Cognitive Trap: Misperceptions in the US and China Relations

Weimin Wang, Shitao Huo

Abstract


Existing scholarship focuses on power or dysfunctional institutions to explain instability of international relations and resulting conflict among great powers. We argue that the extant deterioration of the US-China relation is the result of cognition based on self-centric generated misperception. Our study shows that rather than asymmetric power distribution or the dysfunctional institutions, it is biased and distorted cognition that trigger misunderstanding, which ultimately invites the spiral escalation of suspicions and hostile competition between the two sides. Our argument is primarily justified by our critique over normative approaches, and our proposed political-cognitive model; and then we evaluate the political implications of neglected commonalities, ignored distinctions and exaggerated differences in each party’s cognitive processes. Utilizing several analytical variables incorporating observable past experiences and current development in the power transition and in domestic politics of both countries, we found how often the states can be easily galvanized into actions of hostility with misperceptions; and how easy a benign environment for co-evolution can be cooked down to vicious situation for confrontation. We concluded that any action taken by great powers in their relations are the result of cognitive approaches. Clarifying ignorance and misinterpretations in their cognitive activities help mitigate the tensions instigated by biases and distortions. Competition through reciprocity for the great power relations is critical not only due to the deadly constraints in the militarily option, it is pragmatically most cost-beneficial because all it requires is to nurture appropriate cognition that respects the difference over uniformity, and trust regime's rationality for innovation.


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DOI: https://doi.org/10.11114/ijsss.v8i4.4886

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International Journal of Social Science Studies   ISSN 2324-8033 (Print)   ISSN 2324-8041 (Online)

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