拟像、模式识别与计算形式主义——反思AI在艺术创作与艺术史研究中的运用
Simulacra, Pattern Recognition, and Computational Formalism——Reflections on the Application of AI in Artistic Practice and Art History Research
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摘要: 随着人工智能（AI）、机器学习广泛运用于艺术创作和艺术史研究，对其内在逻辑的揭示和反思变得越来越迫切。通过福柯的《这不是一只烟斗》和罗莎琳·克劳斯的《关于索引的笔记》两个文本，可以看出算法在艺术创作和艺术史研究中依循的是“拟像”的原理，而主导它的则是“索引”及其内在的形式主义逻辑。为了克服“拟像”尤其如AI影像生成带来的“白噪声”效应，艺术家黑特·史德耶尔提出应回到数字基础设施。这亦恰好回应了艺术史家阿曼达·瓦西列夫斯基针对“计算形式主义”的检讨和艺术家帕格伦关于“机器现实主义”的质询。但事实上，正是数字基础设施与“机器现实主义”，重构了艺术（史）的“客观性”，并开启了一条AI时代人文学科研究的新道路。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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Key words:
- pattern recognition /
- computational formalism /
- machine realism /
- AI art /
- methodology of art history
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