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March 25, 2026Societies4 citationsOpen Access

Artificial Truth: Algorithmic Power, Epistemic Authority, and the Crisis of Democratic Knowledge

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RPRosario PaleseUniversidad de Salamanca

Key Points

  • The aim is to analyze how AI influences knowledge production and authority in digital societies.
  • Conceptual analysis of algorithmic systems and epistemic governance.
  • Development of a theoretical framework integrating Foucault, Bourdieu, and Actor-Network Theory.
  • Investigation of algorithmic recommendation systems and fact-checking as epistemic devices.
  • Trust economies are shifting from institutional expertise to metrics-based platform capital.
  • Generative AI creates 'synthetic truth' through fluency rather than understanding.
  • Algorithmic fact-checking institutionalizes a new form of computational veridiction.

Abstract

This article examines how artificial intelligence and algorithmic systems are reconfiguring truth regimes in digital societies, introducing the concept of “Artificial Truth” to describe an emerging form of epistemic governance where knowledge production and validation become infrastructural functions of sociotechnical systems. The study develops an integrated theoretical framework combining Foucault’s notion of truth regimes, Bourdieu’s theory of symbolic capital and fields, and Actor-Network Theory’s constructivist approach. Through conceptual analysis, the article investigates how algorithmic recommendation systems, generative AI, and automated fact-checking operate as epistemic devices that actively shape what is recognized as credible, authoritative, and true in public discourse. The analysis reveals three fundamental transformations: (1) the restructuring of trust economies, with epistemic authority shifting from institutional expertise to platform-native capital based on engagement metrics and affective proximity; (2) the emergence of generative AI as an epistemic actor producing “synthetic truth” through linguistic fluency rather than propositional understanding; (3) the institutionalization of computational veridiction in algorithmic fact-checking systems that translate situated epistemic judgments into probabilistic classifications presented as neutral. These dynamics configure a regime where truth is evaluated less by correspondence with reality and more by computational plausibility and platform integration. The article’s primary contribution lies in providing a unified theoretical framework for understanding contemporary transformations of epistemic authority, moving beyond disinformation studies to analyze AI as an epistemic actor. By integrating classical sociological perspectives with Science and Technology Studies, it conceptualizes algorithmic systems as epistemic infrastructures that embody specific power relations, restructure symbolic capital economies, and distribute epistemic authority asymmetrically, with profound implications for democratic knowledge, citizen epistemic agency, and public sphere pluralism.

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Cite This Study

Rosario Palese (2026) studied this question.

synapsesocial.com/papers/69c37be2b34aaaeb1a67eac3https://doi.org/10.3390/soc16030102
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