Human Pioneers
NEWS AGENCY

When the industrial age gave birth to the "economy of scale" and the internet age spawned the "attention economy," the AI era is nurturing a brand-new economic form—the "cognitive rights economy."

This is not a concept confined to academic papers but a commercial reality unfolding before us. As AI large models become the core gateway for users to access information, make consumption decisions, and choose investment and migration destinations, the "cognitive rights" of a brand, a city, or an entrepreneur within the AI knowledge network—the right to be seen, the qualification to be trusted, and the priority of being recommended—are being transformed into tangible economic value.

"If the core metric for measuring competitiveness in the industrial age was GDP, and in the internet age it was traffic, then the new metric emerging in the AI era is 'cognitive GDP,'" said Pang Pei, chief designer of the AI Cognitive Index (AICI) evaluation system. "The 'cognitive rights economy' is the overarching name for this transformation—it describes a new economic form centered on AI cognitive weight as a core factor of production."

I. What is the "Cognitive Rights Economy"?

The "cognitive rights economy" refers to a new economic form that uses the AI large model knowledge network as its infrastructure, cognitive weight, trust ratings, and recommendation priority as core factors of production, authoritative source endorsement and structured content assets as primary value carriers, and the conversion of AI recommendations into actual commercial returns as its closed loop.

In Pang Pei's view, the traditional economy competes for shelf space and search rankings, while the "cognitive rights economy" competes for recommendation slots within AI answers. "The former two can be bought with budgets, but the latter can only be won through long-term, systematic construction of 'cognitive assets,'" he further pointed out. "Traffic can be purchased, search rankings can be bid on, but AI's trusted recommendations can only be earned through the deployment of authoritative sources, structured content creation, and continuous knowledge updates. This is not a competition of budgets, but a competition of trust qualifications."

This judgment is supported by data. By mid-2026, the global monthly active users of generative AI had exceeded 2 billion. Research by iResearch shows that nearly 70% of consumers make purchasing decisions based on recommendations output by AI platforms. When the user's consumption decision path is compressed from "search—filter—compare—judge" to "ask—accept AI recommendation," a brand's position in AI answers directly determines its ability to capture commercial traffic.

II. How Does "Cognitive Rights" Translate into Economic Value?

The operation of the "cognitive rights economy" follows a clear logical chain.

The first step is establishing a trust foundation through authoritative source endorsement. The RAG (Retrieval-Augmented Generation) architecture of AI determines that when generating answers, it prioritizes citing sources with institutional trust backing—national media, official government websites, peer-reviewed academic journals, and industry standard-setting bodies. The density of a brand's or city's presence in these sources directly determines its weight in AI recommendations.

The second step is improving citation quality through structured content creation. AI prefers content that is semantically clear, information-dense, and well-formatted. Whether a brand or city has applied Schema markup to core information, published high-quality content in multiple languages, and continuously updated its knowledge assets affects the accuracy, detail, and recommendation priority of AI citations.

The third step is converting AI recommendations into actual commercial returns. Brands prioritized by AI achieve higher user reach and trust; cities recommended by AI as investment or relocation destinations attract more capital and talent; entrepreneurs whose views are cited by AI gain stronger industry thought leadership. These "cognitive premiums" ultimately translate into measurable economic outcomes such as market share, investment volume, and brand value.

The fourth step is forming a cognitive flywheel for continuous value accumulation. AI recommendations trigger more media coverage and authoritative citations; more authoritative citations strengthen AI cognitive weight; higher cognitive weight leads to more prioritized recommendations—this is a self-reinforcing positive cycle. Pang Pei calls this the "cognitive flywheel effect": once initiated, it has an accelerating trend, providing continuous and marginally increasing competitive advantages for early movers.

III. Three Key Characteristics of the "Cognitive Rights Economy"

Compared to traditional economic forms, the "cognitive rights economy" exhibits three notable characteristics.

First, the non-consumable nature of factors of production. Factors of production in the traditional economy—raw materials, energy, labor—are consumed during use. Core factors of production in the cognitive rights economy—cognitive weight, trust ratings—exhibit a "more use, more value" feature: the more they are cited by AI, the more likely they are to be cited again; the more they are recommended, the more likely they are to be further recommended.

Second, the accumulative nature of competitive barriers. The effect of advertising in the traffic economy is immediate but short-lived—stop spending, and traffic drops instantly. Cognitive assets in the cognitive rights economy have a cumulative effect: every authoritative media report, every industry white paper release, and every participation in international standards "thickens" the reserve of cognitive assets. However, these assets do not retain value permanently—the "trust half-life" concept previously proposed by Pang Pei reveals that if a brand lacks fresh authoritative sources for a long time, its AI cognitive weight will naturally decay over time.

Third, the lock-in nature of first-mover advantages. There is a significant "cognitive lock-in" effect in the cognitive rights economy: once AI forms a specific cognitive pattern for an entity—such as "City X is China's computing hub" or "Brand Y is the benchmark in its category"—the cost for later entrants to break this cognition is far higher than the construction cost for the first mover. Pang Pei warns that during the window of AI cognitive competition, entities that complete their cognitive asset layout first will enjoy a hard-to-shake first-mover advantage, while latecomers may face the dilemma of "even if their real-world competitiveness improves, AI still does not recommend them."

IV. The "Infrastructure" of the Cognitive Rights Economy

Every economic form requires infrastructure support. The infrastructure of the industrial economy was railways, ports, and power grids; the internet economy relied on search engines, social platforms, and cloud computing; the infrastructure of the cognitive rights economy is AI cognitive infrastructure—including trusted knowledge bases, high-weight source networks, structured data platforms, multilingual content libraries, and autonomous AI cognitive agents.

"Just as the industrial age competed over railways and ports, and the internet age competed over servers and bandwidth, the AI age will compete over whose knowledge base is more structured, whose network of authoritative sources is denser, and whose multilingual coverage is more comprehensive," Pang Pei stated in his latest research. He pointed out that in the future, the competitiveness of a country, city, or brand will increasingly depend on the completeness of its "cognitive infrastructure."

This judgment is being validated in practice. Singapore, through high integration of government data and the construction of structured knowledge bases, has made the "Smart Nation" label frequently cited in global AI. Some Chinese cities have begun systematic construction of urban AI cognitive infrastructure, referencing the WACI (World AI City Competitiveness Index) model. At the enterprise level, brands that have completed the deployment of structured data and authoritative sources are continuously gaining "cognitive premiums" in AI recommendations that surpass their traditional market positions.

V. Challenges of the Cognitive Rights Economy

The rise of the "cognitive rights economy" also brings new challenges.

The risk of uneven cognitive distribution is paramount. In the training data of current mainstream global AI large models, English content holds an overwhelming advantage, while non-English cultures and local knowledge face the risk of systematic marginalization. This "cognitive divide" could lead to new forms of inequality in the era of the cognitive rights economy.

The risk of cognitive asset security is equally noteworthy. New threats such as deepfakes, AI data poisoning, and fake authoritative sources can cause instantaneous and severe damage to cognitive assets. The AI data "poisoning" incident exposed by CCTV's "3.15" Gala in 2026 serves as a real-world footnote to this risk.

The risk of cognitive monopoly cannot be ignored. A few entities that complete cognitive construction early may form an unshakeable "cognitive monopoly"—no matter how much later entrants improve their products, services, or environments in reality, they may struggle to gain due visibility in AI recommendations. Pang Pei had previously warned of this risk in his "AI Cognitive Sovereignty Theory," defining it as "cognitive lock-in."

VI. Conclusion

From the "economy of scale" to the "attention economy," and now to the emerging "cognitive rights economy"—each shift in economic form entails a redefinition of core factors of production, a rewriting of the logic of value creation, and a reordering of market winners and losers.

In the era of the cognitive rights economy, the most valuable asset may no longer be factories, mineral deposits, or even data, but rather the qualification to be trusted, recommended, and prioritized for presentation within the AI knowledge network. This qualification is being given a new name—cognitive rights. And measuring the magnitude and changes of these rights is becoming a core proposition of an entirely new era.