Notes, summaries, and thoughts on the papers I read
Find the summaries here: https://medium.com/a-paper-a-day
- Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification
- A case study of algorithm-assisted decision making in childmaltreatment hotline screening decisions
- An AI Race for Strategic Advantage: Rhetoric and Risks
- Street–Level Algorithms: A Theory at the Gaps Between Policy and Decisions
- Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
- Regulating Transparency? Facebook, Twitter and the German Network Enforcement Act
- Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning
- “The Human Body is a Black Box”: Supporting Clinical Decision-Making with Deep Learning
- https://www.aclweb.org/anthology/2020.emnlp-main.47.pdf
- https://dl.acm.org/doi/pdf/10.5555/1858681.1858696
- https://www.aclweb.org/anthology/N19-1220.pdf
Mitacs reading list
- https://arxiv.org/abs/2101.11103
- https://arxiv.org/abs/2101.04893
- https://arxiv.org/pdf/2101.09194.pdf
Reading groups:
- Web, IR and NLP Public Reading Group at NUS
- Precog, IIITD
- Masakhane's NLP study group