Data ethics
Undergraduate · Data science
Syllabus focus
Topics typically covered
Standard syllabus
Foundations
- Values at stake: autonomy, justice, non-maleficence, transparency
- Stakeholders and power asymmetries in data systems
- Consent, notice, and secondary use of data
- Public vs private data and contextual integrity
- Dual-use and misuse scenarios
- Professional codes and institutional review basics
Privacy and security
- Identifiability, anonymization limits, and re-identification
- Differential privacy intuition (intro)
- Security breaches and data stewardship duties
- Minimization and purpose limitation
- Cross-border data transfer awareness (survey)
- Incident response ethics for analysts
Fairness and accountability
- Sources of bias in data and labels
- Fairness metric tradeoffs (survey)
- Disparate impact case studies
- Explainability vs performance tensions
- Contestability and human oversight
- Procurement and vendor diligence (intro)
Communication and governance
- Misleading visualization and rhetorical harm
- Documentation: datasheets and model cards
- Open data benefits and risks
- Regulation survey (GDPR/CCPA-style themes)
- Whistleblowing and organizational ethics
- Building an ethics review checklist for projects
Notes
Standard-track course (no separate STEM section in catalog). Pair discussions with concrete pipelines from other DS courses when possible.