AI, Art, and Ethics
By Ramya Malur Srinivasan With the rapid expansion of the use of generative AI, it is important to understand the implications of this emerging technology in different domains and sectors. In this module, Srinivasan explores the ethical challenges that emerge from the use of generative AI in the field of visual art, often referred to as generative art. Through a series of case studies, Srinivasan highlights existing biases in the field and shares specific tools that can drive the responsible development of art datasets and the use of ethical frameworks to assess the impact of AI systems.
Read, Watch, and Listen
- Biases in generative art: A causal look from the lens of art history., Srinivasan, Ramya, and Kanji Uchino. "Biases in generative art: A causal look from the lens of art history." In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, pp. 41-51. 2021.
- Artsheets for Art Datasets, Srinivasan, Ramya, Emily Denton, Jordan Famularo, Negar Rostamzadeh, Fernando Diaz, and Beth Coleman. "Artsheets for Art Datasets." In Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2). 2021.
- AI Ethics Impact Assessment: From Principles to Practice, Fujitsu Research. 2023. "AI Ethics Impact Assessment: From Principles to Practice."