Ethereum co-founder Vitalik Buterin has issued a cautionary note to developers about the complexities and potential risks of integrating artificial intelligence (AI) with blockchain technology. In a blog post dated January 30, Buterin outlined his concerns and advised a cautious approach, particularly in high-stakes applications.
Buterin sees significant potential for AI in specific areas, such as enabling its participation in prediction markets at a micro-scale, a task impractical for humans. Additionally, he suggests AI could enhance crypto wallet interfaces, aiding users in understanding and securely engaging with cryptocurrency by clarifying transactions, signatures, and identifying potential scams.
However, Buterin expresses reservations about relying solely on AI interfaces. He believes that while AI can complement traditional interfaces effectively, fully AI-driven systems might increase the risk of errors. He advocates for a balanced approach where AI supports, rather than replaces, conventional methods.
A particularly high-risk application, in Buterin’s view, is the use of AI to govern or enforce rules in cryptocurrency systems. He points out the vulnerability of open-source AI models to adversarial attacks, as their transparency allows malicious actors to study and exploit their code.
Buterin contrasts the vulnerabilities of open-source AI with the “security through obscurity” offered by closed-source AI. While closed-source models may be less susceptible to targeted attacks, they lack transparency, making it difficult to verify their fairness and unbiased nature. He cites Worldcoin, a crypto startup adjacent to OpenAI, as an example of a project using closed-source AI in a controlled environment.
The ultimate challenge, according to Buterin, lies in creating a decentralized AI using blockchain and crypto technologies that other applications can utilize. He envisions the development of a “singleton” – a single, decentralized, trusted AI entity that applications could rely on. While recognizing the potential benefits of such applications in enhancing functionality and AI safety without centralization risks, Buterin also acknowledges the numerous ways in which the foundational assumptions of this approach could fail.
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