Art as counter-truth: intersections between artificial intelligence, artistic practices, and contemporary epistemologies

Authors

DOI:

https://doi.org/10.24310/umatica.2025.v8i8.21787

Keywords:

Artificial Intelligence, Truth, Feminism, Art, Society, Amy LaViers, Stephanie Dinkins

Abstract

This essay analyzes the contemporary reconfiguration of the concept of truth in a context marked by artificial intelligence (AI) and neoliberal structures. Its main objective is to explore how these technological and political dynamics transform truth, challenging its traditional definition and affecting its understanding in everyday life and artistic practices. To this end, an interdisciplinary approach is adopted, combining critical theories such as those of Nelson, Wittgenstein, Brown, and LaViers, which allow us to conduct a contemporary analysis of the impact of AI on society and art. Likewise, it showcases some artistic practices that move in this direction, such as those of Stephanie Dinkins or Vladan Joler and Kate Crawford.

The research focuses on the epistemological and cultural changes caused by digital acceleration and neoliberalism, observing how truth is questioned in art. The findings allow us to identify the conversion of truth into a commodified object, controlled by neoliberal dynamics, with AI as a central actor in this process. The role of art as a space of resistance against the manipulation of truth is discussed. Finally, it advocates for an ethical (digital) approach to AI that promotes critical thinking. With this analysis, the aim is to invite reflection in favor of other common alternatives on which to collectively rethink the idea of truth. Other alternatives where values are established from perspectives not subordinated to authoritarianism and hierarchical manifestations of domination.

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Published

2025-12-08

How to Cite

Daniel, L. (2025). Art as counter-truth: intersections between artificial intelligence, artistic practices, and contemporary epistemologies. UMÁTICA. Journal on Image Creation and Analysis, 8(8). https://doi.org/10.24310/umatica.2025.v8i8.21787

Issue

Section

Articles (RESEARCH AREA)