AI is a snapshot of our generation and we need to get it right. That’s what Stanford University professor Fei-Fei Li told Joe Biden this month when he became the first president to talk about the impact of artificial intelligence in his State of the Nation address. Our original moonshot required new technology and new ways of thinking to propel us forward. While the unimaginable possibilities of the latest AI models capture most of the attention, the most important AI story yet to be told is the technology emerging to make it safe, accountable and useful for everyone.
Blockchain and Web3: Ideal Hosts for Neutral Artificial Intelligence
Blockchain and Web3 technologies are uniquely positioned to address the challenges of modern AI applications. By securely anchoring AI training data, models, and operations, Web3 provides the guardrails and transparency that closed AI systems lack. This visibility into data origins and decision-making processes is critical to preventing bias, ensuring fair use of content, and managing the capabilities of increasingly powerful AI models.
The core technologies that power Web3 lend themselves naturally to neutral artificial intelligence. Blockchains, decentralized computing and transparent governance address the risk of AI becoming an unaccountable black box that puts us at the mercy of any player.
With distributed ledgers, blockchains offer an undeniable level of transparency and provenance. No single player owns a truly decentralized blockchain. Independent parties keep their own copies of each transaction, ensuring that data origins are traceable and immutable. This cryptographic security, along with consensus mechanisms, guarantees data integrity, making blockchains an ideal platform for securing neutral AI applications.
While blockchains support the data security of a neutral API, Web3’s decentralized computer networks provide the power. Decentralization creates an open market of servers, GPUs and storage available on demand to train and run AI. The code portability required for decentralization creates strong incentives around open source AI frameworks instead of proprietary tools favored by tech giants. This open market also provides a rational basis for anyone who owns computing resources—be it a cloud service provider, startup, university, or public consortium—to run neutral AI by removing the economic benefit of hoarding those resources.
However, the biggest Web3 innovation that will promote neutral artificial intelligence is transparent governance. This is how we as users of AI will be able to decide how to keep it safe, fair and honest. Transparent governance, expressed through smart contracts and other forms of verifiable code, provides clear rules and switches that align with our societal consensus about what we want AI to do for us. The ability to get paid when AI uses the content you create can be automatically applied to all work produced. Biases and blind spots can be permanently eradicated by enforcing coding requirements and training data. And all these rules can be continuously, publicly checked for harmonization.
Verified Compute makes Web3 right for business
Web3 has the power to make AI trustworthy and neutral, and technology is advancing rapidly to meet that need. Web3 skeptics have previously pointed to scalability, data privacy and environmental impact as barriers to adoption. The new generation of blockchain and the greatly expanded Web3 technology set close these gaps. This positions Web3 to become a key part of the emerging infrastructure for AI, and further advances in Web3 will require investments smaller than the astronomical cost of purchasing GPU chips.
Zooming in even further on the Web3 set, verified compute stands out as a capability that unlocks the potential to create neutral artificial intelligence. Verified compute enables networks of independently owned computers to operate securely and transparently. While blockchains provide a ledger for recording the audit trail of a decentralized network, verified computing makes it safe to send AI training tasks and model inference requests to servers you don’t control. Verification allows observation of the code, inputs, and outputs of an AI computing task and provides immutable proof of correctness.
This ability to auditably run any code anywhere also serves as a transparent management platform. The complex code needed to independently track training data across myriad sources and enforce AI security can be reliably run on a trusted computer network without any one party holding dictatorial control. This approach ensures that AI applications remain unbiased, transparent and verifiable, fostering trust and integrity in digital ecosystems.
The marriage of Web3 and AI
It’s no secret that there’s a race to understand the positives of AI in every industry and scientific discipline. As we wrestle with the larger question of how to lay the groundwork for these profound changes without sowing the seeds of destruction, we must move deliberately toward a level playing field. Web3 allows us to pool resources, collaborate on the development of underlying technology, and fairly compensate for the real human work that AI makes possible. When rationally weighed against a model where only a few players invest trillions of dollars to “win it all”, an AI-driven Web3 is the fastest route to the most profit for all.