Ethereum developers have introduced a new privacy model for AI chatbots that protects user identities while allowing providers to verify payments and prevent abuse. Vitalik Buterin and Davide Crapis detailed a proposal to use zero-knowledge cryptography to separate identity from usage. The framework lets users fund a smart contract once and then make thousands of private API calls without repeated identity checks. The system aims to address risks associated with email logins, credit card payments, and traceable blockchain transactions as AI adoption expands.
Most AI systems require email logins or credit card payments, and each request is directly tied to a real identity. Providers can log and track every API call, with the records linking to individuals and exposing sensitive data.
Buterin and Crapis explain that such logs can create profiling risks. They also warn about tracking and legal exposure if courts access stored records. They argue that such privacy concerns can no longer be ignored, considering the pace at which AI usage grows.
Blockchain payments do not solve the issue. Paying on-chain for every request creates a public record, where each transaction becomes visible and traceable. Per-request payments also seem impossible, as the process is slow and costs more.
If companies rely on familiar payment systems, privacy risks remain, with every chatbot interaction connecting to a real identity. This structure increases exposure and leaves users vulnerable to tracking.
Ethereum developers are proposing a deposit-based system to address these concerns: After a user funds a smart contract once, they make thousands of private API calls. This way, providers can confirm that each request draws from deposited funds, and the user does not reveal their identity during every interaction.
Zero-knowledge cryptography allows users to prove payment validity without exposing personal data. The model includes a tool called Rate-Limit Nullifiers. This system allows anonymous requests while detecting rule violations, with each request receiving a ticket index tied to the deposit.
Users must generate a ZK-STARK proof for every call. The proof shows that funds support the request and confirms any refund owed. A unique nullifier would prevent the reuse of the same ticket, exposing double-spending attempts immediately.
Refund logic remains built into the system as AI queries vary in cost. Users can recover their unused funds, and providers can maintain payment assurance at the same time.
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Buterin and Crapis note that misuse of this system could go beyond double-spending. Some users may attempt harmful prompts, jailbreak efforts, or requests for illegal content such as weapon instructions. The framework addresses these risks without removing anonymity.
The proposal introduces a dual staking layer, with one layer following strict mathematical rules tied to deposits and the second layer enforcing policies from the provider. This structure would allow providers to punish rule breakers, while honest users remain anonymous. Zero-knowledge proofs confirm valid participation while exposing attempts to cheat.
The process begins with an account owner generating a secret key and depositing funds into a smart contract buffer. The user then submits private API calls against that balance. The system verifies each request through cryptographic proof rather than identity disclosure.
Ethereum developers have proposed a zero-knowledge framework that separates identity from AI chatbot payments through smart contract deposits and Rate Limit Nullifiers. The model verifies usage, prevents abuse, and blocks double-spending without exposing users.