17 citations · 29 across the 4 of their papers we have counts for
14 papers
Segmenting across places: The need for fair transfer learning with satellite imagery
Miao Zhang, Harvineet Singh, Lazarus Chok +1
The increasing availability of high-resolution satellite imagery has enabled the use of machine learning to support land-cover measurement and inform policy-making. However, labell…
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty
Umang Bhatt, Javier Antorán, Yunfeng Zhang +12
Algorithmic transparency entails exposing system properties to various stakeholders for purposes that include understanding, improving, and contesting predictions. Until now, most…
Machine Learning in Population and Public Health
Vishwali Mhasawade, Yuan Zhao, Rumi Chunara
Research in population and public health focuses on the mechanisms between different cultural, social, and environmental factors and their effect on the health, of not just individ…
Quasi-experimental Designs for Assessing Response on Social Media to Policy Changes
Yijun Tian, Rumi Chunara
Regulation of tobacco products is rapidly evolving. Understanding public sentiment in response to changes is very important as authorities assess how to effectively protect populat…
No computation without representation: Avoiding data and algorithm biases through diversity
Caitlin Kuhlman, Latifa Jackson, Rumi Chunara
The emergence and growth of research on issues of ethics in AI, and in particular algorithmic fairness, has roots in an essential observation that structural inequalities in societ…
Fairness Violations and Mitigation under Covariate Shift
Harvineet Singh, Rina Singh, Vishwali Mhasawade +1
We study the problem of learning fair prediction models for unseen test sets distributed differently from the train set. Stability against changes in data distribution is an import…