AI agents require new identity frameworks because fundamental differences from humans in substrate, persistence, verifiability, and legal standing create five unresolved structural gaps in verification, delegation, integrity, governance, and sustainability.
Personhood credentials: Artificial intelligence and the value of privacy-preserving tools to distinguish who is real online
3 Pith papers cite this work. Polarity classification is still indexing.
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ZK-AMS enables credibly anonymous admission to Web 3.0 platforms by folding admission proofs off-chain via recursive aggregation for constant per-batch on-chain verification cost.
The agentic web requires new normative infrastructure of laws, norms, and practices to allow user-delegated AI agents to access online properties without being blocked as malicious bots.
citing papers explorer
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AI Identity: Standards, Gaps, and Research Directions for AI Agents
AI agents require new identity frameworks because fundamental differences from humans in substrate, persistence, verifiability, and legal standing create five unresolved structural gaps in verification, delegation, integrity, governance, and sustainability.
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ZK-AMS: Credibly Anonymous Admission for Web 3.0 Platforms via Recursive Proof Aggregation
ZK-AMS enables credibly anonymous admission to Web 3.0 platforms by folding admission proofs off-chain via recursive aggregation for constant per-batch on-chain verification cost.
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The Agentic Web Requires New Normative Infrastructure
The agentic web requires new normative infrastructure of laws, norms, and practices to allow user-delegated AI agents to access online properties without being blocked as malicious bots.