Civic Tech and Algorithms for Social Good

Through real-world cases, this course explores how civic technologies can both strengthen and undermine social good. It introduces students to the normative, technical, and evaluative foundations needed to design and assess the impact of public interest tech. Drawing on frameworks from data science, policy evaluation, and political philosophy, students learn to reason about “social good”, how algorithmic systems embed values, and how to assess whether they achieve their intended outcomes. Students will:

• engage normative frameworks for thinking about algorithmic fairness, social welfare and utility; ​​
• examine real-world civic technology and algorithms through a responsible design lens. We’ll analyze both successful and problematic examples to see how design choices encode values and trade-offs;
• get a foundational understanding of data interpretation, bias, and causal inference needed to audit and build civic tech.

The course culminates in a project where students either propose their own project design that addresses a social challenge, or assess an existing civic technology. By the end of the course, students will be able to connect normative reasoning with empirical analysis and design of civic tech.