Nfts
AI Could Transform NFT Markets, But Ethical Challenges Loom, Nuklai CEO Warns
Speaking to crypto.news, Matthijs de Vries, CEO and founder of Nuklai, reflected on the ethical implications of using AI around the world. NFT sector.
The advent of AI has opened up many new possibilities, and one of the sectors that has heavily leveraged this technology is NFTs. From generate NFT art to improve verification processAI is becoming an essential tool in the world of decentralized digital art.
However, this rapid integration also raises some ethical concerns. Issues such as intellectual property rights, the potential for misuse of AI-generated content, and the transparency of AI algorithms are at the forefront of this debate.
The need for strong ethical guidelines and policies becomes more critical as AI’s influence in the NFT space grows. Striking a balance between innovation and ethical considerations will be essential to fostering a sustainable and trustworthy ecosystem.
De Vries sees AI as a transformative force for improving the verification and security of NFTs, but he says that addressing its ethical challenges is crucial to maintaining a reliable and sustainable digital art ecosystem.
AI is under criticism for copyright issues and is also seen as a solution to the copyright issues of NFTs. How can AI effectively address these issues, given its own copyright challenges?
Technology can be a double-edged sword. For example, generative models in AI have both helped and harmed. They have been used to copy artists’ work without permission – this misuse is quite common in scams. A scammer’s unauthorized use of an artist’s work often results in AI-generated creations that are similar to or indistinguishable from the artist’s original work. Such creations spark debate over property rights violations and illustrate the need for stricter regulations in the development of AI. At the same time, AI algorithms can detect derivative works and counterfeits, even if they have subtle modifications. Humans might miss them. For example, AI can learn an artist’s style and then identify their copies. This ability is crucial for resolving copyright issues.
There are also some ethical concerns. These include intellectual property and potential misuse of AI-created content. How should platforms address these concerns to maintain trust and integrity?
AI requires specific data for training. Artists can embed ownership details into the NFT representing a work of art. This clear traceability back to the original creator ensures that anyone can verify the owner of the piece. Platforms can deploy AI to analyze this data and crawl the internet for works that attempt to replicate the creator’s art. If it finds similar parts, it can check the authentication information. This will flag any differences and help artists assert their intellectual property rights. Platforms can also distribute automatic royalty payments based on authorized use of the art.
This system ensures fair payment and tracks data usage in blockchains. It protects the rights of creators and encourages ethical use of content. Additionally, an NFT marketplace with advanced AI protects artists from misuse of ownership and buyers from fake art. These steps reduce scams, thereby strengthening the trust and integrity of the platform.
In your experience, what progress is being made toward achieving real-time NFT verification using AI?
With information about the provenance of NFTs, AI can process these large amounts of data to verify a real or fake NFT in near real-time. We can train AI to recognize unique attributes only found in authentic NFTs. This quick check prevents fraudulent listings and can alert users before they potentially purchase counterfeits. This helps prevent the sale of counterfeit or even stolen NFTs.
How do you think these advances impact the user experience?
As AI gets better at detecting this information, it can expand its capabilities beyond identifying fake NFTs. For example, AI can be used to detect volume spikes for a particular NFT listing. It could also report multiple NFT listings with similar attributes. This would shut them down before anyone had a chance to buy. NFT marketplaces all operate on blockchain networks, known for their open source nature. A trustworthy NFT marketplace will make its AI’s learnings public for anyone to see, allowing buyers to view the history of an NFT. This is not to say that blockchains are immutable, meaning users can rest assured that the data in an NFT has not been tampered with.
More and more people are using AI-based systems to verify the origin of NFTs. How do these systems guarantee the authenticity of digital assets?
To verify whether a digital asset is authentic, AI needs a robust data trail to determine its origin and ownership. Public data sources provide a verifiable trace of authenticity. They are the perfect way to train AI because they show the many ways fraudsters attempt to exploit the system. Collaborations on data and on-chain verification can add significant value to AI-enabled digital assets. AI can also assess real-world assets (RWA) and intellectual property rights.
What do you see as the biggest challenges in maintaining data accuracy and preventing fraud?
Of course, bad actors will continue to find ways to circumvent existing systems. This is why public collaboration is essential, as developing trainable data will help AI detect new fraud methods as they emerge. AI training also requires accurate data. This requires NFT owners to properly document the history of their assets. As long as the human side of NFTs is correct, so will the AI results. When it comes to privacy, AI can know what information to share and what to keep private. This comes down to the fact that NFT developers and marketplaces build their systems in a way that promotes artist privacy. AI doesn’t decide what information should be private or not – that’s up to humans to decide.
Digital product passports (DPPs) are a growing concept. It aims to track the history and ownership of luxury items and NFTs. How do AI and blockchain enhance the security and authenticity of PLRs?
Digital passports are easily created by verifying and tracing all supply chain data. This data is then put into an NFT to show its origin. It tracks everything, like its environmental footprint, ownership, and maintenance. AI models can then detect fraud by finding unusual patterns. AI can explore the web faster than humans and does not require rest. Essentially, AI can monitor multiple NFTs 24/7 and immediately flag NFTs with inauthentic DPPs. However, AI works best with publicly available data. Blockchain-powered supply chains are completely transparent. They allow AI to understand their inner workings and note discrepancies, making them more effective when tracking NFTs.
Finally, could you explain to our readers how neural networks and machine learning make NFT authentication more accurate and efficient?
Anyone could replicate an NFT collection and create a counterfeit version, but the underlying data would reveal that it is not the original. Neural networks analyze everything, from the metadata of the NFT to the style of its creator, in ways that the human eye could never pick up. Hackers and scammers are getting smarter and smarter. They are constantly finding new ways to deceive people. But AI can reliably validate the authenticity of an NFT when trained on various datasets and combat any new method proposed by a bad actor. It’s difficult for most people to tell counterfeits apart – and training AI on large data sets makes fraud detection easier. Technological advancements, such as neural networks, are further improving the ability to integrate in-depth verification methodologies into NFT marketplaces.