We investigate the structure of interactive beliefs in networks: the epistemic state in which agents hold, revise, and act on their models of the epistemic states of other agents. What a group believes depends on what each member agent takes the others to believe, and on what each takes the others to believe about still others. We posit that the proper unit of social-epistemic analysis is not the individual belief but the tensor of mutual attribution, the array that records what every agent takes every agent to believe. We separate three layers of this object: what is privately held, what is publicly expressed, and what is to be believed by others. Social belief evolves by contraction of the tensor against a signed matrix of epistemic influence. Collective misperception decomposes exactly into a component that observation dissolves and a component that observation cannot touch. Social conformity amplifies pluralistic ignorance without generating it. The stable forms of collective epistemic consensus, polarization, entrenched misperception, and instability are spectral regimes of a single operator. Higher-order belief reduces to walks in the epistemic network, under a stated assumption of cognitive consistency whose boundary we mark precisely.
It is concluded that cascades are not only likely to occur but are sometimes unavoidable by “rational” means: in some situations, the group’s inability to track the truth is the direct consequence of each agent’s rational attempt at individual truth-tracking.
It is concluded that cascades are not only likely to occur but are sometimes unavoidable by “rational” means: in some situations, the group’s inability to track the truth is the direct consequence of each agent’s rational attempt at individual truth-tracking.
It is concluded that cascades are not only likely to occur but are sometimes unavoidable by “rational” means: in some situations, the group’s inability to track the truth is the direct consequence of each agent’s rational attempt at individual truth-tracking.
This work demonstrates how agent-based modeling, a computational approach well-suited for studying complex social systems, can be applied to investigate pluralistic ignorance, and suggests that it may be a robust emergent phenomenon.
In their provocative paper, Shiffrin, Stigler, and Keil (SSK) declare that scientists have illusions of understanding the phenomena they study “more deeply” than they really do. In this comment I grant their claim a degree of truth and focus on the nature of illusions of understanding. These are a form of meta-ignoranc...
M. Smithson· Computational Brain & Behavi...· 0 citations
Models of social contagion usually assume how individuals adopt beliefs and derive population behavior from it. We instead empirically measure belief adoption in language model agents, quantifying the probability an agent adopts a claim given how many peers endorse it. We find this adoption kernel to be sigmoid, a char...
Tathagata Banerjee, N. Moghaddas· 0 citations
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