Copyright breakpoint: AI works without human input belong to everyone

Generative AI systems now produce complex creative outputs that mimic human expression, yet they lack intention, emotion, and consciousness, the traditional hallmarks of authorship. Despite this, these systems are being used by millions of artists, designers, and content producers worldwide. This blurs the distinction between human originality and machine assistance.

Artificial intelligence is redrawing the boundaries of creativity and ownership. As generative systems compose music, write literature, and produce digital art, the question of who, or what, can be called an author has never been more urgent. A new study titled “Reconceptualizing Human Authorship in the Age of Generative AI: A Normative Framework for Copyright Thresholds,” published in Laws offers a comprehensive framework for redefining authorship in the age of algorithmic creativity.

The work confronts one of the most pressing challenges in global copyright law: determining whether works created with the help of AI can qualify for protection, and how much human input is required for authorship. By examining international legal traditions and current court decisions, the study lays the groundwork for a new approach to evaluating creativity in hybrid human–machine works.

Defining authorship in an AI-driven creative economy

The study answers a key question: What is the threshold of human creativity necessary for copyright protection when artificial intelligence contributes to the creative process? According to the author, current copyright frameworks, rooted in the idea of a human author as the sole source of originality, are no longer sufficient.

Generative AI systems now produce complex creative outputs that mimic human expression, yet they lack intention, emotion, and consciousness, the traditional hallmarks of authorship. Despite this, these systems are being used by millions of artists, designers, and content producers worldwide. This blurs the distinction between human originality and machine assistance.

The study argues that a purely human-centered notion of authorship is unsustainable in a digital ecosystem where creation increasingly involves collaboration between human users and autonomous systems. At the same time, the author rejects the idea of granting authorship to AI itself, noting that creativity without human control or intention cannot meet the standards of intellectual creation recognized under international law.

To navigate this complexity, the author proposes the concept of “substantial creative direction” as the defining threshold for copyright eligibility. This test requires proof that a human has exercised meaningful control over the AI’s operation, contributed verifiable creative input, and demonstrated expressive intent. If these elements are met, the human user can be recognized as the author.

This normative standard bridges the gap between two extremes: denying protection to all AI-assisted works and granting full authorship to autonomous systems. It focuses instead on human agency, the ability to guide, select, and refine machine output toward a creative goal.

Legal traditions and the boundaries of human creativity

Across jurisdictions, courts consistently uphold the human authorship requirement as the foundation of copyright protection. In the European Union, the Berne Convention and subsequent Court of Justice of the EU (CJEU) rulings emphasize that a work must reflect “the author’s own intellectual creation.” This standard, the study notes, demands personal expression and creative choices that stem from human personality. French, German, and Spanish courts have similarly reaffirmed that non-human entities cannot claim authorship.

In the United States, the debate has become particularly visible following the Thaler v. USPTO decision, in which a federal court ruled that only human creators can hold copyright. This position was later reinforced by the U.S. Copyright Office, which requires applicants to identify and document human contributions in AI-generated works.

Despite this international consistency, the author highlights a critical weakness: none of these legal systems clearly define how much human involvement is enough. The absence of a measurable threshold leaves AI-assisted works in a legal grey area, leading to uncertainty for creators, businesses, and cultural institutions.

The author proposes that this ambiguity be resolved through a tiered protection model:

• Full Copyright Protection for works where human direction, selection, and editing substantially influence the output.
• Limited Sui Generis Protection for cases where human input is creative but not dominant.
• Public Domain Classification for fully autonomous, machine-generated works lacking meaningful human participation.

This framework ensures that copyright continues to reward human creativity while maintaining the public domain as a space for freely available machine outputs.

Building a normative framework for the AI era

The study offers a practical roadmap for policymakers and copyright offices to operationalize his proposed standard. The paper advocates for mandatory disclosure of AI involvement during copyright registration, requiring applicants to specify which portions of a work were generated by machines and what human decisions shaped them.

This would involve maintaining detailed records of prompts, iteration histories, and post-production edits. Such documentation would enable regulators to assess whether the “substantial creative direction” threshold has been met. Similar disclosure requirements are already emerging in the European Union’s Artificial Intelligence Act and the U.S. Copyright Office’s 2023 guidelines, both of which call for transparency regarding the role of AI in creative processes.

The study also introduces the concept of algorithmic traceability, a procedural safeguard ensuring that the human contribution to an AI-generated work can be verified after production. By mandating technical logs or metadata tracking creative decisions, this system would strengthen authorship claims and reduce disputes over ownership.

The author stresses that the future of copyright law depends on this type of procedural innovation. Without transparency, he warns, courts and regulators will struggle to separate human creativity from algorithmic replication, undermining the very foundations of intellectual property law.

Another key proposal involves cross-disciplinary oversight. The author calls for collaboration between copyright authorities, AI regulators, and creative industry bodies to develop unified guidelines for human-AI co-creation. This would align copyright thresholds with the EU’s broader digital policy objectives, ensuring consistency between cultural, technological, and legal governance.

Redefining authorship for a post-human creative future

The author argues that AI challenges not only copyright law but also society’s understanding of creativity, expression, and moral rights. The study distinguishes between functional creativity, AI’s ability to produce aesthetically pleasing results, and authentic creativity, which involves human consciousness, intention, and self-expression. The latter, the author contends, remains uniquely human and should remain the basis for legal authorship.

However, as AI tools become more advanced and accessible, distinguishing between these categories will grow increasingly difficult. A composer who uses an AI to generate a melody, an illustrator who refines AI-generated imagery, or a writer who prompts a model to produce text, all operate within hybrid creative systems. Each case demands a nuanced assessment of control and intent.

The framework provides this nuance by tying authorship to creative direction, not mere input. It asserts that originality arises from the human capacity to make aesthetic choices and impose vision on a technological process. AI may execute tasks, but it does not possess moral authorship, the sense of personal accountability and expressive purpose that underpins creative identity.

Preserving human authorship is not a matter of resisting technological change but of redefining creative agency in the digital age, the study concludes. By recognizing and protecting meaningful human involvement, legal systems can adapt to a future where creativity is increasingly shared between people and machines.