Professors Tracie Mahaffey and Michael Nair-Collins participated in a debate, organized by the Office of Public Policy, on organ and tissue donation policy.

Her paper, “An Attunement Account of Forgiveness,” won the prize for best graduate student essay at the 2024 Great Lakes Philosophy Conference: Blame and Forgiveness.

Benjamin Hause successfully defended his dissertation, “Essays at the Intersection of Population Ethics and Animal Ethics,” on March 25th. Ben’s committee was chaired by Piers Rawling.

Georgia Rae Rainer successfully defended her dissertation, “Evaluating Values: Understanding the Epistemic Worth of Values in Science,” on March 28th. Georgia Rae’s committee was chaired by Piers Rawling.

Brenden Kost successfully defended his master’s thesis, “Symmetry without Skepticism: Compromising with Rosen on Moral Ignorance and Responsibility,” on March 27th. Brenden’s committee was chaired by Mark LeBar.

Christina Karabiyik successfully defended her master’s thesis, “In Defense of Longstanding Anger,” on March 26th. Christina’s committee was chaired by Andrea Westlund.

Tucker Sigourney successfully defended his dissertation, “Charity as a Foundation of Ethics,” on March 18th. Tucker’s committee was chaired by Andrea Westlund.

Joseph Masotti successfully defended his master’s thesis, “Decision Theory, Action Guidance, and Moral Uncertainty,” on March 5th. Joe’s committee was chaired by Piers Rawling.

Her paper, “An Attunement Account of Forgiveness,” won the prize for best graduate student paper at the Eastern Regional Meeting of the Society of Christian Philosophers.

It’s easy for a data scientist (or indeed, for any of us in our professional lives!) to get their work done by putting their head down, ignoring the social context of that work and the ethical concerns it might raise. In Data Ethics, I try to help students develop an ability to identify ethical issues as they arise and become comfortable discussing difficult moral and political questions. When concepts like privacy and transparency are mentioned in data science, they’re often treated just as buzzwords. So I also want to equip students with arguments about why exactly such values matter.