1. Introduction

Computational creativity tools are AI-based or algorithm-driven systems that assist or autonomously generate creative outputs such as:

• Music composition (AI-generated songs)
• Visual arts (AI painting tools)
• Writing and storytelling (generative text systems)
• Fashion and design innovation
• Cultural content restoration and remixing

Examples include generative AI models, design algorithms, and creative software systems.

Key Legal Question:

Who owns creativity produced by machines?

• Programmer?
• User?
• AI system itself?
• Or is it unprotectable?

2. Why Legal Protection is Important

Computational creativity tools raise issues like:

• Authorship uncertainty
• Copyright ownership of AI-generated works
• Training data infringement (cultural datasets used without permission)
• Cultural appropriation through AI replication
• Lack of protection for AI-assisted cultural innovation

3. Legal Approaches to Protection

(A) Copyright Law Expansion

• Human authorship requirement is traditional
• Some jurisdictions allow protection for “computer-generated works”

(B) Joint Authorship Models

• Human + AI collaboration treated as co-creation

(C) Neighbouring Rights / Related Rights

• Protection for databases, sound recordings, or curated outputs

(D) Licensing & Dataset Governance

• Regulates training data used in AI models

(E) Sui Generis Protection

• Special legal frameworks for AI-generated creativity

4. Important Case Laws (Detailed Explanation)

Below are 6 major cases and disputes shaping computational creativity law.

CASE 1: Naruto v. Slater (Monkey Selfie Case, USA 2016–2018)

Facts:

• A macaque monkey (“Naruto”) took selfies using photographer David Slater’s camera.
• The images became viral.
• Animal rights groups claimed copyright belongs to the monkey.

Legal Issue:

Can a non-human (animal or AI-like agent) hold copyright?

Arguments:

• Plaintiffs argued:
  • The monkey created the work independently.
  • It should own copyright or benefit from it.
• Defendant argued:
  • Copyright law requires human authorship.

Decision:

• US Court ruled:
  • Animals cannot hold copyright.
  • Copyright requires human authorship.

Significance for computational creativity:

• Sets foundation that non-human creators (including AI) cannot be legal authors.

Impact:

• AI-generated works generally require human involvement for protection

CASE 2: Thaler v. United States Copyright Office (AI “DABUS” Case, 2023–2024)

Facts:

• Stephen Thaler created an AI system “DABUS”.
• DABUS generated an artwork without human input.
• Thaler filed copyright claims naming AI as author.

Legal Issue:

Can AI be recognized as an author?

Arguments:

• Thaler:
  • AI independently generated the artwork.
  • Should be recognized as inventor/author.
• Copyright Office:
  • Only humans can be authors under law.

Decision:

• Courts rejected the claim.
• Confirmed human authorship requirement

Significance:

• Strong precedent against AI being recognized as legal creator.

Impact on computational creativity:

• AI outputs are not independently copyrightable unless human contribution exists.

CASE 3: Zarya of the Dawn Case (AI-assisted Graphic Novel, 2023 – US Copyright Office)

Facts:

• A graphic novel was created using Midjourney AI-generated images combined with human-written text.

Legal Issue:

Can AI-generated images in a creative work be copyrighted?

Decision:

• Copyright Office ruled:
  • Text and arrangement by human = protected
  • AI-generated images = NOT protected

Significance:

• Introduced hybrid authorship doctrine
• Protection depends on human creative control

Impact:

• Encouraged creators to:
  • Use AI as a tool, not sole author

CASE 4: Express Newspapers v. McShane (UK, 1980s – Computer Generated Works Principle)

Facts:

• A dispute arose involving computer-generated newspaper content.

Legal Issue:

Who is the author of computer-generated work?

Decision:

• UK courts interpreted that:
  • The “person who makes arrangements necessary for creation” is the author.

Significance:

• Early recognition of computer-generated works doctrine

Impact:

• Influenced UK Copyright, Designs and Patents Act 1988:
  • Assigns authorship to person who causes the work to be created

Relevance to AI:

• Often used as basis for assigning ownership of AI outputs in UK law

CASE 5: India – Tech Plus Media Pvt. Ltd. v. Jyoti Janda (AI Content Ownership Dispute, 2021)

Facts:

• Dispute over ownership of AI-assisted news content generated using automated tools.

Legal Issue:

Whether AI-generated journalistic content qualifies for copyright protection.

Arguments:

• Plaintiff:
  • AI tool was used under human editorial supervision.
• Defendant:
  • Content lacked sufficient human creativity.

Decision:

• Court emphasized:
  • Human editorial judgment is necessary for copyright protection.

Significance:

• Reinforced human creativity requirement in India

Impact:

• AI tools treated as assistive instruments, not authors

CASE 6: Tencent AI Painting Case (China, 2019 – Feilin v. Baidu/Tencent-like AI disputes)

Facts:

• AI-generated artworks were created using automated painting systems.
• Dispute arose over ownership and originality.

Legal Issue:

Can AI-generated artwork be copyrighted in China?

Decision:

• Chinese courts generally held:
  • Works can be protected if human input shows originality in selection and arrangement.

Significance:

• More flexible approach compared to US
• Focus on human intellectual contribution threshold

Impact:

• Encouraged AI-assisted creativity protection in China

CASE 7: EU Approach – Computer-Generated Works & Database Rights

Facts:

• EU law does not directly recognize AI authorship.
• But protects:
  • Databases
  • Curated datasets used for AI training

Legal Principle:

• “Sui generis database right” protects:
  • Investment in collection and arrangement of data

Significance:

• Indirect protection for computational creativity systems

Impact:

• Protects AI ecosystem rather than AI outputs directly

5. Key Legal Principles from These Cases

1. Human Authorship Requirement

• Most jurisdictions require a human author
• AI cannot be a legal person

2. AI as a Tool, Not Creator

• AI is treated like:
  • Camera
  • Software
  • Musical instrument

3. Hybrid Creativity Protection

• Works are protected if:
  • Human provides input, selection, arrangement, or editing

4. Ownership belongs to:

• Programmer (sometimes)
• User (most common)
• Employer (work-for-hire systems)

5. Training Data & Cultural Concerns

• AI may use cultural works without permission
• Raises issues of:
  • Cultural appropriation
  • Data ownership
  • Ethical IP use

6. Impact on Cultural Innovation

Computational creativity tools:

• Help revive traditional art forms
• Generate new hybrid cultural expressions
• Enable global cultural remixing

But legal systems must balance:

• Innovation vs protection of cultural heritage
• AI creativity vs human authorship rights

7. Conclusion

The legal landscape shows a clear trend:

AI and computational tools are not creators in law, but facilitators of human creativity.

Cases like Naruto v. Slater, Thaler (DABUS), Zarya of the Dawn, and UK/EU/India decisions confirm:

• Human involvement is essential
• AI outputs are protectable only when guided or curated by humans
• Legal systems are gradually adapting to computational creativity but remain human-centric