AI Trust Crisis Escalates, Blockchain Becomes an Indispensable 'Anti-Counterfeiting Layer'

比推Publicado a 2026-02-05Actualizado a 2026-02-05

Resumen

AI systems are disrupting the internet, which was designed for human-scale interactions, by making it difficult to distinguish between human and machine-generated content, identities, and transactions. The core issue is the lack of a native method to differentiate humans from AI while preserving privacy and usability. Blockchain technology offers critical solutions through five key mechanisms: 1. AI can cheaply mimic human behavior at scale, but decentralized proof-of-personhood systems (e.g., World ID) increase the marginal cost of impersonation by enforcing uniqueness and scarcity. 2. Decentralized identity systems shift control from centralized platforms to users, reducing single points of failure and enhancing security and censorship resistance. 3. AI agents require portable, universal "passports" to operate across platforms without being locked into specific ecosystems, enabled by blockchain-based identity layers. 4. Existing payment systems are inadequate for AI agent-scale transactions; blockchain enables micro-payments, smart contracts, and programmable revenue sharing suitable for machine-to-machine commerce. 5. Privacy and security are intertwined: zero-knowledge proofs allow verification of attributes without exposing personal data, denying AI the raw materials needed for imitation. In summary, blockchain restores trust, raises impersonation costs, protects human-scale interactions, decentralizes identity, enforces privacy by default, and provides nati...

Author: a16z crypto

Compiled by: Deep Tide TechFlow

Original title: a16z: Why AI Urgently Needs Encryption Technology?


Deep Tide Introduction: a16z crypto points out that AI systems are breaking the internet designed for human scale, making coordination, transactions, and the generation of voices, videos, and text indistinguishable from human activities difficult. The problem is not the existence of AI, but that the internet has no native method to distinguish between humans and machines while protecting privacy and usability. This is precisely where blockchain comes into play. The article elaborates on five core reasons: AI can forge identities on a large scale, blockchain makes it difficult to cheaply replicate human uniqueness; centralized identity systems become points of failure, decentralization reverses this dynamic; AI agents need portable universal 'passports'; agent-scale payments require new infrastructure; and privacy and security are the same issue, with zero-knowledge proofs being the core defense.

Full text as follows:

AI systems are breaking the internet designed for human scale, making coordination, transactions, and the generation of voices, videos, and text increasingly indistinguishable from human activities. We are already troubled by CAPTCHA verification codes; now we are beginning to see agents interact and trade like humans (as we previously reported).

The problem is not the existence of AI; it is that the internet has no native method to distinguish between humans and machines while protecting privacy and usability.

This is precisely where blockchain comes into play. The idea that cryptocurrency can help build better AI systems, and vice versa, may be subtle; therefore, we summarize here several reasons why AI now needs blockchain more than ever.

1. The Cost of AI Imitating Humans

AI can forge voices, faces, writing styles, videos, and entire social personalities on a large scale: one actor can appear as thousands of accounts, opinions, customers, or voters at an increasingly lower cost.

These impersonation strategies are not new. Any enterprising scammer has always been able to hire voice actors, forge phone calls, or send phishing text messages. What is new is the price: conducting these attacks on a large scale is becoming increasingly affordable.

At the same time, most online services assume one account corresponds to one person. When this assumption fails, everything downstream collapses. Detection-based methods (such as CAPTCHA) will inevitably fail because AI improves faster than the tests designed to catch it.

So where does blockchain play a role? Decentralized proof-of-humanity or proof-of-personhood systems make it easy to be one participant but difficult to persistently be multiple participants. For example, while scanning your iris and obtaining a World ID may be relatively easy and affordable, it is almost impossible to obtain a second one.

This makes it harder for AI to achieve large-scale impersonation by limiting ID supply and increasing the marginal cost for attackers.

AI can forge content, but encryption makes it much more difficult to cheaply replicate human uniqueness. By restoring scarcity at the identity layer, blockchain increases the marginal cost of impersonation without adding friction to normal human behavior.

2. Creating Decentralized Systems to Prove Human Identity

One way to prove you are human is through a digital ID, which contains everything a person can use to verify their identity—username, PIN, password, and third-party proofs (e.g., citizenship or creditworthiness) as well as other credentials.

What does encryption add? Decentralization. Any identity system located at the center of the internet becomes a point of failure. When agents act on behalf of humans—transacting, communicating, and coordinating—whoever controls the identity effectively controls participation. Issuers can revoke access, impose fees, or assist in monitoring.

Decentralization reverses this dynamic: users, rather than platform gatekeepers, control their own identities, making them more secure and censorship-resistant.

Unlike traditional identity systems, decentralized proof-of-humanity mechanisms allow users to control and custody their own identities and verify their humanity in a privacy-preserving and credibly neutral manner.

3. AI Agents Need Portable Universal 'Passports'

AI agents do not reside in one place. A single agent can appear in chat applications, email threads, phone calls, browser sessions, and APIs. However, there is no reliable way to know whether interactions across these contexts point to the same agent, with the same state, capabilities, and authorization provided by its 'owner'.

Furthermore, binding an agent's identity solely to one platform or marketplace makes it unusable in other products and other important venues.

A blockchain-based identity layer allows agents to have portable universal 'passports'. These identities can carry references to capabilities, permissions, and payment endpoints, and can be resolved from anywhere, making agents harder to forge. This will also allow builders to create more useful agents and better user experiences: agents can exist in multiple ecosystems without worrying about being locked into any specific platform.

4. Supporting Machine Payments

As AI agents increasingly conduct transactions on behalf of humans, existing payment systems become bottlenecks. Large-scale agent payments require new infrastructure, such as micropayment systems capable of handling tiny transactions from many sources.

Many existing blockchain-based tools—Rollups and L2s, AI-native financial institutions, and financial infrastructure protocols—show potential to solve this problem, enabling near-zero-cost transactions and more granular payment splitting.

Critically, these rails support machine-scale transactions—micropayments, frequent interactions, and agent-to-agent commerce—that traditional financial systems cannot handle.

  • Nanopayments can be distributed among multiple data providers, allowing a single user interaction to trigger tiny payments to all contributing sources via automated smart contracts.

  • Smart contracts allow executable retroactive payments triggered by completed transactions, compensating information sources that contributed to purchase decisions after the transaction occurs, with full transparency and traceability.

  • Blockchain enables complex and programmable payment splitting allocations, ensuring fair distribution of revenue through code-enforced rules rather than centralized decisions, creating trustless financial relationships between autonomous agents.

5. Enhancing Privacy in AI Systems

At the core of many security systems lies a paradox: the more data they collect to protect users (e.g., social graphs, biometrics), the easier it is for AI to impersonate them.

This is where privacy and security become the same issue. The challenge is to make personal proof systems private by default and obscure information at every turn to ensure that only humans can produce the information needed to prove they are human.

Blockchain-based systems paired with zero-knowledge proofs allow users to prove specific facts—PINs, ID numbers, qualification criteria (e.g., drinking age at a bar)—without revealing the underlying data (e.g., address on a driver's license).

Applications get the assurance they need, and AI systems are denied the raw materials needed for imitation. Privacy is no longer a feature layered on top; it is a core defense.

AI makes scale cheap but difficult to trust. Blockchain restores trust, increases the cost of impersonation, protects human-scale interactions, decentralizes identity, enforces privacy by default, and provides native economic constraints for agents.

If we want an internet where AI agents can operate without eroding trust, blockchain is not optional infrastructure but the missing layer that makes an AI-native internet a reality.


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Original link: https://www.bitpush.news/articles/7609116

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Preguntas relacionadas

QAccording to a16z crypto, why is the internet struggling to differentiate between humans and AI systems?

AThe internet has no native method to distinguish between humans and machines while preserving privacy and usability, as AI systems can generate content and interactions that are increasingly indistinguishable from human activities.

QHow do blockchain-based human proof systems help combat AI's ability to impersonate humans at scale?

ADecentralized human proof systems, like World ID, make it easy to be one participant but difficult to be multiple participants by limiting ID supply and increasing the marginal cost for attackers, thereby raising the cost of large-scale impersonation.

QWhat advantage does a decentralized identity system offer over centralized ones in the context of AI agents?

ADecentralized identity systems allow users to control and custody their own identities, making them more secure and censorship-resistant, whereas centralized systems become points of failure and can be controlled by platform gatekeepers.

QWhy do AI agents need a portable universal 'passport', and how can blockchain provide this?

AAI agents operate across multiple contexts (e.g., chat apps, emails, APIs), and a blockchain-based identity layer provides a portable universal 'passport' that carries references to capabilities, permissions, and payment endpoints, enabling agents to exist in multiple ecosystems without platform lock-in.

QHow do zero-knowledge proofs enhance privacy and security in AI systems when combined with blockchain?

AZero-knowledge proofs allow users to prove specific facts (e.g., age, eligibility) without revealing underlying data, ensuring that applications get the necessary assurances while AI systems are denied the raw materials needed for imitation, making privacy a core defense.

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