Digital Ethics and Curation
The spectacular success of machine learning over the past decade has brought with it explosive growth in the use of computational decision-making tools. As these become increasingly ubiquitous, and our reliance upon them increasingly widespread, it becomes increasingly important to develop an understanding of how fairness, justice, and value considerations apply to these tools.
At JFI, we are advancing this conversation in three ways. First, we are supporting promising new researchers in the field, and building on their expertise to develop course materials that can be adapted for use in a broad range of fields, from computer science to social work. Second, we are building partnerships and infrastructure to facilitate cross-disciplinary engagement around these questions, so that thinkers from a broad base of perspectives – computer science, data science, and statistics, of course, but also philosophy, history, Africana studies, and law – can more easily combine their knowledge and experience. Finally, we are developing prototype algorithms and systems useful for both investigating these questions and implementing solutions, including novel feature detection algorithms, generative models, and decision support tools that can take user-specified values, goals, and constraints into account.