How Blockchain Can Serve AI Rights Management

As AI technologies continue to evolve and become more integral to creative industries, one of the most pressing challenges is how to ensure authenticity and verifiability in AI-generated content. Whether we’re talking about images generated via platforms like Alias.studio or information retrieved and augmented by Retrieval-Augmented Generation (RAG) techniques for large language models (LLMs), the need for clear provenance, traceability, and verification is paramount. Indeed, one of the key challenges in AI Rights Management (AI-RM) is ensuring that the ownership, creation process, and license associated with generative AI works are clearly defined and cannot be easily altered or disputed. This is where blockchain technology comes into play, providing a transparent, secure and immutable ledger for managing rights and ownership over time, ensuring that AI-generated content is both authentic and properly licensed.

1. Ensuring Authenticity & Verifiability

In the world of AI-generated art, authenticity is one of the most significant concerns. As artists and creators increasingly rely on AI platforms like Alias.studio to generate works, the question arises: How can we prove that these works are genuinely stemming from the original model created by the artist, and not tampered with or misattributed?

Blockchain offers a solution by recording every step of the creation process in a decentralized and immutable ledger.

For instance, when a user purchases the collectible of AI-generated artwork on Alias.studio, the hash of the artwork is timestamped on the blockchain, along with metadata information (stored on IPFS) concerning the model’s training parameters and the specific prompt used. As such, the NFT can be regarded as a digital fingerprint that can be used to verify the authenticity of the content, preventing counterfeit or unauthorized copies from circulating. Every transaction — whether it’s the creation, sale, or transfer of the NFT — is recorded on the blockchain, creating an immutable audit trail of who owns the rights to a particular piece of AI-generated content at any given time. This creates a transparent and verifiable history of the work ownership, which can be accessed by anyone to verify its originality.

2. Provenance & Traceability of AI-Generated Content

In addition to authenticity, provenance is crucial in both the art world and in fields where AI-generated data is used for producing useful or meaningful content — be it a visual artwork, written text, or data-driven insights. Indeed, being able to trace the origin of an AI-generated work is often vital to establishing trust in the content.

One of the main advantages of using blockchain-based legal tech for AI-RM is that it provides full transparency and traceability. As a tamper-resistent and append-only ledger, a blockchain can be used to record, for example, what data was a model trained on, where an AI-generated image was sourced from, and who prompted it. As a result, artists, researchers, and businesses can ensure that their generative AI models are trained on legitimately sourced data and that all relevant licensing agreements are met. This can help avoid data misuse and infringement issues that can arise when AI models are trained on datasets without proper consent from data owners.

Another critical concern when it comes to generative AI is understanding where the data comes from and how it is used to train generative models. With blockchain, it’s possible to create a transparent record of the datasets used in training an AI model, which can be accessed by the public or relevant stakeholders to verify the proper use of such data. This is particularly relevant for AI-generated works that incorporate RAG or similar techniques for information retrieval in large language models (LLMs). For example, if a language model is tasked with retrieving and summarizing information from a dataset, blockchain can track the source of that data, for others to be able to verify that it’s from legitimate sources, and therefore ensure that the model’s output is also legitimate. Without blockchain, the source content would be vulnerable to manipulation, making it harder to prove the legitimacy of the resulting information.

3. Preventing Tampering & Ensuring Data Integrity

One of the key benefits of blockchain technology is its immutability. Once data is recorded on a blockchain, it cannot be altered or erased without consensus from the network, providing a level of security that is crucial when it comes to managing AI-generated content.

This is particularly important in areas like LLM outputs or content augmentation where RAGs are used to retrieve and generate information. Blockchain can help ensure that the AI’s input (i.e. training dataset or RAG source information) has not been tampered with at the time of use. For instance, the embeddings of a RAG could be hash on a blockchain every time the RAG is being updated with new information, so that, if a user were to generate a report about specialized knowledge using that, it could use the blockchain to verify that the content of the RAG has not been altered after it was originally created, ensuring the information is still trustworthy and intact. The transparency and immutability of the blockchain ensures that any modification of the RAG can be easily identified, maintaining both the integrity of the data and the trustworthiness of the AI model’s output, without ever having to disclose the raw information that has been collected into the RAG.

4. Blockchain for Copyright Licensing & Fair Use

Another key challenge of using AI in content creation is managing copyright and ensuring that AI-generated works comply with intellectual property (IP) laws. Indeed, generative AI models might be trained on datasets that contain copyrighted materials, creating potential concerns about fair use and whether the output is infringing upon the rights of the original creators.

Blockchain technology provides a mechanism to verify that the training data used by AI models is legally licensed and that the resulting work complies with copyright regulations. Regardless of their legal status, the use of smart contracts can support the enforcement of existing contractual agreements, e.g. by distributing royalties based on the copyright license’s terms, ensuring that artists, creators, and data owners are compensated fairly for the use of their work.

On Alias.studio, we leverage blockchain-based legal tech to not only ensure authenticity and provenance but also to create a system of dynamic rights management that adapts to the needs of the artist and the buyer. This is achieved through the use of token-bound licenses linked directly to non-fungible tokens (NFTs).

The Role of Token-Bound Licenses in AI-RM

At the heart of this system is the NFT, which serves as both a digital representation of the AI-generated artwork and the mechanism for managing its associated rights. Traditionally, when a piece of art or content is sold, the license to use or distribute the work is often separate from the transaction itself, leading to confusion, miscommunication, or even disputes over what rights the buyer actually holds. With blockchain, we can eliminate this issue by embedding legal contracts and licenses directly into the NFT.

Token-bound licenses on Alias.studio work by linking the rights associated with a generative AI artwork to the NFT itself. These licenses are embedded (i.e. “hashed”) into smart contracts on the blockchain, ensuring that the rights (such as the ability to commercially use the artwork) are automatically transferred when the token is sold or transferred. This means that the license follows the token: wherever the token goes, the rights attached to it go with it.

For example, if an artist creates an AI-model on Alias.studio, they can define specific terms of use, such as whether the resulting artworks can be sold commercially or displayed publicly. When users generate images from that model, they can tokenize these images as an NFT, and a token-bound license containing those specific terms is automatically attached to the token. This means that when the NFT is transferred on the secondary market, the rights associated with the image (as dictated by the smart contract) are automatically transferred to the new owner. The blockchain will continue to track the specific licensing agreements associated with that work, ensuring that the next purchasers clearly understand the rights they’re purchasing.

This system is particularly important in the context of AI-generated content because it ensures that the rights are clear, legally binding, and easily transferable. It eliminates the need for traditional licensing intermediaries and minimizes the risk of license infringement or misuse.

Conclusion

AI Rights Management systems represent a paradigm shift in how digital content is managed, transferred, and protected. Blockchain technology provides the transparency and security necessary for AI-RM systems to provide verifiable proofs of authenticity and provenance, as well as the real-time traceability of rights, allowing creators, consumers, and businesses to confidently engage with AI-generated content in a fair, legal, and transparent manner.

By embedding token-bound licenses within NFTs, platforms like Alias.studio enable artists to retain control over the rights to their AI-generated works while ensuring that those rights are easily transferred, tracked, and verified throughout the lifecycle of the work. This innovative approach not only helps protect artists. but also empowers buyers with clear and enforceable licenses that follow the content wherever it goes.

Thus, whether it is for the creation of AI-generated artwork on platforms like Alias.studio or through the use of RAGs in large language models, the integration of blockchain-based legal tech into AI Rights Management (AI-RM) is an invaluable addition to create the confidence and trust necessary to address legal concerns, copyright infringement, and ethical questions in the use of AI technologies.