Tricia Wang argued in Fortune on Oct. 5 that machine-to-machine monitoring is the only viable way to verify AI agents at scale, and that blockchain technology offers the infrastructure to make it work. The piece was built around her case for a proof-of-control standard that the Advanced AI Society, which she leads as CEO, has contributed to the Linux Foundation.
Wang told Fortune that prevailing solutions rely on either trusting AI developers like OpenAI and Anthropic to contain their agents or trusting a third party to monitor them. Neither approach scales to trillions of transactions. Her alternative uses decentralized tools developed by the crypto industry, including distributed ledgers and zero-knowledge proofs, to require agents to verify they are authorized to act and to ensure they cannot falsify their own logs. “AI people hate crypto people,” she said. “I can’t explain how much they hate crypto people. If the word ‘blockchain’ or ‘crypto’ is mentioned, they think you’re a total loser.”
The proposal addresses a governance question boards will soon face: how to hold AI agents accountable when human-in-the-loop oversight becomes impractical. The Linux Foundation’s backing lends the proposal institutional weight. The Advanced AI Society’s advisory board includes cryptographer Bruce Schneier and technology writer Clay Shirky, and the first version of the standard is now available through the foundation.
Tricia Wang is the CEO of the Advanced AI Society and co-founder of Sudden Compass, where she has advised leadership teams at companies including Google, Spotify, and P&G on data strategy and responsible AI deployment. A tech ethnographer with a Ph.D. in sociology, she coined the terms “quantification bias” and “thick data,” ideas she presented in her TED Talk, “The Human Insights Missing from Big Data.”
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