The intersection of crypto and AI is one of the most hyped spaces in tech—but where does the actual science stand?
Crypto x AI, AI x Crypto: A Survey, a new paper by IC3, cuts through the noise to provide a comprehensive, clear-eyed analysis of this evolving sector. Survey co-author Professor @AriJuels also points out fundamental challenges come down to how these two technologies operate.
"Crypto is a ‘hard’ technology, built on cryptographic primitives with rigorous security properties and programs that enforce unambiguous results. AI is a ‘soft’ technology: No one fully understands or can fully trust the models on which it depends. Combining the two naively can be like soldering Jell-O. Combined well, though, crypto can channel AI’s fluid power into secure and reliable systems."
When combined systematically, crypto tools can channel AI's fluid power into secure, reliable, and highly autonomous systems. At the same time, this combination could have far reaching consequences for users and the financial system.
Key takeaways from the survey:
- AI makes crypto flexible: Machine learning models can dramatically improve smart contract security, enhance real-world data processing, and optimize fraud detection.
- New vectors for market abuse: AI-powered trading systems could enable collusion between autonomous agents and create unfair insider advantages through opaque strategies.
- Crypto can help secure the AI supply chain: Cryptographic infrastructure can create highly secure, trustworthy, and tamper-proof data pipelines for AI model training.
- A reality check on decentralization: Despite the industry hype, there is still little public, quantitative evidence proving decentralized AI pipelines actually reduce end-to-end costs or improve metrics.
As co-editor Prof. @giuliacfanti notes, the sheer volume of research makes it hard to separate signal from noise. This paper maps out the next decade of blockchain research for academics, and serves as an essential R&D roadmap for business leaders.
Crypto x AI, AI x Crypto: A Survey is the culmination of several months of research. Huge congratulations to the team of over two dozen researchers across industry and academia who contributed to this paper!
Access the full survey and interact with our AI chatbot here: https://aic3.io/
Authors: @sarahalle_ (IC3, Flashbots); @pranaytej (@Offchain ); James Austgen (IC3, @cornell_tech ); @bahrani_maryam (@ritualnet); @roibarzur (IC3, @TelAvivUni); @sjbreck (IC3, @cornell_tech ); @AaronBuchwald (@AvaLabs); @cczurich (IC3, University of Bern); James Hsin-yu Chiang (IC3, @ETH); @desilvaneil (IC3); @ittayeyal (IC3, @TechnionLive); Andrés Fábrega (IC3, @cornell_tech ); @giuliacfanti (IC3, @CarnegieMellon); @FernJared (@CarnegieMellon ); @AriJuels (IC3, @cornell_tech ); @socrates1024 (IC3, Teleport, FlashbotsX); Marwa Mouallem (IC3, @TechnionLive); Christian Sillaber (University of Bern); @danivilardell77 (IC3, @cornell_tech); @viswanathpramod (@Princeton); @0xWenhaoWang (IC3, @Yale); Matt Weinberg (IC3, @Princeton); @syang2ng (IC3, @Yale); Jianzhu Yao (@Princeton); @0xFanZhang (IC3, @Yale).
