1. Introduction

AI-generated tourism storytelling involves the use of artificial intelligence systems to create:

Narratives about local provinces

Cultural histories and folklore

Virtual tour scripts

Audio-visual guides

Promotional materials

These AI systems may rely on large datasets, including copyrighted books, photographs, travel blogs, archival records, and audiovisual works. This creates two major legal questions:

Who owns AI-generated tourism content?

Does AI training or output infringe existing copyrights?

Copyright law traditionally protects human authorship, so AI-generated works challenge foundational doctrines.

PART I: AUTHORSHIP AND OWNERSHIP OF AI-GENERATED WORKS

2. Human Authorship Requirement

Most copyright systems require human creativity.

🔹 Case 1: Burrow-Giles Lithographic Co. v. Sarony

Facts:
Napoleon Sarony photographed Oscar Wilde. A company reproduced it without permission.

Issue:
Can a photograph be copyrighted?

Decision:
Yes — because it reflected Sarony’s creative choices (pose, lighting, composition).

Legal Principle:
Copyright protects works that originate from human intellectual conception.

Relevance to AI Tourism Storytelling:
If AI autonomously generates a tourism story without meaningful human creative input, it may lack copyright protection, because there is no human author.
However, if a tourism board official carefully designs prompts, selects outputs, edits the narrative, and curates structure, copyright may vest in that human.

🔹 Case 2: Feist Publications, Inc. v. Rural Telephone Service Co.

Facts:
Rural Telephone published a directory. Feist copied listings.

Issue:
Are facts protected by copyright?

Decision:
No. Facts are not protected; only original selection and arrangement are protected.

Legal Principle:
Copyright requires originality, not mere compilation of facts.

Relevance:
AI tourism storytelling often includes:

Historical dates

Geographic facts

Cultural information

Facts about a province are not protected, but creative narrative structuring is.
If AI merely reorganizes factual data, copyright protection may be weak.

3. AI as Non-Human Author

🔹 Case 3: Naruto v. Slater

Facts:
A monkey named Naruto took selfies using a photographer’s camera. PETA sued claiming copyright on behalf of the monkey.

Decision:
The court held that non-humans cannot hold copyright.

Legal Principle:
Only humans (or legal entities representing humans) can be authors.

Relevance:
AI systems generating tourism narratives cannot be copyright owners.
If an AI autonomously creates a tourism video script for a province without human creative control, the work may fall into a legal gray area or public domain.

🔹 Case 4: Thaler v. Perlmutter

Facts:
Stephen Thaler tried to register a work created entirely by his AI system “Creativity Machine.”

Decision:
The court ruled copyright requires human authorship.

Legal Principle:
AI-generated works without human input are not registrable.

Relevance to Tourism Storytelling:
If a provincial tourism board uses fully autonomous AI to generate brochures, those materials may not qualify for copyright protection — meaning competitors could potentially reuse them.

PART II: COPYRIGHT INFRINGEMENT DURING AI TRAINING

4. Use of Copyrighted Data to Train AI

AI systems are trained on massive datasets, which may include:

Travel blogs

Local historians’ books

Indigenous folklore texts

Photographs

Tourism documentaries

This raises questions of reproduction and fair use.

🔹 Case 5: Authors Guild v. Google, Inc.

Facts:
Google scanned millions of copyrighted books to create a searchable database.

Issue:
Was scanning entire books copyright infringement?

Decision:
Held to be fair use, because it was transformative and did not replace the original books.

Legal Principle:
Transformative use for indexing/search may qualify as fair use.

Relevance:
If AI training involves scanning travel books to generate new tourism stories, developers may argue it is transformative like Google Books.
However, unlike search indexing, AI may generate competing expressive content — making the defense less certain.

🔹 Case 6: Andy Warhol Foundation for the Visual Arts, Inc. v. Goldsmith

Facts:
Warhol created silkscreens based on a photograph by Lynn Goldsmith.

Decision:
The Supreme Court narrowed the scope of “transformative use.”

Legal Principle:
Even if new meaning is added, commercial use competing with the original may still infringe.

Relevance:
If AI generates tourism storytelling using stylistic imitation of a local travel writer, it may infringe — especially if the output competes commercially.

5. Derivative Works & Substantial Similarity

🔹 Case 7: Rogers v. Koons

Facts:
Jeff Koons copied a photograph into a sculpture.

Decision:
Infringement — copying expression, not just idea.

Legal Principle:
Even altered works can infringe if they copy protected expression.

Relevance:
If AI-generated tourism narratives reproduce distinctive phrases or story structure from a local author’s book, it may constitute infringement.

🔹 Case 8: Infopaq International A/S v. Danske Dagblades Forening

Facts:
A media monitoring company copied short text extracts.

Decision:
Even 11-word extracts can infringe if they reflect originality.

Legal Principle (EU):
Small portions can infringe if they contain original expression.

Relevance:
AI-generated tourism brochures that replicate distinctive descriptive sentences about a province could infringe, even if only short excerpts are used.

PART III: PROTECTION OF LOCAL CULTURE AND FOLKLORE

AI tourism storytelling often incorporates:

Indigenous legends

Traditional songs

Cultural rituals

These may not always be protected by standard copyright but could fall under:

Moral rights

Cultural heritage laws

Traditional knowledge protections

🔹 Case 9: Community for Creative Non-Violence v. Reid

Facts:
Dispute over ownership of a sculpture commissioned by an organization.

Decision:
The creator retained copyright because he was an independent contractor.

Legal Principle:
Authorship depends on employment relationship.

Relevance:
If a provincial tourism department commissions AI developers, ownership depends on contract terms.
Without clear agreements, disputes may arise between:

Government agencies

Software companies

Content editors

Key Legal Challenges in AI Tourism Storytelling

1. Ownership Uncertainty

AI cannot be an author. Protection depends on human contribution.

2. Training Data Liability

Using copyrighted local histories may trigger infringement claims.

3. Style Imitation Risks

Mimicking a famous regional author may violate derivative rights.

4. Cultural Sensitivity & Moral Rights

Misrepresentation of local traditions could violate integrity rights.

5. International Complications

Tourism content is distributed globally — meaning multiple copyright regimes apply.

Conclusion

AI-generated tourism storytelling for local provinces exists at the intersection of:

Human authorship doctrine

Fair use and transformative use

Derivative work analysis

Cultural heritage protection

Contractual ownership issues

From Burrow-Giles Lithographic Co. v. Sarony establishing human creativity as the foundation of copyright, to Thaler v. Perlmutter confirming AI alone cannot be an author, courts consistently emphasize human intellectual contribution.

At the same time, decisions like Authors Guild v. Google, Inc. and Andy Warhol Foundation for the Visual Arts, Inc. v. Goldsmith show that transformative use has limits — especially in commercial settings like tourism promotion.