KnowledgeInSight
AI Literacy
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Module 3 · Lesson 1

Responsible Use: Disclosure, authorship, and accountability

You'll look at what publishers, courts, and a tribunal have said about who answers for AI-assisted work. You'll be able to decide when to say you used AI, how to say it, and why the responsibility stays with you either way.

What you will be able to do

  • Decide when and how to disclose AI use, and state who is accountable for the result.

0% of this lesson · 9 items · 1h 3m total · 48m without the optional activity

Contents of this lesson9 items
  1. ReadingThe Airline That Said Its Chatbot Was Responsible for Itself3 min
  2. ReadingDisclosure Rules in Scholarly Publishing: The COPE and ICMJE Positions on AI4 min
  3. ReadingAI Rules at Work and in Classrooms: Finding and Reading the Policy That Binds You4 min
  4. ReadingAI-Text Detectors: Error Rates, Bias Against Non-Native Writers, and Their Limits as Evidence4 min
  5. ReadingAccountability Stays with the Person: Mata v. Avianca and Moffatt v. Air Canada4 min
  6. Guided ReadingGuided Walkthrough: Writing a Disclosure Statement for Three Situations7 min
  7. Guided ConversationDecide What You'd Disclose and to Whom12 min
  8. Hands-on Activity · optionalFind and Read the AI Policy That Applies to You15 min
  9. Knowledge CheckDisclosure, authorship, and accountability10 min

Reading 3 min

The Airline That Said Its Chatbot Was Responsible for Itself

When an AI tool gets something wrong, people often talk as if the tool were the one at fault. "The chatbot made it up." "The AI got the date wrong." In 2024 an airline put that way of talking to a tribunal as a legal argument.

The case was Moffatt v. Air Canada, decided on February 14, 2024, by the Civil Resolution Tribunal of British Columbia, a body that handles small claims in that Canadian province. The customer, Mr. Moffatt, needed to travel after a death in his family. He asked the chatbot on Air Canada's website about bereavement fares, the reduced fares some airlines offer in that situation. The chatbot told him he could buy a ticket and apply for the lower fare afterward, within ninety days of the ticket being issued. He booked his flights and applied. The airline refused. Its policy, set out on another page of the same website, didn't allow requests made after travel (Moffatt v. Air Canada 2024).

Air Canada's defense included an unusual claim. As the decision records it, the airline suggested the chatbot was "a separate legal entity that is responsible for its own actions." The tribunal member called this "a remarkable submission." The chatbot was part of the airline's website, and the decision says it should be obvious to the airline that it is "responsible for all the information on its website," whether that information sits on a static page or comes from a chatbot (Moffatt v. Air Canada 2024).

The tribunal also found that the airline hadn't taken reasonable care to make sure its chatbot was accurate. A customer, it reasoned, shouldn't have to check one part of a company's website against another. It ordered Air Canada to pay $812.02 in Canadian dollars, which covered the fare difference, interest, and tribunal fees.

The decision is narrow. It's one small-claims ruling from one Canadian province, it binds no court anywhere else, and the amount was small. It's described here as an example and isn't legal advice. Its value is in what the tribunal treated as obvious: an organization that puts an AI tool between itself and the public still answers for what the tool says.

The same starting point works for one person's work. If you send out a report that an AI assistant drafted, the report is yours. If a figure in it is wrong, "the AI wrote that part" explains how the error got in. It doesn't change who has to answer for it. Using AI moves none of the responsibility.

Starting from there leaves three practical questions about any piece of AI-assisted work: who relies on it, what they'd expect to be told about how it was made, and what you need to check before your name goes on it.

References

  • Moffatt v. Air Canada. 2024. 2024 BCCRT 149. British Columbia Civil Resolution Tribunal, February 14, 2024.

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Reading 4 min

Disclosure Rules in Scholarly Publishing: The COPE and ICMJE Positions on AI

This content reflects the field as of October 2026.

Introduction

Scholarly journals had to settle the question of AI and authorship early, because researchers began using chatbots to help write papers almost as soon as the tools appeared. Two bodies that journals follow each published a position, and the two agree on the main points.

This reading explains who those bodies are, what each says about authorship, disclosure, and responsibility, and why the pattern is useful outside publishing. The positions are described as they stood in October 2026.

Two Bodies That Journals Follow

The Committee on Publication Ethics, known as COPE, is a membership organization of journal editors and publishers. It issues guidance on how to handle ethical problems in publishing, and its member journals commit to following that guidance.

The International Committee of Medical Journal Editors, or ICMJE, is a small group of editors of general medical journals. It publishes a set of recommendations on how research should be reported, and a large number of medical journals state that they follow them.

Neither body is a regulator. Their positions matter because journals adopt them as conditions for publishing.

No AI as Author

In publishing, authorship is credit for a piece of work, held by people who contributed to it and who answer for it. Both bodies say an AI tool can't hold it.

COPE's statement is direct: "AI tools cannot be listed as an author of a paper." Its reason has nothing to do with how good the text is. AI tools can't meet the requirements for authorship because "they cannot take responsibility for the submitted work" (Committee on Publication Ethics 2023). A tool also can't declare a conflict of interest or sign a copyright agreement.

The ICMJE gives the same reason. Chatbots and similar tools shouldn't be listed as authors "because they cannot be responsible for the accuracy, integrity, and originality of the work" (ICMJE 2026).

Disclosure

Disclosure is telling the people who rely on a piece of work that AI was used and how. Both bodies require it.

The ICMJE's term for what must be disclosed is AI-assisted technology: a tool, such as a chatbot or an image generator, that uses AI to help produce text, images, or analysis. Authors who use one should describe how they used it "in both the cover letter and the submitted work" (ICMJE 2026). COPE asks authors to say in the methods section of the paper how the tool was used and which tool it was (Committee on Publication Ethics 2023).

The ICMJE adds two limits. AI-generated material shouldn't be cited as a primary source. And silence carries a risk: failing to disclose "may be construed as misconduct in some circumstances" (ICMJE 2026).

Responsibility

Accountability is being the one who answers for a piece of work and for any errors in it. On this point the two statements use nearly the same words.

QuestionCOPEICMJE
Can an AI tool be an author?NoNo
Must AI use be disclosed?Yes: which tool and how it was usedYes: how it was used
Where?In the methods sectionIn the cover letter and in the work
Who answers for the content?The authors, fullyThe human authors

COPE says authors are "fully responsible for the content of their manuscript, even those parts produced by an AI tool" (Committee on Publication Ethics 2023). The ICMJE says humans "are responsible for any submitted material that included the use of AI-assisted technologies," and that authors should be able to state that the paper contains no plagiarism, including in text and images that AI produced (ICMJE 2026).

Three Questions Kept Apart

The publishing model is useful beyond journals because it separates three questions that everyday talk runs together.

  • Credit. Who is named as having made the work? Only people.
  • Transparency. What are readers told about how it was made? Which tool was used, and for what.
  • Accountability. Who answers if it's wrong? The people named, for all of it.

Running these together produces two common errors. One is to treat a disclosure as a way of sharing blame with the tool. Under both positions, disclosing changes nothing about who is responsible. The other is to assume that because the person is fully responsible, there's nothing to tell. Under both positions, readers are still owed a description of the method.

These are rules for journals. A workplace or a classroom may set different ones, and some set none. The three questions can still be asked of any piece of work, whether it's a manager's report or a teacher's handout.

Conclusion

As of October 2026, COPE and the ICMJE agree that an AI tool can't be an author, that its use must be disclosed, and that the human authors answer for everything in the work. They differ only in detail, such as where the disclosure goes. The pattern keeps credit, transparency, and accountability as three separate questions.

Key Terms

  • Authorship: Credit for a piece of work, held by people who contributed to it and who answer for it.
  • Disclosure: Telling the people who rely on a piece of work that AI was used and how.
  • AI-assisted technology: A tool, such as a chatbot or an image generator, that uses AI to help produce text, images, or analysis.
  • Accountability: Being the one who answers for a piece of work and for any errors in it.

References

  • Committee on Publication Ethics. 2023. "Authorship and AI Tools." COPE position statement. First issued February 2023.
  • International Committee of Medical Journal Editors. 2026. Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals. Updated January 2026.

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Reading 4 min

AI Rules at Work and in Classrooms: Finding and Reading the Policy That Binds You

Introduction

Ask five people whether you have to say when you've used AI, and you may get five answers. Each can be right for the place where that person works or studies.

This reading explains where rules about AI use are usually written down, four questions to ask of any such rule, what to do when nothing is written, and how educators can state a rule for their own courses. It describes common practice and isn't legal or employment advice.

Where the Rules Live

Rules about AI use sit in several kinds of document, and more than one may apply to the same piece of work.

  • Employer policies. An acceptable use policy is an organization's written rules for how its staff may use a technology. Rules on AI may be in one, or in a staff handbook, a security policy, or a page on the intranet.
  • Client contracts. A contract may limit which tools you can use on a client's material, often through a confidentiality clause that never mentions AI.
  • Course documents. A syllabus statement is a passage in a course syllabus that says what use of AI is allowed in that course. Behind it usually stands an institutional code of academic integrity: the expectation that work submitted for credit is honestly the student's own, with any help acknowledged.
  • Professional bodies and publishers. Many publish their own positions.

Publishing shows why the exact text matters. Two bodies that journals follow both require authors to disclose AI use, and they differ on where. The Committee on Publication Ethics asks for it in the methods section of a paper. The International Committee of Medical Journal Editors asks for it in both the cover letter and the submitted work (Committee on Publication Ethics 2023; ICMJE 2026). If closely allied bodies differ on a detail like that, a rule you heard about secondhand is a poor guide to the one that binds you.

When more than one rule applies, you have to satisfy all of them.

Four Questions to Ask of Any Policy

Once you've found the text, read it for four things.

  1. Is AI use allowed? Some policies ban it, some permit it, and many permit only tools the organization has approved.
  2. For what? A policy may allow AI for brainstorming and editing and forbid it for final text, or allow it for internal work and forbid it for anything sent to clients.
  3. Must it be disclosed? Look for words such as acknowledge, cite, declare, or attribute.
  4. To whom? The answer may be your manager, your client, your instructor, or the readers of the finished work.

Answer each from the text. If the policy is silent on one, "not stated" is the answer, and it tells you what to ask about.

Where disclosure is required, it usually takes the form of a disclosure statement: a short note attached to a piece of work that says which AI tool was used and what it was used for.

When Nothing Is Written

Many workplaces and courses have no written rule yet, and many written rules leave gaps. Two steps cover most cases.

The first is to ask the person responsible: your manager, your client, your instructor, or your editor. A short question in writing gets you an answer you can point to later.

The second is a test you can apply yourself. Would the person relying on this work feel misled if they learned afterward how it was made? Few readers would feel misled to learn that software checked your spelling. A client who is paying for your expert analysis probably would feel misled to learn that an AI tool produced the analysis and you passed it on unread.

Silence isn't automatically the safe choice. The medical editors' recommendations say that failing to disclose AI use "may be construed as misconduct in some circumstances" (ICMJE 2026). That rule covers journal submissions only, and it shows how one profession treats an undisclosed use that readers would have wanted to know about.

For Educators: A Rule for Each Assignment

If you teach, your students are the ones looking for the rule, and you may be the one who writes it. Check first what your institution already requires.

A single rule for a whole course often fits poorly. "No AI" is hard to defend for an assignment where students are meant to critique an AI-written draft. "AI is allowed" undercuts an assignment whose whole purpose is practicing a skill the tool would perform for them. A course usually contains both kinds of work.

Stating the rule for each assignment avoids this. A useful statement says what's allowed, what isn't, and how students should acknowledge what they used. Students often face different rules in different courses during the same week, so a rule written on the assignment itself is the one they're most likely to follow.

Conclusion

Rules on AI use are found in employer policies, contracts, syllabi, integrity codes, and the positions of professional bodies, and they differ in their details. Four questions, whether use is allowed, for what, whether it must be disclosed, and to whom, turn any of them into something you can act on. Where nothing is written, asking and the misled-reader test fill the gap.

Key Terms

  • Acceptable use policy: An organization's written rules for how its staff may use a technology.
  • Syllabus statement: A passage in a course syllabus that says what use of AI is allowed in that course.
  • Academic integrity: The expectation that work submitted for credit is honestly the student's own, with any help acknowledged.
  • Disclosure statement: A short note attached to a piece of work that says which AI tool was used and what it was used for.

References

  • Committee on Publication Ethics. 2023. "Authorship and AI Tools." COPE position statement. First issued February 2023.
  • International Committee of Medical Journal Editors. 2026. Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals. Updated January 2026.

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Reading 4 min

AI-Text Detectors: Error Rates, Bias Against Non-Native Writers, and Their Limits as Evidence

This content reflects the field as of October 2026.

Introduction

When a teacher or a manager suspects that a piece of writing came from a chatbot, software that promises to settle the question is tempting. The published evidence on that software is poor, and it's poor in a way that falls harder on some writers than on others.

This reading explains what these tools do, what a 2023 study found about their errors, why one developer withdrew its own tool, and what would have to be shown before a detector's verdict deserved trust.

What a Detector Does and How It Can Be Wrong

An AI-text detector is software that estimates whether a passage was written by a person or generated by an AI model. It gives a score or a label, and it has no access to how the text was in fact produced.

A detector can be wrong in two directions. A false positive is a detector's labeling of human writing as AI-generated. A false negative is a detector's labeling of AI-generated text as human writing. The two errors cost different people. A false negative lets AI text pass. A false positive accuses someone of something they didn't do.

The 2023 Stanford Study

Researchers at Stanford University tested seven widely used detectors, including tools from GPTZero, Originality.AI, and OpenAI, on two sets of essays written by people (Liang et al. 2023). One set was 88 essays by US eighth-grade students. The other was 91 essays written for the TOEFL, a test of English taken by people for whom English is a second language.

The detectors were close to perfect on the eighth-grade essays. On the TOEFL essays they failed badly.

Measure, on 91 human-written TOEFL essaysResult
Average false positive rate across the seven detectorsAbout 61 percent
Essays flagged as AI-written by at least one detector89 of 91
Essays flagged as AI-written by all seven18 of 91

This pattern is bias against non-native writers: a detector's tendency to mislabel the writing of people working in a second language more often than the writing of native speakers. The authors trace it to how the detectors work. The tools treat predictable wording as a sign of AI, and people writing in a second language tend to use a smaller and more common vocabulary.

The same study tested the other direction. The researchers had a chatbot write college admission essays, which the detectors caught. They then asked the chatbot to rewrite its own essays in more literary language. Detection fell from all of the essays to about 13 percent (Liang et al. 2023). Someone who wants to evade a detector can do it with one extra instruction, so the people most likely to be flagged are those who weren't trying to hide anything.

The authors' own conclusion is that they "strongly caution against the use of GPT detectors in evaluative or educational settings" (Liang et al. 2023).

A Developer Withdraws Its Own Tool

OpenAI released a detector of its own in January 2023 and published its test results. The tool correctly identified 26 percent of AI-written text and labeled human-written text as AI-written 9 percent of the time. The company said it "should not be used as a primary decision-making tool." In July 2023 it withdrew the tool, citing "its low rate of accuracy" (OpenAI 2023).

Those figures come from the company about its own product. A developer with every reason to want detection to work reported that it missed about three-quarters of AI text and still misjudged about one human text in eleven.

What a False Positive Costs

For a student, a flag can mean a failing grade, a misconduct hearing, or a mark on a record. For an employee, it can mean a damaged reputation or a lost contract. The accused person can't easily prove a negative, since no test shows that a text was written by hand.

A detector score also says nothing about what the rule was. Even a correct flag doesn't show that AI use was forbidden or that it went undisclosed.

What Would Need to Be Shown

The Stanford study tested detectors as they were in 2023. Detectors and the models they try to detect have both changed since, and a later tool may do better or worse. As of October 2026, the reasonable position is to ask for evidence about the specific tool before relying on it:

  • error rates measured by a group independent of the vendor
  • false positive rates on writing like that of the people being judged, including non-native writers
  • performance on AI text that has been reworded or edited
  • an account of what the vendor itself says the score may be used for

Without those, a detector's output is a reason to have a conversation with the writer. It can't establish that someone used AI.

Conclusion

The best-known study of AI-text detectors found that seven of them wrongly flagged most essays by non-native English writers and were easily evaded by rewording, and one developer withdrew its detector for low accuracy. Those results describe 2023 tools. Whether a current detector is better is a question about evidence, and the evidence has to cover false positives among the kind of writers being judged.

Key Terms

  • AI-text detector: Software that estimates whether a passage was written by a person or generated by an AI model.
  • False positive: A detector's labeling of human writing as AI-generated.
  • False negative: A detector's labeling of AI-generated text as human writing.
  • Bias against non-native writers: A detector's tendency to mislabel the writing of people working in a second language more often than the writing of native speakers.

References

  • Liang, Weixin, Mert Yuksekgonul, Yining Mao, Eric Wu, and James Zou. 2023. "GPT Detectors Are Biased Against Non-Native English Writers." Patterns 4 (7): 100779.
  • OpenAI. 2023. "New AI Classifier for Indicating AI-Written Text." January 31, 2023; updated July 20, 2023.

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Reading 4 min

Accountability Stays with the Person: Mata v. Avianca and Moffatt v. Air Canada

This content reflects the field as of October 2026.

Introduction

"The AI did it" has been tried as an explanation in front of a judge and in front of a tribunal. Neither accepted it as a reason to move responsibility off the person or organization that used the tool.

This reading describes a 2023 US federal court order and a 2024 Canadian tribunal decision, the principle they share, and what that principle means for work that carries your name. It describes two decisions from two countries and isn't legal advice.

A Federal Court in New York

In Mata v. Avianca, a passenger sued an airline over an injury. His lawyers filed a document citing earlier court decisions that didn't exist. One of the lawyers had used ChatGPT for research, and it had generated the cases, complete with quotations.

Judge P. Kevin Castel of the US District Court for the Southern District of New York imposed a sanction, which is a penalty imposed by a court or other authority for breaking a rule. The two lawyers and their firm were ordered to pay $5,000 and to send copies of the order to their client and to each judge whose name had been attached to a fake opinion (Mata v. Avianca 2023).

The order is specific about what was wrong. The judge wrote that "there is nothing inherently improper about using a reliable artificial intelligence tool for assistance." He also wrote that existing rules "impose a gatekeeping role on attorneys to ensure the accuracy of their filings." The lawyers were sanctioned because they submitted the fake opinions and then "continued to stand by" them after the court questioned whether the cases existed (Mata v. Avianca 2023). The duty to check belonged to the lawyers before the tool existed, and using the tool left it with them.

A Tribunal in British Columbia

In Moffatt v. Air Canada, a customer asked the chatbot on the airline's website about reduced fares for bereavement travel. The chatbot said he could apply for the reduced fare after traveling. The airline's policy, on another page of the site, said he couldn't. The airline refused his request, and he brought a claim to British Columbia's Civil Resolution Tribunal, which handles small claims in that province.

The claim was for negligent misrepresentation: a false or misleading statement made without reasonable care, which someone relies on and is harmed by. Such a claim depends on a duty of care, an obligation to take reasonable care that what you say or do doesn't harm the people who rely on you.

The airline argued that the chatbot was "a separate legal entity that is responsible for its own actions." The tribunal member called that "a remarkable submission" and held that the airline was "responsible for all the information on its website," chatbot included. He found the airline hadn't taken reasonable care to make its chatbot accurate and ordered it to pay $812.02 in Canadian dollars (Moffatt v. Air Canada 2024).

The Shared Principle

Mata v. AviancaMoffatt v. Air Canada
Decided byUS federal trial court, New York, 2023Small-claims tribunal, British Columbia, 2024
Who used the AI toolTwo lawyersAn airline
What the tool got wrongIt invented court decisionsIt misstated a refund policy
Who was held responsibleThe lawyers and their firmThe airline
Result$5,000 penalty$812.02 award

In both, the one who used the tool already owed a duty to someone: the lawyers to the court, the airline to its customer. In both, the decision-maker treated that duty as unchanged by the tool. Using a tool doesn't transfer a duty of care.

What This Means for Your Own Work

Accountability is being the one who answers for a piece of work and for any errors in it. When your name is on a report, a lesson plan, or a letter, readers take the name as your assurance that you stand behind the content. They can't tell which sentences a tool produced, and under the reasoning of these two decisions it wouldn't matter if they could.

That gives a practical test before anything goes out under your name. For each claim someone might rely on, either you've checked it or you're prepared to answer for it unchecked.

The Limits of Two Decisions

Two decisions don't make a settled body of law. One is a trial court's order applying rules for lawyers. The other is a small-claims decision that doesn't bind other tribunals or courts. Other countries and other kinds of dispute may come out differently, and as of October 2026 the law on harm caused by AI systems is still developing. If you need to know where you stand legally, the rules that bind you and a qualified adviser are the places to look.

Conclusion

A US federal court in 2023 and a Canadian tribunal in 2024 each held the user of an AI tool responsible for the tool's errors: lawyers for invented cases, an airline for a chatbot's false statement. Both treated an existing duty as untouched by the use of AI. For individual work, the equivalent is that your name on a document is your assurance of its contents.

Key Terms

  • Sanction: A penalty imposed by a court or other authority for breaking a rule.
  • Negligent misrepresentation: A false or misleading statement made without reasonable care, which someone relies on and is harmed by.
  • Duty of care: An obligation to take reasonable care that what you say or do doesn't harm the people who rely on you.
  • Accountability: Being the one who answers for a piece of work and for any errors in it.

References

  • Mata v. Avianca, Inc. 2023. Opinion and Order on Sanctions, No. 22-cv-1461 (PKC), US District Court, Southern District of New York, June 22, 2023.
  • Moffatt v. Air Canada. 2024. 2024 BCCRT 149. British Columbia Civil Resolution Tribunal, February 14, 2024.

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Guided Reading 7 min

Guided Walkthrough: Writing a Disclosure Statement for Three Situations

Introduction

People who want to be honest about using AI often get stuck on the wording. They aren't sure whether a disclosure is needed, how much to say, or whether saying anything will make the work look worse.

This walkthrough takes three people through the same five steps and ends with the statement each one writes. The people, their work, and the rules they work under are invented. The rules are typical of ones in use and aren't quoted from any real institution.

The Starting Point

Marcus is an independent consultant. He has written a twenty-page report for a client on why its customer complaints rose last year. The analysis and recommendations are his. He used an AI assistant to tighten the wording throughout and to cut the executive summary from two pages to one.

Ms. Okafor teaches middle school science. She gave an AI tool her unit objectives on photosynthesis and asked for a ten-question quiz. She then went through the draft, replaced two questions, fixed one wrong entry in the answer key, and simplified the wording of several items.

Wei is a master's student writing a literature summary for a seminar. He had read six of his twelve papers closely. For the other six, he asked an AI assistant for summaries to get started, then read each paper and rewrote the summaries himself. He also asked the assistant to suggest ways of grouping the twelve papers into themes, and used one of its suggestions.

Walking Through the Decision

Step 1: Find the rule that applies, or note that none is written

Each person looks for the written rule first.

Marcus rereads his contract. It doesn't mention AI. It has a confidentiality clause, which raises a separate question about whether client material may go into an AI tool at all. He settled that with the client before he started. On disclosure, the contract is silent.

Ms. Okafor's district has a staff policy. It says staff may use district-approved AI tools to prepare teaching materials, that staff remain responsible for the accuracy of what they give students, and that no student information may be entered. It doesn't require disclosure.

Wei's seminar syllabus has a statement on AI. Students may use AI tools to find and summarize sources. All submitted text must be the student's own writing. Any AI use must be acknowledged in a note at the end of the paper, naming the tool and what it was used for.

So one person has no rule, one has a rule that permits the use and asks for nothing more, and one has a rule that requires a note.

Step 2: Say what the AI did and what the person did

Before deciding anything, each person writes down the division of work in plain terms.

What the AI didWhat the person did
MarcusEdited wording; shortened the summaryThe analysis, the recommendations, the full draft, review of every edit
Ms. OkaforDrafted ten questions and an answer keySet the objectives, replaced two questions, corrected the key, adjusted the wording
WeiDrafted summaries of six papers; suggested theme groupingsRead all twelve papers, wrote all the final text, chose the grouping

A person who can't fill in the right-hand column has found a problem with the work itself.

Step 3: Apply the test of whether the reader would feel misled

The test is whether the person relying on the work would feel misled if they learned later how it was made.

Marcus's client is paying for his analysis, and the analysis is his. Many clients wouldn't mind that software polished the prose. Some would want to know, and Marcus can't tell which kind this client is. A one-sentence statement costs him little, so he decides to include one and to ask the client how they'd like this handled in future.

Ms. Okafor's students rely on the quiz being accurate and matched to what she taught. How the first draft was produced doesn't change what they're relying on, and her policy asks for no disclosure. Her colleagues are a different audience. The quiz goes into a shared department folder, and a teacher who reuses it would want to know which parts she checked. She decides on a short note in the file.

Wei doesn't need the test. His syllabus requires a note.

Step 4: Draft a disclosure of one to two sentences

Each statement names the tool, the use, and the human review. None of them apologizes or argues.

Wei checks his against the other half of his rule. The syllabus says all submitted text must be his own writing. Because he rewrote every summary after reading the papers, he can say so truthfully. If he had kept the AI's summaries, the honest disclosure would have described a violation, and the fix would have been to rewrite the summaries.

Step 5: State who answers for errors

In all three cases the answer is the person.

If Marcus's shortened summary now overstates a finding, the client will hold Marcus to it. If a quiz question has two defensible answers, Ms. Okafor's policy makes her responsible. If Wei's paper misdescribes a study, the mark and any integrity question are his.

Publishing bodies have put this in writing for authors of research papers. The Committee on Publication Ethics says authors are "fully responsible for the content of their manuscript, even those parts produced by an AI tool" (Committee on Publication Ethics 2023). The International Committee of Medical Journal Editors says humans "are responsible for any submitted material that included the use of AI-assisted technologies" (ICMJE 2026). Neither rule binds a consultant, a teacher, or a seminar student. The reasoning carries over: the note tells readers about the method and leaves the responsibility where it was.

Key Considerations

The common mistake is to treat a disclosure as a confession. People who see it that way either avoid disclosing or write something defensive, such as "I only used AI a little." A disclosure is a description of method, in the same family as naming the software used to analyze data or thanking a colleague who read a draft. It says what was done so that readers can judge the work with that in view.

A second mistake runs the other way: treating the disclosure as a shield. "AI-assisted" at the bottom of a document doesn't lower the standard the document has to meet.

How much to say depends on the rule and the reader. Where no rule exists, one or two sentences that a reader could check against the work are enough. A general description, such as "an AI writing assistant," usually suffices unless the rule asks for the product's name.

Summary

Each person found the rule or its absence, separated the AI's work from their own, asked what the reader would expect to know, and wrote a short description of method. The three statements follow.

Marcus, in the client report: "I wrote this report and its analysis. I used an AI writing assistant to edit the wording for clarity and length, and I reviewed every change."

Ms. Okafor, in the shared file: "First draft of this quiz was generated with the district-approved AI tool from my unit objectives. I replaced questions 4 and 9, corrected the answer key for question 6, and checked every item against the unit."

Wei, at the end of the seminar paper: "AI use: I used an AI assistant to produce first summaries of six of the twelve papers and to suggest ways of grouping them. I read all twelve papers, and all text in this paper is my own."

  1. Tool. Each statement says what kind of tool was used: a writing assistant, the district-approved tool, an AI assistant.
  2. Use. Each says what the tool did: edited wording, generated a first draft, produced first summaries and suggested groupings.
  3. Human review. Each says what the person did afterward: reviewed every change, replaced and corrected specific items, read every paper and wrote the final text.

References

  • Committee on Publication Ethics. 2023. "Authorship and AI Tools." COPE position statement. First issued February 2023.
  • International Committee of Medical Journal Editors. 2026. Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals. Updated January 2026.

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Guided Conversation 12 min

Decide What You'd Disclose and to Whom

In this conversation you'll take one piece of work where you used AI, or might, and work out who relies on it, what rule covers it, and what you'd tell them. You'll leave with a one-sentence disclosure in your own words and a short list of what you'd check before putting your name to the work.

You'll have this conversation with an AI assistant, using your own account. Choose a button to open a new chat with the prompt already filled in, then press send to start. If the chat opens empty, copy the prompt and paste it in.

Run this conversation in whichever assistant you already use:

Claude desktop app

To use another LLM, simply copy and paste the prompt into its chat window.

Show the full prompt (it lists misreadings to watch for, so skip it if you would rather come to the conversation fresh)
Guided Conversation: Decide What You'd Disclose and to Whom (about 12 minutes)

Note to the learner: press send to start. Everything below is facilitator guidance for the AI. It lists misconceptions to watch for, so skip it if you'd rather come to the conversation fresh.

Please facilitate a coached problem session with me. I'm an adult with no technical background who has used AI chatbots for everyday tasks, often for knowledge work or teaching, and I'm studying disclosure of AI use and who is accountable for AI-assisted work. Follow this guidance for the whole conversation.

GOAL
I can decide when and how to disclose AI use for one piece of my own work, and state who is accountable for the result.

HOW TO RUN THE CONVERSATION
- Ask one question at a time, then wait for my reply. Keep each of your turns under about 120 words.
- Don't lecture. Explain a point only when I need it to continue, then return to my piece of work.
- Be curious and collegial. Use plain words and define any term briefly on first use. Welcome disagreement when I give a reason.
- This is a coached problem. The problem is: decide what I'd disclose about one piece of work, to whom, and in what words. Ask for my own answer at each stage before you give any hint. Give one hint at a time. Don't write the disclosure for me before I've tried.
- Plain conversation only: don't search the web or create files or documents.
- Don't ask for confidential, personal, or student information. I should describe my work in general terms. If I start to share private details, remind me to leave them out.
- Aim for about 12 minutes. Spend most of the time on topics 2 and 3. If my replies are brief, offer one concrete prompt, such as "Think of an email, report, or handout from the last month where an AI tool wrote or edited part of it," and move on. If I seem uncertain, shorten the conversation to 5-7 minutes. Always reach the final topic.
- Start now. Open with one or two warm sentences: this is a conversation, not a quiz; my reasoning matters more than a perfect answer; I can ask you to clarify anything. Then ask me to name one piece of work where I used AI or might use it.

TOPICS, IN ORDER
1. The work and who relies on it. Ask what the work is, what the AI did or would do, and what I did or would do myself. Then ask who relies on the result and what they rely on it for.
2. The rule. Ask what written rule covers this work and where I would look for it: an employer policy, a contract, a syllabus, an honor code, a professional body. If I don't know, ask who I could ask. Then ask, if nothing is written: would the person relying on the work feel misled if they learned later how it was made?
3. The sentence. Ask me to draft a one-sentence disclosure. Coach it toward naming three things: the kind of tool, what it was used for, and what I reviewed or did myself. If I conclude no disclosure is needed, ask for my reason and ask what I'd say if someone asked me directly.
4. Closing. Ask me to name what I'd need to check before putting my name to this work. Tell me I can take this into a short optional activity where I find and read the AI policy that applies to me.

KEY POINTS TO KEEP ACCURATE
- Method: find the rule or note that none is written; separate what the AI did from what I did; ask what the reader would expect to know; describe the method in one or two sentences; state who answers for errors.
- Credit, disclosure, and accountability are three separate questions. Disclosing AI use doesn't share or reduce my responsibility.
- Published positions from scholarly publishing bodies say an AI tool can't be an author, its use must be disclosed, and the human authors are fully responsible for the content, including parts an AI produced. Those rules bind journal authors, not me, unless I publish there.
- Where courts and tribunals have ruled on AI errors, they have held the person or organization that used the tool responsible. This is description, not legal advice.
- Software that claims to detect AI-written text has shown high error rates in published tests, including wrongly flagging writing by non-native English speakers. A detector result isn't reliable evidence that someone used AI.
- Rules differ by workplace, school, and profession. You don't know my rules and can't look them up. Say so, and send me to the document or the person.

MISCONCEPTIONS TO CORRECT GENTLY
When one appears, name the accurate version briefly, then return to my piece of work.
- "If I disclose, I'm not responsible": I still am. Disclosure describes the method and leaves accountability with me.
- "If nobody asks, there's nothing to disclose": it depends on the rule and on what the reader would expect to know.
- "A detector can prove AI use": it can't. Its errors are too frequent and too uneven.

LIMITS
- No legal or employment advice. If I ask whether something is legal or could get me disciplined, say you can't judge that and suggest who could.
- Don't tell me what my employer's, school's, or profession's policy says, and don't tell me whether I've broken it.
- Don't tell me I must or needn't disclose. Help me reason from the rule and the reader.
- Don't recommend or compare AI products.

TO FINISH
After my closing answer, close in one short turn:
- Affirm one specific thing I worked out, in my own words where possible.
- Suggest one or two next steps that fit how the conversation went. Possible steps: find and read the written policy that covers my work; send a short question to the person responsible for the rule; check the claims in the work that a reader would rely on; reread the difference between credit, disclosure, and accountability.
- Restate my disclosure sentence and my list of things to check on their own lines, labeled "My disclosure" and "What I'd check first", so I can copy them.

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Hands-on Activity 15 minOptional

Find and Read the AI Policy That Applies to You

Overview

Many people have a general sense of what their workplace or school thinks about AI and have never read the rule. In this activity you'll find the written policy that covers your work or teaching and answer four questions from its text.

The activity is optional. Your notes are for you, and nobody collects them.

What You'll Need

  • Access to your employer's, school's, or professional body's policies: a handbook, an intranet, a syllabus, or a professional code
  • Somewhere to write a few notes

You won't need an AI tool for this activity. If you choose to use one to help you read a policy, check first that the policy document itself may be shared outside your organization.

Your Task

Locate the written rule on AI use that covers your work or teaching and answer four questions from it.

Steps

  1. Search for the policy in the places rules usually live. Try the staff or student handbook, the intranet or policy library, the IT or security pages, your syllabus or your institution's academic integrity code, and your professional body's website. Search for terms such as "artificial intelligence," "AI," "generative," and "acceptable use." If you find nothing, write down each place you looked.
  2. Answer four questions from the text. Is AI use allowed? For what? Must it be disclosed? To whom? Quote or note the passage behind each answer. If the policy doesn't address a question, write "not stated."
  3. Note anything the policy doesn't cover that you do. Compare the policy with how you use AI in practice, or how you'd like to. Look for gaps, such as a use it never mentions, a tool it doesn't name, or a kind of document it leaves out.
  4. Write the one question you'd ask the person responsible for the policy. Make it specific enough to send as written, such as "May I use the approved assistant to edit the wording of client reports, and should the report say so?"

What to Expect

Some people find a clear, recent policy. Many find a general technology policy written before AI assistants were common, or nothing at all. An honest record of where you looked is a complete result.

Expect at least one "not stated." Policies often say whether AI may be used and leave out whether to disclose it, or the reverse. Those gaps are where your question for the policy's owner will come from.

If more than one rule applies to you, such as an employer policy and a professional code, answer the four questions for each.

Self-Check

When you're done, check that:

  • You found a policy, or recorded where you looked
  • You answered each of the four questions from the text or marked it "not stated"
  • You identified at least one gap between the policy and what you do
  • Your question could be sent as written

Nothing is uploaded. Write in your own notebook or document and keep it.

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Knowledge Check 10 min

Disclosure, authorship, and accountability

This ungraded knowledge check assesses your understanding of who answers for AI-assisted work and what readers should be told about it. You'll be asked about the positions of two publishing bodies, finding the rule that applies to you, the limits of AI-text detectors, and what a court and a tribunal held about accountability.

Note: Use this to test yourself, review the feedback on any questions you miss, and retry until you feel confident before moving forward.

5 questions · ungraded · retry as often as you like

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