创造性人工智能:从表达性模仿到批判性探究

IF 0.2 0 HUMANITIES, MULTIDISCIPLINARY
Artnodes Pub Date : 2020-07-20 DOI:10.7238/a.v0i26.3370
A. Forbes
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引用次数: 7

摘要

被称为“创造性人工智能”的新兴领域包括一系列新媒体艺术、人机交互和人工智能交叉的活动。本文概述了最近的项目,这些项目强调使用机器学习算法来识别、复制和修改现有媒体中的特征,促进用户输入和媒体输出之间的新的多模式映射,推动生成艺术体验的边界,并批判性地研究特征检测和模式识别技术在当代生活中的作用。尽管此类项目激增,但应用机器学习的最新进展尚未被创造性的人工智能项目纳入或质疑,本文还强调了在该领域工作的计算艺术家的机会。文章最后设想了创造性的人工智能实践如何包括通过从人工制品和经验中提取特征来划定可以学习和不能学习的界限,探索如何将新的解释形式编码到神经网络中,阐明如何使用多种机器学习算法的交互来对我们生活中相互交织的社会技术系统产生新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Creative AI: From Expressive Mimicry to Critical Inquiry
The nascent field of what has come to be known as “creative AI” consists of a range of activities at the intersections of new media arts, human-computer interaction, and artificial intelligence. This article provides an overview of recent projects that emphasise the use of machine learning algorithms as a means to identify, replicate, and modify features in existing media, to facilitate new multimodal mappings between user inputs and media outputs, to push the boundaries of generative art experiences, and to critically investigate the role of feature detection and pattern identification technologies in contemporary life. Despite the proliferation of such projects, recent advances in applied machine learning have not yet been incorporated into or interrogated by creative AI projects, and this article also highlights opportunities for computational artists working in this area. The article concludes by envisioning how creative AI practice could include delineating the boundaries of what can and cannot be learned by extracting features from artefacts and experiences, exploring how new forms of interpretation can be encoded into neural networks, and articulating how the interaction of multiple machine learning algorithms can be used to generate new insight into the intertwining sociotechnical systems that encompass our lives.
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来源期刊
Artnodes
Artnodes HUMANITIES, MULTIDISCIPLINARY-
CiteScore
0.70
自引率
0.00%
发文量
26
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