Put broadly, my research interests involve ethics, public communication, and risk analysis of emerging technologies. I also have a keen interest in democratic education and exploring alternative classroom and learning models.

Technology and Ethics

  • The Authority of "Fair" in Machine Learning: Co-authored with Micha Gorelick, this piece looks at the currently literature of Fair ML, discussing the implications of expanding the operating definition of fairness. The aim of the paper is to push ML engineers to consider contextual and democratically-derived notions of fairness within their practice.
  • Survey of Data Ethics: Written for my PhD comps examination at CU-Boulder in Summer 2016, the paper gives a survey of the emerging field of data ethics. The paper gives a historical overview of where questions within data ethics find their roots and what open problems the field has right now.

Risk and Speculation

  • Designing a Moral Compass for Computer Vision Using Speculative Analysis: This paper take a critical look at trends within the contemporary computer vision (CV) literature. Synthesizing topics out of research and current events, the paper discusses what technological trends might lead to the biggest harm. The paper then offers scenarios meant to provoke debate on the future trajectories of certain CV technologies.

Education and Science Communication

  • How Do Neural Networks Learn?: Written as a blog post at the end of my internship with Fast Forward Labs, I designed a visualization and wrote a plain-language explanation of what learning means in the context of neural networks.
  • Beyond The Flipped Classroom: This is a paper published in SIGSCE 2015 about a model and implementation of hackathons for active, flipped classrooms in a college class setting.