Who Owns the AI Tutor? Faculty Intellectual Property, Publisher Licenses and Copyright

Course materials, AI agents, licenses and fair use: what is decided, what is argued, and how to write the policy

A higher education course from ibl.ai (self-paced, 7 to 9 hours, free). An intermediate, self-paced course for academic leaders, counsel, faculty senates, librarians and instructional designers on who owns course materials and the AI tutors built from them, what publisher licenses allow, what the Copyright Office and the courts have concluded about AI, and how to write a campus policy, taught from the Copyright Act, Copyright Office reports, court opinions, AAUP statements and published university policies.

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Course description

Who Owns the AI Tutor? teaches the ownership, licensing and copyright questions that arise when AI agents are built from faculty course materials. You will learn what copyright protects in a course, how the work-made-for-hire doctrine applies to faculty and why the academic exception remains unsettled, what the AAUP says, and how published university IP policies at the University of California, Stanford and the University of Scranton allocate ownership. You will separate an agent into its parts, apply the Copyright Office's conclusions on AI-generated material and digital replicas, and work through faculty-built and institution-built agents and departing faculty. You will read publisher and library license language on AI and text and data mining, the four fair use factors and the education cases, the Copyright Office's report on AI training and the decided court cases, each labelled for what it did and did not decide. The course ends with a draft campus policy section of your own. Last verified 2026-11-03. Training, not legal advice.

About this course

When an AI tutor is built on a professor's lectures, slides and a publisher's textbook, who owns it, who may keep running it, and what may go into it? This course gives provosts, counsel, faculty senates, teaching centers, librarians and instructional designers a working method for those questions, taught from primary sources: the Copyright Act, the U.S. Copyright Office's Copyright and Artificial Intelligence reports, the court opinions themselves, AAUP statements, published university IP policies and library and publisher license language. Every legal statement is labelled by what it is: statute, a court's holding, the Copyright Office's view, or an argument. Worked examples, templates, labs and an AI tutor turn the sources into policy you can take to your senate and your general counsel.

What you will be able to do

  1. Explain who owns course materials under the Copyright Act's default rules, the work-made-for-hire definition in 17 U.S.C. § 101 and § 201(b), and the unsettled academic exception, stating what Hays v. Sony and Weinstein v. University of Illinois did and did not decide.
  2. Read an institutional IP policy clause by clause and classify course materials by likely ownership, comparing published policies such as those of the University of California, Stanford and the University of Scranton with the AAUP's positions.
  3. Separate an AI agent built from a professor's materials into its components and state the rights of the faculty member and the institution in each, including AI-generated outputs, voice and likeness, and what happens when the faculty member leaves.
  4. Read publisher and database license terms on AI use and text and data mining, mark up a restrictive clause, and route licensed content through the library before it enters an agent.
  5. Summarize what the U.S. Copyright Office has concluded in its three Copyright and Artificial Intelligence reports and how fair use has been argued and decided in the AI training cases, labelling each statement by its source and status.
  6. Draft a campus policy section covering faculty-built and institution-built agents, consent and agreements, licensed content, likeness, departing faculty, attribution and student work, consistent with your own institution's IP policy.

Who this course is for

Roles: provosts, deans and academic affairs staff; general counsel offices; faculty senate leaders and IP committee members; teaching and learning center staff; library copyright, licensing and scholarly communication officers; instructional designers and online learning units.

Institutions: colleges and universities in the United States that are building or buying AI agents for teaching, or writing policy for them.

Before you start: no legal training is needed. Have your institution's intellectual property or copyright policy at hand, and any AI policy or recordings policy; the labs and the capstone ask you to work from them.

Format

Time: 7 to 9 hours, self-paced. Level: intermediate.

Structure: a Start here section, four content sections of readings, worked examples, templates and hands-on labs, each ending in an AI assessment, and a capstone in which you draft a campus policy section on AI agents built from course materials, followed by a reading list.

Grading: the four section AI assessments count for 60 percent of the grade and the capstone assessment for 40 percent. The pass mark is 70 percent.

Currency

Last verified 2026-11-03 against the Copyright Act, the Copyright Office's AI page and reports, and the court opinions cited, including the Third Circuit's September 29, 2026 decision in Thomson Reuters v. ROSS Intelligence.

The law and practice are still changing. On the verification date the Copyright Office listed Part 3 of its report, on generative AI training, as a pre-publication version, lawsuits over AI training were still pending, and universities and faculty unions were writing and negotiating AI provisions. Check the current sources before relying on any page, and take specific questions to your general counsel's office. This course is training, not legal advice.

Outline

  1. Section 0 · Start here

    • 0.1 Welcome and orientation
  2. Section 1 · Know who owns course materials

    • 1.1 Copyright, work made for hire and the AAUP
    • 1.2 Reading campus IP policies
    • 1.3 Section 1 assessment
  3. Section 2 · Decide who owns an agent built from a professor's materials

    • 2.1 The agent's parts, AI outputs and likeness
    • 2.2 Faculty-built, institution-built and after departure
    • 2.3 Section 2 assessment
  4. Section 3 · Read licenses and apply fair use, as argued and as decided

    • 3.1 Publisher and database licenses
    • 3.2 Fair use, the Copyright Office and the courts
    • 3.3 Section 3 assessment
  5. Section 4 · Write campus policy for faculty-built and institution-built agents

    • 4.1 The policy decisions
    • 4.2 Drafting and adoption
    • 4.3 Section 4 assessment
  6. Section 5 · Capstone and wrap-up

    • 5.1 Capstone: draft your campus policy on AI agents built from course materials
    • 5.2 Capstone assessment
    • 5.3 Reading list and next steps