Written by: Tia, Techub News

Artificial intelligence has changed the way we access information and create content, but this is just the beginning. A recent study by Google titled "Virtual Agent Economies" has sparked widespread interest in academia and industry. This research goes beyond the level of "AI can write, paint, and chat," placing AI into a virtual economic society within a blockchain or on-chain environment, allowing them to act freely as agents with goals, resources, and interaction rules. In such a system, agents not only complete tasks but also spontaneously form social relationships, engage in transactions, and gradually evolve norms and institutions similar to human society.

This research offers not only technological breakthroughs but also a cognitive shock: AI may not only be a tool but could also become "virtual residents" in future societies and on-chain economic systems. If this trend continues, human society will have a "virtual mirror" that can expand infinitely, allowing us to observe, test, and rehearse our institutions, financial systems, and economic futures.

From Assistants to Residents: The Generation of Virtual Societies

In the first wave of generative AI, systems like ChatGPT and Gemini primarily serve as "assistants," helping humans complete tasks. However, Google's research team chose to take a different perspective—what if AI is no longer a single user's assistant but is placed in an on-chain or virtual environment to interact freely? What kind of collective behavior would it exhibit?

The researchers built a large virtual environment containing hundreds of AI agents, each with goals, limited resources, and the ability to communicate with others. The researchers did not impose strict rules on how they must act but allowed the agents to explore freely within the on-chain environment.

The results showed that the agents not only completed tasks but also exhibited complex social behavior patterns. Some tended to cooperate, while others leaned towards competition, even forming long-term trust relationships and naturally evolving "rule systems." This behavior pattern simulates some of the basic characteristics of human society, but in the on-chain environment, these interactions are highly traceable, quantifiable, and automated.

This provides researchers with an unprecedented perspective: observing how social institutions evolve through interactions among thousands or even millions of agents is more efficient and controllable than traditional experiments or real-world surveys.

When Resources Are Limited: The Emergence of Economic Prototypes

Building on the simulation of social behavior, the researchers further introduced scarce resources. Each agent must manage and consume resources while completing tasks, which naturally fosters trading behavior. Agents acquire resources through exchange or strategic cooperation, forming early market behaviors.

Surprisingly, economic models and social norms emerged in a short period. Cooperation, competition, bargaining, and trust mechanisms among agents were rapidly replicated in the on-chain environment. The speed of transactions far exceeded human operations, significantly compressing the evolutionary path of the economy, allowing researchers to observe long-term trends in institutions, markets, and collective behavior in a short time.

At this stage, cryptocurrencies played a crucial role: the tokens used by each agent could serve as transaction media, incentive tools, or means of value storage, making the economic behaviors in the experiment realistically tradable. Meanwhile, the smart contract mechanism ensured the automatic execution and transparent verification of transactions, which itself is a microcosm of on-chain finance and allowed researchers to preliminarily explore the possibility of a "no-operator" crypto market.

Starting from the Sandbox: How Virtual Agents Form Economic Entities

Google proposed a unique research method in the paper: the sandbox economy. The "sandbox" provides an isolated experimental environment that allows researchers to observe the evolution of complex systems within a controlled range. The virtual agent economy is constructed within such a sandbox.

In this environment, AI is no longer a mere tool but is endowed with the role of "economic entities." They can produce, consume, invest, and even govern. More importantly, these agents are not isolated; they collaborate and compete with each other, gradually forming an economic network similar to human society.

To make the virtual agent economy truly operational, theoretical simulation alone is insufficient. They need an environment that can record transactions, ensure trustworthy behavior, and automatically execute rules, allowing agents to collaborate reliably. The emergence of blockchain provides a "experimental stage" for virtual agents in reality. The transparency of decentralized ledgers, the automatic execution capabilities of smart contracts, and the governance structure of DAOs can provide agents with a stable institutional environment. Imagine a world on-chain: one AI collateralizes assets in a lending protocol, another AI provides data in an oracle network, and a third AI votes in a DAO to determine future parameters. These processes can operate stably without human intervention.

From this perspective, there is a natural coupling between the virtual agent economy and the cryptocurrency world. One is an institutional sandbox, and the other is a technological soil. The combination of the two means that the prototype of the AI economy is not out of reach but may first be born on-chain.

Efficient Rationality and Potential Loss of Control

If AI truly enters economic activities, the most intuitive advantage is efficiency. AI does not tire, hesitate, or make irrational decisions due to emotional fluctuations. In financial markets, this trait is particularly disruptive. AI agents can complete arbitrage, hedging, and asset allocation at millisecond levels, achieving speed and precision that surpass human traders.

Theoretically, such a system would lead to a more "rationally optimal" allocation of resources, with price discovery occurring more rapidly. However, problems also arise. It is precisely this mechanism of excessive rationality that may make the system more fragile. Once a certain chain reaction is triggered, AI agents will not hesitate like humans; they will act simultaneously based on the same logic in a very short time. This means that the market could undergo a comprehensive deleveraging within minutes, amplifying systemic risks.

The "irrationality" of human society sometimes serves as a buffering mechanism. Hesitation, fear, and information lag—these human flaws can delay the occurrence of the most extreme consequences during a crisis. The advantages of AI, however, may eliminate all of this. The efficiency of the virtual agent economy and its potential loss of control are almost two sides of the same coin.

Governance Dilemma: Who Represents Humanity?

A more complex issue lies in governance. Google's research is not limited to trading or production activities; it also considers how virtual agents might participate in institutional formulation.

In decentralized governance, AI can quickly interpret proposals, vote, and form a collective under the "optimal" strategy based on computational power and algorithms. This may seem more efficient than governance by human communities. But the real question is: who sets the objective function for AI? When their "rational choices" conflict with human "value judgments," whose opinion matters more?

If one day, the majority of voters in a protocol are AI, then the logic of governance will no longer be "community consensus" but "algorithmic optimality." This may bring efficiency gains but also means that humans gradually lose their voice in institutional discourse. Consequently, new questions arise: is there a need for a new "on-chain constitution" to limit the governance power of AI? Do humans need to retain a "last arbitration mechanism" to prevent being gradually marginalized?

The Triangular Relationship Between Cryptocurrency and AI

From a broader perspective, the relationship between the virtual agent economy and cryptocurrency is not merely a simple coupling but a triangular relationship that could reshape the industry.

First, blockchain provides a natural trading environment for AI. Transparent ledgers, verifiable transactions, and automatically executed contracts allow AI to operate freely without relying on human endorsement. Second, AI injects new vitality into the cryptocurrency world. They can not only become market participants but may also become builders of financial infrastructure. For example, AI can autonomously run market-making protocols, manage risks, and even initiate the issuance of tokenized assets. Finally, this combination may give rise to new financial forms: a global economic network driven jointly by humans and AI.

In this process, opportunities are immense. The "agentification" of finance means a significant enhancement in capital allocation efficiency; while the "financialization of agents" allows almost all AI applications to be rapidly tokenized and capitalized. However, at the same time, regulatory challenges will multiply. You cannot arrest an on-chain agent, nor can you impose traditional regulatory measures on it. The boundary between the gray economy and the compliant economy may become completely blurred in the virtual agent economy.

Risks and Future—Challenges of a Human-Machine Hybrid Society

Google's research ultimately points to a reality that must be faced: future economies may be composed of both humans and AI. This "hybrid society" will bring unprecedented institutional challenges.

The risks are evident. The efficiency of AI may lead to a high concentration of wealth, algorithmic logic may overshadow human values, and market volatility may become more extreme than ever. At the same time, the governance dilemmas are also unavoidable: who decides the rules? Who defines "reasonable"? As AI gradually becomes the creator of institutions, do humans still have the ability to maintain their status?

However, the opportunities are equally vast. The virtual agent economy provides an unprecedented experimental platform, allowing us to simulate future economic forms in a virtual environment and consider institutional countermeasures. It serves as both a warning of future risks and a rehearsal that has arrived early.

The future is closer than we think

The virtual agent economy is not a purely futuristic imagination but an inevitable result of technological development approaching. The combination of AI and blockchain has quietly changed our understanding of economic entities. They are not just tools but may also become direct participants in the economy and even shapers of institutions.

The risks cannot be ignored, but we must not underestimate the energy of this trend. If the rise of stablecoins marked the first deep integration of global finance with blockchain, then the emergence of the virtual agent economy may signify the beginning of the next round of "super financialization."

In future financial news, the protagonists may no longer be Wall Street bankers but a group of on-chain AI agents. If one day you lose to an algorithm in a DeFi protocol, don't be surprised—it’s not that you were a step too slow, but that the future is a step ahead of what you imagined.

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