Intensive instruction in the ethics governing biomedical big data
Large amounts of data pervade biomedical engineering, from imaging analysis down to systems level analysis of tissues and cells. To become competitive, undergraduates need the analytical and technical skills to handle big data, no matter which branch of biomedical engineering they pursue after graduation.
According to Mete Civelek, assistant professor in the department of biomedical engineering and resident faculty in the School of Medicine's Center for Public Health Genomics, there’s another dimension of data science that crosses scales and sub-disciplines—the ethical challenges that govern the practice of biomedical data science. Here's his plan for preparing undergraduate students to tackle this equally important topic.
Civelek teaches a fourth year elective called “BME Data Science” at the University of Virginia. He plans to bring ethics to the fore, with the backing of a Donchian Teaching Fellowship. The fellowship comes with a $7,000 stipend and consultation from the UVA Institute for Practical Ethics and Public Life. The revised syllabus devotes four course periods to informed consent, data ownership, privacy and anonymity, data validity, algorithmic fairness, and societal consequences.
Theoretical discussion will equip students to develop a Code of Ethics for Data Science by the course's end. As technology grows, and as more of his students bring their ideas to emerging issues in data science, the Code of Ethics document will evolve.
Contact Mete Civelek for more information and a course syllabus.
More about the UVA Institute for Practical Ethics and Public Life (IPE), Faculty Fellowships in Ethics, and the Donchian Teaching Fellowship.