Automated Certainty
Automated certainty is a technologically mediated condition in which experienced perplexity is reduced more rapidly than users acquire the competence required to evaluate the apparent resolution thereby produced. The phenomenon is not specific to religion: algorithmically generated summaries, recommendations, and explanations may produce shallow confidence and derivative expertise across educational, political, scientific, and professional domains. This article examines its religious form. Drawing on research in the cognitive science of religion (CSR), processing fluency, predictive processing, and cognitive ecology, I argue that algorithmic systems may increase the accessibility and apparent completeness of theological representations without producing correspondingly developed interpretive competence. In domains of doctrinal complexity, such competence often depends on sustained instruction and practice of the kind associated with McCauley’s “cognition possessing practiced naturalness.” The central empirical prediction is therefore a divergence between subjective certainty and demonstrated competence. I propose a research program comparing singular-fluent, interpretively plural, and scaffolded-complexity presentations in their effects on confidence-accuracy calibration, comprehension, source evaluation, intellectual humility, delayed retention, and transfer. The article also identifies boundary conditions, including algorithmic specificity, user expertise, and cross-cultural and tradition-specific variation. Automated certainty names a conditional risk rather than an inevitable effect: where fluent algorithmic resolution outpaces interpretive formation, theological confidence may become progressively decoupled from theological competence.
Publisert i Journal for the Cognitive Science of Religion, 2026
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