DMA 171: Topics In Interactivity And Games: Cultural Appropriation With Machine Learning - Fall 2020
Topics In Interactivity And Games: Cultural Appropriation With Machine Learning
Exploration of how artists engage with visual culture through its remix and adaptation. Starting from early collage and montage practices, exploration of how artists have used visual fragments as their medium to explore meaning through juxtaposition and appropriation. Exploration of how machine learning has enabled artists to generate content in increasing and surprising fidelity and magnitudes of data, leading to new aesthetics and questions surrounding underlying data. Study also speculates on future of visual culture and machine learning, by following its progression from dataset creation to more advanced techniques in adversarial and latent image generation. Discussion of perception, augmentation, deep fakes, surveillance, privacy, and ethical and legal considerations. Students apply methods in machine learning and explore how to work with datasets; understand similarities, distances, and associations between data; and how to generate content with neural networks.