Autonomy, Authenticity, Authorship and Intention in computer generated art

TL;DR

This paper explores fundamental questions about autonomy, authenticity, authorship, and intention in AI-generated art, analyzing historical perspectives and recent advances in deep learning to understand their impact on art's nature.

Contribution

It synthesizes decades of research on AI art's philosophical issues and evaluates how modern deep learning techniques influence these longstanding debates.

Findings

Deep learning techniques challenge traditional notions of authorship.

Public interest in AI art has increased due to high-profile sales.

Historical debates remain relevant despite technological advances.

Abstract

This paper examines five key questions surrounding computer generated art. Driven by the recent public auction of a work of `AI Art' we selectively summarise many decades of research and commentary around topics of autonomy, authenticity, authorship and intention in computer generated art, and use this research to answer contemporary questions often asked about art made by computers that concern these topics. We additionally reflect on whether current techniques in deep learning and Generative Adversarial Networks significantly change the answers provided by many decades of prior research.