Society is becoming increasingly digitized and datafied. Important decisions impacting criminal justice, housing, finance, labor, healthcare, and education are frequently determined by or are aided by artificially intelligent algorithmic technologies that are built and trained on large datasets. The rise in these technologies presents a challenge for social justice. Though often presented as neutral decision aids, these technologies often produce harmful predictions that operate to reinforce old legacies of racial, class, gender, and heteropatriarchal subordination. Datafication practices, computational techniques, legal doctrine, and policy play a key role in facilitating these disparate outcomes. This course will center on the complicated relationship between social justice and data science. The course will introduce students to the historical and current role of datafication and computation practices in social subordination. Students will leave the course having developed the skill set needed to identify and critically engage with the social justice challenges posed by these new technologies.

Note that this information may change at any time. Please visit the MyBU Student Portal for the most up-to-date course information.