DATA AND ALGORITHMS: ETHICS AND POLICY

Prerequisites & course information

Requisites: Sophomore standing. Not open to students with credit for L I S 462 . Course Designation: Core GenEd - Humanities & Arts Breadth - Humanities Level - Intermediate L&S Credit - L&S Liberal Arts and Science Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Identify, analyze, and evaluate moral problems relevant to data science Audience: Undergraduate 2. Distinguish and explain different types of legal and moral concerns including harm, discrimination, procedural unfairness, respect for persons, and democratic legitimacy. Audience: Undergraduate 3. Examine and critique the arguments, and to bring original and creative ideas to bear on those arguments in oral and written form. Audience: Undergraduate 4. Understand and apply theories and concepts to problems in data and ethics in a variety of domains Audience: Undergraduate 5. Demonstrate professional analytic competencies important for management of information organizations Audience: Graduate Learning Outcomes: 1. Identify, analyze, and evaluate moral problems relevant to data science Audience: Undergraduate 2. Distinguish and explain different types of legal and moral concerns including harm, discrimination, procedural unfairness, respect for persons, and democratic legitimacy. Audience: Undergraduate 3. Examine and critique the arguments, and to bring original and creative ideas to bear on those arguments in oral and written form. Audience: Undergraduate 4. Understand and apply theories and concepts to problems in data and ethics in a variety of domains Audience: Undergraduate 5. Demonstrate professional analytic competencies important for management of information organizations Audience: Graduate