Industries in all places are asking “What can AI do for us?”
However the blockchain business, recognized for difficult norms, can be asking the other query: “What can blockchain do for AI?”
Whereas there are some compelling solutions, three narratives have emerged round this query which might be often deceptive and, in a single case, probably even hazardous.
Narrative #1: Blockchain can fight misinformation brought on by generative AI
An professional panel at a latest Coinbase occasion concluded that “blockchain can counter misinformation with cryptographic digital signatures and timestamps, making it clear what’s genuine and what’s been manipulated.”
That is true solely in a really slender sense.
Blockchains can file digital-media creation in a tamper-proof approach, i.e., in order that modification of particular photos is detectible. However this can be a far cry from clarifying authenticity.
Think about a photograph of a flying saucer hovering above the Washington Monument. Suppose that somebody has registered its creation in, say, block 20,000,000 of the Ethereum blockchain. This reality tells you one factor: The flying saucer picture was created earlier than block 20,000,000. Moreover, whoever posted the picture to the blockchain — let’s name her Alice — did so by digitally signing a transaction. Assuming that Alice’s signing key wasn’t stolen, it’s clear that Alice registered the photograph on the blockchain.
None of this, nonetheless, tells you how the picture was created. It may be a photograph that Alice snapped together with her personal digital camera. Or Alice might need gotten the picture from Bob, who Photoshopped it. Or possibly Carol created it with a generative AI device. In brief, the blockchain tells you nothing about whether or not aliens have been touring Washington, D.C.—until you already belief Alice to start with.
Some cameras can digitally signal pictures to authenticate them (assuming their sensors can’t be fooled, which is a giant if), however this isn’t blockchain expertise.
Narrative #2: Blockchain can deliver privateness to AI
Mannequin coaching is a node=”[object Object]” goal=”_blank” rel=”nofollow”>trumpeting blockchain applied sciences as an answer.
Blockchains, nonetheless, are designed for transparency — a property at odds with confidentiality.
Proponents level to privacy-enhancing applied sciences superior by the blockchain business to handle this pressure — particularly zero-knowledge proofs. Zero-knowledge proofs, nonetheless, don’t clear up the issue of privateness in AI mannequin coaching. That’s as a result of a zero-knowledge proof doesn’t conceal secrets and techniques from whoever is developing the proof. Zero-knowledge proofs are useful if I need to conceal my transaction knowledge from you. However they don’t allow me to compute privately over your knowledge.
There are different, extra related cryptographic and safety instruments with esoteric names, together with totally homomorphic encryption (FHE), safe multiparty computation (MPC) and safe enclaves. These can in precept help privacy-preserving AI (particularly, “federated studying”). Every has necessary caveats, although. And claiming them as blockchain-specific applied sciences can be a stretch.
Narrative #3: Blockchains can empower AI bots with cash — and that’s an excellent factor
Jeremy Allaire, CEO of Circle, has famous that bots are already performing transactions utilizing cryptocurrency and tweeted that “AI and Blockchains are made for one another.” That is true within the sense that cryptocurrency is an efficient match for the capabilities of AI brokers. However it’s additionally worrisome.
Many individuals fret about AI brokers escaping human management. Traditional nightmare eventualities contain autonomous automobiles killing folks or AI-powered autonomous weapons going rogue. However there’s one other vector of escape: The monetary system. Cash equals energy. Give that energy to an AI agent and it could possibly do actual harm.
This downside is the subject of a analysis paper that I co-authored in 2015/6. My colleagues and I examined the opportunity of sensible contracts, applications that autonomously intermediate transactions on Ethereum, getting used to facilitate crime. Utilizing the strategies in that paper and a blockchain oracle system with entry to LLMs (Giant Language Fashions) equivalent to ChatGPT, unhealthy actors might in precept launch “rogue” sensible contracts that robotically pay bounties for committing severe crimes.
Learn extra from our opinion part: How a sensible contract will get away with homicide: A overview of ‘The Oracle’
Fortunately, rogue sensible contracts of this type aren’t but doable in at this time’s blockchains — however the blockchain business and crypto fans might want to take AI security critically as a future concern. They might want to contemplate mitigations, equivalent to community-driven interventions or guardrails in oracles to assist implement AI security.
The combination of blockchains and AI does maintain clear promise. AI could add unprecedented flexibility to blockchain techniques by creating pure language interfaces to them. Blockchains could present new monetary and transparency frameworks for mannequin coaching and knowledge sourcing and put the ability of AI within the arms of communities, not simply enterprises.
It’s nonetheless early days, although, and as we wax lyrical about AI and blockchain as an attractive mixture of buzzwords and applied sciences, we have to actually suppose — and see — issues via.
Ari Juels is the Weill Household Basis and Joan and Sanford I. Weill Professor within the Jacobs Technion-Cornell Institute at Cornell Tech and the Technion and a Laptop Science college member at Cornell College. He’s a Co-Director of the Initiative for CryptoCurrencies and Contracts (IC3). He’s additionally Chief Scientist at Chainlink Labs. He’s the creator of crypto thriller novel The Oracle (Talos Press), which was launched on 20 February 2024.
