I’m thrilled to sit down with Desiree Sainthrope, a renowned legal expert with a wealth of experience in drafting and analyzing trade agreements. With her deep expertise in global compliance and a keen interest in the intersection of intellectual property and emerging technologies like AI, Desiree offers invaluable insights into the complex challenges facing content creators today. In this interview, we dive into the urgent issues surrounding AI and copyright law, exploring how unauthorized data scraping impacts independent publishers, the push for stronger regulatory protections, and the balance between technological innovation and creator rights. Join us as we unpack these critical topics and discuss the future of digital content in an AI-driven world.
Can you walk us through the motivations behind recent calls for AI copyright protections, particularly why immediate action is seen as necessary?
Absolutely. The core issue driving these calls is the rampant use of copyrighted content to train AI models without permission, attribution, or compensation. On August 7, 2025, a significant petition was launched to address this, spurred by the realization that waiting for the market to self-regulate—as suggested by some authorities—simply isn’t viable. The stakes are incredibly high for content creators, especially independent digital publishers, who are seeing their work exploited systematically. AI scraping erodes the economic value of their content and threatens their long-term sustainability. The urgency comes from the understanding that without swift intervention, the foundation of copyright law itself is at risk.
How are independent digital publishers currently being impacted by AI practices like content scraping?
The impact on independent publishers is profound and multifaceted. Representing over 17,000 publishers, many are finding that their original content is being extracted by AI systems without consent, often used to train models or generate responses that compete directly with their work. This cuts into their visibility and revenue, as traffic is diverted away from their sites. For instance, when AI assistants provide answers without linking back to the source, creators lose ad revenue and audience engagement. The feedback from these publishers is overwhelmingly one of frustration and concern—many feel their livelihoods are under threat as their content is devalued by these practices.
Why do you think training AI on copyrighted content without permission shouldn’t fall under fair use, and how does this affect the value of original work?
The argument against fair use in this context is rooted in the fundamental purpose of copyright law, which is to protect and incentivize original creation. Training AI models on copyrighted material without permission isn’t transformative in a way that benefits the public under fair use doctrine; instead, it often directly competes with the original content by replicating or summarizing it without credit. This undermines the economic value of the work—creators invest time and resources into producing content, only to see AI companies profit from it without giving anything back. It’s a clear imbalance that disrespects intellectual property rights and discourages future innovation if left unchecked.
What are some of the most pressing policy changes being advocated for to protect content creators in the AI era?
Among the key demands are policies that ensure AI-generated content credits and links back to the original source, alongside establishing that training on copyrighted material without consent isn’t fair use. Crediting and linking are crucial because they maintain the creator’s visibility and drive traffic back to their platforms, which is often their primary revenue source. Another urgent policy is the creation of licensing frameworks where creators can opt in and be compensated for the use of their work. This would shift the dynamic from exploitation to a fair business model, ensuring creators are part of the AI value chain rather than sidelined by it.
Transparency from AI companies is a big focus in these discussions. What kind of disclosures are being requested, and why do they matter to creators?
The push for transparency centers on requiring AI companies to disclose the sources of their training data, specifically whether copyrighted content was used, and how it’s being applied in their models. This matters to creators because it gives them insight into whether their work is being exploited and provides a basis for seeking compensation or opting out. Without this openness, creators are in the dark about how their intellectual property is being used. There’s a strong belief that many AI companies might resist this due to competitive concerns or the sheer scale of their data practices, but transparency is essential for building trust and accountability in this space.
There’s a concern that AI could jeopardize creators’ visibility and long-term viability. Can you elaborate on how this is happening?
Certainly. The rise of AI assistants and changing search behaviors means that users often get answers directly from AI outputs without ever visiting the original content source. This “zero-click” trend drastically reduces traffic to publishers’ sites, which is a lifeline for their revenue through ads or subscriptions. Additionally, as AI-generated content or summaries dominate search results or walled garden platforms, independent voices risk being drowned out. If this continues without regulation, many creators could lose their audience entirely, making it impossible to sustain their work over time. It’s a critical inflection point for how content is discovered and valued.
Beyond petitions, there are broader advocacy efforts involving industry groups and regulatory bodies. Can you share more about these initiatives and their goals?
There’s a robust effort underway to engage with key stakeholders like federal agencies, Congress, and industry groups to advocate for creator rights. This includes filing public comments that highlight the erosion of copyright protections and participating in coalitions with media executives to develop industry standards for AI content access. The goal is to create a unified front that pushes for policies like collective licensing models and transparency mandates. These partnerships amplify the voice of creators, ensuring their concerns are heard at the highest levels of policy-making and within the tech industry, fostering solutions that prioritize fairness over unchecked AI expansion.
What is your forecast for the future of copyright protections in the context of AI and digital content creation?
I believe we’re at a pivotal moment where the trajectory of copyright protections will depend heavily on the actions taken in the next few years. If advocacy efforts succeed, we could see a framework emerge that balances innovation with creator rights—think robust licensing systems and transparency rules that ensure fair compensation. However, if the “wait and see” approach persists, there’s a real risk that AI companies will further entrench practices that marginalize creators, potentially leading to a less diverse and vibrant digital ecosystem. My hope is for proactive regulation that adapts to technology’s pace, preserving the open web while embracing AI’s potential as a tool, not a threat.
