Asking AI Services: What’s your view on Trump’s comments on AI & Copyright? GPT-4o: Trump sets up a false binary. Grok: The comparison between human learning and AI training is flawed.

Asking AI Services: What’s your view on Trump’s comments on AI & Copyright?

ChatGPT-4o’s answer:
Donald Trump’s comments on AI and copyright reflect a politically charged yet legally and ethically problematic stance that prioritizes competitive expediency over rights-based frameworks. Here's a critical breakdown of his statement and what it means in the context of AI, copyright law, and international technology competition:

🧠 What Trump Said – In a Nutshell

• Common sense over contracts: He argues that requiring AI developers to compensate rights holders for training data is impractical.

• “Reading isn’t stealing”: He suggests that if a human can learn from a book without violating copyright, AI should be able to do the same.

• China as the competitive benchmark: He frames licensing rules as a disadvantage in the race against China, implying the U.S. should “play by the same rules”—or lack thereof.

• Opposes complexity in licensing: He suggests the AI industry can’t function if it must negotiate thousands of contracts.

📚 Why This View Is Problematic

1. It Ignores Copyright Law’s Purpose

Trump’s analogy—comparing AI ingestion of copyrighted content to human reading—is legally flawed. U.S. copyright law permits human reading and learning under fair use, but:

• AI doesn’t “read” in the human sense; it copies, stores, and processes vast datasets—acts that often constitute reproduction, a protected right under copyright law.

• Courts, such as in the Authors Guild v. Google decision, have narrowly defined fair use in the context of transformative use, not wholesale ingestion.

2. It Dismisses Author & Publisher Rights

By saying “you just can’t do it,” Trump dismisses the value of labor and investmentby authors, journalists, researchers, and publishers. This:

• Undermines content ecosystems—especially in scholarly publishing, journalism, and the arts.

• Encourages extraction without compensation, echoing historical patterns of digital platform abuse (e.g., news aggregation without pay).

3. It Misrepresents the China Comparison

Trump’s “China doesn’t pay, so why should we?” argument:

• Confuses authoritarian practice with competitive advantage. China’s lack of IP enforcement is a trade issue, not a model to emulate.

• Risks normalizing IP theft as a patriotic strategy, which weakens the very IP system the U.S. has long championed.

⚖️ Strategic Implications

For AI Companies:

• Following this logic might offer short-term efficiency, but it creates long-term legal exposure, including class actions and reputational harm.

• OpenAI, Meta, and others are already in court facing these very issues. Trump’s view could embolden non-compliance, increasing legal risk.

For Creators & Publishers:

• Trump’s comments are a clear signal of political hostility to licensing demands.

• This highlights the need for defensive contracts, clearer legislation, and collective licensing frameworks to protect content from unilateral ingestion.

For Regulators:

• The comments downplay the importance of rule-of-law enforcement in AI development.

• They point to a need for international alignment on copyright rules for AI, or at least enforceable standardsin democratic jurisdictions.

🧾 Conclusion: A False Choice

Trump sets up a false binary:

But that overlooks practical alternatives such as:

• Collective licensing (akin to music royalties),

• Data trusts for ethical data pooling,

• Synthetic or synthetic-but-grounded datasets, and

• Public domain and licensed corpora (e.g., PubMed Central, Creative Commons content).

📌 Final Thought

Trump’s comments may resonate with Silicon Valley disruptors and those prioritizing U.S. AI dominance—but they undermine creators’ rights, distort copyright law, and set a dangerous precedent for digital content exploitation. Long-term competitiveness depends not just on speed, but on building trust, sustainable ecosystems, and legal clarity.

Grok’s answer:
Trump’s comments on AI and copyright, as expressed in the provided text, reflect a perspective prioritizing rapid AI development over strict adherence to existing copyright frameworks. He argues that requiring AI companies to pay for every piece of copyrighted material used in training models is impractical and would hinder the U.S.’s ability to compete globally, particularly with China. His analogy likening AI training to human learning—where reading a book doesn’t require payment to the author—suggests he views AI’s use of copyrighted material as a form of knowledge acquisition rather than direct copying or plagiarism. He advocates for a “common sense” approach to intellectual property rules, implying a relaxation of copyright enforcement to enable unfettered AI innovation.

However, this stance oversimplifies a complex issue and dismisses legitimate concerns from creators and rights holders. The comparison between human learning and AI training is flawed: humans don’t reproduce or distribute copyrighted works verbatim, whereas AI models often rely on vast datasets that include copyrighted material, raising questions about fair use and economic impact on creators. The creative industries, employing millions and contributing significantly to the U.S. economy (e.g., over 2.3 million jobs and $229 billion in wages annually, as noted in public discourse), argue that weakening copyright protections risks undermining their livelihoods and cultural contributions. They advocate for licensing models, similar to those used in music or digital media, to ensure fair compensation.

Trump’s position aligns with tech industry arguments, particularly from companies like OpenAI and Google, who claim that flexible copyright rules (e.g., fair use or text-and-data mining exceptions) are critical for AI advancement and national competitiveness. Yet, his assertion that “China’s not doing it” overlooks that China also faces internal debates about IP rights and AI, and its approach isn’t necessarily a model for the U.S. to emulate. Critics, including over 400 Hollywood creatives like Paul McCartney and Ben Stiller, have warned that eroding copyright protections could harm America’s creative economy and cultural influence, as seen in their open letter to the Trump administration in March 2025.Additionally, Trump’s comments sidestep the legal nuance that courts are still grappling with—whether AI training on copyrighted material constitutes fair use.

The U.S. Copyright Office’s 2025 report, which questioned fair use claims, sparked significant controversy, leading to the firing of its head, Shira Perlmutter, suggesting political pressure to favor tech interests. This move underscores the tension between creators and AI companies, with Trump’s remarks leaning heavily toward the latter.In my view, while fostering AI innovation is crucial, dismissing copyright concerns risks alienating creators and destabilizing industries that are vital to U.S. soft power and economic health. A balanced approach—such as streamlined licensing frameworks or collective bargaining models—could support both AI development and creators’ rights without resorting to a free-for-all that disproportionately benefits tech giants. Trump’s rhetoric, while appealing to deregulation advocates, ignores the long-term consequences of undermining intellectual property protections in a rush to “beat China.”

Claude’s answer:
Trump's comments reflect a pragmatic but controversial perspective on AI training and copyright that's at the heart of ongoing legal battles in the AI industry.

His core argument is essentially that AI systems should be able to learn from copyrighted content in the same way humans do when they read books or articles - absorbing knowledge and patterns without needing to pay licensing fees for each piece of content consumed during training. He frames this as necessary for maintaining competitive advantage against China and calls it "common sense."

This position aligns with what many AI companies have argued in court - that training AI models on copyrighted works constitutes "fair use" because it's transformative and doesn't directly reproduce the original works. The analogy to human learning is compelling: when you read a novel, you don't pay the author every time you apply insights from that book in your own thinking or writing.

However, this view is strongly contested by content creators, publishers, and some legal scholars who argue that:

• The scale is fundamentally different - AI systems can process millions of copyrighted works simultaneously

• There's significant commercial value being extracted from this training data

• It potentially undermines creators' ability to monetize their work

• The "human learning" analogy may not hold legally or ethically at this scale

The practical reality Trump points to is also important: negotiating individual licensing deals for every piece of training data would indeed be nearly impossible at the scale modern AI systems require. But this doesn't necessarily resolve the underlying question of whether such massive copying should be permissible without compensation.

This remains one of the most significant unresolved issues in AI development, with major lawsuits pending and different courts potentially reaching different conclusions.

Perplexity’s answer:
Analysis of Trump's Comments on AI and Copyright

Donald Trump's recent remarks on artificial intelligence and copyright law signal a clear stance: the U.S. should adopt "common sense" intellectual property rules that do not require AI companies to pay each time copyrighted works are used for training AI models. His core argument is that requiring licensing deals for every article or book used in AI's learning process is "not doable" and would hinder America’s competitiveness, especially in relation to China, which he claims does not impose such restrictions.

Key Points from Trump's Comments

• Common Sense IP Rules: Trump calls for a practical approach to AI and intellectual property—one that enables AI companies to access existing knowledge without being burdened by copyright licensing for every piece of content ingested for training.

• Global Competition: He frames the issue as one of national interest and international rivalry, asserting that the United States must “play by the same set of rules” as China and that restrictions would put the U.S. at a disadvantage in the AI race.

• Distinction Between Learning and Copying: Trump differentiates between an AI “learning” from existing content (which he supports) and outright copying or plagiarism (which he opposes). He likens AI training to a person reading and learning from books without entering into contracts with every author.

• Complexity of Licensing: He argues that the scale of content involved makes individualized agreements with rights holders practically impossible and would create excessive administrative and financial burdens.

Policy Context

• AI Action Plan: The Trump administration's new AI Action Plan does not address content creator concerns or propose copyright reforms. Instead, it focuses on accelerating AI infrastructure, limiting regulation, and ensuring federal funding is withheld from states with "burdensome" AI regulation.

• Industry Alignment: Trump’s comments reflect the AI industry’s push for “fair use” of copyrighted material in training data. Many AI firms and some courts have asserted that this should be covered under fair use, while creators and lawmakers (e.g., Senators Hawley and Blumenthal) are pushing for stricter consent requirements.

• Regulatory Priorities: The broader AI policy outlined by the administration prioritizes rapid U.S. development, reduced oversight, and minimizing what it terms “ideological bias” in AI systems, sometimes at the expense of content moderation and creator protections.

Reception and Criticisms

• Tech Community: Many AI developers support this stance, arguing that requiring blanket licenses would be unworkable and stifle innovation.

• Content Creators and Advocates: Authors, publishers, and rights holders strongly oppose this view, warning it may deprive creators of fair compensation and set a negative precedent for intellectual property protection.

• Ongoing Debate: The policy notably sidesteps significant unresolved legal questions about what constitutes fair use for AI model training in the U.S.—an area currently being litigated and debated in Congress.

Conclusion

Trump's position is pragmatic from a technology and competitiveness perspective, emphasizing the impracticality of negotiating countless copyright contracts for AI training and the importance of maintaining U.S. leadership in AI. However, the approach raises ongoing questions about creators’ rights and the long-term sustainability of content industries in the AI era, leaving core legal and ethical issues unresolved.

Gemini’s answer:
Of course. Here is a breakdown and analysis of the provided text regarding Donald Trump's comments on artificial intelligence and copyright.

The comments articulate a clear and assertive stance on a central legal and ethical question facing the AI industry. His viewpoint can be broken down into three main arguments: the analogy to human learning, the practicality of licensing, and the imperative of geopolitical competition.

1. The Core Argument: AI Learning is Like Human Learning

Trump's primary argument is an analogy: an AI model "reading" or "studying" content is fundamentally similar to a human doing the same.

• His Point: "When a person reads a book or an article, you've gained great knowledge, that does not mean that you're violating copyright laws... we have to allow AI to use that pool of knowledge."

• Analysis: This is a powerful and intuitive argument favored by many AI developers. It frames the ingestion of training data not as reproduction or theft, but as a necessary step for learning and knowledge acquisition. The core idea is that the AI isn't storing and reselling the book; it's using the book to understand language, concepts, and facts, similar to a student. This line of reasoning directly supports the legal argument of "fair use."

• Counterpoint: Critics and rights holders argue this analogy is flawed. A human's learning is internal and its scale is limited. An AI, however, ingests and makes mathematical copies of millions of works at a scale impossible for any human. Furthermore, the output of a generative AI can directly compete with the original works it was trained on, potentially destroying the market for the creators. This goes to the heart of the fourth factor of the fair use test: the effect of the use upon the potential market for the copyrighted work.

2. The Practicality Argument: Licensing is "Not Doable"

He dismisses the idea of negotiating licenses for all training data as logistically and financially impossible.

• His Point: "You can't be expected to have a successful AI program when every single article, book, or anything else that you've read or studied, you're supposed to pay for... you just can't do it because it's not doable... the complexity of contract negotiations of which there would be thousands."

• Analysis: This is a pragmatic argument that reflects the reality of building large language models (LLMs). The datasets used for training are colossal, often scraped from the public internet. Identifying every rights holder and negotiating a license for every piece of content would be a monumental task that could stifle innovation and concentrate AI development in the hands of only the few companies wealthy enough to attempt it.

• Counterpoint: Content creators argue that "difficult" does not mean "unnecessary." They point to existing models for mass licensing, such as performing rights organizations like ASCAP and BMI in the music industry, which handle royalties for millions of songs. They contend that the tech industry's "move fast and break things" ethos shouldn't allow it to build multi-trillion-dollar industries on the uncompensated use of their work.

3. The Geopolitical Argument: Competing with China

Trump frames the issue as a matter of national competitiveness, specifically with China.

• His Point: "China's not doing it and if you're gonna be beating China... you have to be able to play by the same set of rules."

• Analysis: This is a powerful political framing that elevates the debate from a domestic copyright dispute to a matter of national strategic interest. It suggests that imposing strict licensing requirements on U.S. companies would be a form of unilateral disarmament in the global AI race, allowing competitors like China, which may have looser intellectual property standards, to accelerate past the United States.

• Counterpoint: Opponents might argue this is a "race to the bottom" that sacrifices the legal and property rights of U.S. creators to benefit large technology corporations. They might question whether abandoning foundational principles of intellectual property is the correct way to compete, suggesting it undermines the very creative economy the U.S. purports to lead.

Summary of the View

In essence, Donald Trump’s comments strongly align with the position of many major AI developers and tech companies. His view is that:

1. Training AI is fair use: He sees it as analogous to human learning, not copyright infringement.

2. Licensing is impractical: The scale of AI training makes individual content licensing an inhibitor of progress.

3. Strict IP enforcement is a national liability: Relaxed rules are necessary to maintain a competitive edge over rivals like China.

This perspective places him directly at odds with authors, artists, news organizations (like The New York Times, which is actively suing OpenAI and Microsoft), and other rights holders who argue for consent and compensation. His comments concisely capture one side of a complex, high-stakes debate that courts, lawmakers, and society are currently grappling with, a debate that will define the economics of both the technology and creative sectors for decades to come.

0:00 But we, what we really need to be successful is a very simple phrase called common sense, and that begins with a common sense application of artificial and intellectual property rules.

0:13 It's so important.

0:15 You can't be expected to have a successful AI program when every single article, book, or anything else that you've read or studied, you're supposed to pay for gee, I read a book.

0:25 I'm supposed to pay somebody and you know we, we appreciate that, but you just can't do it because it's not doable.

0:32 And if you're gonna try and do that, you're not gonna have a successful program.

0:35 I think most of the people in the room know what I mean.

0:38 When a person reads a book or an article, you've gained great knowledge, that does not mean that you're violating copyright laws or have to make deals with every content provider.

0:51 And that's a big thing that you're working on right now, I know, but you just can't do it.

0:55 China's not doing it and if you're gonna be beating China and right now we're leading China very substantially in AI very, very substantially, and nobody's seen the, the amount of work that's gonna be bursting upon the scene.

1:09 But you have to be able to play by the same set of rules.

1:13 So when you have something, when you read something and when it goes into this vast intelligence, , machine, we'll call it, , you cannot expect to every time, every single time, say, oh let's pay this one that much, let's pay this one just doesn't work that way, of course you can't copy or plagiarize an article.

1:35 But if you read an article and learn from it, we have to allow AI to use that pool of knowledge without going through the complexity of contract negotiations of which there would be thousands.