Abstract

This paper builds on the premise that art has a significant role to play in engaging with and exploring new technologies and in contributing to interdisciplinary conversations. Artists have often been pioneers in reflecting upon social and technological transformations by creating work that makes explicit the dangers, but also the exciting possibilities ushered in by innovation. After having, albeit briefly, traced the history of art engagement with technology (computer/net-art, generative art), the paper will focus on AI-art, now defined as GAI-art, to understand whether artificial intelligence is “set to become art’s next medium?” The question was prompted by the sale at Christie’s in October 2018 for $432,500 of a portrait entitled Edmund de Belamy , a work created by an algorithm called Generative Adversarial Network (GAN). The source code used by the Paris based art collective Obvious (borrowed from AI researcher/artist Robbie Barrat) to create the “artwork” triggered a debate as to the authenticity, authorship and ethics of using GAN to produce AI-art. The paper will contribute to such debate by exploring also the implications of systems more sophisticated than GAN – which seem to be able to act as “autonomous artificial artists” and produce new styles of art – and by showcasing the works of some of the most representative machine vision researchers/artists – Anna Ridler and Mario Klingeman, among others. AI artworks raise major philosophical questions, the meaning to be human in a hyper-connected world and the true nature of human creativity. In fact conceptualising AI through the artificial artist’s eye might even challenge our understanding of what it means to be human.

Highlights

  • In 2009 I wrote a paper in which I argued that the contemporary interest in the human-like artificial actor should have been considered in the context of humanity’s fascination with the idea of artificial life created from inanimate materials

  • Derived art is not a new genre, “Roman Verostko and the Algorists were an early1960s group of visual artists that designed algorithms that generated art” (Cizek, Uricchio & Wolozin 2019), for a new wave of Algorists to appear one needs to wait till computer scientist Ian Goodfellow released his influential paper outlining the concept of generative adversarial networks (GANs) in 2014

  • What Kogan has in mind is a generative art programme emerging from the collective intelligence, one where the profits are shared among the people who build and feed it

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Summary

INTRODUCTION

In 2009 I wrote a paper in which I argued that the contemporary interest in the human-like artificial actor (synthespian) should have been considered in the context of humanity’s fascination with the idea of artificial life created from inanimate materials. Cohen’s drawing and colouring programme AARON, developed over forty years and exhibited all over the world, is a case in point Cohen compared his relationship with AARON to that of Renaissance artists and their studio assistants, and as to whether the work produced was evidence of intelligence, Cohen argued that: “AARON did just what human artists did, taking knowledge of forms and applying them to the creation process” (Garcia 2016). Interactive artist Rama Allen (2018) thinks that AI can make us more creative and create a new kind of art: We as artists can truly collaborate with a tool to harness new abilities, tap into greater complexities, explore possibilities, and create a new kind of art The output of this expression differs categorically from all art previously made by humans through history, and this intelligent contribution inspires deeper investigations of the meanings of authorship, creativity, and art. One even endorsed by the “new master of AI created painting” Mario Klingemann, who went on to suggest that “what AI really adds is new ideas — it’s about augmenting the human imagination” (Carstensen 2018, emphasis mine)

He is a jolly Goodfellow
From GAN to CAN
Abraham the autonomous artificial artist
CONCLUSION
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