Creative AI: From Expressive Mimicry to Critical Inquiry

Abstract

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.