Abstract
From a small community of pioneering artists who experimented with artificial intelligence (AI) in the 1970s, AI art has expanded, gained visibility, and attained socio-cultural relevance since the second half of the 2010s. Its topics, methodologies, presentational formats, and implications are closely related to a range of disciplines engaged in the research and application of AI. In this paper, I present a comprehensive framework for the critical exploration of AI art. It comprises the context of AI art, its prominent poetic features, major issues, and possible directions. I address the poetic, expressive, and ethical layers of AI art practices within the context of contemporary art, AI research, and related disciplines. I focus on the works that exemplify poetic complexity and manifest the epistemic or political ambiguities indicative of a broader milieu of contemporary culture, AI science/technology, economy, and society. By comparing, acknowledging, and contextualizing both their accomplishments and shortcomings, I outline the prospective strategies to advance the field. The aim of this framework is to expand the existing critical discourse of AI art with new perspectives which can be used to examine the creative attributes of emerging practices and to assess their cultural significance and socio-political impact. It contributes to rethinking and redefining the art/science/technology critique in the age when the arts, together with science and technology, are becoming increasingly responsible for changing ecologies, shaping cultural values, and political normalization.
Highlights
Artists have been working with artificial intelligence (AI) since the 1970s
With uncanny robotic works that question the meaning of agency, creativity, and expression, artists such as Ken Feingold, Ken Rinaldo, Louis Philippe-Demers, Patrick Tresset, and others had articulated some of the contemporary AI art’s topics
They used natural language processing (NLP), pattern recognition, and computer vision (CV) algorithms to address various features of human perception reflected in AI, and to explore higher-level cognitive traits by interfacing human experiential learning with machine learning (ML) [2,3]
Summary
Artists have been working with AI since the 1970s. AI art pioneers, such as Harold. Since the 2000s, artists such as Luke DuBois, Sam Lavigne, Sven König, Parag Kumar Mital, Kyle McDonald, Golan Levin, Julian Palacz, and others, have been creating generative and interactive works based on logical systems or statistical techniques which conceptually and technically overlap with, or belong to, AI technologies They used natural language processing (NLP), pattern recognition, and computer vision (CV) algorithms to address various features of human perception reflected in AI, and to explore higher-level cognitive traits by interfacing human experiential learning with machine learning (ML) [2,3]. I identify the conceptual, discursive, and ethical issues that affect the poetic outcomes, cultural status, and socio-political impact of AI art This allows me to outline some of the creative, conceptual, tactical, and strategic prospects for the advancement of the field
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