Discipline-specific practice
Use DOMAIN to define legitimate purposes, evidence requirements, professional authority, high-risk activities, contestability, and remedy within a chosen field.
Module overview
Module 6 is the final instructional module before the capstone. It situates generative AI within disciplinary, organizational, regulatory, societal, and future contexts. You will examine how responsible AI practice varies across disciplines, how organizations can govern AI adoption, how emerging systems and societal changes create new challenges, and how to integrate all course learning into a coherent human-centred approach.
Organizational governance
Use GOVERN to map AI inventories, risk classification, approval pathways, procurement, monitoring, incident response, and lifecycle governance.
Future directions & integration
Use FUTURES to explore emerging capabilities, scenarios, adaptive safeguards, revalidation, rollback, and retirement. Use HUMAN to integrate all dimensions of responsible AI use.
Module principle: Responsible AI practice is not a checklist. It requires continuing attention to human purpose, authority, capability, relationships, participation, alternatives, evidence, reflection, and adaptation. Course completion does not establish permanent competence—systems, evidence, policies, and contexts change.
Module learning outcomes
By the end of Module 6, you should be able to:
- Define discipline-specific legitimate purposes, evidence requirements, professional authority, validation, contestability, and remedy using DOMAIN.
- Conduct an organizational AI inventory, risk classification, approval pathway, and lifecycle governance using GOVERN.
- Identify governance theatre, distinguish effective governance from symbolic compliance, and design meaningful oversight.
- Analyze emerging capabilities (multimodal AI, memory, personalization, agents, robotics, synthetic media) and their societal, labour, and environmental implications.
- Develop plausible future scenarios and design adaptive safeguards, revalidation, rollback, and retirement plans using FUTURES.
- Apply the author-approved HUMAN framework to integrate all course frameworks into a coherent human-centred analysis.
- Prepare a bounded, feasible capstone proposal, including problem, purpose, stakeholders, evidence, AI role, human authority, safeguards, monitoring, and stop conditions.
- Complete Assignment 1 (AI Learning and Reflection Journal) with a comprehensive final synthesis.
- Define continuing responsible-use commitments and transition to Module 7.
Module 6 units
Responsible AI Across Disciplines
Apply DOMAIN to your discipline: legitimate purpose, evidence, professional authority, high-risk activities, validation, contestability, and remedy.
AI Governance and Organizational Adoption
Map AI inventories, risk classification, approval, procurement, monitoring, incident response, and lifecycle governance using GOVERN.
Emerging AI Systems and Future Directions
Analyze emerging capabilities, societal impacts, scenario planning, adaptive safeguards, revalidation, rollback, and retirement using FUTURES.
Becoming an Effective and Responsible AI User
Integrate all frameworks through HUMAN, complete Assignment 1, prepare your capstone proposal, and define continuing commitments.
Implementation note: replace placeholder anchors with the corresponding Moodle activity or section URLs.
Embedded Module 6 study guide
Use this one-week schedule unless Moodle specifies different dates. This is the final instructional week. Complete Assignment 1 and prepare your capstone proposal for Module 7.
Week 11: Units 17–20
Recommended: 12–14 hours- Retrieve Modules 1–5.
Review all frameworks: ORBIT, PCAFE-V, SCOPE, PARTNER, FAIRER, PROTECT, CREATE, TRACE, CLAIM, LEARN, RIGOUR, VOICE, WORKS, LIFE. - Read Chapters 17–20 and complete Units 17–20.
Apply DOMAIN, GOVERN, FUTURES, and HUMAN to a discipline-specific use case. - Complete the capstone stream selection.
Choose your disciplinary stream and define a bounded proposal topic. - Apply HUMAN.
Integrate purpose, authority, capability, relationships, participation, alternatives, safeguards, evidence, reflection, and learning. - Finalise Assignment 1.
Review journal entries, write the final synthesis, and submit by the LMS deadline. - Prepare the capstone proposal.
Define problem, purpose, stakeholders, evidence, AI role, human roles, authority, safeguards, monitoring, and stop conditions. - Define continuing commitments.
Draft your Responsible AI Commitment and plan for lifelong learning and revalidation.
Evidence to retain
- Discipline-specific AI map (DOMAIN)
- Governance inventory and risk classification (GOVERN)
- Scenario plan and adaptive safeguards (FUTURES)
- HUMAN integration analysis
- Assignment 1 final synthesis
- Capstone proposal brief
- Responsible AI Commitment draft
Show the Module 6 integration sequence
- Identify your discipline and its norms (DOMAIN).
- Map organisational governance structures (GOVERN).
- Explore future scenarios and adaptive safeguards (FUTURES).
- Apply HUMAN to integrate all dimensions:
- Human purpose and legitimate benefit
- Human authority, agency, judgment, and accountability
- Human capabilities, learning, creativity, autonomy, and meaningful work
- Human relationships, participation, accessibility, and community
- Adaptive safeguards, alternatives, correction, remedy, and stopping
- Necessary evidence, transparency, reflection, and continuing learning
- Complete Assignment 1 and prepare for Assignment 6.
Assessment milestones in Module 6
Assignment 1: AI Learning and Reflection Journal
Weight: 15%
Started: Module 1, Week 1
Continues: Modules 1–6
Final preparation: Unit 20
Recommended submission: End of Module 6, at the end of Week 11
Official Moodle due date and time: [INSERT LMS DUE DATE AND TIME]
Check the course schedule and LMS. The LMS date and time control if they differ from this study guide.
Assignment 6: Capstone Project
Weight: 20%
Preparation begins: Module 6, especially Units 17–20
Main development period: Module 7, Weeks 12 and 13
Recommended submission: End of Module 7
Official Moodle due date and time: [INSERT LMS DUE DATE AND TIME]
Product: Discipline-Specific Responsible AI Integration Strategy
Recommended length: Approximately 4,000 to 5,000 words
Critical reminders: Begin Assignment 1 review before the final Unit 20 study session. Avoid leaving journal synthesis to the final day. Select a capstone stream during Unit 17. Establish governance during Unit 18. Prepare future scenarios during Unit 19. Finalise the bounded capstone proposal during Unit 20. Begin full Assignment 6 development in Week 12.
Show the Assignment 1 completion checklist
- Chronological development: entries from each module (1–6)
- Evidence of learning: specific examples of changed understanding
- Changed boundaries: personal, academic, professional, organisational
- Framework use: reflection on which frameworks resonated and why
- Personal authorship: the journal is your own work
- AI-use disclosure: if used, disclose per policy
- Final synthesis: integrates entries into a coherent narrative
- Submission self-review: proofread, formatted, word count
- Deadline recorded: [INSERT LMS DUE DATE AND TIME]
Show the capstone proposal readiness checklist
- Stream selection: chosen and approved
- Scope: bounded and feasible
- Problem and evidence: defined
- Purpose: legitimate and articulated
- Stakeholder map: affected people and groups
- Authority map: all authority types defined
- Framework selection: primary and supporting frameworks chosen
- Information governance: PROTECT considerations
- Workflow design: AI and human roles
- Verification and validation: TRACE, CLAIM
- Governance: GOVERN structures
- Adaptive safeguards: FUTURES scenarios
- HUMAN check: all six dimensions addressed
- Feasibility: manageable within 4,000–5,000 words
- Work plan: scheduled time in Weeks 12 and 13
- Questions for coordinator: list of clarifications needed
Core learning activities
| Activity | Purpose | Product to retain | Connection |
|---|---|---|---|
| Discipline-specific AI map | Identify purposes, evidence, professional authority, high-risk activities, and stop conditions. | DOMAIN analysis | Assignments 1 and 6 |
| AI use-case inventory | Document systems, purposes, users, data, integrations, risks, ownership, and approval status. | Inventory record | Assignment 6 |
| Risk-classification workshop | Classify AI uses and assign proportionate approval and review requirements. | Risk classification table | Assignment 6 |
| Governance theatre audit | Evaluate whether governance controls can change behaviour, detect failures, support remedies, and stop unsafe use. | Governance audit | Assignments 1 and 6 |
| Agent-permission matrix | Distinguish read, draft, modify, send, approve, transact, and delete permissions. | Permission matrix | Assignment 6 |
| Scenario-planning exercise | Develop human-centred, uneven-adoption, automation-first, and restricted-adoption scenarios. | Scenario set | Assignment 6 |
| HUMAN integration exercise | Apply the integrated HUMAN model to your proposed capstone topic. | HUMAN analysis | Assignment 6 |
| Capstone stream selection | Select your discipline-specific stream and prepare a concise project proposal. | Proposal brief | Assignment 6 |
Live AI, supplied-material, and non-platform options
Option A: Approved AI
Use an approved system with synthetic, public, supplied, verified, or authorized information and no consequential external action.
Option B: Supplied materials
Use supplied case studies, governance examples, scenario descriptions, and HUMAN analysis templates.
Option C: Non-AI analysis
Complete the same governance, scenario, and integration analysis without an AI platform.
Students must not be disadvantaged for lacking workplace access, paid AI access, or permission to use live systems.
Frameworks emphasized in Module 6
DOMAINGOVERNFUTURESHUMANIntegrationScenario planningAdaptive safeguards
DOMAIN
Use the author-approved framework to define discipline-specific purpose, evidence, professional authority, validation, contestability, and remedy.
GOVERN
Use the author-approved framework for organisational inventory, ownership, risk classification, approval, procurement, monitoring, incidents, and lifecycle governance.
FUTURES
Use the author-approved framework to address emerging capabilities, uncertainty, scenarios, adaptive safeguards, revalidation, rollback, and retirement.
HUMAN
Use the author-approved integration framework to ensure all human dimensions—purpose, authority, capability, relationships, participation, alternatives, safeguards, evidence, reflection, and learning—are coherently addressed.
Responsible-use boundaries, accessibility, and support
Boundaries
- Do not upload real organisational, professional, personal, proprietary, or culturally governed information.
- Do not require live agentic actions, connected tools, or transactional permissions.
- Do not represent AI-generated governance analysis as a binding organisational decision without authorised review.
- Do not treat disclosure as permission, verification, or validation.
- Preserve human authority, appeal, remedy, and stop authority.
Support and escalation
- Contact the course coordinator for capstone stream selection and proposal scope.
- Use library, accessibility, privacy, security, copyright, or professional support as appropriate.
- Seek qualified assistance when health, legal, financial, safety, or professional boundaries arise.
- Use supplied alternatives whenever live AI or real-world information would be inappropriate.