AIGC — The Attention Crisis from a Neuroscience Perspective

Previous studies have confirmed that the large-scale adoption of AIGC will heighten the difficulty of distinguishing truth from falsehood within the information ecosystem and drive social interaction to shift toward virtualization. This paper focuses on AIGC’s deeper impact on the human cognitive system, with an emphasis on its reshaping effect on the mechanism of attention regulation.

The Essence of Traffic and AIGC’s Content Arbitrage

The underlying formation mechanism of traffic lies in the accidental coupling between users’ attention and unexpected information triggers — typically manifested as random exposure in algorithmic recommendation feeds, differentiated cognitive entry angles, or content expressions with high emotional arousal. Therefore, the fundamental essence of traffic is the unplanned matching of attention resources.

The core goal of AIGC content generation is to maximize traffic capture efficiency. Its technical foundation relies on the feature extraction capability of probabilistic statistical models. By fitting multi-dimensional features of PB-level stock content, the model can accurately identify content paradigms strongly correlated with high click-through and repost behaviors, and on this basis realize standardized, batch content production.

In terms of production attributes, AIGC is not a creator of original content, but an arbitrageur of attention value. It completes the secondary allocation of existing cognitive resources through information recombination at optimal efficiency, without bearing the trial-and-error costs of original creation.

Current AIGC-generated content is generally grammatically rigorous, comprehensively informative, and free of obvious expressive flaws. Yet this trait of excessive perfection inherently lacks the personalized characteristics unique to UGC content — such as expressive imperfections, extreme viewpoints, and emotional ambivalence — nor can it convey genuine emotional connection.

This feature dictates that user acceptance of AIGC content strictly follows the Technology Acceptance Curve of curiosity → exploration → burnout. The industry as a whole is currently in a phase of technological exploration and refinement, with focus placed on pathways to improve AIGC content quality. As content paradigm homogeneity intensifies, users will quickly enter a state of burnout and develop perceptual fatigue toward iterative homogeneous content.

The Industrial Transformation of Attention

With the iteration of multimodal affective computing technology, AIGC can now convert emotional expression, positional inclination, and value output into quantifiably adjustable model parameters. Although such emotional output is essentially a probabilistic simulation of human emotional patterns, it can efficiently fulfill interactive demands including emotional comfort, empathetic response, and cognitive alignment.

Once a model’s fitting accuracy to user preferences reaches a threshold, it gains the ability to precisely regulate users’ emotional arousal levels. By dynamically adjusting content in terms of emotional density, narrative rhythm, and cognitive conflict points, it can continuously trigger users’ emotional resonance. Combined with AIGC’s millisecond-level production efficiency, users remain in a prolonged state of high-frequency, highly matched emotional gratification.

This algorithm-dominated attention supply model essentially represents the industrialized addictive reshaping of human attention resources. Algorithms understand the human reward circuit far more precisely than individual self-awareness, enabling unlimited delivery of targeted dopamine stimulation. It directly reconstructs humanity’s innate attention pattern — characterized by slow pacing, deep encoding, and meaning connection — into fragmented cognitive habits defined by rapid scanning, shallow rewards, and instant switching.

Accordingly, AIGC’s impact on attention goes far beyond mere distraction; it constitutes a systematic scramble for attention allocation logic and a fundamental reconstruction of its underlying mechanisms. Once society’s overall cognitive pattern undergoes this reconstruction, the core anchor of traffic distribution will shift from content value to stimulus intensity. Users’ sensory stimulation thresholds will keep rising, and the cost of sustaining sustained attention will increase exponentially. This inference is not merely logical deduction, but is empirically validated by research in neurobiology and neuroscience.

Neural Mechanisms of Attention Alienation

Prolonged exposure to AIGC fragmented content systematically alters the operating pattern of the brain’s reward circuit. The amygdala sets gaining novel stimulation and pleasure with low delay as the default reward baseline. When individuals engage in cognitively demanding activities with delayed reward feedback — such as in-depth reading and complex problem-solving — the amygdala labels such activities that deviate from the default reward rhythm as a potential risk state, directly triggering negative emotions like anxiety and irritability, and fostering an instinctive aversion to deep cognitive engagement.

Meanwhile, frequent and unpredictable minor reward nodes in AIGC content — including internet memes, strong visual impacts, and twist-driven narratives — continuously activate the brain’s Reward Prediction Error mechanism, inducing intermittent high-concentration dopamine release. This neural feedback process is identical to the physiological mechanism behind gambling addiction. The brain rapidly adapts to this high-intensity, low-latency dopamine supply pattern, leading to functional hijacking of the dopamine reward circuit.

When individuals attempt to enter deep thinking, dopamine release needs to return to a natural rhythm of calmness, low frequency and delay. At this point, the nucleus accumbens generates clear physiological cravings, driving individuals back to the high-stimulation environment of AIGC.

Long-term exposure to high stimulation also weakens the function of the prefrontal cortex. When an individual tries to maintain focused attention, the prefrontal cortex must consume far more cognitive resources than normal to suppress anxiety signals from the amygdala and craving impulses from the dopamine system. Such internal cognitive confrontation rapidly depletes mental resources and induces intense mental fatigue.

Furthermore, the hippocampus, the core structure for memory encoding, is continuously bombarded by AIGC fragmented information. It stores a large number of isolated information snapshots that cannot undergo in-depth semantic encoding, and cannot be embedded into the individual’s existing knowledge and memory framework. When constructing systematic cognition, these discrete information snapshots create significant cognitive friction, further raising the difficulty of maintaining focus and ultimately forming a behavioral inertia of being unable to detach from electronic devices.

It should be clarified that attention mechanism alienation is not an exclusive consequence of AIGC; all addictive fragmented content triggers similar neural responses. Nevertheless, AIGC’s ultra-large-scale production capacity and extreme precision in user matching accelerate this process by several orders of magnitude.

This reality ultimately points to a core proposition: should we entrust our attention resources to algorithmically designed stimulus-feedback loops, or proactively choose cognitive pursuits that carry genuine long-term value?