arXiv:2607. 20796v1 Announce Type: new Abstract: This paper examines the question of whether artificial intelligence (AI) systems can be creative, approached from the dual perspective of a researcher trained in electrical engineering, pattern recognition, machine learning, and neural networks, who has also spent most of his life engaged in the arts as actor, stage and film director, writer, composer, and visual artist, and in philosophy.
By Ivan Magrin-Chagnolleau
arXiv:2601. 15797v2 Announce Type: replace Abstract: Many theorists maintain that conscious intentional agency is a necessary condition of creativity.
By James S. Pearson, Matthew J. Dennis, Marc Cheong
arXiv:2607. 15027v1 Announce Type: new Abstract: The integration of AI-driven systems in creative work has sparked debates among artists and legal communities about notions of ownership.
By Sofi Gjing Jovanovska, Kuntal Ghosh, Daniel Muhu Njenga, Ahmed Mufassir, Shadan Sadeghian
arXiv:2606. 13196v2 Announce Type: replace Abstract: Recent AI systems can generate texts, software architectures, hypotheses, designs, and scientific workflows that appear creative.
By Yong Zeng
arXiv:2606. 13196v1 Announce Type: new Abstract: Recent AI systems can generate texts, software architectures, hypotheses, designs, and scientific workflows that appear creative.
By Yong Zeng
arXiv:2607. 08331v1 Announce Type: cross Abstract: Understanding how artworks are created requires reasoning about the iterative decisions, material operations, and contextual influences that shape artistic production.
By Kaustubh Kumar, Ashutosh Ranjan, Vivek Srivastava, Blessin Varkey, Shirish Karande
The article discusses how generative AI is reshaping the creation and circulation of cultural artifacts, prompting debate over whether these tools enrich or impoverish culture. It distinguishes between novelty—an attribute of individual artifacts—and diversity—an attribute of populations—arguing that creativity should be viewed as a property of hybrid collectives composed of people and algorithms. The authors find that AI-assisted ideation increases the novelty of individual outputs while potentially narrowing overall diversity, but that mixed human–machine groups can outperform single-type groups and sustain machine-generated solutions within human culture, depending on the composition and connectivity of the agents involved.
By Mason Youngblood, Katie Mudd, Manuel Anglada-Tort, Cameron Jones, Elena Miu, Diana Omigie, Margaret Schedel
Understanding how artworks are created requires reasoning about the iterative decisions, material operations, and contextual influences that shape artistic production. While recent generative AI systems can synthesize artworks with high fidelity, they primarily model distributions over finished artifacts rather than the creative processes underlying their creation.
arXiv:2607. 09705v1 Announce Type: cross Abstract: Since 2023, computer scientists have warned against model collapse -- the contamination of training sets with AI-generated outputs that progressively degrade model performance.
By Violaine Boutet de Monvel (LIRA, IRCAV)
arXiv:2608. 05545v1 Announce Type: cross Abstract: Generative AI used as a capable servant has greatly accelerated intellectual work, but it also risks eroding human epistemic agency by encouraging uncritical acceptance of AI-generated reasoning.
By Riichiro Mizoguchi, Tomoki Aburatani, Kento Koike, Machi Shimmei
arXiv:2608. 14405v1 Announce Type: cross Abstract: Art style is a signature of professional digital artists that develops through repeated experimentation, reflection, and adaptation.
By Wen-Fan Wang, TsaiHsuan Lin, Chi-Lan Yang, An-Ru Cheng, Bing-Yu Chen
arXiv:2608. 16213v1 Announce Type: new Abstract: Intelligence is constituted by \textit{process} (iterative activity through which output emerges), not in the output itself.
By Michael J. Richardson, Ayeh Alhasan, Cassandra Crone, M. Paula Diaz Monfort, Patrick Nalepka, Mark Dras, Rachel W. Kallen, David M. Kaplan