论文标题
生成艺术的偏见 - 艺术史的因果外观
Biases in Generative Art -- A Causal Look from the Lens of Art History
论文作者
论文摘要
随着人工智能（AI）的快速发展，生成艺术的普及已大大增长。从创作绘画到生成新颖的艺术风格，基于AI的生成艺术都展示了各种应用。但是，关于基于AI的生成艺术的道德影响，几乎没有重点。在这项工作中，我们调查了生成艺术AI管道中的偏见，该偏差是由于与算法设计相关的问题提出不当的问题而起源的偏差。从艺术史的角度来看，我们讨论了这些偏见的社会文化影响。利用因果模型，我们强调了当前方法在建模艺术创造过程中如何缺乏，从而导致各种类型的偏见。我们通过案例研究，尤其是与样式转移相关的案例研究来说明这一点。据我们所知，这是从艺术史的角度研究生成艺术AI管道中偏见的首次广泛分析。我们希望我们的工作激发与生成艺术的责任制有关的跨学科讨论。
With rapid progress in artificial intelligence (AI), popularity of generative art has grown substantially. From creating paintings to generating novel art styles, AI based generative art has showcased a variety of applications. However, there has been little focus concerning the ethical impacts of AI based generative art. In this work, we investigate biases in the generative art AI pipeline right from those that can originate due to improper problem formulation to those related to algorithm design. Viewing from the lens of art history, we discuss the socio-cultural impacts of these biases. Leveraging causal models, we highlight how current methods fall short in modeling the process of art creation and thus contribute to various types of biases. We illustrate the same through case studies, in particular those related to style transfer. To the best of our knowledge, this is the first extensive analysis that investigates biases in the generative art AI pipeline from the perspective of art history. We hope our work sparks interdisciplinary discussions related to accountability of generative art.
