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Module 7 · Lesson 1

Copyright and AI-Generated Content

Who owns what when a machine does the making — and what the courts have already decided.
If you typed the prompt, does that make you the author?

In February 2023, the U.S. Copyright Office issued a landmark ruling on Zarya of the Dawn — a graphic novel submitted by Kristina Kashtanova. The Office initially granted full registration, then rescinded protection for the AI-generated images created with Midjourney, while retaining copyright on Kashtanova's written text and the creative selection and arrangement of panels. The ruling was explicit: because the images were produced by Midjourney's autonomous system, Kashtanova lacked the human authorship required by U.S. copyright law.

That same month, the Copyright Office released formal guidance stating that AI-generated content alone is not copyrightable under current U.S. law, because copyright requires human creative expression. The standard is not whether a human was involved, but whether a human exercised creative control over the final expressive elements.

The Human Authorship Requirement

U.S. copyright law, rooted in the 1976 Copyright Act and interpreted through decades of case law, has always required a human author. The 1884 Supreme Court decision in Burrow-Giles Lithographic Co. v. Sarony established that photographs could be copyrighted because a human made creative choices about lighting, pose, and composition. That principle has never changed — it just now applies to AI tools.

The Copyright Office's March 2023 guidance on AI-generated works distinguishes three categories: (1) purely AI-generated content with no human creative input — not copyrightable; (2) AI-generated content where a human made sufficiently creative choices in selection, arrangement, or modification — potentially copyrightable to the extent of those human choices; (3) human-created work that used AI as a tool, similar to Photoshop filters — likely copyrightable in full.

The key phrase in the guidance is "sufficient human creative control." Typing a short prompt and accepting the AI's first output likely does not meet that standard. Iterating through hundreds of generations, selecting specific outputs, combining them with original writing, and making compositional choices pushes toward protectable expression.

Critical Case

In Thaler v. Vidal (Fed. Cir. 2022), the Federal Circuit affirmed that AI systems cannot be listed as inventors on U.S. patents. Stephen Thaler attempted to list his DABUS AI as the sole inventor of two patents. The court held that "inventors" must be natural persons under the Patent Act. The same human-authorship principle extends to copyright in creative works.

What This Means for Your Creative Work

If you are a writer, illustrator, musician, or designer using AI tools in your workflow, the practical implication is this: document your creative choices. Keep records of your prompts, the iterations you rejected, the modifications you made manually, and the editorial decisions that shaped the final work. This documentation becomes your evidence of human authorship if ownership is ever challenged.

For written text, the situation is considerably clearer. If you write text and use AI to polish grammar or suggest synonym choices — and you make the final decisions — the work is yours. If you paste a prompt into an AI and publish the unedited output verbatim, you likely hold no copyright in that output. Between those extremes lies a spectrum of creative collaboration that courts have not yet fully mapped.

Human AuthorshipThe U.S. Copyright Office requirement that copyrightable work reflect the creative expression of a natural person, not an autonomous machine process.
Sufficient Creative ControlThe threshold level of human decision-making over expressive elements — selection, arrangement, modification — that may qualify AI-assisted work for copyright protection.
Work Made for HireA copyright doctrine under which an employer or commissioning party owns work created by an employee or contractor. AI tools are not employees; this doctrine does not transfer AI output ownership to users.
Practical Takeaway

Register copyright on your AI-assisted creative work promptly, describe your human creative contributions clearly in the application, and keep a working log of your iterative process. The Copyright Office accepts applications for works containing AI-generated elements — you simply must disclose those elements and claim only the human-authored portions.

Quiz — Lesson 1

Copyright and AI-Generated Content · 5 questions
1. What did the U.S. Copyright Office conclude about the Midjourney images in Kristina Kashtanova's Zarya of the Dawn?
Correct. The Copyright Office retained protection for Kashtanova's original written text and arrangement while ruling the Midjourney-generated images lacked the required human authorship.
Not quite. The ruling was nuanced: the AI images lost protection, but Kashtanova's written text and creative arrangement retained copyright. Review the Zarya ruling in Lesson 1.
2. Under current U.S. Copyright Office guidance, which of the following is most likely to be copyrightable?
Correct. When a human writes the text and makes all final creative decisions — even with AI suggestions — the work reflects sufficient human authorship for copyright protection.
Not quite. The Copyright Office's standard focuses on whether a human exercised creative control over expressive elements. Unmodified AI output typically doesn't meet this standard.
3. What did the Federal Circuit rule in Thaler v. Vidal (2022)?
Correct. The Federal Circuit held that the Patent Act requires inventors to be natural persons — AI systems cannot hold inventorship, reinforcing the human-authorship principle across intellectual property law.
Not quite. The court was unambiguous: under the Patent Act, inventors must be natural persons. DABUS could not be listed as an inventor at all.
4. Which 1884 Supreme Court case established that copyright requires human creative choices?
Correct. Burrow-Giles (1884) held that photographs could be copyrighted because a human made creative choices about lighting, pose, and composition — establishing the human creative expression standard still applied today.
Not quite. Burrow-Giles Lithographic Co. v. Sarony (1884) is the foundational case that tied copyright to human creative choices, specifically in the context of photography.
5. When registering a copyright on AI-assisted creative work with the U.S. Copyright Office, what must an applicant do regarding AI-generated elements?
Correct. The Copyright Office requires disclosure of AI-generated content in applications. Applicants claim protection only for the human-authored elements, not the AI output itself.
Not quite. The Copyright Office requires honest disclosure of AI involvement and limits protection to the human-authored portions — concealing AI use can invalidate a registration.

Lab 1 — Copyright Ownership Analysis

Practice identifying what is and isn't copyrightable in AI-assisted creative work.

Your Scenario

You're a creative professional deciding how to protect your AI-assisted work. Describe a specific creative project — a novel, an illustrated article, a music album, a design portfolio — and explain how you used AI in its creation. The assistant will help you analyze which elements are likely copyrightable, which aren't, and how to document your human creative contributions.

Try: "I wrote a thriller novel where I used Claude to help brainstorm plot twists. I wrote all the prose myself. How do I protect this?" — or describe your own creative workflow.
Copyright Analysis Assistant
M7 · L1
Welcome to Lab 1. I'm here to help you think through copyright ownership for your AI-assisted creative work. Tell me about a specific project — what did you create, and how did AI tools factor into your process? The more detail you share, the more precise my analysis can be.
Module 7 · Lesson 2

Training Data, Scraped Work, and the Lawsuit Landscape

Your published work may already be inside an AI model — here is what legal action has actually achieved.
When AI learns from your work without permission, what recourse do you have?

In January 2023, three visual artists — Sarah Andersen, Kelly McKernan, and Karla Ortiz — filed suit in the Northern District of California against Stability AI, Midjourney, and DeviantArt, alleging that their artwork was scraped from the internet and used to train image-generation models without consent or compensation. The complaint invoked copyright infringement and right of publicity violations, arguing that the models effectively encoded their artistic styles in a way that allowed users to generate images "in the style of" named artists.

That same month, Getty Images filed suit against Stability AI in the UK High Court of Justice and separately in the U.S. District of Delaware, alleging that Stability AI scraped 12 million images from Getty's licensed library without permission. Getty's complaint included evidence of Stability AI's DALL-E competitor producing images that still contained distorted Getty watermarks — a striking indication of direct training on protected material.

The Legal Theories in Play

These lawsuits are testing several distinct legal theories simultaneously. The first is direct copyright infringement during training: the argument that copying millions of images or text passages into training datasets, even temporarily, constitutes reproduction under 17 U.S.C. § 106. AI companies counter that this constitutes fair use — transformative use for research and technological development.

The second theory concerns outputs that are substantially similar to training data. This is harder to prove: AI models do not store images literally, but plaintiffs argue that when a model reliably produces outputs "in the style of" a specific artist, the model has encoded protected expression in a form that infringes upon generating similar outputs. Courts have not yet resolved whether this theory survives.

In November 2023, a federal judge in the Andersen v. Stability AI case dismissed most claims but allowed a direct infringement claim by artist Andersen to proceed regarding images that were allegedly reproduced too closely to her specific work. This was a partial victory for plaintiffs — establishing that the door to infringement claims is not closed.

The Writers Guild Cases

In September 2023, the Authors Guild filed suit against OpenAI, alleging that GPT models were trained on books scraped without authorization. Separately, authors including John Grisham, Jodi Picoult, and George R.R. Martin filed a class action against OpenAI in the same month. These cases focus on text: the argument that a language model trained on complete novels without licensing them infringes the reproduction right, regardless of whether outputs directly copy those novels.

The Fair Use Defense

AI companies have consistently advanced fair use as their primary defense. Fair use analysis under 17 U.S.C. § 107 weighs four factors: (1) the purpose and character of the use (commercial vs. educational; transformative vs. reproductive); (2) the nature of the copyrighted work; (3) the amount and substantiality of the portion used; and (4) the effect on the market for the original work.

The strongest argument for AI companies is transformativeness: in Authors Guild v. Google (2d Cir. 2015), the Second Circuit held that Google's mass digitization of books to create a searchable index was transformative fair use. AI companies argue their training use is analogous. Critics counter that unlike Google's index, AI models generate commercial products that directly compete with the original creators' markets — which weighs heavily against fair use on factor four.

No appellate court has yet ruled on AI training fair use. The outcomes of the pending cases — expected to produce significant rulings by 2025 and 2026 — will define the legal landscape for a generation of creative workers.

Training Data ScrapingThe automated collection of publicly available images, text, or audio from the internet to create datasets used to train AI models, without necessarily obtaining permission from copyright holders.
Substantial SimilarityThe legal standard for copyright infringement of expression: whether an ordinary observer would recognize the allegedly infringing work as taken from the copyrighted original.
Fair Use (§ 107)A statutory defense to copyright infringement based on four factors, including transformativeness and market effect. Currently the central dispute in AI training data litigation.
What Creators Can Do Now

Register your copyright promptly — registration is a prerequisite for statutory damages and attorney's fees in U.S. infringement suits. Opt out of AI training datasets where opt-out mechanisms exist (Adobe Firefly, OpenAI's web crawler opt-out via robots.txt). Track whether your work appears in training datasets using tools like Have I Been Trained (haveibeentrained.com). Document your publication dates and creative process for any future infringement claims.

Quiz — Lesson 2

Training Data, Scraped Work, and the Lawsuit Landscape · 5 questions
1. What notable evidence did Getty Images present in its lawsuit against Stability AI?
Correct. The distorted watermarks in AI outputs were compelling evidence that the model had been trained directly on Getty's watermarked licensed images without permission.
Not quite. The striking evidence was that generated images still contained distorted Getty watermarks — visually demonstrating that the model had trained on Getty's watermarked library.
2. In the Andersen v. Stability AI case, what did the federal judge rule in November 2023?
Correct. The judge dismissed most claims but permitted Andersen's direct infringement claim to proceed — a partial victory establishing that such claims are not categorically foreclosed.
Not quite. The ruling was mixed: most claims were dismissed, but Sarah Andersen's direct infringement claim survived, keeping the litigation alive on that theory.
3. Which precedent do AI companies most frequently cite in their fair use defense for training data?
Correct. The Second Circuit's ruling in Authors Guild v. Google — holding that mass digitization of books for a searchable index was transformative fair use — is the key precedent AI companies invoke to argue training data use is similarly transformative.
Not quite. AI companies lean heavily on Authors Guild v. Google (2d Cir. 2015), where mass book digitization was found to be transformative fair use, arguing their training use is analogous.
4. Which of the four fair use factors is most damaging to AI companies' training data defense, according to critics?
Correct. Critics argue that unlike Google's index, AI models generate commercial outputs that directly compete with the original creators — a market substitution effect that weighs heavily against fair use on factor four.
Not quite. Factor 4 — market effect — is the most problematic for AI companies, because their tools generate commercial outputs that can substitute for the original creators' work, unlike Google's search index.
5. What practical step can creators take to potentially exclude their work from future AI training datasets?
Correct. Robots.txt opt-outs and platform-specific mechanisms (like OpenAI's GPTBot exclusion and Adobe's opt-out) are currently the most reliable practical tools creators have to signal non-consent for AI training.
Not quite. The most accessible current tools are robots.txt directives and opt-out mechanisms offered by specific AI platforms. No universal AI-exclusion registry or watermark standard currently exists.

Lab 2 — Training Data Rights Advisor

Explore your options when your creative work may have been used to train AI models.

Your Scenario

You're a professional creative — illustrator, author, photographer, or musician — who has published work online and is concerned about AI training data use. Use this lab to investigate your legal options, understand the current lawsuit landscape, and identify practical protective steps specific to your medium.

Try: "I'm a freelance illustrator. My work has been on ArtStation for five years. What are my realistic options if Midjourney trained on my images?" — or ask about your own situation.
Training Data Rights Advisor
M7 · L2
Welcome to Lab 2. Tell me about your creative work and your concerns about AI training data use. I can walk you through the current legal landscape, what the active lawsuits mean for creators in your field, and what practical steps you can take right now to protect your interests.
Module 7 · Lesson 3

Disclosure, Attribution, and Professional Ethics

When should you tell your audience — or your client — that AI helped you create?
Is undisclosed AI use in professional creative work a form of deception?

In June 2023, the science fiction magazine Clarkesworld — one of the most respected short fiction publications in the field — was forced to temporarily close submissions after receiving a flood of AI-generated stories submitted as human work. Editor Neil Clarke reported that submission volume had increased fivefold, with the vast majority being machine-generated text submitted without disclosure. The magazine had to implement new screening protocols and explicitly ban AI-generated submissions.

In July 2023, Sports Illustrated was found to have published articles under fictional AI-generated author bylines — complete with fabricated headshots produced by an AI avatar service. The publication's parent company, The Arena Group, initially denied the articles were AI-generated before later acknowledging the use of AI content tools. The incident resulted in significant reputational damage and raised serious questions about disclosure obligations in journalism.

Industry Standards Are Forming Rapidly

The response from professional organizations has been swift. The Authors Guild issued AI disclosure guidelines in 2023, stating that authors should disclose significant AI assistance in the creation of work submitted for publication. The Society of Professional Journalists updated its ethics code guidance to address AI tools, emphasizing that journalists must disclose AI use that materially affects the content of published reporting.

In academic publishing, major journals moved quickly. Nature announced in January 2023 that AI tools cannot be listed as authors, that their use must be disclosed in methods sections, and that authors bear full responsibility for AI-assisted content. Science, The Lancet, and most major academic publishers followed with similar policies within weeks. The International Association of Scientific, Technical and Medical Publishers (STM) issued joint guidance endorsing disclosure as the baseline standard.

For visual artists and designers, the situation is more complex. The Graphic Artists Guild and the American Institute of Graphic Arts (AIGA) have both issued position statements encouraging disclosure when AI generation was used in client work. But no binding professional standard yet governs client contracts in most jurisdictions.

The Getty Images Policy

In September 2022, Getty Images banned AI-generated images from its platform entirely, citing legal uncertainty and the rights of contributing photographers. In 2023, Getty reversed course and launched its own licensed AI image generator trained only on its licensed content, with compensation to contributing photographers built into the model. This illustrates how platforms are being forced to develop explicit disclosure and compensation frameworks — creating a precedent for the broader industry.

Client Contracts and Commercial Disclosure

For freelancers and agencies, disclosure to clients is increasingly a contractual and ethical obligation. Several major advertising agencies — including WPP and Publicis — have developed internal AI use policies that require disclosure to clients when AI tools are used in campaign creation. The underlying concern is twofold: clients want to ensure they are receiving what they are paying for, and clients need to know about potential copyright complications in AI-generated elements they intend to use commercially.

A practical standard emerging in commercial creative work is the "material assistance" threshold: if AI performed work that a human would otherwise have been paid to perform (writing copy, generating images, composing music), that use should be disclosed. If AI was used as a productivity tool analogous to spell-check or a thesaurus, disclosure is generally not required by emerging norms — though some clients contractually require disclosure of any AI use.

Check your contracts carefully. An increasing number of publishers, studios, and clients are including explicit AI disclosure and warranty clauses, requiring creators to warrant that delivered work was not substantially created by AI without prior written approval.

Material Assistance ThresholdAn emerging disclosure standard: AI use should be disclosed when AI performed creative work a human would otherwise have been paid to perform, not when used as a minor productivity tool.
AI Disclosure ClauseA contract provision requiring creators to warrant that their delivered work was not substantially generated by AI, or to obtain prior approval before using AI generation tools.
Byline IntegrityThe journalistic principle that a byline accurately represents who created the work. Publishing AI-generated text under a human or fictitious byline without disclosure violates this standard.
A Working Disclosure Framework

When in doubt, disclose upward — to clients, editors, and audiences — rather than downward. Describe specifically what AI did (generated image drafts, suggested structural outlines, produced alternative copy options) and what you did (selected, modified, directed, edited, approved). This framing positions AI as a tool you deployed rather than a replacement for your creative judgment — which is both more honest and more protective of your professional reputation.

Quiz — Lesson 3

Disclosure, Attribution, and Professional Ethics · 5 questions
1. What triggered Clarkesworld magazine's temporary closure of submissions in early 2023?
Correct. Editor Neil Clarke reported that the overwhelming majority of new submissions were AI-generated text submitted without disclosure, forcing the magazine to close submissions and implement new screening protocols.
Not quite. Clarkesworld was overwhelmed by undisclosed AI-generated submissions — submission volume increased fivefold, with most being machine-generated text presented as human work.
2. What policy did the journal Nature announce in January 2023 regarding AI tools?
Correct. Nature's policy set the standard quickly adopted by most major academic publishers: no AI authorship, mandatory disclosure of use, and human authors retain full accountability.
Not quite. Nature's policy has three elements: AI cannot be listed as an author, AI use must be disclosed in methods sections, and human authors remain fully responsible for any AI-assisted content.
3. What was the nature of the Sports Illustrated AI controversy in July 2023?
Correct. The magazine published AI-generated articles under entirely fictitious author names with fabricated AI-generated headshots — a clear violation of byline integrity and disclosure obligations in journalism.
Not quite. The specific issue was fabricated author identities: AI-generated articles were published under made-up bylines with AI-generated profile photos, misrepresenting both the content's origin and its supposed authors.
4. What is the "material assistance threshold" as an emerging disclosure norm?
Correct. The material assistance threshold distinguishes between AI as a substantive creative contributor (requiring disclosure) versus AI as a minor workflow tool analogous to spell-check (generally not requiring disclosure under emerging norms).
Not quite. The emerging norm focuses on whether AI performed work a human would otherwise have been paid to do — that's the threshold for disclosure — rather than any bright-line percentage or technical standard.
5. How did Getty Images ultimately respond to the challenge of AI-generated images on its platform?
Correct. Getty's evolution — from ban to building its own licensed, compensating AI generator — illustrates the broader industry pattern of establishing controlled frameworks rather than outright prohibition.
Not quite. Getty's response evolved: initial ban, then development of its own AI generator trained exclusively on licensed content, with photographer compensation built in — a model for licensed AI generation.

Lab 3 — Disclosure Statement Workshop

Draft professional AI disclosure language for real-world creative and commercial situations.

Your Scenario

You need to communicate your AI use to a client, editor, publisher, or audience. This lab helps you craft clear, professional disclosure language appropriate to your specific situation — one that is honest, specific about what AI did and what you did, and positions your creative judgment as the driving force.

Try: "I'm a copywriter who used Claude to generate ten different headline options, then rewrote the best one substantially. How should I disclose this to my agency client?" — or describe your own disclosure need.
Disclosure Statement Workshop
M7 · L3
Welcome to Lab 3. I'll help you craft disclosure language that's honest, specific, and professionally appropriate. Tell me about your situation: what type of creative work did you produce, what did the AI tool specifically do in your process, and who needs to receive the disclosure — a client, an editor, a publication, or a general audience?
Module 7 · Lesson 4

Contracts, Licensing, and Protecting Your Future Work

How to use agreements to claim your AI-assisted output, limit others' rights to train on your work, and negotiate in an evolving landscape.
What contract language can actually protect your creative output from being used to train AI?

In July and August 2023, the Screen Actors Guild–American Federation of Television and Radio Artists (SAG-AFTRA) struck against the major studios in part over AI protections — specifically, the right of studios to scan an actor's likeness and use it in AI-generated performances without additional compensation or consent. The strike, which ended in November 2023 with a new contract, won explicit protections: studios must obtain consent before creating a digital replica of a performer's likeness, and residuals must be paid when such replicas are used. The agreement established a precedent for consent and compensation frameworks across the entertainment industry.

Simultaneously, the Writers Guild of America (WGA), which had been on strike since May 2023, secured in its September 2023 contract that AI cannot write or rewrite literary material used in Guild-covered productions, that AI-generated material does not constitute "literary material" under the MBA (Minimum Basic Agreement), and that writers cannot be required to use AI tools. The WGA deal also required studios to disclose when AI-generated material is given to writers as source material.

Key Contract Provisions for Creative Professionals

The SAG-AFTRA and WGA agreements set a template that is influencing contracts far beyond Hollywood. The provisions that matter most for working creatives fall into several categories:

AI Generation Restrictions: Language stating that AI cannot be used to generate, substantially rewrite, or replace the contracted human's creative output without written approval. This is now standard in many book publishing contracts, particularly for major commercial publishers, and is being negotiated into music recording agreements.

Likeness and Voice Protections: Post-SAG-AFTRA, contracts in music, voice acting, and modeling increasingly include explicit prohibitions on creating AI replicas of an individual's likeness, voice, or performance style without consent and additional compensation.

Training Data Exclusions: Contract language specifying that delivered work product cannot be used to train AI models — by the contracting party, its licensees, or any third parties. This has become a standard ask in contracts between creators and tech platforms.

IP Ownership Clarity: Language explicitly establishing that the creator — not the AI tool used — owns the copyright in the delivered work, and that the contracting party receives only the rights explicitly granted.

Terms of Service and Your Work

Every AI tool's Terms of Service contains provisions about ownership of outputs and potential use of your inputs. OpenAI's Terms (as of 2024) state that users own their outputs and OpenAI does not claim rights in them, but that OpenAI may use inputs to improve services. Adobe Firefly's Terms state that images generated using licensed content are safe for commercial use and indemnified by Adobe. Midjourney's Terms previously granted users only a limited license to outputs (with full commercial use requiring a paid plan) and included broad rights for Midjourney to use generated images. Read the ToS of every tool you use commercially. These terms change — set a calendar reminder to review them annually.

Licensing Your AI-Assisted Work

If you are licensing — rather than selling outright — your creative work, the license agreement must address AI specifically. A robust license for AI-assisted creative work should: (1) specify which elements of the work are human-authored and which were AI-generated; (2) limit the licensee's right to use the work as training data for AI systems; (3) include a "no derivative AI works" clause if you do not want the licensee to feed your work into an AI to generate variations; and (4) require the licensee to pass the training-data restriction through to any sublicensees.

For musicians and songwriters, the emergence of AI voice-cloning and style-transfer tools has made it essential to address these explicitly in sync licenses, recording contracts, and producer agreements. A growing number of music publishers are including "AI voice clone" restrictions in standard deal language — prohibiting licensees from creating AI-generated performances in an artist's voice using licensed sound recordings as training material.

Digital ReplicaAn AI-generated likeness, voice, or performance that realistically replicates a specific person's appearance or sound. SAG-AFTRA's 2023 contract established consent and compensation requirements for their creation in entertainment contexts.
Training Data ExclusionA contract clause explicitly prohibiting a contracting party or its licensees from using delivered creative work as training data for AI models.
No Derivative AI WorksA license restriction prohibiting the licensee from inputting the licensed work into an AI system to generate derivative variations or outputs.
Module Summary: Your Protection Checklist

Register copyrights promptly with the Copyright Office, disclosing AI elements and claiming human-authored portions. Document your creative process — prompts, iterations, decisions. Implement robots.txt opt-outs. Review every AI tool's Terms of Service annually. Add AI-specific provisions to your contracts: training data exclusions, digital replica protections, IP ownership clarity. Disclose AI use to clients and editors at the "material assistance" threshold. Follow the SAG-AFTRA and WGA precedents: consent, disclosure, and compensation are the three pillars of fair AI use in professional creative work.

Quiz — Lesson 4

Contracts, Licensing, and Protecting Your Future Work · 5 questions
1. What specific AI protection did SAG-AFTRA win in its 2023 contract agreement?
Correct. SAG-AFTRA's landmark win established the consent-and-compensation framework: studios cannot create digital replicas without performer consent, and residuals are owed when those replicas are used in productions.
Not quite. SAG-AFTRA won a consent-and-compensation framework, not an outright ban. Studios can create digital replicas only with performer consent and must pay residuals for their use.
2. What did the WGA's 2023 contract establish about AI writing scripts?
Correct. The WGA agreement explicitly bars AI from writing or rewriting literary material in covered productions, and protects writers from being compelled to use AI tools. It also requires disclosure when AI-generated material is provided as source material to writers.
Not quite. The WGA contract is more protective: AI cannot write or rewrite production scripts, AI output is not "literary material" under the MBA, and writers cannot be forced to use AI tools at all.
3. Which of the following is a "training data exclusion" clause?
Correct. A training data exclusion clause specifically prevents the party receiving your creative work from using it as training input for AI systems — either directly or through sublicensees.
Not quite. A training data exclusion clause is a protective provision that explicitly bars the contracting party from using your delivered work as AI training data — its purpose is to prevent your work from being incorporated into future AI models.
4. Regarding AI output ownership, what do OpenAI's Terms of Service (as of 2024) state?
Correct. OpenAI's terms assign output ownership to users and disclaim OpenAI's rights in those outputs — but OpenAI retains the right to use inputs for service improvement, which is why training data exclusion clauses in your client contracts matter.
Not quite. OpenAI's Terms state users own their outputs and OpenAI doesn't claim rights in them — but OpenAI may use inputs to improve its models. The output ownership provision is favorable to users; the input-use provision is a separate consideration.
5. What is a "no derivative AI works" clause in a creative license?
Correct. A no derivative AI works clause protects the licensor by prohibiting the licensee from feeding the licensed work into AI systems to generate new variations — preventing indirect exploitation of your work through AI-generated derivatives.
Not quite. This clause protects the licensor (you) by preventing the licensee from using your work as AI input to generate derivative variations — it runs against the licensee, not the creator.

Lab 4 — Contract Clause Builder

Draft AI-protective contract language for your specific creative work and professional context.

Your Scenario

You need to add AI-protective provisions to a contract you're negotiating — or reviewing one that a client has sent you. This lab helps you draft specific clause language for training data exclusions, digital replica protections, IP ownership clarity, and disclosure obligations appropriate to your creative field.

Try: "I'm a freelance illustrator about to sign a contract with a tech company for product illustrations. What AI-specific clauses should I add to protect my work from being used as training data?" — or describe your own contract situation.
Contract Clause Builder
M7 · L4
Welcome to Lab 4. I'll help you build contract language that protects your creative work in the AI era. Tell me about your situation: what type of creative work are you contracting for, who is the other party (publisher, tech company, ad agency, studio, private client), and what aspect of AI protection concerns you most — training data use, digital replicas, IP ownership, or disclosure requirements?

Module 7 — Final Test

Protecting Your Work and Your Credit · 15 questions · Pass at 80%
1. Under current U.S. copyright law, what is the fundamental requirement for a work to receive copyright protection?
Correct. Human authorship — creative expression by a natural person — is the foundational requirement for U.S. copyright protection, established in case law dating to 1884.
Not quite. Copyright requires human authorship: the creative expression of a natural person. Registration is beneficial but not required for the copyright to exist; automated processes alone cannot create copyrightable work.
2. In the Zarya of the Dawn ruling, which elements of Kristina Kashtanova's work retained copyright protection?
Correct. The Copyright Office's ruling preserved protection for the human-authored elements — the written text and the creative arrangement of content — while removing it from the autonomously generated Midjourney images.
Not quite. The ruling was nuanced: the written text and creative arrangement (human-authored elements) retained copyright; the Midjourney-generated images (autonomously created) lost protection. AI elements do not void the entire work.
3. What is the primary argument AI companies make in their fair use defense for using copyrighted works as training data?
Correct. Transformativeness is the central fair use argument, with Authors Guild v. Google (2015) as the key precedent. The counterargument focuses on market effect: unlike Google's index, AI tools generate commercial outputs competing with original creators.
Not quite. The primary argument is transformativeness — that training use creates something fundamentally different from the original works, similar to how Google's digitization created a searchable index. Market effect (factor 4) is where this argument faces its greatest challenge.
4. What did the partial ruling in Andersen v. Stability AI (November 2023) establish?
Correct. The ruling's significance was that it kept the door open for direct copyright infringement claims — the court didn't dismiss all claims, signaling that certain theories of AI-related infringement remain viable.
Not quite. The ruling was mixed: most claims were dismissed, but Andersen's direct infringement claim survived. The key takeaway is that direct infringement claims against AI companies are not categorically barred at the pleading stage.
5. Which professional organization was the first major scientific publisher to establish that AI tools cannot be listed as authors on submitted papers?
Correct. Nature's January 2023 policy — no AI authorship, mandatory disclosure, human author accountability — set the template quickly adopted by Science, The Lancet, and most major academic publishers.
Not quite. Nature published its landmark AI authorship policy in January 2023, establishing the template — no AI authors, mandatory disclosure, human accountability — that was rapidly adopted across academic publishing.
6. The "material assistance threshold" for AI disclosure means that disclosure is generally expected when:
Correct. The material assistance threshold focuses on whether AI substituted for compensable human creative labor — not on minor workflow tools or precise percentage calculations.
Not quite. The threshold is about whether AI did work a human would have been paid to do. Grammar checking and thesaurus use generally don't meet this bar; generating images, copy, or music drafts generally does.
7. What is a "digital replica" as defined by the SAG-AFTRA 2023 contract?
Correct. In the SAG-AFTRA framework, digital replicas are AI-generated likenesses or voices that realistically reproduce a specific performer — the consent and compensation requirements apply specifically to these AI-created replicas.
Not quite. A digital replica in the SAG-AFTRA context means an AI-generated reproduction of a performer's likeness, voice, or performance — the kind created by training AI on that performer's work and then generating new content in their image or voice.
8. When registering copyright on AI-assisted work with the U.S. Copyright Office, what is the applicant's obligation regarding AI-generated content?
Correct. Full disclosure of AI elements is required, and registration covers only the human-authored portions. Concealing AI involvement can invalidate the registration.
Not quite. The Copyright Office does accept registrations for AI-assisted works. The requirements are: disclose AI-generated elements and claim protection only for the human-authored portions of the work.
9. What did the WGA's 2023 contract require studios to do when giving writers AI-generated material to work from?
Correct. The WGA contract's disclosure requirement runs in both directions: studios cannot use AI to write scripts, and when they provide AI-generated material as source for writers, they must disclose its AI origin.
Not quite. The WGA contract includes a transparency provision: if studios give writers AI-generated material as source content, they must disclose that it was AI-generated — ensuring writers know what they are working with.
10. What did Getty Images ultimately do after initially banning AI-generated images from its platform?
Correct. Getty's pivot from ban to building its own compensating AI generator established a precedent: rather than permanent exclusion, structured licensed use with creator compensation is a viable industry response.
Not quite. Getty built its own AI image generator trained exclusively on its licensed image library, with photographer compensation built into the model — demonstrating that licensed, compensating AI generation is a viable alternative to uncontrolled scraping.
11. Which case established that Google's mass digitization of books for a searchable index was transformative fair use?
Correct. Authors Guild v. Google (2d Cir. 2015) is the precedent AI companies rely on most heavily in their training data fair use defense — the Second Circuit found Google's book scanning for a searchable index to be transformative fair use.
Not quite. Authors Guild v. Google (2d Cir. 2015) is the key case: the Second Circuit held that scanning books to create a searchable index was transformative fair use, which AI companies argue is analogous to training data use.
12. What is the primary function of a "training data exclusion" clause in a creative services contract?
Correct. A training data exclusion clause is a forward-looking protective provision: it prevents the party receiving your work from using it — directly or through sublicensees — as AI training input, blocking one of the primary ways creative work is currently exploited without compensation.
Not quite. This clause protects your work from being fed into future AI training pipelines. It runs against the party receiving your work, prohibiting them and their licensees from using your deliverable as AI training data.
13. In Thaler v. Vidal (Fed. Cir. 2022), the court held that under the Patent Act:
Correct. Thaler v. Vidal confirmed that the human-authorship principle applies in patent law as in copyright: only natural persons can be inventors, reinforcing the broader framework that excludes AI from legal personhood in intellectual property contexts.
Not quite. The Federal Circuit was unambiguous: the Patent Act's use of "individuals" means natural persons. DABUS could not be listed as an inventor, and Thaler had no standing to claim the patents himself since he was not the inventor of the specific contributions.
14. What practical documentation practice is most important for establishing copyright in AI-assisted creative work?
Correct. Process documentation — showing your prompts, the variations you rejected, the modifications you made, and the editorial judgments that shaped the work — is the evidence of human creative control that supports copyright claims in AI-assisted work.
Not quite. Your evidence of human authorship is your process documentation: the prompts you crafted, the iterations you selected from and rejected, the manual edits you made, and the creative decisions that drove those choices. This documentation demonstrates the human creative control that copyright law requires.
15. The three pillars of the SAG-AFTRA and WGA AI frameworks — which have become the reference model for fair AI use in professional creative work — are:
Correct. The SAG-AFTRA and WGA agreements establish consent (permission before use), disclosure (transparency about AI involvement), and compensation (payment when AI substitutes for or uses human creative work) as the foundational standards for fair AI use in professional creative contexts.
Not quite. Both major 2023 labor agreements converge on the same three principles: consent (you must agree before your work or likeness is used), disclosure (AI use must be transparent), and compensation (use of your creative work in AI contexts requires payment).