Module 13 · Responsible systems
Teach and adapt Module 13
Link the entry page as additional reading/practice. Its reading-site route is /lessons/13-ethics-fairness/ relative to the served site base. For a repository link, select a tested commit or release.
Facilitation and access
Use the same outcomes and written evidence for in-person/asynchronous learners. Begin with the foundation bridge, predict-before-run questions, and the shared script/notebook. Discussion has a solo equivalent. Optional depth is skippable, and GenAI is not required.
Interpretation can use named values and exact tables; code/artefacts demonstrate execution or authoring when those are assessed. A screenshot cannot substitute for an explanation, and a script does not prove notebook-interface operation. Verify the learner's actual assistive-technology route and provide private help.
Adaptation decisions
IT AI governance should examine purpose, access, affected groups, proxy inputs, feedback loops, reporting channels, and authority to stop a system.
When changing a dataset, define its license/provenance, observation unit, target if any, availability, split, and limits first. Update preprocessing, inference contracts, examples, feedback, and tests together. Preserve the original source and disclose transformations. Do not label a tiny mechanics check as a credible production evaluation.
Outcome/evidence alignment
- M13.1: Identify stakeholders, historical label limitations, and inappropriate uses.
- M13.2: Fit a declared training pipeline without protected audit columns.
- M13.3: Report group counts, confusion denominators, selection rates, TPR, and FPR.
- M13.4: Explain metric trade-offs, proxy effects, and uncertainty without causal/legal claims.
- M13.5: Write a governance recommendation, including reasons not to deploy.
Course alignment opportunities: Supports CLO2, CLO5, CLO6, CLO8; explicit ethics is a curriculum extension. Advisory computing-outcome opportunities from the planning register: A1, A3, A4. These are opportunities for evidence, not proof of master's-level attainment or accreditation compliance. The original-module crosswalk remains in the previously prepared planning resources. Confirm adopted program criteria before formal use.
Verification limits
The real-data workflow, public script, and notebook are exercised in Windows/Linux core CI. Exact counts/results are in the verified results table and commit-specific CI. Consult the accessibility evidence log for human interface-review coverage. Public feedback is for self-study; local grading/AI-use rules remain the adopting instructor's responsibility.
Continue the learning route
Use the course review and pilot protocol. Review a changed-case explanation, not only passing visible checks. Preparation and activity times need observation with actual learners.