Ethics & Responsible Computing

Course Description

Ethics & Responsible Computing asks final-year students to bring everything they've learned about how to build systems face-to-face with questions about whether, and how, those systems should be built at all. The course uses case studies rather than abstract principles, several drawn from the department's own research projects.

Learning Outcomes

Apply an ethical framework to a real computing case study.
Identify likely stakeholders and harms before a system is built, not after.
Evaluate a technology policy or governance proposal critically.
Articulate a personal professional ethics stance grounded in specific cases, not slogans.

Weekly Topics

Examines why ethics belongs in computing from a practical angle, using a case drawn from real systems to motivate the concepts.

Builds directly on the previous week to extend ethical frameworks overview, with an emphasis on where the earlier techniques stop working.

Combines a short lecture on privacy & surveillance with an in-class exercise students carry into the week's assignment.

Focuses on common mistakes and misconceptions around algorithmic bias & fairness, using student work from the previous assignment as material.

Introduces case study: automated decision systems and immediately puts it to use in a small design or implementation task.

Situates accessibility as an ethical practice within the broader arc of the course, showing how it connects to what comes next.

Uses a guest dataset or scenario to explore mid-semester review in a setting closer to professional practice.

Introduces platform responsibility through short lectures and worked examples, building the vocabulary the rest of the course relies on.

Works through case study: ai governance in a lab-driven session, with guided exercises students complete and discuss in small groups.

Covers whistleblowing & professional responsibility in depth, connecting the underlying theory to a concrete example the class builds together.

Examines environmental costs of computing from a practical angle, using a case drawn from real systems to motivate the concepts.

Builds directly on the previous week to extend position paper workshop, with an emphasis on where the earlier techniques stop working.

Combines a short lecture on revision with an in-class exercise students carry into the week's assignment.

Assessment

Assignments — 40%

Practical Work — 10%

Mid-Semester — 20%

Final Examination — 30%

Prerequisite Map

Related Courses

Core300 Level

CSC305

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Sofia Reyes 4 cr