A bibliography
Here are some of the readings and resources that the faculty cohort has read over the course of this past year along with the coordinator’s suggestions for other resources:
Machine learning and cultural computing
- Ted Chiang’s essay on LLMs
- Practical Deep Learning, free online course
- Make Your Own Neural Network, Tariq Rashid an excellent gentle introduction to the basics of neural networks
- You Look Like a Thing and I Love You, Janelle Shane a conceptual mathless overview to machine learning
- On The Dangers of Stochastic Parrots, Bender &al.’s paper on the inherent limitations of Large Language Models
- Data Conscience, Brandeis Marshall’s excellent book on the ethics of how data is gathered, instrumented, and interpreted in data science and machine learning
- Biases in Generative Art — A Causal Look from the Lens of Art History, Srinivasan and Uchino
- Reclaiming Conversation, Sherry Turkle’s book on the importance of retaining autonomy and control over human interactions that are being increasingly automated, particularly with machine learning
- Alone, Together, Sherry Turkle’s book on our troubling trends in our relationships to robots and digital companions
- Situated Computations, a sampling of Vernelle Noel’s work on using computational tools to preserve a traditional art form from Trinidad-Tobago
- Tools for Conviviality, Ivan Illich’s manifesto on how technologies can reify hierarchies
- Technopoly, Neil Postman being his usual polemical self as he asks us to consider that new technologies aren’t always better and that the luddites had a point
- Real World of Technology, a lightly edited version of a series of talks by Ursula Franklin on the ways technologies encode & reinforce social values
- Indigenous protocol and artificial intelligence position paper, Lewis &al. this is the output of a series of workshops from indigenous technologists and researchers about what it would mean for AI to come from their cultures and serve their needs rather than Silicon Valley
- AIAIArt, a series of free tutorials by researcher John Whitaker on generative art with machine learning
- Culturally Situated Design Tools, Eglash &al.’s influential paper on the intersection of education, generative art tools, and cultural computing
- Weapons of Math Destruction, Cathy O’Neil’s accessible overview to the anti-social uses of automation and machine learning in everything from crime prediction to college admissions
- Cross-cultural computing: an artist’s journey a very rare kind of monograph from Naoko Tosa, describing her experience as an artist at the intersection of art, robots, and computers in both Japan and the U.S.
- Beyond the creative species: Making machines that make art and music, excellent overview of computational creativity and machine learning by Oliver Brown