While I am pleased to see that the future challenges for music and culture, with AI as a top priority, are being widely debated and largely agreed upon in panels around the world, it is likely that policymakers in the US and UK were either not in the audience—or, at the very least, not convinced by “our” messages.
This isn’t entirely surprising. Policymakers often feel more comfortable supporting established technologies that have proven to be at the forefront and promise clear revenue streams.
This was precisely why, during the EU Copyright Reform, we had to demonstrate to policymakers that we possessed the technological capabilities to back up our proposals. By doing so, we ensured that the new legislation could have a tangible impact, which in turn gave politicians the confidence to provide the necessary support. The same principle applies now to the development of AI.
We shouldn’t just talk about legislation in order to get legislation. We need to show the value it could deliver, supported by the technology that already exists—even if it hasn’t been widely implemented yet.
Interestingly, legal progress is, to some extent, already aligning with the demands of AI-driven developments. This is largely because AI demonstrates its value through practical applications rather than abstract statements.
Below is my take on the recent developments in AI policy, particularly from the US and UK. To practice what I preach, I’m also highlighting some technological solutions already available that could play a key role in convincing policymakers to support our perspective. I look forward to hearing your thoughts on this.
Introduction
Artificial intelligence (AI) is transforming how content is created, consumed, and monetized. While the opportunities are vast, the challenges for copyright holders are significant, especially in the wake of recent AI policies in the United States and the United Kingdom. These policies—while designed to foster innovation—have inadvertently opened the door to practices like copyright laundering.
Copyright laundering occurs when copyrighted works are altered or repurposed without proper attribution or compensation. For example, an AI system might remix or repurpose a copyrighted song to create a derivative track without properly crediting the original creator, making it difficult for the creator to claim royalties or prove ownership. This practice undermines the financial stability of creators by denying them royalties and damages their ability to legally assert ownership, as it obscures the provenance of their work and complicates enforcement efforts. Additionally, unauthorized AI training jeopardizes billions in royalties for creators in two of the largest music markets.
New technology offers transformative solutions to these issues, leveraging blockchain, AI detection tools, and decentralized governance to safeguard the economic and creative rights of copyright holders.
The Economic Stakes: AI Policies in the U.S. and UK
U.S. Policies and Copyright Laundering Risks
The U.S. executive order on AI from 2019 emphasized reducing barriers to AI development, including broad interpretations of “fair use” in copyright law. This has led to an environment where AI developers can train models on copyrighted works without proper licensing, undermining traditional revenue streams for artists and copyright holders.
The absence of mandatory frameworks for compensating creators risks eroding the value of original works and diluting creators’ bargaining power. For instance, a mandatory licensing system could require AI developers to secure usage rights before training on copyrighted data, ensuring fair compensation and accountability. Such frameworks could also include automated royalty distribution systems tied to verified data usage, minimizing disputes and delays.
UK’s Approach to AI Training Data
The UK has proposed expansive exceptions for text and data mining (TDM), which allow AI developers to use copyrighted data without explicit permission. For creators, this permissiveness threatens not only income from licensing but also their ability to enforce rights when derivative AI-generated content enters the market.
Together, these policies endanger billions of dollars in potential royalties. Such financial losses can disproportionately impact smaller creators who rely also on consistent royalty streams for their livelihood. Additionally, the reduced income across the creative sector threatens the sustainability of innovation and diversity within the industry, as fewer resources become available to support emerging talent and new projects. For instance, artists like Grimes and Holly Herndon have highlighted cases where AI-generated music closely imitated their styles, leading to public debates over attribution and compensation. Platforms such as Spotify have also reported difficulties in tracking the origins of AI-created tracks, further complicating royalty distributions.
With the U.S. music market generating over $15 billion annually and the UK market adding $3 billion, even a modest 5% revenue loss due to AI misuse could amount to $900 million annually. For example, AI systems trained on copyrighted music without proper licensing have led to disputes over derivative works, including cases where AI-generated tracks closely mimic the style of popular artists, effectively bypassing traditional royalty structures.
How New Technology Provides a Holistic Solution
To combat the risks posed by AI policies and centralized systems, new technology empowers creators to protect, track, and monetize their intellectual property. Here’s how:
1. Blockchain-Based Copyright Registration
This technology utilizes blockchain to create immutable records of ownership. Blockchain ensures immutability by recording data across a distributed network, where each block is securely linked to the one before it. This interconnected structure prevents tampering, as altering any part of the chain would require changing all subsequent blocks across the network. Each registered work is assigned a unique identifier linked to a decentralized ledger, providing creators with tamper-proof documentation of their intellectual property. This transparency ensures that ownership disputes can be resolved swiftly and fairly, even in cross-border contexts.
2. AI-Driven Infringement Detection
The technology’s AI monitoring tools analyze metadata and content patterns to detect unauthorized usage. By leveraging advanced algorithms, these tools provide greater precision and efficiency compared to traditional methods, enabling faster identification of derivative works and more reliable enforcement of licensing agreements. For example, an artist can track how their music is being used across streaming platforms, ensuring royalties are accurately distributed.
3. Decentralized Licensing and Governance
Through decentralized licensing systems, creators can define and enforce usage terms dynamically. Smart contracts automate royalty payments, ensuring transparency and reducing administrative overhead. Unlike traditional royalty payment systems that often rely on manual processing or intermediaries, smart contracts execute automatically when specific conditions are met. For example, when a song is streamed, the smart contract can instantly calculate and distribute royalties to all stakeholders, eliminating delays and reducing the risk of errors.
4. Proof of Content (PoC) Staking
This mechanism enables creators to validate their ownership through token staking. By staking their content, creators establish a financial and legal claim to their works, deterring unauthorized use and fostering accountability within the ecosystem.
5. Audio Copyright Laundering Prevention
The audio protection framework incorporates model-level detection pipelines that analyze musical elements to differentiate between original, laundered, and synthetic audio. This ensures that derivative AI-generated content cannot bypass copyright protections.
Transforming Challenges into Opportunities
Securing Royalties Amid AI Disruption
With these tools, creators can safeguard their revenue streams in an era of AI-driven disruption. This new technology combines blockchain-based rights management with advanced AI detection and decentralized governance, offering a more transparent and scalable framework tailored for the complexities of the digital age. By automating licensing and enhancing monitoring capabilities, the platform ensures that every use of a copyrighted work is tracked and compensated.
Strengthening Global Enforcement
The cross-border applicability of blockchain-based records allows creators to enforce their rights globally, overcoming jurisdictional hurdles that traditional copyright systems often face. For example, a song registered via this technology within a robust legal framework can be confidently defended in international markets, thanks to immutable blockchain records.
Ethical AI and Fair Compensation
The approach aligns with emerging global standards for ethical AI usage. By integrating transparency, accountability, and fair compensation into its framework, this technology sets a benchmark for how AI and creative industries can coexist harmoniously. The emphasis on provenance and equitable licensing ensures that innovation does not come at the expense of creators.
Conclusion
The challenges posed by recent AI policies in the U.S. and UK underscore the urgent need for robust copyright protection mechanisms. These markets are pivotal as they set global benchmarks for copyright standards, driven by their significant market size, extensive intellectual property frameworks, and influential legal precedents. Their ability to set legal and economic benchmarks inspires other nations to align their regulations accordingly.
New technology provides a transformative solution, combining blockchain, AI-driven detection, and decentralized governance to protect creators’ rights and income. By addressing the systemic risks of copyright laundering and unauthorized AI training, these tools empower creators to thrive in the evolving digital economy.
As the world’s largest music markets grapple with the implications of AI, these innovations are not just solutions—they are essential infrastructures for safeguarding the future of creativity. Creators, investors, and policymakers must act now to embrace these tools, ensuring that innovation and integrity go hand in hand.
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