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 has brought explosive knowledge growth to human society, but it has also triggered a paradox: when the cost of obtaining information is almost zero, what is truly scarce is no longer the information itself, but the cognitive resources we use to process that 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 trapped in this. Faced with the overwhelming content inundated by social media, short videos, and news pushes, the cognitive boundaries of humanity are being continuously squeezed, making it increasingly difficult to filter, judge, and assign value.

The scarcity of attention has evolved into a resource competition in the digital age. In the traditional Web2 model, platforms firmly control traffic entry through algorithms, and the true creators of attention resources—whether they are users, content creators, or community evangelists—often serve as "free fuel" in the profit logic of the platform. Major platforms and capitalists harvest repeatedly in the chain of attention monetization, while ordinary individuals who truly drive information production and diffusion 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 Information Financialization (InfoFi) is occurring against this backdrop. It is not an incidental new concept, but rather a fundamental paradigm shift based on blockchain, token incentives, and AI empowerment, with the goal of "reshaping the value of attention." InfoFi attempts to transform users' viewpoints, information, reputation, social interactions, trend discoveries, and other unstructured cognitive behaviors into quantifiable and tradable asset forms. Through a distributed incentive mechanism, it enables every user who participates in the creation, dissemination, and judgment within the information ecosystem to share in the value generated. This is not just a technological innovation, but also an attempt to redistribute power concerning "who owns attention and who dominates information."

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

From an agricultural society where "land" is the scarce factor, to the industrial era where "capital" is the engine of growth, and now to today's digital civilization where "attention" has become the core production material, the resource focus of human society is undergoing a profound shift. InfoFi is a concrete expression of this macro paradigm shift 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 restructuring of digital world governance structures, intellectual property logic, and financial pricing mechanisms.

However, no paradigm shift is linear; it inevitably comes with bubbles, hype, misunderstandings, and fluctuations. Whether InfoFi can become a truly user-centered attention revolution depends on whether it can find a dynamic balance between incentive mechanism design, value capture logic, and real demand. Otherwise, it will merely be another illusion sliding from "inclusive narrative" to "centralized harvesting."

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 computing, and game mechanisms in the contemporary network context, where information is highly rampant and value is difficult to capture. Its ecological architecture is not a single-dimensional "content platform" or "financial protocol," but rather the intersection of the information value discovery mechanism, behavior incentive system, and intelligent distribution engine—forming a full-stack ecosystem that integrates information trading, attention incentives, reputation ratings, and intelligent forecasting.

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 originally unpriced into measurable and tradable "quasi-assets", assigning them market prices. The intervention of finance means that information is no longer scattered and isolated "content fragments" during the processes of production, circulation, and consumption, but rather "cognitive products" with gaming attributes and value accumulation capabilities. This implies that a comment, a prediction, or a trend analysis can be an expression of individual cognition and can also become a speculative asset with risk exposure and future income rights. The popularity of some prediction markets is a prime example of this logic taking shape in public opinion and market expectations.

However, relying solely on financial mechanisms is far from sufficient to address the noise flood and the "bad money drives out good money" dilemma brought about by information explosion. Therefore, AI has become the second pillar of InfoFi. AI mainly takes on 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 multi-dimensional data modeling based on users' social network behaviors, content interaction trajectories, originality of opinions, etc. Some platforms are typical representatives of incorporating AI technology into content evaluation and user profiling, playing the role of "algorithmic referee" in the Yap-to-Earn model, deciding who should receive token rewards and who should be blocked or downgraded. In a sense, the function of AI in InfoFi is equivalent to market makers and clearing mechanisms in exchanges, which is core to maintaining ecological stability and credibility.

Information is the foundation of all this. It is not only the subject of transactions but also the source of market sentiment, social connections, and consensus formation. Unlike DeFi, the asset anchors of InfoFi are no longer on-chain hard assets like USDC and BTC, but rather more liquid, loosely structured yet more timely "cognitive assets" 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 ecology that heavily relies on social graphs, semantic networks, and psychological expectations. Within this framework, content creators act as the market's "market makers", providing opinions and insights for the market to judge their "prices"; users are the "investors", expressing their value judgments on certain information through actions like liking, sharing, betting, and commenting, thus pushing it to rise or sink throughout the network; while the platform and AI serve as the "referees + exchanges", responsible for ensuring the fairness and efficiency of the entire market.

The collaborative operation of this trinary structure has given rise to a series of new species and new mechanisms: prediction markets provide clear targets for speculation; Yap-to-Earn encourages knowledge as mining and interaction as output; reputation protocols transform an individual's on-chain history and social behavior into credit assets; attention markets attempt to capture the "emotional fluctuations" propagated on-chain; and token-gated content platforms reconstruct the logic of information payment through permissioned economies. Together, they form the multi-layered ecosystem of InfoFi: encompassing not only value discovery tools but also value distribution mechanisms, while embedding multi-dimensional identity systems, participation threshold designs, and anti-witch-hunt mechanisms.

It is precisely within this cross-structured framework that InfoFi evolves from merely being a marketplace to a complex information game system: it uses information as a medium of exchange, finance as an incentive engine, and AI as a governance hub, ultimately aiming to build a self-organizing, distributed, and adjustable cognitive collaboration platform. In a sense, it attempts to become a "cognitive financial infrastructure" that serves not only content distribution but also provides the entire crypto community with a more efficient information discovery and collective decision-making mechanism.

However, such a system is destined to be complex, diverse, and fragile. The subjectivity of information determines the non-uniformity of value assessment, 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 among the three-dimensional tensions; otherwise, it is likely to slide under capital drive towards the opposite of "de facto gambling" or "attention harvesting field."

The ecological construction of InfoFi is not an isolated project of a single protocol or platform, but a co-performance of a whole set of socio-technical systems. It represents a profound attempt by Web3 to "govern information" rather than "govern assets." It will define the pricing mechanisms of information in the next era and even build a more open and autonomous cognitive market.

III. Core Game Mechanism: Incentivizing Innovation vs. Harvesting Trap

In the InfoFi ecosystem, behind all the appearances of prosperity, it ultimately comes down to the design game of incentive mechanisms. Whether it is the participation in prediction markets, the output of mouth-to-mouth behavior, the construction of reputation assets, the trading of attention, or the mining of on-chain data, it essentially revolves around a core question: Who puts in the effort? Who gets the dividends? Who bears the risk?

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, returning value to the original contributors of information. However, from an internal structural standpoint, this value return is not inherently fair but is based on a delicate balance of a series of incentives, validations, and game mechanisms. If designed properly, InfoFi has the potential to become an innovative experimental field for user win-win; if the mechanisms are unbalanced, it could easily devolve into a "retail investor harvesting ground" dominated by capital + algorithms.

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

Prediction markets realize cognitive consensus through market pricing mechanisms; the Mouth Loo ecosystem turns speech into economic behavior; reputation systems build a type of inheritable and pledgeable social capital; attention markets redefine content value by treating trending topics as trading objects, through the logic of "information discovery → betting signals → obtaining price differences"; while AI-driven InfoFi applications attempt to construct a data and algorithm-driven information financial network through large-scale semantic modeling, signal recognition, and on-chain interaction analysis. These mechanisms give information the "cash flow" property for the first time, and make "saying a word, sharing a tweet, endorsing someone" a real productive activity.

However, the more intense the incentive system, the easier it is to breed "game abuse". The greatest systemic risk faced by InfoFi is the alienation 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, but in actual execution, many projects quickly fall into "information haze" after briefly attracting a large number of content creators during the initial incentive period — rampant issues such as robot matrix accounts flooding, major influencers participating in internal testing early, and project parties manipulating interaction weights. A leading KOL bluntly stated: "If you don’t boost your numbers, you simply can’t make the rankings; AI has been trained to specifically recognize keywords and ride trends." Furthermore, a project party disclosed: "Invested $150,000 for a round of soft promotion, but 70% of the traffic was from AI accounts and fake accounts competing; true KOLs are not participating, and it is 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, going live, building groups, only to find they are not qualified to participate in airdrops. 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 comparison between Magic Newton and Humanity is particularly typical: the former has a clear allocation mechanism during the mouth-to-mouth phase, with substantial token value returns; while the latter has triggered social issues due to an imbalanced allocation mechanism and insufficient transparency.