| Popis: |
During the 2018 Data Science Leadership Summit, a panel discussion on data ethics generated active participation. The panel featured opening remarks by the chairs and presentations by three panelists representing a broad, multidisciplinary range of views—computer science, history and philosophy of science, and developmental psychology—followed by a question-and-answer period that included lively audience participation. Key topics covered in the panel included an overview of pedagogical approaches to engaging students with human and societal issues in data science, the historical context of ethics and science from the perspective of human-subjects research ethics, and a comparison between approaches to ethical research in industry and academia and the limits of Institutional Review Boards in predicting ethical harms created by technology. Some of the main takeaways from the ethics panel and the discussion that followed were: group consensus is that ethics education is a critical component of data science education; current protections (e.g., protections to maintain privacy, limit the targeting of vulnerable populations, minimize bias) are currently inadequate and must be updated in response to evolving world of technology; differing views and some uncertainty persist over how to adequately approach ethics education in data science; conversations about ethics must move beyond a discussion of individual actions within the data science workflow to include the larger social context and societal structures, as well as to broaden participation and justice. |
