The dramatic increase in use of technological and algorithmic-based solutions for research, economic, and policy decisions has led to a number of high-profile ethical and privacy violations in the last decade. Current disparities in academic curriculum for data and computational science result in significant gaps regarding ethics training in the next generation of data-intensive researchers. Libraries are often called to fill the curricular gaps in data science training for non-data science disciplines, including within the University of California (UC) system. We found that in addition to incomplete computational training, ethics training is almost completely absent in the standard course curricula. In this report, we highlight the experiences of library data services providers in attempting to meet the need for additional training, by designing and running two workshops: Ethical Considerations in Data (2021) and its sequel Data Ethics & Justice (2022). We discuss our interdisciplinary workshop approach and our efforts to highlight resources that can be used by non-experts to engage productively with these topics. Finally, we report a set of recommendations for librarians and data science instructors to more easily incorporate data ethics concepts into curricular instruction.

In this panel, presenters from Santa Barbara, Berkeley, San Francisco, Los Angeles, and Davis will describe their efforts to foster collaboration within their campus libraries as well as across campuses and the whole UC system, to address research data management, data science training, and education in data literacy. We will discuss approaches, activities, successes and challenges, and identify how others can participate in these activities. Speakers include: Santa Barbara: Greg Janée, Renata Curty, and Torin White; Berkeley: Anna Sackmann and Erin Foster and Amy Neeser; San Francisco: Ariel Deardorff; Los Angeles: Ibraheem Ali and Leigh Phan; Davis: Pamela Reynolds.