Major media organizations are increasingly signing licensing agreements with the AI Giants. For newspapers like The New York Times, such transactions protect intellectual property and provide additional revenue streams.
Meanwhile, companies like Openai and Amazon can train their models with accurate information and avoid copyright infringement lawsuits. However, experts from IoTex Network, O.Xyz and Ar.io told Beincrypto that existing decentralized alternatives could achieve the same results for content creators more transparently and equitably.
New York Times’ new AI strategy
In a fairly high-profile move, the New York Times signed a deal with Amazon earlier this month, allowing Amazon to use its editorial content to train AI (AI) models for high-tech companies.
The New York Times and Amazon licensing agreement allows high-tech companies to use articles from newspapers and other publications. However, newspaper publications regarding the transaction did not reveal financial conditions.
The decision illustrates public change in the New York Times strategy that previously opposed large-scale language modeling (LLMS) using content without permission.
In January 2024, the newspaper sued Openai and Microsoft over copyright infringement. The New York Times alleged that these companies used copyrighted articles to train LLMS without permission or compensation. The lawsuit is still ongoing and has not yet reached results.
The New York Times is not the first media organization to sues technology companies for unfair use of intellectual property.
“In recent years, many large-scale high-tech projects have encountered many legal challenges and fines. For example, Google has faced fines of more than 8 billion euros from the EU due to insufficient data practices over the past decade.”
Such transactions are becoming increasingly common as major LLM creators require broader access to accurate information.
The rise of license transactions
Licensing transactions are becoming more popular. Last year, Openai, led by Sam Altman, signed a contract with European multinational media company Axel Springer SE. The deal closely reflects what it has done recently between the New York Times and Amazon.
The agreement allows Openai to use articles from media organizations owned by Axel Springer, such as Politico, Business Insider, and Morning Brew.
Altman later signed similar agreements with the parent companies of outlets such as Financial Times, Vogue and The New Yorker, Cosmopolitan and Le Monde. Openai has agreed to backlink all relevant information to the original article as part of these transactions.
These situations are advantageous to all involved as major tech companies face increased pressure on intellectual property violations and copyright infringement.
“After the lawsuits like the ones filed by the New York Times, AI companies are becoming more cautious about what they train. Licensing transactions provide peace of mind. It’s an opportunity for publishers to turn archived content into stable revenue.
But is there a better way to increase transparency and achieve the same results?
Can decentralization bring transparency to AI trading?
It is becoming increasingly urgent to find solutions that will broaden your access to trustworthy information when interacting with AI and significantly compensate for its creators. A license agreement provides one path to this goal.
“There’s great strategic value. These transactions include better visibility, such as being featured in AI-generated answers and summaries. They also have access to analytics that show how content is being used or interacted with,” says Basi.
It also helps to prevent false alarms when using LLMS.
“Training AI without validated transparent data is like a blind flight. If you can’t track what comes out, you can’t trust what comes out. This is a way to end with a quiet obstacle created by a fragile AI model with no long-term considerations.”
However, these licensing agreements are often private, making it difficult for small content creators to secure similar transactions or protect themselves from unfair use. Decentralization could potentially level the arena here.
“The closed model wins a short-term sprint. The distributed model wins a marathon. The trust is the best governance along with transparency and auditability,” added Mataras.
There are several different tools that Web3 has to offer and you can achieve such things.
Tokenizing content in a distributed network
Decentralized technology allows all creators to create more democratic and transparent systems for their content to be licensed. This is particularly beneficial for those who are often overlooked by traditional private agreements.
“Instead of reducing individual licensing transactions in a closed room, creators can upload content to a distributed network. Smart contracts can force terminology and process payments automatically, making it easier for independent creators or small organizations to participate.
Tokenization provides creators with a way to track the active use of content by AI models.
“Tokenizing content can allow publishers to have more control and better tracking. For example, you could set rules about access and use and get paid automatically through smart contracts. It’s too early, but for digital first media companies, this kind of setup might offer a new way to earn revenue without giving up on control,” Basi added.
Other blockchain-based solutions can ensure unbreakable record maintenance to further enhance these decentralized options.
Protect your intellectual property through blockchain-based systems
Another important aspect of a truly equitable digital ecosystem is ensuring reliability, tracking usage, and protecting intellectual property. This is where blockchain-based origin systems emerge as powerful solutions.
Blockchain-based origin systems are designed to fine-tune the history and genealogy of digital content. They leverage the core blockchain features (tracing, transparency, immutability) to create reliable tamper-proof records.
From its creation to changes and transfers, all important events in the content lifecycle are recorded in a distributed ledger, allowing you to create an unbreakable record of its history.
“The source system has been extremely useful in the technology industry. To be precise, it requires that you portray the history of the dataset in which the dataset is utilized or transferred. It shows that the first owner, the person sold, the current holder of that dataset, and the current holder already have a permanent storage mechanism.
Building on this foundation of verifiable history, watermark tools complement the origin system by embedding hidden, identifiable information directly into digital content.
“Watermark tools play an important role in preventing copyright infringement, data theft, and illegal claims of ownership… These techniques bring a tougher game to data thieves and hackers to provide data integrity, fairness and ethics,” Shadid added.
The principles of decentralization can also be extended to collective governance and management of content.
Media Daos: Strengthen the power of content license creators
Instead of individual creators and large media organizations’ leadership, simply make content licensing decisions, and a distributed autonomous organization (DAO) can work together to enable a group of creators, such as journalists, to control decision-making.
“A group of creators can pool their work and manage licensing, payments and governance using DAOs. This approach gives the table an independent voice when dealing with large AI companies. It also makes it easier to negotiate fair terms and make decisions collectively.
Despite focusing on transparency, the licensing agreement between the AI model and the source is still in its infancy. This raises an important question. Will the open source model be delayed as AI companies ensure exclusive data trading?
License Transactions vs. Decentralization: Which Passes Will Succeed?
The unauthorized and opaque use of LLMS content initially caused major dissatisfaction among the original creators. The licensing agreement has improved the situation.
However, there has not been a full transparency yet. The kind of deal that’s been struck between The New York Times and Amazon isn’t enough for creators who want to know where their data is available, or understand how their content is being used.
“The closed model wins a short-term sprint. The distributed model wins a marathon. The trust is the best governance along with transparency and auditability,” Mataras said.
Basi agreed, add:
“Transparency is a powerful advantage. People want to understand what comes into the tools they use, especially in sensitive areas such as health and education. Open source projects can quickly adapt, get help from the community, and build trust through openness.
While licensing transactions are a good starting point, the real transformation of content creators and AI transparency can be attributed to a decentralized and open source approach.
Post-content tokenization could be the next biggest AI trend. This is why it first appeared in Beincrypto.
