pattern recognition, and text prediction. But it lacks:

- Legal judgment
- Contextual knowledge
- Duty of loyalty
- Ethical constraints
- Responsibility
- Accountability

Hallucinations are baked into model architecture.
They are not defects; they are features.

When used for research, summarization, translation, or document organization, AI can be highly productive—because any errors are still filtered through the lawyer.

But when used to generate legal analysis or draft documents without human supervision, it crosses a line.

The profession must therefore embrace a clear rule:

AI may assist. It may accelerate. It may enhance.
But AI may not replace the attorney’s judgment.
A lawyer must remain in the loop.

III. Confidentiality: The Hard Stop

Confidentiality problems are not solved by:

- Clicking “I agree”
- Relying on vendor assurances
- Hoping no one accesses the data

Cloud-based drafting tools—especially those that store client data on shared infrastructure—present structural risks:

1. Lawyers do not control the data

Third parties decide:
Where it lives.
How long it’s retained.
Who has access.
What it is used for.

2. Vendors often have contractual access that waives privilege

Buried in terms of service.

3. Future training of AI models is often permitted

Meaning confidential client material may become part of a system’s internal data representation.

4. Confidentiality is compromised even by encryption

Because encryption protects data in transit, not control, retention, or reuse.

5. Privilege is vulnerable to compelled disclosure

Cloud providers may be subject to subpoenas or government requests that bypass the attorney-client relationship entirely.

The profession cannot rely on hope or goodwill.
It must rely on control.

Offline document automation—like TheFormTool’s own software—provides that architectural control.
Cloud platforms cannot.

Thus confidentiality is not merely a risk; it is a bright-line rule.

IV. When Vendors Admit Their AI ‘Learns’ From User Data

In recent interviews, leaders of prominent AI-drafting startups have begun saying things like:

- “Our system gets better as lawyers use it.”
- “It continually improves based on interactions.”
- “It learns from the documents lawyers put into it.”

For venture capital, this is a selling point: user activity becomes training data, training data becomes a proprietary asset, and the product “improves itself.”

For lawyers, this should be an immediate red flag.

Under basic confidentiality principles, if an AI vendor claims:

1. It learns from user inputs,
2. It gets better because of what lawyers upload, or
3. Its model adapts based on real-world client documents,

then the vendor is telling you—plainly—that:

- Client information is being transmitted outside the lawyer’s control.
- Client data is being retained.
- Client material is influencing the model or its internal analytic pipelines.
- The platform, not the lawyer, controls the knowledge derived from client files.
- Privilege may be compromised by design, not accident.

Even if the vendor avoids the word “training,” any promise that the system “learns from users” necessarily means the platform captures some aspect of the content, metadata, patterns, or decisions lawyers make inside it. That is incompatible with the duty of confidentiality.

No court in the country would permit a paralegal to peruse client files and reuse that knowledge for other purposes. AI vendors are openly telling us their systems do exactly that.

This is why LITL is not simply a workflow model—it is a professional protection standard.
A Lawyer-In-The-Loop system requires:

- No external data retention
- No model training on client material
- No vendor access to client files
- No ambiguous “learning from interactions”

Without these guarantees, “lawyer in the loop” becomes marketing, not ethics.

LITL demands more.
It requires a lawyer to remain in control—not the model, not the vendor, and not the cloud.

V. The LITL Standard: What Lawyers Should Require

A true Lawyer-In-The-Loop system requires five non-negotiables:

1. Human Validation of All Legal Output

No AI-generated text is used without lawyer review.
No exceptions.

2. Human Ownership of Data

Client information never leaves the lawyer’s environment without informed consent.

3. Human Responsibility for Reasoning

AI does not “decide.” It predicts.
Only lawyers reason to the point of creating judgement.

4. Human Accountability to Clients and Courts

Responsibility cannot be outsourced to a model or platform.

5. Human Oversight of All Technology (Rule 5.3)

AI is supervised the same way lawyers supervise staff.

**VI. What AI Can Do Safely Under LITL**

AI can dramatically speed:

- Research synthesis
- Summaries
- Timelines
- Document review
- Internal document management
- Issue spotting (preliminary)
- Translation
- Structuring large sets of information

These are high-efficiency, low-risk uses—because the lawyer remains in the loop.

VII. Conclusion: LITL Is the Future of Responsible AI in Law

As AI becomes increasingly woven into legal workflows, the profession must draw a clear, ethical line:

**AI may assist lawyers, but may not replace them.
AI may accelerate work, but may not shoulder responsibility.
AI may draft, but may not decide.

A lawyer must remain in the loop. Always.**

LITL is not only the safest framework; it is the only framework consistent with our ethical duties—and with what clients deserve.

The post The Lawyer-In-The-Loop (LITL™): The New Professional Standard for AI in Legal Work appeared first on TheFormTool.

AI Is a Tool. Judgment Is a Duty.

The Team at TheFormTool — Sat, 15 Nov 2025 19:31:29 +0000

AI Is a Tool. Judgment Is a Duty.

AI can draft a clause; it can’t explain why it matters—or what it costs when it’s wrong. Our position is simple: every client deserves a Lawyer in the Loop.

We’re inviting Bar associations to partner on a 60-minute CLE: Evaluating AI for Legal Work—Ethics, Confidentiality, and Informed Use.

Real cases (hallucinations ≠ “minor typos”)
Privilege, confidentiality, and “no-cloud” compliance
A practical vendor checklist firms can use tomorrow

We’d like to hear from and help every Bar.

Bars: Host this CLE with us → email inquiry

Read about our solution, Lawyer in the Loop

The post AI Is a Tool. Judgment Is a Duty.  appeared first on TheFormTool.

The Judge, the Machine, and the Missing Lawyer

The Team at TheFormTool — Mon, 10 Nov 2025 19:40:59 +0000

The Judge, the Machine, and the Missing Lawyer

Why Mattox v. Product Innovations Research USA may mark the moment courts began defining Lawyer-in-the-Loop.

When federal judges invoke Rule 11(b), it’s never casual. That rule requires every lawyer who signs a pleading to certify that the filing rests on truth, evidence, and law—not invention.

In Mattox v. Product Innovations Research USA (W.D. Okla., Oct 22 2025), Judge Timothy DeGiusti confronted a violation on a scale that would have been unimaginable only a few years ago:

28 false or misleading citations
14 cases that did not exist
14 real authorities misquoted or distorted by AI-generated text

No malice was alleged. The problem, the court wrote, came from “a lawyer who used the technology to make his writing more persuasive.” The AI didn’t know better—but the lawyer should have.

The opinion avoids the overheated tone that often follows AI mishaps. Instead, Judge DeGiusti performed a lawyer’s audit: tracing every citation, documenting each fabrication, and recording precisely how unverified text entered the record. Then he did what the rules already require—he held the humans accountable.

“Machines don’t hold responsibility—people do.”

His opinion reads like a user manual for competence in the age of automation:

Control. The lawyer must remain in charge of process and output.
Validation. Every AI-generated statement must be checked against reliable sources.
Disclosure. Courts and opposing counsel are entitled to know when automation has influenced a filing.

The opinion’s tone is measured but unmistakable: technology may assist, but it cannot certify, explain, or defend reasoning. The duty of candor and accuracy remains personal, not programmable.

From Judicial Reasoning to Professional Rule

Judge DeGiusti’s analysis points toward the inevitable next step. Sanctioning misconduct after the fact is not enough. The profession needs a clear, affirmative standard before the next “hallucinated citation” reaches a docket.

That standard already has a name: Lawyer-in-the-Loop.

Lawyer-in-the-Loop would make explicit what Mattox implies—every AI-assisted document must have a responsible lawyer who is:

Informed about the system’s limits and data sources;
Accountable for factual and legal accuracy; and
Answerable for privilege, confidentiality, and ethical compliance.

The Real Solution

Courts like the one in Oklahoma are teaching the same lesson case by case: machines are tools, not practitioners. But that principle should not depend on judicial patience or sanctions after damage is done.

The bar should lead by codifying Lawyer-in-the-Loop as the modern expression of Rule 11(b): the lawyer’s personal signature on truth, reason, and responsibility—even when assisted by algorithms.

Every lawyer already promises that duty with each filing. Lawyer-in-the-Loop simply updates that promise for the age of AI.

Read the full opinion

See more about the intersection of AI and the practice of Law.

The post The Judge, the Machine, and the Missing Lawyer appeared first on TheFormTool.

When Word Loses Count: The Case for Sanity in Numbering

The Team at TheFormTool — Wed, 15 Oct 2025 18:33:15 +0000

When Word Loses Count: The Case for Sanity in Numbering

We thought Microsoft was fixing numbering in Word. 

Five years later, we checked… and Word numbering is still broken. 

So we’re fixing it again, with Snapnumbers.

If you’ve ever tried to number paragraphs in Microsoft Word, you already know the symptoms:  You apply numbers to a list and—without warning—your indents shift, your spacing changes, and your perfectly formatted outline suddenly looks like it went through a blender.

We’ve heard the laments. They come from every corner of the Word universe:

“Reverts unexpectedly.”

 “Not intuitive.” 

“Changes all my other numbering.”

Those are real comments from users on Microsoft’s own support forums, Stack Overflow, and Reddit. One frustrated user called it “Word’s longest-running unsolved mystery.” Another confessed, “I’ve spent more time fixing numbering than writing my entire report.”

Search for “Word numbering problem” and you’ll find decades of frustration — posts dating back to Word 97 and every version since. Microsoft has patched, renamed, and reorganized the feature half a dozen times, but the complaints keep coming. The underlying problem hasn’t changed: Word’s numbering system is built on a fragile foundation.

What Went Wrong: Numbering by Engineers

Word’s numbering system isn’t really a numbering system. It’s an engineering exercise.  Instead of treating numbers as characters—like letters on a page—Word ties them to styles and levels. Every number is part of a hidden hierarchy of outline templates and style definitions.

That approach is fine for programmers or for documents that never change.  But for anyone who writes, edits, or rearranges content, it’s a minefield. Move one numbered paragraph and the whole structure can collapse. Copy a list into a new document and the formatting mutates. Try to reset numbering, and Word may “helpfully” renumber everything—wrongly.

In short, Word’s numbering is designed for engineers, not everyday humans.

The Human Solution: Snapnumbers

That’s where Snapnumbers comes in.  Snapnumbers replaces Word’s numbering system entirely. It takes the logic back to basics—character-based numbering that stays exactly where you put it.

- One click to apply or adjust numbering
- Character-based design: not tied to styles or outlines
- Predictable behavior: copy, paste, move, or delete freely
- Instant feedback: what you see really is what you get

No mysterious levels. No cascading errors. No all-night formatting rescues.

It’s the numbering system Word should have built.

Real-World Relief

Snapnumbers isn’t theoretical. Thousands of users have relied on earlier versions for years—lawyers numbering clauses, accountants listing conditions, engineers organizing specifications, writers drafting reports.

One attorney told us:

“Word’s numbering used to terrify me. Snapnumbers fixed it in five minutes.”

Another user summed it up perfectly:

“It’s like Word’s numbering, but it actually works.”

When we gave up licensing of the original Snapnumbers years ago, we thought maybe Microsoft would eventually fix the problem. They didn’t. So we outright purchased Snapnumbers for ourselves and are doing it. Again.

What Makes It Different

Here’s how Snapnumbers compares to Word’s built-in tool:

	Word Numbering	Snapnumbers
Method	Style-based, outline-driven	Character-based, direct
Predictability	Fragile and dependent on templates	Stable and portable
Editing behavior	Reformatting can break numbering	Edits are local and safe
Ease of use	Multi-menu, multi-level setup	One click
Learning curve	Steep	None

The difference is immediate and visible. Snapnumbers makes documents feel solid again.

Because Sanity Is Worth Something

If you’ve ever spent an afternoon re-aligning subparagraphs or manually repairing cross-references, you already know how much sanity is worth.

Snapnumbers installs in seconds, works with every version of Word from 2010 forward, and costs less than lunch. It’s fast, private, and local—no internet connection, no cloud dependency, no risk to confidentiality.

Your paragraphs deserve better. 

Your nerves do too.

See a demo, believe your eyes, get Snapnumbers now →→

The post When Word Loses Count: The Case for Sanity in Numbering appeared first on TheFormTool.

The Human Advantage: Why AI Will Always Need a Supervisor

The Team at TheFormTool — Tue, 09 Sep 2025 19:59:14 +0000

The Human Advantage

Why AI Still Needs Will Always Need a Supervisor

Artificial Intelligence is fast becoming a fixture in legal drafting—from contract clauses to court filings. But as the tools evolve, a hard truth remains:

AI doesn’t know what it’s saying.

And it certainly doesn’t know what it means.

Which is why lawyers—real lawyers—must stay firmly in the loop

When AI Fails Loudly

We’ve all seen the headlines: AI-generated court briefs citing non-existent cases; legal assistants drafting with tools that “hallucinate” clauses or invent facts.

Fortunately, litigators discover these errors quickly. Filings are public. Opposing counsel reads them. Judges push back. There’s a built-in correction mechanism—even if it’s embarrassing.

But what about the legal work that’s invisible until it’s too late?

- Wills and trusts that sit in a drawer for a decade
- Health care directives that emerge only in crisis
- Commercial contracts with buried errors
- Real estate documents with quietly missing protections

When AI creates those, and no one checks the work?

That’s not a correction mechanism — it’s a time bomb.

HITL Isn’t Good Enough

In tech circles, the phrase “Human in the Loop” (HITL) is offered as a safety valve: a person, somewhere, monitors the machine.

But in legal practice, not just any human will do.

And passive oversight isn’t enough.

Confidentiality. Judgment. Responsibility. These aren’t tasks that can be outsourced to an untrained user or anonymous reviewer.

The law demands more than HITL.

It requires something better:

Introducing LITL – Lawyer in the Loop

Lawyer in the Loop (LITL) is a professional standard for the ethical use of AI in legal work.

It means no AI-generated content enters the legal record—or reaches the client—without being directly reviewed, supervised, and signed off by a licensed attorney.

It’s not an obstacle to progress. It’s the only path forward that protects:

- Attorney-client privilege
- Ethical accountability
- Human judgment
- Legal integrity

Why This Matters Now

Some in the legal tech world are quietly promoting HITL as the way forward: hire non-lawyers to review AI output, let junior staff handle the oversight, or worst of all—let clients verify their own documents.

That’s not scalable.
It’s not ethical.
And it’s not professional.

Clients rely on lawyers to apply training, experience, and judgment. If we’re not in the loop—really in the loop—we’ve outsourced more than work.
We’ve outsourced responsibility.

LITL Sets the Standard

LITL ensures that:

- A real lawyer makes the call
- The client’s data stays protected
- Privilege and ethics are preserved
- Errors are caught before they explode

It’s a standard for professionals.
A defense against carelessness.
And a stake in the ground for legal ethics in the AI era.

No LITL, No Trust.

We don’t let AI argue in court.
We shouldn’t let it sign off on a will, either.

If you’re a legal professional using—or thinking about using—AI for drafting, document automation, or legal intake:

- Stay in the loop.
- Be the loop.

LITL is how we build trust in the tools we choose to use.

Formal Definition for LITL:

Lawyer in the Loop (LITL) is a professional standard for the responsible use of AI in legal work. It requires that a licensed attorney—not a machine, not a paralegal, not a non-lawyer reviewer—directly supervises, reviews, and accepts responsibility for any AI-generated or AI-assisted legal output before it is relied upon or delivered to a client.

To review the white papers we’ve published on this subject, please click here.

The post The Human Advantage: Why AI Will Always Need a Supervisor appeared first on TheFormTool.

Defining the Duty: AI Use and Informed Consent in Legal Practice

The Team at TheFormTool — Sun, 07 Sep 2025 23:22:55 +0000

Defining the Duty: AI Use and Informed Consent in Legal Practice

The Illusion of Intelligence: Legal Risk in the Age of AI

Executive Summary

Click to download a copy of the white paper

Artificial intelligence has rapidly become a fixture in legal technology, powering everything from drafting assistants to research tools. But its rise poses a foundational question: Can a machine that does not understand truth, responsibility, or harm be trusted with legal reasoning?

We conclude with a specific call to action: Bar associations and ethics boards must establish a duty of informed consent when AI is used in client work. This includes disclosure of AI use, sharing of client data, and the risks involved. In all cases, lawyers must closely supervise and review AI-generated work to ensure accuracy and appropriateness—because responsibility cannot be outsourced.

“When the assistant starts making things up, the problem isn’t that it’s wrong — it’s that it doesn’t know what wrong is.”

Introduction: The Temptation of the Substitute

Large language models (LLMs) are changing the way legal work is done. They can summarize long documents, suggest arguments, and even draft contracts or pleadings in seconds. For overwhelmed lawyers, they offer relief. For technologists, they promise transformation.

But beneath the efficiency lies a serious risk: substitution without understanding and informed consent.

The legal profession is increasingly relying on systems that mimic intelligence without possessing it. The danger is not just in overuse—it’s in misplaced trust. A machine that cannot understand the difference between a statute and a story, a precedent and a prediction, cannot be trusted to reason through legal matters. Yet that is exactly the illusion that powerful LLMs create.

This paper explores why that illusion is dangerous, and why the profession must act now to draw clear ethical boundaries before the line between tool and surrogate disappears.

The Philosophical Perspective: Can AI Know Right from Wrong?

Law is not just rules and procedures; it is a human endeavor grounded in values, ethics, and judgment. Lawyers are not mere technicians—they are moral agents who balance competing interests, interpret nuance, and take responsibility for their decisions.

Artificial intelligence cannot do that.

Unlike human beings, AI does not possess:

Awareness — It does not know what it is doing.

Intention — It does not aim to serve justice.

Consequences — It does not bear the burden of its actions.

Instead, AI systems operate through mathematical prediction. When asked to draft a motion or respond to a query, an LLM simply calculates which words are most likely to follow based on patterns in its training data. It does not know what those words mean. It cannot evaluate their truth or their fairness.

The result is an uncanny illusion of competence. But it is just that: an illusion.

This is why hallucinations occur. When an AI tool invents a case citation, it is not making a mistake in the way a human would. It is doing exactly what it was trained to do: produce language that sounds plausible.

“If it has seen similar phrases in similar contexts, it will echo them — without knowing they are wrong.”

That lack of grounding is a fundamental limitation, not a bug to be patched.

In legal practice, where the cost of error is borne by clients, courts, and the public, this absence of understanding is not acceptable. Responsibility requires more than fluency. It requires judgment—a distinctly human faculty rooted in experience, empathy, and accountability.

To replace that judgment with probabilistic output is not just risky. It is a category error.

The Societal Perspective: Trust, Institutions, and Responsibility

The justice system depends on public trust. Courts, law firms, and legal professionals operate not merely by force of law, but by a shared belief that the system is principled, responsible, and humane. That belief is fragile.

Artificial intelligence, when misused or misunderstood, poses a threat not only to accuracy but to legitimacy.

When lawyers submit AI-generated briefs with fictitious citations, it doesn’t just embarrass a single practitioner—it casts doubt on the competence of the profession. When contract generators or will-writing tools fail silently, the public may never know what rights they have lost or which responsibilities were left unenforced.

A. Trust Requires a Responsible Actor

The public expects that a person is ultimately responsible for legal advice and documentation. AI lacks standing, status, and soul. It cannot swear an oath, hold a license, or be disbarred. It cannot be questioned under oath or found liable in court.

The legal system was not designed to accommodate machines that can do the work of a lawyer but carry none of the responsibility. If that division is not clarified soon—and enforced—the credibility of legal institutions may erode from within.

B. Lawyers Cannot Abdicate Responsibility to AI

In today’s legal marketplace, many lawyers are relying on AI-powered document automation to generate complex legal instruments: wills, trusts, healthcare directives, real estate filings, commercial contracts, and more. These tools are fast, inexpensive, and convincing. But when lawyers fail to closely supervise and review the results, they are placing clients’ futures in the hands of systems that do not understand law and cannot be held accountable.

Clients, unaware of the risks, rely on their lawyer’s assurance that the work is sound. But that assurance is increasingly being given without basis—because the lawyer has not fully reviewed the output, has not tested it, and may not even understand the technology that produced it. Without is there can be no informed consent.

“The lawyer tells the client it’s done right. The client believes it. Years later, the document fails.”

This is not hypothetical. These time bombs are already being embedded in legal records across jurisdictions—in language that no one will read until it is too late to fix.

C. The Role of the Profession

If lawyers do not lead in setting ethical standards for AI use, someone else will: courts, regulators, malpractice insurers, or public scandal.

The legal profession must reaffirm its role as a human-centered institution. Not in opposition to technology, but in recognition of what only human lawyers can do:

Exercise independent judgment

Take moral and legal responsibility

Supervise and explain what machines cannot

Public confidence in the law depends on knowing that real people are still responsible for justice.

The Legal Practitioner’s Perspective: Risk, Ethics, and Informed Consent

AI tools offer significant benefits to legal practitioners—faster drafting, document summarization, research assistance. But they also bring substantial risks that cannot be outsourced or ignored.

A. The Hallucination Problem

AI-generated content can be persuasive and articulate, yet completely false. Lawyers using AI to draft documents must recognize that hallucinated citations, inaccurate dates, or inconsistent logic are not rare edge cases—they are built-in limitations of current models.

AI does not know when it is wrong. It simply predicts what “sounds right” based on patterns in data. That gap between surface fluency and substantive accuracy presents a core risk for legal professionals.

B. The Risk of Unsupervised Client-Facing Drafting

Consumer-facing legal AI tools now draft wills, trusts, health care directives, prenuptial agreements, and more. These are documents with profound, long-term consequences that often remain unread or unchallenged until someone has died, become incapacitated, or left the jurisdiction.

AI-generated documents in this context may:

Include legally invalid or contradictory provisions

Use ambiguous language that fails under stress or scrutiny

Misapply or omit jurisdiction-specific requirements

These failures may not emerge until it is far too late to remedy them. As one practitioner observed decades ago about consumer credit agreements: “Some documents only work because no one ever reads them.” In the context of personal legal instruments, this is not just bad drafting—it’s a betrayal of trust.

The risk of time bombs in legal drafting—errors that won’t surface until a crisis occurs—must be contrasted with the more obvious dangers of public court filings that can be reviewed, challenged, or corrected quickly. In sensitive documents like wills or directives, a flaw may remain hidden until the damage is irreversible.

C. Recommendation: Establish a Duty of Informed Consent

To protect clients, the public, and the integrity of the profession, we recommend that Bar associations adopt a duty of informed consent when AI is used in any capacity related to client legal work. This duty should require lawyers to:

Inform clients when AI is used in document creation, analysis, or drafting

Disclose any sharing of client data with AI systems, particularly cloud-based tools

Explain the risks, including hallucinations, data leakage, and non-reviewable reasoning

Closely supervise and review all AI-generated work before it is relied upon or shared

“You can delegate tasks. You cannot delegate responsibility.”

Lawyers must remain the accountable party. No AI tool should ever be treated as a surrogate for legal judgment.

A Call to Action for Bars and Ethics Boards

Bar associations and regulators must act now to define ethical use of AI in legal work.

We recommend:

A duty of informed consent.

Lawyers must disclose to clients when AI is used in drafting or advising. This includes identifying what data is shared and the risks of relying on machine-generated output and receiving informed consent

Lawyer-in-the-Loop (LITL) supervision.

AI-generated work must be closely reviewed and approved by the responsible attorney. Supervision must be meaningful and documented.

Prohibition on unsupervised client-facing tools.

Lawyers must not offer AI-powered drafting tools to clients without attorney oversight. Responsibility cannot be transferred.

Ethics and CLE training requirements.

Continuing education standards should include practical instruction on AI’s capabilities and limits—alongside legal ethics.

This framework ensures that AI can be used safely—without undermining the foundations of professional duty.

Conclusion: AI as Tool, Not Colleague

Artificial intelligence is not going away. It will grow more fluent, more persuasive, and more deeply embedded in the workflows of law firms, courts, and clients. But its growth must not be confused with maturity.

Legal AI is not a new lawyer. It is a new assistant.

Assistants can be brilliant, but they must be supervised. They can organize, draft, and suggest—but they cannot decide. They do not bear responsibility for what happens if something goes wrong. That burden falls on the lawyer. Always.

In an age of dazzling automation, the core value of the profession is not its speed or formatting skill, but its judgment. That cannot be outsourced. That cannot be replaced.

“When the assistant starts making things up, the problem isn’t that it’s wrong—it’s that it doesn’t know what wrong is.”

The challenge for the profession is to embrace the future without surrendering its soul. That means using tools wisely, drawing boundaries clearly, and reaffirming that the law is a human institution, founded on human responsibility.

AI will be part of the legal future. But it must remain just that: a part, not a partner.

This is the fourth in our series of White Papers discussing the intersection of Artificial Intelligence and the legal profession. See the three predecessor white papers in our Security section.

The post Defining the Duty: AI Use and Informed Consent in Legal Practice appeared first on TheFormTool.

What does AI think of Document Assembly Firms?

The Team at TheFormTool — Mon, 28 Oct 2024 22:50:49 +0000

Most of us have seen thousands of articles on Artificial Intelligence. As always aspiring “experts” in document assembly and automation, we’ve been required to read far too many of them.

Fair is fair, so we thought it would be interesting to ask the leading large language model AI what it thinks of the firms in our business.

We found Open AI ChatGPT 4.0’s first answer a bit unsettling until it explained how it came to it’s conclusion. We wouldn’t have answered the way it did, but realistically, it’s answer was better. Two of its follow-on answers were a complete surprise.

If you’re interested in document assembly and automation or artificial intelligence, you’ll find this white paper interesting and informative.

Click to download

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Another Pro Bono Initiative

The Team at TheFormTool — Wed, 18 Sep 2024 19:27:17 +0000

Another Pro Bono Initiative

We’re honored to support classes at Arizona State University’s Sandra Day O’Connor College of Law with Doxserá^® software for students.

Whether assisting with legal education or providing tools to pro bono organizations, we’re committed to supporting the future of legal services. In fact, we’ve approved every pro bono request we’ve received in the past decade and intend to continue doing so.

For more on our pro bono efforts, please see Pro Bono & Access to Justice

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