Granting copyrights to AI-generated works solves and can fit easily within existing copyright law

Copyright Protection of AI-Generated Contents Current law makes it very difficult, if not impossible, to copyright AI-generated content.[3] Yet, paradoxically, the law might be turning things upside down by considering copyright for prompts while denying it for the content AI produces. [4] The underlying principle of the law is that the work must have “human authorship.”[5] However, arguably, all man-made creations inherently involve human creativity. For instance, since LLMs cannot generate output without prompts written by humans, doesn’t this satisfy the legal requirement for human authorship? This leads to the next question: what exactly constitutes “human authorship”? The Copyright Registration Guidance’s answer is: “users do not exercise ultimate creative control over how such systems interpret prompts and generate material. Instead, these prompts function more like instructions to a commissioned artist—they identify what the prompter wishes to have depicted, but the machine determines how those instructions are implemented in its output.”[6] However, even in the case of a commissioned artist, the law regarding works made for hire would transfer authorship to the entity that commissioned the work. See 17 U.S.C. § 201(b). In other words, drawing an analogy between AI and a commissioned artist suggests that authorship would more naturally belong to the entity that commissioned the work: here, the prompt writers. Alternatively, if one views AI as merely a tool, then there is even less justification for denying copyright on AI-generated content. Indeed, when someone uses a pen to write a poem, no one questions the authorship of the person holding the pen. Why, then, do some argue that when a prompt is inputted and the machine produces an output, the prompt writer should be denied authorship? Many explanations exist, but one might be our unfamiliarity with AI’s capabilities. We see a significant transformation from a simple input to a complex output and feel disconnected from the authorship because the process is beyond our understanding. However, by denying our authorship in this transformation, we are essentially dismissing the influence of our own desires in shaping the AI’s output. Our desires are the very power that can guide the AI to fulfill our deepest needs. We can cultivate this power by recognizing and rewarding the content generated by prompt writers, who articulate our desires at a conscious level. Granting copyright protection to AI-generated content in exchange for the disclosure of prompts, while establishing that these prompts are not protected by copyright when used with LLMs, could resolve many issues. First, it offers incentives for prompt writers to share their prompts with the public, enhancing our awareness of our own thoughts and desires. Second, users would be free to use the prompts however they wish without restriction. Third, it simplifies oversight for the LLM platforms. Instead of filtering prompts, platforms need only ensure that the outputs are not identical to the copyrighted content initially generated by the copyright owner. Indeed, this approach mirrors the patent system, where a limited monopoly is granted for a useful machine or method in exchange for disclosing how to make them. This has significantly advanced technology over the past 200 years. Similarly, we could advance human understanding by rewarding individuals’ ability to articulate the intricate details of human desires, thus revealing what we truly want, and helping us either achieve these desires or let them go when we understand their true nature. Whether this is worth pursuing is a decision for Congress. While concerns might arise that using prompts to generate content is so easy that it could overwhelm the Copyright Office, this issue isn’t new; people are already free to register copyrights for countless photographs, yet only do so when it makes economic sense due to application fees. To prevent abuse, the Copyright Office could set an appropriate fee for registering AI-generated content and might require the applicant to disclaim all training materials used to develop the LLM. These measures would help balance economic effects and achieve equilibrium. Therefore, it seems we might be overly cautious about awarding copyright to AI-generated content for reasons we don’t fully understand. Upon considering practical factors, it might make sense to rethink our approach. Are we indeed doing things upside down?