🔬 Research Summary by Angelina Wang, a PhD student in computer science at Princeton University studying issues of machine learning fairness and algorithmic bias. [Original paper by Angelina Wang, Vikram V. … [Read more...] about Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation
Emerging Technology
The Larger The Fairer? Small Neural Networks Can Achieve Fairness for Edge Devices
Summary contributed by Yi Sheng, a Ph.D. student at George Mason University, advised by Weiwen Jiang, and interested in software and hardware co-design, AutoML, and dermatology diagnosis. [Original paper by Yi … [Read more...] about The Larger The Fairer? Small Neural Networks Can Achieve Fairness for Edge Devices
Responsible sourcing and the professionalization of data work
✍️ Column by Natalie Klym, who has been leading digital technology innovation programs in academic and private institutions for 25 years including at MIT, the Vector Institute, and University of Toronto. Her insights … [Read more...] about Responsible sourcing and the professionalization of data work
Understanding Toxicity Triggers on Reddit in the Context of Singapore
Summary contributed by Yun Yu Chong and Haewoon Kwak. Chong Yun Yu is a recent graduate from Singapore Management University who is interested in understanding human behaviour through data. Haewoon Kwak, an … [Read more...] about Understanding Toxicity Triggers on Reddit in the Context of Singapore
Predatory Medicine: Exploring and Measuring the Vulnerability of Medical AI to Predatory Science
🔬 Research Summary by Shalini Saini, a doctoral researcher exploring privacy and security of AI in Medicine, Voice Biometrics, and Mobile Apps. She is working with Dr. Nitesh Saxena, Professor Of Computer Science at … [Read more...] about Predatory Medicine: Exploring and Measuring the Vulnerability of Medical AI to Predatory Science