This paper describes how computational generative models can describe aspects of the artistic process, and how these generative models can provide tools for formulating and testing psychological theories of art. The term “generative models” here refers to algorithms that can generate artistic imagery, video, text, or other artistic media, including techniques developed in both computer graphics and AI research. Generative models can both describe artistic processes and offer useful experimental tools. This paper first outlines different ways to understand the types of research in generative models. It then surveys several recent examples of using generative models to develop theories and to perform experiments. The paper then discusses misleading uses of the concept of “AI-generated art” in psychological studies, and the need for study of our relationship with new artistic technologies. Finally, the paper offers a few remarks on pursuing interdisciplinary research across psychology and computer graphics.

中文翻译：

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艺术与美学心理学的生成模型


本文描述了计算生成模型如何描述艺术过程的各个方面，以及这些生成模型如何为制定和测试艺术心理学理论提供工具。此处的术语“生成模型”是指可以生成艺术图像、视频、文本或其他艺术媒体的算法，包括在计算机图形学和 AI 研究中开发的技术。生成模型既可以描述艺术过程，又可以提供有用的实验工具。本文首先概述了理解生成模型中研究类型的不同方法。然后，它调查了最近使用生成模型开发理论和进行实验的几个示例。然后，本文讨论了心理学研究中对“人工智能生成艺术”概念的误导性使用，以及研究我们与新艺术技术关系的必要性。最后，本文对在心理学和计算机图形学领域进行跨学科研究提供了一些评论。