AI · Studies · 2026-09-11 12:20:00
This article explores a framework for trustworthy human-AI collaboration within a live type-theoretic computational commons. The core argument is that type theory provides formal, verifiable guarantees for interactions between humans and AI agents in a shared computational environment. The commons allows participants to contribute compute and code, while the type system ensures every operation is traceable and verifiable. The authors analyze trust deficiencies in existing AI collaboration systems and propose a protocol based on dependent types and proof assistants, enabling humans and AI agents to exchange intent and results within a unified semantic framework. The work offers a theoretical foundation for open, auditable AI collaboration infrastructure.
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