Do androids dream of electric copyright? Comparative analysis of originality in artificial intelligence generated works

By A. Guadamuz. 2017

73 citations recorded by the source corpus.

Subfields: AI Ethics, Fairness & Society

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In AI Ethics, Fairness & Society

1. Eva Cetinic
2. Percy Liang
3. Dan Jurafsky
4. Mark A. Lemley
5. James She
6. Tatsunori B. Hashimoto
7. Xuechen Li
8. Peter Henderson

Citations in the corpus

• Foundation Models and Fair Use (2023, background): “On the legal side, a large body of work has covered potential legal risks and challenges of machine learning (Sobel, 2017; Burk, 2019; Lemley & Casey, 2019; Gillotte, 2019; Lemley & Casey, 2020; Franceschelli & Musolesi, 2022; Guadamuz, 2017; Grimmelmann, 2015; McCann, 2021; McJohn & McJohn, 2020; L”
• Understanding and Creating Art with AI: Review and Outlook (2021, background): “Several other recent articles indicate that copyright infringement in AI artworks is becoming a relevant topic that needs to be addressed systematically [48, 55, 62].”
• Copyright in generative deep learning (2021, unknown): “However, as reported by Guadamuz (2017), this process typically results in producing new images that do not resemble the original ones.”