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II. New Economic Paradigms

13.3 | AI as a "Connectivity Multiplier"

13.3 | AI as a "Connectivity Multiplier"

In the digital civilization stage, information could already be transmitted instantaneously, but connectivity has not truly achieved automation. The decision of which information is connected, how it is connected, where it is connected, and whether it enters the action level still rests with human nodes. Yet, the human mind is essentially:

  • Fragmented;
  • Localized;
  • Limited in linear processing capability.

Therefore, in the digital economy, humans must artificially set friction coefficients in the information processing and decision-making process:

  • Through procedural approvals;
  • Through hierarchical decision-making;
  • Through delayed verification;
  • Through manual risk control.

These "rational brakes" are necessary in terms of safety, but in the sense of Connectivity Economics, they systematically suppress the potential connectivity velocity and connectivity density. The emergence of AI marks the first time this structural limitation is broken.

13.3.1 | AI = Automated System for Connecting Information

The fundamental breakthrough of AI lies not in being "smarter," but in the fact that it possesses the capability to automatically connect information for the first time. Unlike humans, the information structure of AI has three key characteristics:

  • Information naturally exists in a unified space;
  • All data is interconnected by default;
  • There are no cognitive partitions or attention bottlenecks.

This means:

  • AI does not need to "choose whether to connect";
  • AI does not need to "understand before connecting";
  • AI can complete connections simultaneously as data is generated.

From the perspective of Connectivity Economics, this is a structural leap: connectivity shifts from being "human-triggered" to "system-spontaneous." AI can:

  • Process massive, multi-dimensional, and heterogeneous data simultaneously;
  • Automatically discover potential connectivity paths;
  • Perform structural deduction without explicit goals;
  • Inject all feedback back into the system in real-time to form a flywheel.

Information no longer waits for a decision; instead, it directly enters a cycle of connectivity—feedback—re-connectivity.

13.3.2 | Nodal Reconstruction by AI (Substituting, Enhancing, and Amplifying Humans)

When connectivity automation emerges, nodal structures inevitably undergo rearrangement. The effect of AI on human nodes is not a single-direction interpretation, but rather three simultaneous structural changes:

First, Substitution. All connectivity tasks that rely on rules, repetitive judgment, and stable paths will be taken over by AI. Humans withdraw from a large number of positions as "relay nodes."

Second, Enhancement. In complex systems, human intuition, experience, and value judgment are amplified through AI. Humans no longer execute connections but instead co-define the connectivity structure with AI.

Third, Amplification. High-quality human nodes, with the help of AI’s automated execution capabilities, can simultaneously help the system complete connectivity reconstructions that far exceed personal capacity boundaries. The structural influence of a single node is exponentially amplified.

This means:

  • The economic value of humans no longer comes from the quantity of connections;
  • But from the design capability of the connectivity structure.

13.3.3 | The Evolution into a "Real-Time Economy"

When connectivity judgment, execution, and feedback correction all enter a state of automation, the operational logic of the economic system undergoes a fundamental change. The traditional economy is characterized by:

  • Decision-making preceding action;
  • Action lagging behind;
  • Feedback being delayed.

An AI-driven economy gradually evolves into a Real-Time Economy. Its core characteristics include:

  • Information generation and action are almost synchronized;
  • Prediction and execution are merged into the same process;
  • Nodal rearrangement no longer waits for cycles to complete.

In such a system:

  • The economy no longer relies on "ex-ante design";
  • Instead, it relies on "continuous self-adjustment during operation."

Theoretically, this structure can approach:

  • Instantaneous resource allocation;
  • Real-time demand response;
  • Automated nodal migration.

The economy, for the first time, evolves from a "human-damped system" into a system capable of autonomous connectivity and self-evolution.

The Final Position of Human Nodes

It must be emphasized that the connectivity automation of AI does not mean humans are excluded from the system. On the contrary—the advantage of human nodes is being repositioned:

  • Humans are not suitable for processing high-frequency, repetitive, and full-volume connections;
  • Humans are closer to a "meta-cognitive structure."

Humans are better at:

  • Setting the goal space;
  • Defining the value direction;
  • Designing connectivity principles;
  • Creating entirely new supportive structures.

In the final structure of Connectivity Economics: AI is responsible for connectivity, while humans are responsible for defining where connectivity should lead. This is not a relationship of substitution, but a deep-level structural division of labor.

Once this section is completed, it will naturally lead to the more acute questions in the next chapter: When connectivity automation and structural autonomy become the norm, in what form will inequality reappear?

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