The Gaze Asymmetry Framework: Asymmetry of Social Defence Mechanisms under Human and Algorithmic Gazes
Abstract
In contemporary public spaces, individuals automatically activate social defences when facing the human gaze, yet they relax when confronted with ubiquitous cameras. The difference between humans and machines in triggering social defence has not been explained in a systematic way; existing theories can explain traditional discipline and defence, but they do not clearly explain how algorithmic surveillance in digital contexts, which has no physical body, may cause the structural weakening of individuals' social perception. This paper uses a conceptual approach based on cognitive psychology and micro-sociology, and it proposes the Gaze Asymmetry Framework to fill this gap; this framework explains the phenomenon through a simple three-part logic: the human gaze triggers defences because it contains natural cues of subjectivity; the algorithmic gaze removes subjectivity in a systematic way, and this disrupts the "imagined audience", so traditional defence mechanisms are turned off; long-term exposure to this environment without a subject may lead to a cognitive spillover effect, which can possibly affect individuals' broader social perception abilities. This study offers a theoretical tool for understanding the basic mechanisms behind modern surveillance, and it helps explain how digital contexts change the boundaries of human interaction.
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