SRC@Brown CS

Students have heard of a concept/idea and how it relates to a given technical context. Students are able to recall the concept/idea as relevant in a specific context. ("I know X is a thing.")

Students can explain the meaning and/or significance of a specific concept/idea. They can articulate how it functions and/or why it is important.

Students are able to recognize relevant concerns in a specific technical context without prompting and are able to articulate how they would affect relevant technical decisions.

Students are able to critically evaluate a specific concept/idea, either abstractly or in a specific social or technical context. They are able to cite and engage with different concerns and/or conflicting perspectives on the topic in question.

Students are able to execute concrete technical decisions or use specific techniques to achieve a desired objective.

a. Modeling and Analysis: Understanding how data representation is reductive and incomplete, and how developer perspective shapes data and variable choices.

b. Automated Decision-Making: Addressing sources of bias in algorithmic and AI systems, fairness metrics, bias mitigation, justice, context-specific limitations, interpretability, and AI governance.

c. Generative AI: Understanding mechanisms of harm in generative AI, strategies to mitigate harms, effects on likeness and public perception, copyright and IP issues, and future of work implications.

Students explore the extent and implications of data collection, different collection mechanisms (overt, covert, shared), data sensitivity and re-identification risks, privacy functions and values, regulations (CCPA, GDPR), surveillance, consent, and privacy-preserving technologies. Topics include understanding tradeoffs between privacy and other values such as transparency, accountability, safety, and security.

a. Responsible Design: Design processes for evaluating diverse user needs and understanding how biases influence design decisions.

b. Accessibility: Varying definitions of accessibility, standards and best practices, and intersections between accessibility and other values such as privacy, security, and sustainability.

c. Technology and the Self: How technology directs attention, shapes interests and desires through psychological mechanisms and cognitive biases, effects on self-perception and interpersonal relationships, and the value of attention.

a. Sustainability: Environmental impacts (resource consumption, energy, e-waste, pollution), disproportionate socioeconomic effects, infrastructure sustainability, and data sustainability.

b. Technology and Labor: Skills and roles displaced, created, or evolved by technological advancement; human labor involved in AI training, surveillance, content moderation, and hardware fabrication.

c. The Internet and Public Discourse: Content moderation and social pluralism, tensions between free expression and user safety, algorithmic curation effects, misinformation and disinformation, transparency and sousveillance, and technical infrastructure.

d. Technology, History, and International Relations: Global power structures and technological development, long-term history of technology, and technology's impact on military capabilities and conflict.

Students learn to understand the concept of stakeholders, identify various stakeholders in projects, understand and implement stakeholder needs, analyze competing needs and resolution strategies, communicate with non-technical stakeholders, align projects with stakeholder goals, identify techno-solutionist attitudes, analyze potential negative impacts and unintended consequences, and understand responsible disclosure.