IBM, Casper Labs blockchain-based AI governance solution targets improved transparency

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Blockchain service provider Casper Labs has announced plans to integrate artificial intelligence (AI) systems with Web3 technologies for improved transparency and greater consumer safety.

Casper Labs said it will collaborate with technology firm IBM (NASDAQ: IBM) to combine both emerging technologies for new use cases, including developing a solution to regulate AI training governance across several organizations.

The partnership will seek to create a policy enforcement layer for firms, ensuring that organizations deploying generative AI models conform with the original model’s design. Casper Labs will rely on IBM’s watsonx.governance and publicly distributed ledger to achieve this primary objective.

In deploying generative AI models, it is not uncommon for firms to modify large language models (LLMs) by introducing new data sets in ways that may be at variance with the original model training. Creators are often unaware of the wholesale changes employed by firms deploying their models, leading to intellectual property (IP) issues.

Casper Labs says its blockchain-based solution will allow organizations to share information concerning the changes made to AI systems on its ledger. The firm added that the exchange of information reduced the risk of IP crossover while giving creators the opportunity to “remediate issues” that may crop up during deployment.

“With IBM’s help, we’re committed to delivering a better way to not only understand why AI systems behave the way that they do but also a clearer path to remediate behavior if hallucinations or performance issues occur,” Casper Labs CEO Mrinal Manohar.

Casper Labs’ solution will rely on a compliance dashboard, version control to roll back to previous versions, a quality control toolkit, and an audit and reporting system.

The blockchain service provider is eyeing use cases across financial services, retail, healthcare, and manufacturing, with a growing number of firms pivoting to generative AI to improve their productivity.

“AI’s long-term potential will be dictated by how effectively and efficiently organizations can understand, govern, and react to increasingly massive AI training data sets,” said Manohar.

The marriage of AI and blockchain

As copyright and data handling issues continue to threaten AI’s long-term future, experts are pushing for a wholesale integration with blockchain as a solution. For starters, industry stakeholders point to blockchain’s tamper-proof and transparency properties as features that could improve AI platform data handling and safety.

Others are exploring new use cases, including using blockchain to track content usage by AI firms to prevent copyright infringement.

“Given that blockchain is tamper-resistant, completely time-synched, and can be completely automated, AI governance can be done right, be highly automatable, and highly certifiable right out the gate,” Manohar said.

While AI is regarded as a critical technology that will supercharge innovation, some are still adamant about integrating it into their services despite its growing adoption in enterprises, which is likely rooted in the tech’s infringement and fair use issues.

This is where the importance of integrating AI with blockchain comes in.

Giovanni Franzese, former head of blockchain at Ericsson, said blockchain provides data security that AI lacks in its current state.

“AI will be another key technology to combine with blockchain, and we will see the wonderful things that the technologies will manage to achieve,” noted Franzese in an earlier interview with CoinGeek. “AI needs to achieve the traceability and immutability of data, which only blockchain will achieve.”

Besides providing data security, blockchain also has the ability to validate the authenticity of data, which is of particular importance for AI developers, who heavily rely on data to train their large language models (LLMs), according to nChain Director of Commercial and Strategy Simit Naik.

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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