InfoFi Depth Research: Attention Finance Experiment in the AI Era

I. Introduction: From Information Scarcity to Attention Scarcity, InfoFi Emerges

The information revolution of the 20th century brought explosive growth in knowledge to human society, but it also triggered a paradox: when the cost of obtaining information is almost zero, what is truly scarce is no longer information itself, but the cognitive resources we use to process information—attention. As Nobel laureate Herbert Simon first proposed the concept of "attention economy" in 1971, "information overload leads to attention scarcity," and modern society is deeply mired in this. Faced with the overwhelming content inundated by social media, short videos, and news notifications, the cognitive boundaries of humanity are being continuously squeezed, making filtering, judging, and valuing increasingly difficult.

The scarcity of attention has evolved into a resource competition in the digital age. In the traditional Web2 model, platforms tightly control traffic entry points through algorithms, and the true creators of attention resources—whether they are users, content creators, or community evangelists—often end up being "free fuel" in the profit logic of the platform. Major platforms and capitalists continuously harvest in the chain of attention monetization, while ordinary individuals who truly drive information production and dissemination find it difficult to participate in value sharing. This structural disconnection is becoming a core contradiction in the evolution of digital civilization.

The rise of InfoFi( is happening against this backdrop of financialization of information. It is not a sporadic new concept, but rather a fundamental paradigm shift based on blockchain, token incentives, and AI empowerment, with the goal of "remodeling the value of attention." InfoFi attempts to convert users' perspectives, information, reputation, social interactions, trend discoveries, and other unstructured cognitive behaviors into quantifiable and tradable asset forms, and through distributed incentive mechanisms, allows every user who participates in the creation, dissemination, and judgment within the information ecosystem to share the value generated. This is not merely technological innovation, but also an attempt at redistributing power regarding "who owns attention and who dominates information."

In the narrative lineage of Web3, InfoFi serves as an important bridge connecting social networks, content creation, market games, and AI intelligence. It inherits the financial mechanism design of DeFi, the social drive of SocialFi, and the incentive structure of GameFi, while also introducing AI capabilities in semantic analysis, signal recognition, and trend prediction, thus constructing a new market structure centered around "cognitive resource financialization". Its core is not merely about content distribution or likes and rewards, but rather a complete set of value discovery and redistribution logic centered around "information → trust → investment → return".

From an agricultural society where "land" is the scarce factor, to an industrial era where "capital" serves as the growth engine, and now to today's digital civilization where "attention" has become the core means of production, the resource focus of human society is undergoing a profound shift. InfoFi is the concrete expression of this macro paradigm transformation in the on-chain world. It is not only a new opportunity in the crypto market but may also be the starting point for a deep reconstruction of the governance structure of the digital world, the logic of intellectual property, and the financial pricing mechanism.

However, any paradigm shift is not linear; it inevitably comes with bubbles, hype, misunderstandings, and fluctuations. Whether InfoFi can become a true user-centric attention revolution depends on whether it can find a dynamic balance between incentive mechanism design, value capture logic, and real demand. Otherwise, it will just be another illusion sliding from "inclusive narrative" to "centralized harvesting."

![InfoFi Depth Research Report: Attention Financial Experiments in the AI Era])https://img-cdn.gateio.im/webp-social/moments-abffb20acf2000954842e928181193d7.webp(

2. The Ecological Composition of InfoFi: A "Information × Finance × AI" Triangular Intersection Market

The essence of InfoFi is to build a composite market system that simultaneously nests financial logic, semantic computation, and game mechanics in the contemporary online context, where information is highly saturated and value is difficult to capture. Its ecological architecture is not a single-dimensional "content platform" or "financial protocol," but rather an intersection of information value discovery mechanisms, behavioral incentive systems, and intelligent distribution engines—constituting a full-stack ecosystem that integrates information trading, attention incentives, reputation rating, and intelligent prediction.

From a fundamental perspective, InfoFi is an attempt at the "financialization" of information, transforming cognitive activities such as content, opinions, trend judgments, and social interactions that were previously unpriceable into measurable and tradable "quasi-assets," thereby assigning them market prices. The involvement of finance means that information no longer exists as fragmented and isolated "content fragments" during the production, circulation, and consumption processes, but rather as "cognitive products" with gaming attributes and value accumulation capabilities. This implies that a comment, a prediction, or a trend analysis can be both an expression of individual cognition and a speculative asset with risk exposure and future income rights. The popularity of prediction markets like Polymarket and Kalshi exemplifies this logic manifesting in public opinion and market expectations.

However, relying solely on financial mechanisms is far from sufficient to address the noise overflow and the Gresham's law dilemma brought about by information explosion. Therefore, AI becomes the second pillar of InfoFi. AI primarily assumes two roles: first, semantic filtering, serving as the "first line of defense" against information signals and noise; second, behavior recognition, achieving precise evaluation of information sources through modeling multi-dimensional data such as user social network behavior, content interaction trajectories, and originality of opinions. Platforms like Kaito AI, Mirra, and Wallchain are typical representatives that integrate AI technology into content evaluation and user profiling, playing the role of "algorithmic referees" in the Yap-to-Earn model, deciding who should receive token rewards and who should be blocked or downgraded. In a sense, the role of AI in InfoFi is equivalent to that of market makers and clearing mechanisms in exchanges, being the core that maintains ecological stability and credibility.

Information is the foundation of all this. It is not only a trading target but also the source of market sentiment, social connections, and consensus formation. Unlike DeFi, the assets anchored in InfoFi are no longer on-chain hard assets like USDC or BTC, but rather "cognitive assets" that are more liquid, loosely structured, yet more timely, such as opinions, trust, topics, trends, and insights. This also determines that the operational mechanism of the InfoFi market is not a linear stacking but a dynamic ecosystem that heavily relies on social graphs, semantic networks, and psychological expectations. In this framework, content creators are akin to the market's "market makers," providing opinions and insights for the market to assess their "price"; users act as "investors," expressing their value judgments on certain information through likes, shares, bets, comments, and other actions, thereby pushing it up or sinking it within the entire network; while the platform and AI serve as "referees + exchanges," responsible for ensuring the fairness and efficiency of the entire market.

The synergistic operation of this trinary structure has spawned a series of new species and mechanisms: prediction markets provide clear targets for speculation; Yap-to-Earn encourages knowledge as mining and interaction as output; reputation protocols like Ethos convert individuals' on-chain history and social behavior into credit assets; attention markets like Noise and Trends attempt to capture the "emotional fluctuations" propagated on-chain; and token-gated content platforms like Backroom reconstruct information payment logic through permission economics. Together, they form a multi-layered ecosystem of InfoFi: encompassing value discovery tools, value distribution mechanisms, as well as embedding a multi-dimensional identity system, participation threshold design, and anti-witch mechanism.

It is precisely within this cross-structured framework that InfoFi is no longer just a marketplace, but a complex information game system: it uses information as a trading medium, finance as an incentive engine, and AI as a governance hub, ultimately aiming to construct a self-organizing, distributed, and adjustable cognitive collaboration platform. In a sense, it attempts to become a "cognitive financial infrastructure" that is not only used for content distribution but also provides a more efficient information discovery and collective decision-making mechanism for the entire crypto society.

However, such a system is destined to be complex, diverse, and fragile. The subjectivity of information determines the inability to unify value assessments, the competitive nature of finance increases the risks of manipulation and herd behavior, and the black-box nature of AI poses challenges to transparency. The InfoFi ecosystem must continuously balance and self-repair between these three tensions; otherwise, it is likely to slide under capital drive towards the opposite of "de facto gambling" or "attention harvesting".

The ecological construction of InfoFi is not an isolated project of a single protocol or platform, but a co-performance of an entire socio-technical system, representing a deep attempt by Web3 in the direction of "governing information" rather than "governing assets." It will define the pricing method of information in the next era and even build a more open and autonomous cognitive market.

![InfoFi Depth Research Report: Attention Finance Experiments in the AI Era])https://img-cdn.gateio.im/webp-social/moments-01f9e01e37ba5663e755198caf1ab074.webp(

3. Core Game Mechanism: Incentivizing Innovation vs Harvesting Traps

In the InfoFi ecosystem, behind all the prosperous appearances, it ultimately comes down to the design game of incentive mechanisms. Whether it is the participation in prediction markets, the output of mouth-to-hand behavior, the construction of reputation assets, the trading of attention, or the mining of on-chain data, it fundamentally revolves around a core question: Who contributes? Who shares the profits? Who bears the risks?

From an external perspective, InfoFi seems to be a "production relationship innovation" in the migration from Web2 to Web3: it attempts to break the exploitative chain between "platform-creator-user" in traditional content platforms and return value to the original contributors of information. However, from an internal structural standpoint, this value return is not inherently fair, but rather established on a delicate balance of a series of incentives, validations, and game mechanisms. If designed appropriately, InfoFi is expected to become an innovative experimental field for win-win user scenarios; if the mechanisms are imbalanced, it can easily degenerate into a "retail investor harvesting ground" under the dominance of capital + algorithms.

The first thing to examine is the positive potential of "incentivizing innovation." The essential innovation of all InfoFi sub-tracks is to give clear tradability, competitiveness, and settlement to "information," an intangible asset that has been difficult to measure and financialize in the past. This transformation relies on two key engines: the traceability of blockchain and the assessability of AI.

betting signals

However, the stronger the incentive system, the more likely it is to give rise to "game abuse". The biggest systemic risk faced by InfoFi is the distortion of the incentive mechanism and the proliferation of arbitrage chains.

Taking Yap-to-Earn as an example, on the surface, it rewards users for the value of content creation through AI algorithms. However, in actual execution, many projects quickly fall into "information haze" after temporarily attracting a large number of content creators during the initial incentive phase—issues such as bot matrix accounts flooding, major KOLs participating in beta testing early, and project parties directing the manipulation of interaction weights occur frequently. A leading KOL bluntly stated: "Now if you don't boost your numbers, you can't even make the rankings; AI has been trained to specifically recognize keywords and ride the wave of popularity." Moreover, a project party revealed: "Invested $150,000 for a round of Kaito mouth play, but 70% of the traffic is from AI accounts and paid promoters competing with each other, real KOLs are not participating. It’s impossible for me to invest a second time."

Under the opaque mechanisms of the points system and token expectations, many users have become "free laborers": tweeting, interacting, launching, and building groups, only to find themselves ineligible for airdrops in the end. This kind of "backstabbing" incentive design not only damages the platform's reputation but also easily leads to the collapse of the long-term content ecosystem. The comparative case of Magic Newton and Humanity is particularly typical: the former in Kaito's mouth.