Resources and links to critical computer science discussions and topics
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 Bender et al. (2021) https://dl.acm.org/doi/10.1145/3442188.3445922
Could a Neuroscientist Understand a Microprocessor? Eric Jonas Konrad Paul Kording (2013) https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005268
Geographies of conservation II: Technology, surveillance and conservation algorithm Adams (2019) https://journals.sagepub.com/doi/full/10.1177/0309132517740220
Data Governance is Key to Interpretation: Reconceptualizing Data in Data Science https://hdsr.mitpress.mit.edu/pub/4ovhpe3v/release/6 Sabina Leonelli (2019)
Big Data, new epistemologies and paradigm shifts Rob Kitchin (2014) https://journals.sagepub.com/doi/full/10.1177/2053951714528481
Algorithms of Oppression: How Search Engines Reinforce Racism by Safiya Umoja Noble https://nyupress.org/9781479837243/algorithms-of-oppression/
Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor by Virginia Eubanks https://blackwells.co.uk/bookshop/product/Automating-Inequality-by-Virginia-Eubanks/9781250074317
Data Feminism By Catherine D'Ignazio and Lauren F. Klein https://mitpress.mit.edu/books/data-feminism
Dr. Timnit Gebru: Hierarchy of Knowledge in Machine Learning & Related Fields and Its Consequences https://www.youtube.com/watch?v=OL3DowBM9uc
Dr. Timnit Gebru: Understanding the Limitations of AI: When Algorithms Fail https://www.youtube.com/watch?v=QqZVx6NCkPg
Jaron Lanier: How the Internet Failed and How to Recreate It https://www.youtube.com/watch?v=KNOlqzMd2Zw
Jaron Lanier, Sue Halpern, in conversation with Marcelo Gleise - Doubling Down: Preserving Our Humanity in the Digital Age https://www.youtube.com/watch?v=8qpB9v-OrAU