AI and blockchain can work together, S&P Global report finds

A recent report by S&P Global called “Crypto and AI: Shaping the Future of the Internet” laid out how blockchain technology can mitigate some of the problems and risks associated with artificial intelligence (AI).

While AI has already brought many benefits and will continue to do so, the S&P Global report highlights some risks around privacy, accountability, censorship, bias, cyber threats, data traceability, and even data center energy use.

This is something we’ve been talking about at CoinGeek for years. Finally, it seems the rest of the world is catching on.

The blockchain as an immutable source of truth

Whenever you mention blockchain technology or digital currencies, most people will first discuss the fiat price of Bitcoin or Ethereum. However, that’s slowly changing, and S&P Global’s report indicates that.

Governments, enterprises, and institutions are beginning to realize what blockchain technology is and how it can help them solve real problems. In short, blockchains are digital ledgers with time-stamped records of all the transactions that have ever occurred on them. The records begin with the first block and continue once a single honest node is left.

How can this help with the risks linked to AI? The S&P Global report talks about how it can help with transparency and auditability and how some blockchain projects use micropayments to gather data from IoT sensors. Let’s dig deeper and explore some examples.

Transparency, auditability, and compliance

AI models make decisions, and so do the people who design and refine them. Anyone could audit the models if an immutable record of each of these can be kept on a scalable, low-fee public blockchain like BSV.

This would both reduce risks and create true transparency, which would, in turn, create some much-needed accountability in the AI industry. As AI regulations take shape globally, having a verified record of who did what, where, when, and why would make regulators’ lives easier, not to mention the companies and organizations that must prove they complied with them.

Data provenance

Another growing issue related to AI is data provenance. Where did the data a model trained on come from, and how accurate was it? There have already been several high-profile lawsuits with artists suing OpenAI and others for unauthorized use of their work.

Another related problem is AI model ‘hallucination’ when incorrect answers are given because of lousy training data. Verifying data inputs, ensuring that data is tamper-proof, and proving the source would change AI for the better. Paying people micropayments for access to data they created would also help confirm its authenticity and reduce legal risks; scalable blockchains can help with that.

Privacy, censorship, and bias

More and more people are concerned about privacy when using AI. Where does the information we have shared with LLMs go? What about photos we enhance with AI tools? Will AI assistants and agents collect data on us as social media companies do?

Decentralized control of data would go some way to mitigating these concerns. Blockchain-specific tools like Zero-knowledge proofs, homomorphic encryption, and multi-party computation could make AI models and the apps linked to them much better than Web 2.0 ones from a privacy standpoint.

As for censorship, blockchains are governed by distributed nodes, so they are immune to censorship by default. If a censor were to label AI-generated content misinformation, it could be verified authentic by tracing both the transactions associated with its creation and the data it relied on.

Firms like FICO are already using blockchain technology to weed bias out of their AI models. Transparency and accountability for AI decision-making are crucial, especially in areas like credit scoring, legal decisions, and others that directly impact people’s lives.

The blockchain utility era is growing exponentially

It’s great to see S&P Global and others realize how blockchain can be used as a force for good. After many long years, the utility of this powerful technology is coming to the forefront. Many in the BSV ecosystem have been using it this way for years, but the utility era is gradually spreading beyond the BSV ecosystem.

Of course, for any of these benefits to be realized, a single immutable blockchain must scale to deal with all of the world’s transactions. Transparency is lost when multiple sets of books (private blockchains) controlled by vested interests reemerge.

Currently, only one proof-of-work blockchain can handle the demand: the BSV blockchain. Those interested in how blockchain can create transparency and accountability across many industries, including supply chains, cybersecurity, AI, and others, should learn more about BSV.

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.