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L I S 462

DATA AND ALGORITHMS: ETHICS AND POLICY (COMMUNICATIONS INTENSIVE)

4 credits.

An introduction to ethical, legal and policy issues related to analytics, "big data" and algorithms to support decision making. Gain familiarity with major debates and controversies in a variety of contexts. Critically analyze course materials and apply moral reasoning and legal concepts to assess case studies and critique arguments made by others. Develop ability to write, present, and communicate complex concepts, evidence, and arguments related to data ethics and policy.

Prerequisites & course information

Requisites: Sophomore standing. Not open to students with credit for L I S 461 . Course Designation: Core GenEd - Communication & Literacy Comm QR - Communication B Breadth - Humanities Level - Intermediate L&S Credit - L&S Liberal Arts and Science 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. Communicate ideas orally and in writing. Audience: Undergraduate 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. Communicate ideas orally and in writing. Audience: Undergraduate

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