This course provides an introduction to the legal, policy, and ethical implications of data. The course will examine legal, policy, and ethical issues that arise throughout the full life cycle of data science from collection, to storage, processing, analysis and use including, privacy, surveillance, security, classification, discrimination, decisional-autonomy, and duties to warn or act. Case studies will be used to explore these issues across various domains such as criminal justice, national security, health, marketing, politics, education, automotive, employment, athletics, and development. Attention will be paid to legal and policy constraints and considerations that attach to specific domains as well as particular data-types, collection methods, and institutions. Technical, legal, and market approaches to mitigating and managing discrete and compound sets of concerns will be introduced, and the strengths and benefits of competing and complementary approaches will be explored.
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Advance your data science career with UC Berkeley’s online Master of Information and Data Science.