INFO 1260

Choices and Consequences in Computing

Course Description

Course information provided by the 2026-2027 Catalog.

Computing requires difficult choices that can have serious implications for real people. This course covers a range of ethical, societal, and policy implications of computing and information. It draws on recent developments in digital technology and their impact on society, situating these in the context of fundamental principles from computing, policy, ethics, and the social sciences. A particular emphasis will be placed on large areas in which advances in computing have consistently raised societal challenges: privacy of individual data; fairness in algorithmic decision-making; dissemination of online content; and accountability in the design of computing systems. As this is an area in which the pace of technological development raises new challenges on a regular basis, the broader goal of the course is to enable students to develop their own analyses of new situations as they emerge at the interface of computing and societal interests.

Distribution Requirements (ETH-AG, KCM-AG, OPHLS-AG), (ETM-AS, SDS-AS), (ETM-HA), (STA-IL)

Last 4 Terms Offered 2025SP, 2024SP, 2022SP, 2021SP

Learning Outcomes

• Assess the consequences of design choices for computing systems by combining the technological foundations of their construction with their societal implications.
• Discuss the basic principles underlying freedom of speech and expression, including both legal and sociological dimensions.
• Analyze basic models for ranking and personalization of content, using methods from probability and computational data analysis.
• Identify the fundamental values associated with individual privacy.
• Derive the basic methods for ensuring online privacy and security, including statistical and cryptographic approaches.
• Compare human administrative structures with automated decision systems, emphasizing both the commonalities and the ways in which computation has influenced the structure of large-scale decision-making.
• Reason mathematically about the basic approaches used in prediction based on machine learning, and recognize the differences between predictive and experimental approaches.
• Recognize sources of bias in decision-making and the ways in which it can arise in algorithmic decision-making.
• Discuss and assess key ethical principles and foundations that govern individual and collective decision-making around the design and use of emerging information technologies
• Explain your own policy positions and values, and offer reasoned arguments to support them (including in dialogue with the potentially differing positions of others)
• Identify and evaluate the key policy positions, actions, and strategies of major public and private sector actors in the information field
• Distinguish the key processes through which tech policy is developed, such as legislative action, case law, administrative agencies such as FCC, FTC, and DOJ, and tech companies’ own policies.

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