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, delved into the ethical implications of using AI in NFT sector.
The dawn of AI has opened up many new possibilities, and one of the sectors that has heavily leveraged this technology is NFTs. In generating NFT art to improve verification processesAI is becoming a fundamental tool in the decentralized world of 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 robust ethical and policy guidelines becomes more critical as AI’s influence in the NFT space grows. Balancing innovation with ethical considerations will be key to fostering a sustainable and trustworthy ecosystem.
De Vries sees AI as a transformative force for improving NFT verification and security, but says addressing its ethical challenges is crucial to maintaining a trustworthy and sustainable digital art ecosystem.
AI faces criticism over copyright issues and is also seen as a solution to NFT copyright issues. How can AI resolve these issues effectively, given your own copyright challenges?
Technology can be a double-edged sword. For example, AI’s generative models have both helped and hurt. They have been used to copy artists’ work without permission – this misuse is quite common in scams. Unauthorized use of an artist’s work by a scammer often results in AI-generated creations that are similar to or indistinguishable from the artist’s original work. Such creations spark conversation around property rights violations and illustrate the need for stricter regulations on AI development. At the same time, AI algorithms can detect derivative works and fakes, even if they have subtle changes. Humans might miss that. For example, AI can learn an artist’s style and then identify copies. This ability is crucial in addressing copyright issues.
There are also some ethical concerns. This includes intellectual property and potential misuse of AI-produced content. How should platforms address these concerns to maintain trust and integrity?
AI requires specific data for training. Artists can incorporate 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 scan this data and scour the internet for pieces that attempt to replicate the creator’s art. If you find similar parts, you can check the authentication information. It will flag any differences and help artists enforce their intellectual property rights. Platforms can also distribute automatic royalty payments based on permitted use of the artwork.
This system ensures fair payment and tracks data usage on blockchains. Protects the rights of creators and encourages the ethical use of content. Additionally, an NFT marketplace with advanced AI protects artists from property misuse and buyers from fake art. These steps reduce fraud by increasing trust and platform integrity.
Based on your experience, what advancements are being made to achieve real-time NFT verification using AI?
Given information about the origin 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 can purchase counterfeit products. It 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 find volume spikes for a specific NFT listing. It could also flag multiple NFT listings with similar attributes. This would close them down before anyone had a chance to buy. All NFT marketplaces run on blockchain networks, famous for their open-source nature. A trusted NFT marketplace will make its AI learnings public for anyone to see, allowing buyers to see the history of an NFT. Not to mention that blockchains are immutable, meaning users can be confident that an NFT’s data has not been tampered with.
Increasingly, people are using AI-based systems to verify the origins 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 origin and ownership. Public data sources offer a verifiable trace of authenticity. They are the ideal way to train AI as they show the many ways fraudsters try to game the system. Data collaborations and on-chain verification can add significant value to AI valuation of digital assets. AI can also value real-world assets (RWAs) and intellectual property rights.
What do you think are some of the main challenges in keeping data accurate and preventing fraud?
Of course, bad actors will continue to find ways to bypass existing systems. This is why public collaboration is critical, as expanding trainable data will help AI detect new fraud methods as they emerge. AI training also needs 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 discoveries. When it comes to privacy, AI can learn what information to share and what to keep private. This comes down to NFT developers and marketplaces building their systems in a way that promotes artist privacy. AI doesn’t decide what information should or shouldn’t be private – that’s up to humans.
Digital Product Passports (DPPs) are a growing concept. The goal is to track the history and ownership of luxury items and NFTs. How do AI and blockchain increase the security and authenticity of DPPs?
Digital passports are made easily by verifying and tracking all supply chain data. This data is then placed into an NFT to show its origin. It tracks everything like environmental footprint, ownership, and maintenance. AI models can then detect fraud by finding unusual patterns. AI can crawl the web faster than humans and requires no 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 notice discrepancies, making them more effective at tracking NFTs.
Lastly, 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 NFT’s metadata to its creator’s style in ways the human eye could never capture. Hackers and scammers are getting smarter. They constantly invent new ways to deceive people. But AI can reliably validate the authenticity of an NFT when trained on diverse datasets and combat any new methods a bad actor comes up with. Spotting fakes is difficult for most people – and training AI on large data sets makes it easier to spot fraud. Technological advancements such as neural networks further increase the ability to incorporate extensive verification methodologies into NFT markets.