Course details
Use generative AI with purpose, evidence, and human responsibility
COMP 327 develops the practical judgment needed to use generative AI effectively and responsibly across learning, research, communication, professional practice, workplaces, and everyday life. Through structured prompts, verification, ethical analysis, human-governed workflows, and discipline-specific applications, students examine both the opportunities and corresponding risks of AI while preserving human agency, capability, relationships, and accountability.
Course overview
This interdisciplinary course progresses from the foundations of generative AI to prompt design, ethical and responsible use, learning and research, professional and everyday applications, governance, emerging systems, and a discipline-specific capstone strategy.
- Seven thematic modules organize 20 instructional units.
- Six assignments develop prompting, ethical analysis, verification, workflow design, reflection, and integration skills.
- No final examination is required.
- No programming experience is assumed or required.
Course learning outcomes
By the end of COMP 327, you should be able to:
- Explain how generative AI produces outputs and distinguish fluency from understanding, accuracy, and suitability.
- Design purposeful prompts and staged workflows with explicit context, criteria, evidence, and verification requirements.
- Allocate appropriate roles to people and AI systems while preserving meaningful human authority and accountability.
- Evaluate fairness, accessibility, privacy, security, copyright, authorship, attribution, and academic-integrity implications.
- Identify hallucinations, omissions, reasoning defects, false precision, and uncertainty in AI-generated material.
- Verify claims, sources, citations, and evidence using authoritative and sufficiently independent information.
- Use AI to support learning, research, communication, professional practice, and everyday tasks without replacing essential human work.
- Design responsible AI workflows with information boundaries, review gates, escalation, incident response, fallback, and stop conditions.
- Assess discipline-specific and organizational AI uses through evidence, stakeholder impact, professional authority, and governance.
- Evaluate emerging systems and future scenarios using adaptive safeguards, revalidation, and human-centred judgment.