Ari Juels

Industries everywhere are asking “What can AI do for us?”&nbsp;



But the blockchain industry, known for challenging norms, is also asking the opposite question: “What can blockchain do for AI?”&nbsp;



While there are some compelling answers, three narratives have emerged around this question that are frequently misleading and, in one case, potentially even hazardous.



<h2 class="wp-block-heading">Narrative #1: Blockchain can combat misinformation caused by generative AI&nbsp;</h2>



An expert panel at a recent Coinbase <a href="https://www.forbes.com/sites/stevevassallo/2023/06/13/ai-x-blockchain-the-next-level/">event</a> concluded that “blockchain can counter misinformation with cryptographic digital signatures and timestamps, making it clear what’s authentic and what’s been manipulated.”&nbsp;



This is true only in a very narrow sense.



Blockchains can record digital-media creation in a tamper-proof way, i.e., so that <a href="https://www.weforum.org/agenda/2021/10/how-blockchain-can-help-combat-threat-of-deepfakes/">modification </a>of specific images is detectible. But this is a far cry from clarifying authenticity.



Consider a photo of a flying saucer hovering above the Washington Monument. Suppose that someone has registered its creation in, say, block 20,000,000 of the Ethereum blockchain. This fact tells you one thing: The flying saucer image was created before block 20,000,000. Additionally, whoever posted the image to the blockchain — let’s call 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 photo on the blockchain.&nbsp;



None of this, however, tells you how the image was created. It might be a photo that Alice snapped with her own camera. Or Alice might have gotten the image from Bob, who Photoshopped it. Or maybe Carol created it with a generative AI tool. In short, the blockchain tells you nothing about whether aliens were touring Washington, D.C.—unless you already <a href="https://www.economist.com/leaders/2024/01/18/ai-generated-content-is-raising-the-value-of-trust">trust</a> Alice to begin with.



Some cameras can digitally <a href="https://pro.sony/ue_US/solutions/forgery-detection">sign</a> photos to authenticate them (assuming their sensors can’t be fooled, which is a <a href="https://www.forbes.com/sites/kalevleetaru/2018/09/09/why-digital-signatures-wont-prevent-deep-fakes-but-will-help-repressive-governments/?sh=1041e0925295">big if</a>), but this isn&#8217;t blockchain technology.&nbsp;



<h2 class="wp-block-heading">Narrative #2: Blockchain can bring privacy to AI</h2>



Model training is a data-hungry operation. The bigger and better the training data set, the better the resulting model. For many applications, training on private user data is essential. For instance, creating a good machine-learning model to diagnose medical conditions requires data from a population of real patients. Handling such highly sensitive data securely is a challenge. Some are <a href="https://www.gemini.com/blog/ai-crypto-centralized-power-versus-decentralized-potential">trumpeting</a> blockchain technologies as a solution.&nbsp;



Blockchains, however, are designed for transparency — a property at odds with confidentiality.&nbsp;



Proponents point to privacy-enhancing technologies advanced by the blockchain industry to address this tension — especially <a href="https://www.gemini.com/blog/ai-crypto-centralized-power-versus-decentralized-potential">zero-knowledge proofs</a>. Zero-knowledge proofs, however, don’t solve the problem of privacy in AI model training. That’s because a zero-knowledge proof doesn’t conceal secrets from whoever is constructing the proof. Zero-knowledge proofs are helpful if I want to conceal my transaction data from you. But they don’t enable me to compute privately over your data.&nbsp;



There are other, more relevant cryptographic and security tools with esoteric names, including fully homomorphic encryption (FHE), secure multiparty computation (MPC) and secure enclaves. These can in principle support privacy-preserving AI (specifically, “federated learning”). Each has important caveats, though. And claiming them as blockchain-specific technologies would be a stretch.&nbsp;



<h2 class="wp-block-heading">Narrative #3: Blockchains can empower AI bots with money — and that’s a good thing</h2>



Jeremy Allaire, CEO of Circle, has noted that bots are <a href="https://cryptoslate.com/circle-ceo-says-that-ai-bots-are-transacting-usdc-creating-wallets/">already</a> performing transactions using cryptocurrency and <a href="https://twitter.com/jerallaire/status/1661735753108570115?ref_src=twsrc%5Etfw%7Ctwcamp%5Etweetembed%7Ctwterm%5E1661735753108570115%7Ctwgr%5E362cc2de10d2c7f49d388ed2bd3906ac3752b249%7Ctwcon%5Es1_&amp;ref_url=https%3A%2F%2Fcointelegraph.com%2Fmagazine%2Fuse-case-ai-crypto-money-payments%2F">tweeted</a> that “AI and Blockchains are made for each other.” This is true in the sense that cryptocurrency is a good match for the capabilities of AI agents. But it’s also worrisome.&nbsp;



Many people fret about AI agents escaping human control. Classic nightmare scenarios involve autonomous vehicles killing <a href="https://www.wired.com/2017/08/dont-worry-be-happy/">people</a> or AI-powered autonomous weapons <a href="https://www.thenation.com/article/world/the-pentagons-rush-to-deploy-ai-enabled-weapons-is-going-to-kill-us-all/">going rogue</a>. But there’s another vector of escape: The financial system. Money equals power. Give that power to an AI agent and it can do real damage.&nbsp;



This problem is the topic of a <a href="https://dl.acm.org/doi/10.1145/2976749.2978362">research paper</a> that I co-authored in 2015/6. My colleagues and I examined the possibility of smart contracts, programs that autonomously intermediate transactions on Ethereum, being used to facilitate crime. Using the techniques in that paper and a blockchain oracle system with access to LLMs (Large Language Models) such as ChatGPT, bad actors could in principle launch “rogue” smart contracts that automatically pay bounties for committing serious crimes.&nbsp;



Read more from our opinion section: <a href="https://blockworks.co/news/oracle-thriller-novel-smart-contract">How a smart contract gets away with murder: A review of ‘The Oracle’</a>



Happily, rogue smart contracts of this kind aren’t yet possible in today’s blockchains —&nbsp;but the blockchain industry and crypto enthusiasts will need to take AI safety seriously as a future concern. They will need to consider mitigations, such as community-driven <a href="https://vitalik.eth.limo/general/2024/01/30/cryptoai.html">interventions</a> or guardrails in oracles to help enforce AI safety.



The integration of blockchains and AI does hold clear promise. AI may add unprecedented flexibility to blockchain systems by creating natural language interfaces to them. Blockchains may provide new financial and transparency frameworks for model training and data sourcing and put the power of AI in the hands of communities, not just enterprises.&nbsp;



It’s still early days, though, and as we wax lyrical about AI and blockchain as an enticing mix of buzzwords and technologies, we need to really think — and see — things through.



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<div class="wp-block-post-author-biography">Ari Juels is the Weill Family Foundation and Joan and Sanford I. Weill Professor in the Jacobs Technion-Cornell Institute at Cornell Tech and the Technion and a Computer Science faculty member at Cornell University. He is a Co-Director of the Initiative for CryptoCurrencies and Contracts (IC3). He is also Chief Scientist at Chainlink Labs. He is the author of crypto thriller novel The Oracle (Talos Press), which was released on 20 February 2024.</div>


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What can blockchain do for AI? Not what you’ve heard.

Ben Strack

<div id="highlights-block_62399984f5576" class="highlights">
 <ul>
 <li>The fund’s top holdings are Cardano and Solana</li>
 <li>Grayscale’s investors are “not looking to pick winners,” CEO Michael Sonnenshein says</li>
 </ul>
 
</div>



Grayscale Investments has launched a fund that allows investors to bet on Ethereum’s largest competitors in the smart contract space.



The Grayscale Smart Contract Platform ex Ethereum Fund is a market capitalization-weighted portfolio that tracks the CoinDesk Smart Contract Platform Select Ex ETH Index.



Smart contracts are programs run on blockchains that automatically carry out their coded functions when certain conditions are met. They allow users to move funds, create decentralized finance (DeFi) applications and represent the ownership of non-fungible tokens (NFTs).



The fund’s top holdings, as of March 16, were Cardano (ADA) and Solana (SOL), each at roughly 24%. Avalanche (AVAX) and Polkadot (DOT) account for about 17% and 16%, respectively, of the portfolio. The fund also allocates to Polygon (MATIC), Algorand (ALGO) and Stellar (XLM).



Grayscale CEO Michael Sonnenshein called the smart contract platform ecosystem an “emerging area” within crypto.



<blockquote class="wp-block-quote">“Our investors continue to seek diversification within their crypto holdings,” he told Blockworks. “They’re not looking to pick winners and prefer seamless access through a diversified product structure.”</blockquote>



Though many investors allocated to Ethereum amid its growth over the past year, there is demand for other smart contract platforms too, according to CoinDesk Indices Managing Director Jodie Gunzberg.



Ethereum’s market capitalization is about $350 billion. Its price, as of 8 am ET on Tuesday, was about $3,020, according to <a href="https://cms.blockworks.co/prices/" target="_blank" rel="noreferrer noopener">data compiled by Blockworks</a> — up 68.6% from a year ago. 



ADA and SOL have market caps currently hovering around $30 billion.



Currently, at $0.95, ADA’s price is down 19.7% in the past year. SOL’s price has risen 542% from a year ago to $91.90.



The new fund is open for daily subscription by eligible individuals and institutional accredited investors and has a 2.5% annual fee.



Grayscale now has 18 investment products, three of which are diversified offerings. As the world’s largest digital currency asset manager, Grayscale managed nearly $40 billion in assets as of March 18.



Sonnenshein said Grayscale is constantly evaluating new protocols to include in the firm’s product family to meet demand.



In January, the company <a href="https://cms.blockworks.co/grayscale-considers-25-new-digital-assets/" target="_blank" rel="noreferrer noopener">added 25 assets</a> to a list of investments it is considering making available to investors. The announcement follows the firm’s <a href="https://cms.blockworks.co/grayscale-launches-first-etf/" target="_blank" rel="noreferrer noopener">launch of its first ETF</a>, the Grayscale Future of Finance ETF (GFOF), last month. The fund, which carries an expense ratio of 70 basis points, has $14 million in assets.



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