Artificial Intelligence and blockchain: The “power couple”

With the advent of Web 3.0 capabilities, the use and benefits of Blockchain are clear – Blockchain can be the “Governor” that generative AI needs, enabling you to guard IP, mitigating cyber and regulatory risks, and opening new revenue streams.

The race at almost every company to adopt generative artificial intelligence (AI) technology platforms such as ChatGPT and Co-Pilot drive innovation has started to raise one fundamental question: How do you translate AI into real business results?

So how can business’ unlock that significant potential while also navigating AI’s potentially significant risks is fast becoming THE pressing concern for government and business leaders as AI strategy has moved rapidly from the innovation lab to business adoption using mission critical data to transform business processes.

Our research, backed up by industry experts shows executives are optimistic that AI will drive innovation for their businesses.  Our survey of  executives across a wide range of industries showed that:

• 77% of the executives see generative AI as the most impactful emerging technology they will use
• 71% plan to implement their first generative AI solution within two years

There is a major challenge with this adoption and recent European legislation has highlighted the need to act. Because AI learns by scraping all available data—including yours and, potentially, that of your competitors—how can you protect your intellectual property (IP), avoid the unwitting infringement of IP that others own, and meet the new EU and upcoming UK legislation?

One solution Katlas has been developing is from a previously hyped and often misunderstood technology. Allow us to reintroduce you to blockchain.

Has blockchain found its true calling?

Blockchain—a decentralized, distributed technology that’s primarily been used to develop and manage cryptocurrencies, smart contracts, and nonfungible tokens (NFTs)—is being seen increasingly as the AI “Governor” now needed by the business world.

The limitations of Web 2.0 blockchain platforms and solutions have been overcome with the potential of Web 3.0 and harnessing blockchain’s immutable and transparent nature, enabling  companies to seamlessly integrate valuable IP “guardrails” into generative AI models, not only protecting it from misuse but also opening new business and revenue channels.

Here at Katlas we have developed a blockchain platform that delivers tangible benefits by  protecting against AI misuse, providing control and a detailed audit trail of Gen AI use.

Accurate identity and verification: Being able to decentralize identity and verification through blockchain could ensure the authenticity and ownership of IP used to train AI models. Blockchain can create an irrefutable record of transactions, attributing the IP to its rightful owner and preventing unauthorized use.

Proper attribution and royalties: Transforming IP into cryptographically secured NFTs managed by smart contracts operating across a  blockchain, will enable companies to specify which parts of their IP can be used freely, which require attribution, and which require payment of royalties or compensation.

Protection against infringement: Storing and tagging IP on a blockchain before making it available to generative AI models can significantly reduce the risk of infringing on someone else’s intellectual property. Companies can compare their content with existing blockchain records to identify potential overlaps and avoid lawsuits or copyright violations.

Legal certainty: AI is starting to be regulated. Cases are already emerging demonstrating the need for legal frameworks around copyright protection, ownership, liability and the need to provide irrefutable  proof of the data ingested by AI models. By adopting blockchain technology, companies can proactively address these uncertainties and establish transparent and traceable records of their content.

Data privacy and compliance: Generative AI raises concerns about data privacy, particularly when AI models are trained on publicly available data. By incorporating blockchain into the process, companies can ensure compliance with data protection regulations and demonstrate responsible use of AI technologies.

The (block)chain of secure command

Blockchain has many capabilities that are generative AI’s ideal technology complement —providing the “people” and “process” components are also incorporated.

The legislative frameworks being adopted by governments and organisations will drive increasing data and process management overheads for the adoption and enforcement of responsible AI frameworks.  A key requirement is to develop an approach to designing, building, and deploying AI systems in a safe, trustworthy, and ethical manner that will need to include all parts of that people-process-technology equation.

Can your organisation ensure data integrity, statistical validity, and the accuracy of the predicative models today?  If not it is time to get prepared.

In our recent AI risk survey, over 80% of respondents said their company had a clear definition of AI and “good”  understanding of their predictive models—except that many of the companies surveyed are also using “blackbox” solutions developed by third parties that simply don’t offer a clearly defined level of transparency.

To successfully manage AI risk, companies must consider their entire AI ecosystem and the complete lifecycles of everything within it—and then design an operating model and processes that reflect leading governance practices for establishing a responsible AI framework.

Use Case: Using blockchain to safeguard IP as Gen AI is deployed

Take a hypothetical outsourcing service provider, with terabytes and decades worth of contracts, SoWs, collateral such as white papers, blog posts, and PowerPoint presentations that it has used to market to and engage with clients and potential clients.

Pointing a Gen AI model such as ChatGPT at that content to, for example to generate faster responses to RFPs, or to quickly tailor the company’s point of view on various topics when its executives are asked to make presentations at conferences. The company wants to know that once the AI model has had access to this proprietary data it won’t allow that data to be used unfairly by the company’s competitors. Or, where reuse would be acceptable, the company may want to ensure that it is credited, or even compensated, for that reuse. It also wants to be sure it is able to prove the governance, source and interpretation of the data used should there be a challenge to what the AI model has generated (e.g. resulting in the violating of a confidentiality agreements).

By transforming IP into cryptographically secured NFTs managed by with embedded smart contracts operating across a stored on a blockchain the company could flag each of these with codes so the AI model has traceable records of IP that could be used freely, which could be used only with attribution, and only with permission, and only with the payment of royalties or some other form of compensation. The Katlas platform can recognise these codes with minor user effort.

Similarly, if such a company wants to use their Gen AI model to create a proposal for a client, but then discovers that a key component of the proposal largely mirrors concepts developed and perhaps copyrighted by one of its competitors — with possible lawsuit  implications, it can avoid potential litigation.  By storing and tagging their IP on a Katlas blockchain before making it available to generative AI models, the potential for infringing on someone else’s intellectual property could be reduced significantly.

There are clear drivers in this new Gen AI world where companies want to be first movers and create new value for their business and clients. This could be hindered by the additional  risks of managing these. Some have already ended up in court.