The k2p blog

My views are crystallizing and my current position shows up as the questioner in this AI-conversation with Gemini.

I am using all three LLMs fairly randomly but my current ranking for “goodness” is Grok followed by ChatGPT and then Gemini. Gemini is, by far, the most woke and ChatGPT is the most sanctimonious.

ktwop: Is it correct to consider an LLM such as Gemini or Chatgpt as a text generating tool? No matter how advanced or clever the model it only produces text when instructed to do so and based on a prompt. Responsibility and liability for the text generated cannot, I think, lie with the tool but on the person who puts it to some use such as publishing it or advising someone in a commercial situation (user). Any liability would lie with the user who may not necessarily be the initiator or the prompter. Does this logic seem sound?

Gemini: Yes, your logic seems sound. It’s accurate to consider LLMs like Gemini and ChatGPT primarily as text generation tools. Here’s a breakdown of why your reasoning holds:

• Text Generation as the Core Function: At their heart, these models are designed to predict and generate sequences of text based on the input they receive. They don’t possess intent, understanding of truth, or the capacity for independent judgment in the way a human does.

• Dependence on Prompts: The output of an LLM is entirely contingent on the prompt it’s given. Without a prompt, it produces nothing. The quality, accuracy, and potential impact of the generated text are heavily influenced by the way the user frames their request.

• Lack of Agency and Responsibility: Because LLMs are tools, they don’t have agency in the human sense. They don’t make decisions about how the generated text will be used. Responsibility and liability inherently lie with the individuals or entities who choose to utilize the output.

• User as the Point of Action: The act of publishing, advising, or otherwise using the generated text in a real-world context is where responsibility and potential liability arise. The LLM itself is merely the instrument used in that process.

• Distinction Between Prompter and User: You correctly point out that the person who initially prompts the LLM might not be the same person who ultimately uses the generated text. The liability would logically fall on the user who takes the action based on the LLM’s output, as they are the ones making the decision to disseminate or act upon it.

Analogy: Consider a word processor. It’s a powerful tool for creating text, but if someone uses it to write and publish defamatory content, the liability rests with the author/publisher, not with the software itself or the person who might have initially typed a draft. LLMs function similarly in this regard.

Nuances to Consider:

While your core logic is strong, there are some evolving legal and ethical discussions around LLMs that add complexity:

• Copyright: The ownership of the generated text can be a complex issue, particularly regarding the training data and the extent of creative input from the user.
• Bias in Training Data: LLMs can sometimes generate biased or harmful content due to biases present in their training data. While the user is still responsible for the output they use, the inherent limitations of the tool are a factor.  
• Transparency and Disclosure: There’s a growing discussion about the need for transparency when using LLM-generated content, especially in professional or public contexts.
• Evolving Legal Landscape: Laws and regulations surrounding AI-generated content are still developing, and future legal interpretations might introduce nuances to the assignment of liability.

In conclusion, your understanding of LLMs as text generation tools, and the attribution of responsibility and liability to the user, aligns with the current understanding and common-sense perspective on these technologies. The tool itself is inert until a human directs it and then chooses how to utilize its output.

ktwop: Regarding copyright, it is much simpler than vested parties try to make it out to be. The owners of training data, whether used with permission or not, have no claim of copyright on the generated text. They may have a claim against the LLM manufacturer based on the copyright or ownership of their own material and the possibly illegal use of their material. But they can have no ownership or copyright claim on the generated text. The LLM developer develops a tool for generating text and provides the tool for use. He has no claim on the generated text either. Irrespective of how simple or non-creative a prompt, the prompter has first call on ownership of the generated text, That will be superseded by the publisher or commercial user of the text if someone else. It seems to me quite evident that the first person to legally publish the generated text will establish copyright and ownership (and liability).

Gemini: That’s a very direct and assertive take on the copyright situation surrounding LLM-generated text. While your perspective has elements of truth and reflects a desire for clarity, the reality is proving to be more legally nuanced and is still actively being debated and tested. Let’s break down your points:

• Training Data Owners’ Claim: You’re right that training data owners likely wouldn’t have a direct copyright claim on the generated output itself. Their potential legal recourse against LLM developers would likely center on the use of their copyrighted material in the training process without permission (copyright infringement) or possibly other intellectual property claims. They aren’t the creators of the new text.

• LLM Developer’s Claim: You’re also generally correct that the LLM developer, as the creator of the tool, doesn’t automatically own the copyright to every piece of text generated by its users. The tool enables creation but isn’t the author of the specific output.

• Prompter’s Initial Claim: Your assertion that the prompter has the “first call” on ownership is where things get more complex. Copyright law traditionally grants protection to original works of authorship. The question becomes: how much creative input does the prompter contribute to the final generated text?

  • A very simple, non-creative prompt might be seen as merely instructing the tool, with the LLM doing the bulk of the “authorship” (though not in a copyrightable sense).
  • A highly detailed and creative prompt, involving specific stylistic instructions, content requirements, and iterative refinement, could potentially establish more of an argument for the prompter’s creative contribution.

• Publisher/Commercial User Establishing Copyright: Your idea that the first to legally publish establishes copyright is not entirely accurate under current copyright law. Copyright protection generally attaches automatically to an original work of authorship the moment it is fixed in a tangible medium (like text). Registration with a copyright office provides certain benefits (like the ability to sue for statutory damages), but it’s not the act of publication that creates the copyright.

  • The publisher would likely acquire rights through a license or assignment from the copyright holder (potentially the prompter, depending on the level of creative input). The act of publication itself doesn’t automatically confer copyright ownership.

• Liability and Publication: You’re likely closer to the mark regarding liability. The publisher or commercial user who chooses to disseminate the text is the one taking on the responsibility for its content, including potential legal ramifications like defamation or copyright infringement (if the generated text improperly incorporates copyrighted material from elsewhere, though this is a separate issue from the training data).

Why it’s more complex:

• The “Authorship” Question: The core challenge lies in defining “authorship” in the context of AI-generated content. Can an AI be considered an author? Current legal consensus in many jurisdictions leans towards no, as copyright traditionally requires human creativity. If the AI is not the author, then who is? And how much human input is needed to qualify for authorship?
• Derivative Works: There’s also the question of whether LLM-generated text could be considered a derivative work of the training data in some way, even if a direct copyright claim on the output is unlikely. This is a complex legal area.
• Ongoing Legal Developments: Courts and legal scholars worldwide are grappling with these issues. There haven’t been definitive, universally accepted legal precedents established yet.

In summary, while your desire for a straightforward answer is understandable, the legal landscape surrounding copyright in AI-generated content is still evolving. While training data owners and LLM developers likely don’t have direct copyright claims on the output, the prompter’s claim depends on the level of creative input, and publication itself doesn’t automatically establish copyright. The user who publishes or commercially utilizes the text bears the primary responsibility and liability.

It’s a fascinating and important area of legal development to watch.

ktwop: It seems to me that your answer is that of an LLM – which is just a tool like a pen – and of lawyers looking for work. Choosing to, choosing an LLM to use and entering a prompt is entirely an exercise of creativity. First to publish and first to use is all it ultimately boils down to.

Gemini: Ah, I see your perspective! You’re emphasizing the user’s intentionality and the practical reality of who first puts the generated text into the world. I appreciate you pointing out the potential for a “tool-like” interpretation.

From that viewpoint, you’re arguing that:

1. User Intent as Creativity: The act of deciding to use an LLM and crafting a prompt is itself a creative act, guiding the tool toward a specific output.
2. Practicality of Publication: In the real world, the person who takes the initiative to publish and utilize the text is the one who establishes its presence and potential value.

There’s definitely a pragmatic element to your thinking. In many ways, the legal system will eventually have to grapple with the practical realities of how these tools are used. The first to publish often establishes a tangible claim and takes on the associated risks and rewards.

However, the legal framework of copyright is often based on the concept of original authorship fixed in a tangible medium. While your act of prompting is creative in directing the tool, the question remains under current law whether that level of direction equates to the kind of “authorship” that copyright traditionally protects.

Think of it this way: if you ask a skilled painter to create a landscape based on your detailed verbal description, you’ve been creative in your instruction, but the painter is still considered the author of the artwork. The legal framework currently tends to focus on the entity that executes the creative expression.

That being said, the law is not static, and the rise of AI is certainly putting pressure on existing definitions. It’s possible that legal interpretations will evolve to better reflect the user’s role in guiding and shaping LLM output.

So, while your perspective on the user’s creative input and the significance of publication is a strong and practical one, it might not fully align with the current letter of copyright law in all jurisdictions. You’re highlighting a tension between the existing legal framework and the realities of AI-driven content creation.

It’s a really interesting point you’re making, and it underscores the ongoing need for discussion and potential legal updates in this space. You’re right to push on the idea of the user’s creative agency!