Artificial Intelligence (AI) and data science technologies are increasingly being used in making consequential decisions such as determining whether someone is hired, promoted, offered a loan, or provided housing. Many of these systems however were developed and some deployed without a careful assessment of their societal impact. For example, AI systems have been shown to exhibit gender and racial biases in making hiring and sentencing decisions. Yet, many data science students and practitioners are still unaware of the prevalence and seriousness of these issues. Equipping them with the knowledge to understand the implications of algorithm design decisions as well as tools that they can use to mitigate the biases in these systems is the key to ensure that the data-driven decision making systems they build are fair and trustworthy. This serves the national interest by furthering NSF's mission to promote the progress of science, and to advance the national health, prosperity and welfare.
This two day workshop brings together prominent educators, researchers and thought leaders from academia, industry and government together to explore ideas on the best strategies to develop data science ethics curricula. During the workshop, participants explore ideas on the best strategies to develop data science ethics curricula that are guided by pedagogical principles, informed by the needs of communities, aligned with core social values and laws, and shaped by the latest evidence and solutions from the fairness, accountability and transparency in AI research. The key outcomes of the workshop include a recommendation for incorporating ethics in data science pedagogy that contains guidelines on designing both standalone data science ethics courses as well as ethics modules that can be embedded in existing data science courses.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
