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Leadership guide/Decisions/Notice, disclosure & intellectual property

Notice, disclosure & intellectual property

Tell people what matters.

Useful disclosure helps people understand authorship, interaction or a decision that affects them.

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HumanSkills recommendation · September 2026

In this guideRecommended positionYour local choicesA campus situationWho is responsibleLanguage to useEvidence of implementationSupporting sourcesDownload PDF→

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A considered starting position.

HumanSkills recommendationRequire notice where AI involvement materially affects trust, authorship, evaluation, interaction or a consequential decision. Distinguish routine editing from substantive generation and automated interaction. Respect intellectual-property rights and contractual restrictions separately from disclosure.

A label on every spelling correction may obscure the uses people actually need to understand. A vague label on an automated service may say too little. Attribution also does not establish permission to upload copyrighted, confidential or partner-owned materials.

What the evidence supportsNorthcentral distinguishes routine staff content assistance from autonomous interactions. RPCC takes a broader approach to labeling shared AI-generated content. This is a documented policy variance, not a single settled sector rule.

• Make consequential AI involvement intelligible to affected people.
• Define authorship and disclosure expectations for the task.
• Check rights to inputs and uses rather than assuming attribution is enough.

What your institution decides.

The right arrangement depends on the purpose, consequences, applicable requirements and capacity of your institution. Use these options to make the choice explicit.

Task-based disclosure

Consider this when: The important distinction is the nature and extent of assistance.

The tradeoff: Provide examples so staff and students can apply the rule consistently.

Broad labeling

Consider this when: The institution chooses a simple and widely applicable disclosure rule.

The tradeoff: Clarify routine assistance and avoid labels that obscure more consequential uses.

Interaction and decision notice

Consider this when: People encounter automated assistance or an AI-influenced institutional decision.

The tradeoff: Explain the role, limitations and route to a person without exposing sensitive technical details.

Walk through the situation.

Illustrative campus caseA message looks as though an advisor wrote it.

A student receives a personalized message generated and sent automatically by a college service. It appears under the advisor’s name.

The student needs an accurate understanding of who reviewed the message and where to get help.

1. Make the automated nature and responsible institutional service clear.
2. Verify that the content, sending authority and contact route are approved.
3. Avoid implying personal review that did not happen.

What the team produces: A clear notice, accountable sender and usable support route.

Put responsibility in the right place.

Board & trustees

Ask whether institutional communications and services represent human involvement accurately.

Institutional leaders

Set consistent expectations across communications, services and academic contexts.

AI task force

Develop practical examples and route intellectual-property questions to qualified review.

Apply these roles within your institution’s actual governance and delegated authority.

Language to build on.

Illustrative model clause

AI involvement must be disclosed when it materially affects authorship, evaluation, interaction or understanding of an institutional decision. Communications must not imply human review or personal authorship that did not occur. Users must respect applicable intellectual-property, confidentiality and contractual requirements regardless of disclosure.

Copy the clause

Review this clause with the full policy and local requirements. It is an implementation starting point, not a statement of measured consensus.

Model policy §5→Model policy §8→Model policy §10→

Know whether it is working.

• Examples of acceptable notices for different uses.
• A clear process for rights and permissions questions.
• Communications that accurately represent the human involvement.

When to reconsiderRevisit when services become personalized, synthetic media becomes more realistic or an assistive workflow becomes autonomous.

Read the supporting sources.

Selected precedents and guidance supporting this chapter. These sources do not imply institutional endorsement of HumanSkills or agreement with every recommendation.

• Northcentral Technical College: Artificial Intelligence ↗Employee guidance
• River Parishes Community College: Use of Artificial Intelligence ↗Institutional policy

Source review: 24 September 2026. Read the editorial approach.

Continue the workGive the work an owner.

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See the wider
evidence and choices.

Read the research comparisons and explore the annotated library across US colleges, universities and international institutions. Use the model language as a starting point for your own decision.

Make meaningful AI involvement visible.→Make the policy yours→