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Volume 58 Issue 8
August 2026
Article Contents

Citation: LU Mingjun. Simulacra, Pattern Recognition, and Computational Formalism——Reflections on the Application of AI in Artistic Practice and Art History Research[J]. Academic Monthly, 2026, 58(8): 41-55. shu

Simulacra, Pattern Recognition, and Computational Formalism——Reflections on the Application of AI in Artistic Practice and Art History Research

  • With the widespread application of artificial intelligence (AI)and machine learning in artistic creation and art historical research,the need to uncover and reflect upon their underlying logic has become increasingly urgent. Through an analysis of two texts—Michel Foucault's This Is Not a Pipe and Rosalind Krauss's Notes on the Index—it becomes evident that algorithms in art creation and art history research operate on the principle of “simulacra”,governed by the logic of the “index” and its formalism. To overcome the “simulacra”,particularly the “white noise” effect produced by AI-generated imagery,artist Hito Steyerl proposes a return to digital infrastructure. This perspective also resonates with art historian Amanda Wasielewski's critique of “ computational formalism ” and artist Trevor Paglen's challenge of “ machine realism”. Digital infrastructure and “machine realism” not only reconstruct the “objectivity” of art (history)but also open up a new path for the humanities studies in the age of AI.
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    1. [1]

      WAN Yong ,  LI Yalan . Realizing the Function of Copyright Law in the Era of Artificial Intelligence. Academic Monthly, 2026, 58(7): 104-116.

    2. [2]

      WANG Qian . AI-Generated Content and Copyright Liability: Paradoxes and Resolutions. Academic Monthly, 2026, 58(8): 118-132.

    3. [3]

      NI Liangkang . The Philosophy of History of “New Idealism” after Hegel: Neo-Hegelianism. Academic Monthly, 2026, 58(7): 12-22.

    4. [4]

      LIN Shangli . China's Mission in Constructing Original Theories and Its Methodological Foundation. Academic Monthly, 2026, 58(7): 5-11.

    5. [5]

      YOU Yang . How Does AI Understand Language Meaning. Academic Monthly, 2026, 58(8): 16-28.

    6. [6]

      HE Da'an ,  LI Huaizheng . Digital Adjustment Mechanism in the Application of Artificial General Intelligence. Academic Monthly, 2026, 58(7): 54-63.

    7. [7]

      LIN Xifen ,  FU Zhangyi . How Does Public Trust in the Judiciary Shape Acceptability of Judges' AI-assisted Adjudications——An Empirical Study Based on Questionnaire Data. Academic Monthly, 2026, 58(8): 133-144.

    8. [8]

      ZHANG Yi . Cognitive Transformation in Historical Research in the Age of AI——“Fluency-Induced Occlusion” in LLM-Assisted Reading of Diplomatic Manuscripts. Academic Monthly, 2026, 58(8): 29-40.

    9. [9]

      RAN Gaoran . The Evolution and Game of Property Systems——On the Paradigm Choice for Data Property. Academic Monthly, 2026, 58(7): 117-128.

    10. [10]

      SUO Liming ,  WEI He'ning . Platform Transition: The Re-Evolution of Network Governance Model. Academic Monthly, 2026, 58(7): 90-103.

    11. [11]

      XU Xiangdong . Consciousness and The Moral Status of AI Agents. Academic Monthly, 2026, 58(8): 5-15.

    12. [12]

      WEN Jun . From Technical Tokens to Social Tokens: the Ontological Construction of Token Sociology. Academic Monthly, 2026, 58(8): 145-156.

    13. [13]

      HU Jun . Three Dimensions of Aesthetic Value from the Perspective of Neuroaesthetics——On the Essence of Beauty and Other Issues. Academic Monthly, 2026, 58(8): 184-194.

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        Simulacra, Pattern Recognition, and Computational Formalism——Reflections on the Application of AI in Artistic Practice and Art History Research

        Abstract: With the widespread application of artificial intelligence (AI)and machine learning in artistic creation and art historical research,the need to uncover and reflect upon their underlying logic has become increasingly urgent. Through an analysis of two texts—Michel Foucault's This Is Not a Pipe and Rosalind Krauss's Notes on the Index—it becomes evident that algorithms in art creation and art history research operate on the principle of “simulacra”,governed by the logic of the “index” and its formalism. To overcome the “simulacra”,particularly the “white noise” effect produced by AI-generated imagery,artist Hito Steyerl proposes a return to digital infrastructure. This perspective also resonates with art historian Amanda Wasielewski's critique of “ computational formalism ” and artist Trevor Paglen's challenge of “ machine realism”. Digital infrastructure and “machine realism” not only reconstruct the “objectivity” of art (history)but also open up a new path for the humanities studies in the age of AI.

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