As the world pivots toward artificial intelligence (AI) and machine learning systems, experts are mulling the possibilities of convergence with blockchain technology to foster safe and responsible usage.
Simit Naik, nChain’s Director of Commercial and Strategy, said in an interview with CoinGeek Backstage that the possibilities stemming from interlinking AI and blockchain are endless. Naik shared insights on merging both technologies at an event organized by the Global CIO Institute in Oxford revolving around the use cases of blockchain.
For Naik, blockchain can provide the answer to a host of challenges faced by AI systems, including the challenge of validating data for training large language models (LLMs). Using the immutability properties of distributed ledgers, Naik opines that AI developers can prove the source, legality, and appropriateness of data used to train LLMs.
“The convergence of blockchain and AI is going to be extremely important to ensure that AI is used in the correct way,” said Naik. ”Blockchain technology can be used to ensure that data for LLMs is sourced from the right people or the right data set.”
Apart from verifying sources, Naik remarks that AI systems can make use of blockchain to handle the permissions for data used in training LLMs, ensuring that only authorized individuals have access. The nChain executive pointed out that this feature will improve public trust for AI systems amid growing concerns over the handling of personal data by large technology firms.
In another use case, Naik opined that blockchain could be deployed to track AI-generated content, given the growing difficulty distinguishing synthetic content from human efforts. Machine learning systems have faced an uphill climb in making proper distinctions, prompting Naik to offer to use blockchain to identify AI-generated content.
“Even though the conversation of AI and the convergence with blockchain isn’t something we hear about today, I think with everything that has happened with AI and some of the concerns businesses are facing, the topic around AI and blockchain is going to become extremely important over the next few weeks,” Naik remarked.
Naik disclosed in the course of the interview that a popular misconception is that blockchain is focused solely on digital currencies, non-fungible tokens (NFTs), and decentralized finance (DeFi). He clarified that, on the flip side, the technology offers several use cases in areas of data integrity, transparency, and traceability.
AI developers face challenges
AI firms are operating in uncertain terrain at the moment, underscored by the barrage of regulatory and legal actions. OpenAI, makers of ChatGPT, have faced intense regulatory
scrutiny in several jurisdictions over the handling of user data, while others are probing the company over its data collection methods.
Meta (NASDAQ: META) and Anthropic are facing their share of legal travails revolving around allegations of copyright violations and unjust enrichment by aggrieved intellectual property (IP) holders. A core theme of the class action lawsuits is a claim by plaintiffs that both AI firms illegally used copyrighted materials to train their LLMs without seeking permission from creators.
In order for artificial intelligence (AI) to work right within the law and thrive in the face of growing challenges, it needs to integrate an enterprise blockchain system that ensures data input quality and ownership—allowing it to keep data safe while also guaranteeing the immutability of data. Check out CoinGeek’s coverage on this emerging tech to learn more why Enterprise blockchain will be the backbone of AI.
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