# Autonomy, Authenticity, Authorship and Intention in computer generated art

arXiv: https://arxiv.org/abs/1903.02166 · HTML: https://mlsanity.com/paper/1903.02166/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Mar 2019.

## Built on by (most cited first, 18 of 18)

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- [10 Years of the PCG workshop: Past and Future Trends](https://mlsanity.com/paper/2104.11037/) (2021)
- [Seeding Diversity into AI Art](https://mlsanity.com/paper/2205.00804/) (2022)
- [Generative AI in Mafia-like Game Simulation](https://mlsanity.com/paper/2309.11672/) (2023)
- [Automating Generative Deep Learning for Artistic Purposes: Challenges and Opportunities](https://mlsanity.com/paper/2107.01858/) (2021)
- [Art Creation with Multi-Conditional StyleGANs](https://mlsanity.com/paper/2202.11777/) (2022)
- [On Creativity and Open-Endedness](https://mlsanity.com/paper/2405.18016/) (2024)
- [Interspecies Collaboration in the Design of Visual Identity: A Case Study](https://mlsanity.com/paper/2201.10393/) (2022)
- [Generative models for wearables data](https://mlsanity.com/paper/2307.16664/) (2023)
- ["I made this (sort of)": Negotiating authorship, confronting fraudulence, and exploring new musical spaces with prompt-based AI music generation](https://mlsanity.com/paper/2507.23365/) (2025)
- [Real-Time Intuitive AI Drawing System for Collaboration: Enhancing Human Creativity through Formal and Contextual Intent Integration](https://mlsanity.com/paper/2508.19254/) (2025)
- [Go witheFlow: Real-time Emotion Driven Audio Effects Modulation](https://mlsanity.com/paper/2510.02171/) (2025)
- [Recursivism: An Artistic Paradigm for Self-Transforming Art in the Age of AI](https://mlsanity.com/paper/2601.14401/) (2026)
- [Collective creativity in hybrid societies](https://mlsanity.com/paper/2609.02620/) (2026)

## Abstract (arXiv)

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.