Fairness and inclusion
Use FAIRER to examine representation, assumptions, accessibility, unequal impact, participation, contestability, and remedy.
Module overview
Module 3 examines the ethical, legal, social, privacy, security, fairness, accessibility, authorship, and academic-integrity dimensions of generative AI. Rather than treating responsibility as a property of the model alone, you will evaluate the complete workflow, including human purpose, information use, sources, prompts, outputs, decisions, affected people, correction, contestability, and remedy.
Privacy and security
Use PROTECT to classify information, minimize disclosure, control permissions, and respond to exposure or misuse.
Authorship and integrity
Use CREATE to distinguish permission, attribution, authorship, academic integrity, and AI-use disclosure.
Module principle: Responsible AI use requires evaluating the complete human-AI workflow. A technically capable system does not remove human duties concerning fairness, information, source rights, decisions, correction, and accountability.
Module learning outcomes
By the end of Module 3, you should be able to:
- Distinguish equality, equity, fairness, inclusion, accessibility, representation, stereotype, proxy variable, and disparate impact.
- Identify stakeholders, affected non-users, beneficiaries, risk bearers, and people requiring accessible participation or remedy.
- Apply the author-approved FAIRER framework to a bounded AI-supported workflow.
- Classify information provisionally as public, internal, personal, sensitive, confidential, proprietary, privileged, security-sensitive, or culturally governed.
- Apply purpose limitation, data minimization, source control, and least privilege.
- Recognize privacy, security, retention, memory, secondary-use, and prompt-injection concerns.
- Apply the author-approved PROTECT framework to information and permission boundaries.
- Distinguish copyright permission, licence compliance, attribution, authorship, plagiarism, academic integrity, and AI-use disclosure.
- Apply the author-approved CREATE framework to source rights, human contribution, attribution, and disclosure.
- Design correction, contestability, escalation, redress, remedy, and stop conditions.
Module 3 units
Bias, Fairness, and Inclusion
Examine representation, stereotypes, proxy variables, accessibility, intersectionality, disparate impact, participation, and remedy through FAIRER.
Privacy, Security, and Data Protection
Classify information, minimize disclosure, control permissions, recognize prompt injection, and establish incident and stop conditions through PROTECT.
Copyright, Authorship, Attribution, and Academic Integrity
Distinguish permission, licence, attribution, human authorship, plagiarism, acceptable assistance, documentation, and disclosure through CREATE.
Implementation note: replace placeholder anchors with the corresponding Moodle activity or section URLs.
Embedded Module 3 study guide
Use this two-week plan unless the official Moodle schedule specifies different dates. Begin Assignment 3 during Unit 7 rather than waiting until the end of the module.
Week 5: Unit 7 and the beginning of Unit 8
Recommended: 8–10 hours- Retrieve Module 2 concepts.
Review PCAFE-V, SCOPE, PARTNER, information minimization, human authority, and stopping. - Read Chapter 9 and complete Unit 7.
Focus on representation, stereotypes, accessibility, intersectionality, proxy variables, and unequal effects. - Complete a comparative bias audit.
Compare synthetic outputs for assumptions, tone, detail, omissions, and recommendations without inferring real identities. - Apply FAIRER.
Identify affected people, access barriers, participation needs, contestability, and possible remedy. - Select the Assignment 3 case.
Choose a bounded synthetic, public, supplied, or authorized case with sufficient evidence and stakeholder significance. - Begin Chapter 10.
Classify information and identify purpose limitation, minimization, retention, and permission questions.
Evidence to retain
- Comparative bias audit
- FAIRER analysis
- Stakeholder and affected-non-user map
- Accessibility questions
- Preliminary Assignment 3 case and scope
- Assignment 1 reflection notes
Week 6: Complete Units 8 and 9
Recommended: 8–10 hours- Complete Unit 8.
Build an information inventory, apply minimization, evaluate permissions, and design an incident response. - Apply PROTECT.
Document purpose, information authority, retention questions, security boundaries, escalation, and stopping. - Read Chapter 11 and complete Unit 9.
Distinguish source availability from permission and attribution from authorship. - Draft an AI-use disclosure.
Record the system, purpose, stages supported, retained material, verification, revisions, and final human responsibility. - Apply CREATE and complete Assignment 3.
Integrate ethics, fairness, information governance, authorship, contestability, and remedy. - Consolidate and transition.
Complete the module check and prepare for hallucination, evidence, learning, and research in Module 4.
Evidence to retain
- Information classification and minimized prompt
- PROTECT analysis
- Permission-versus-attribution analysis
- CREATE analysis
- AI-use disclosure draft
- Assignment 3 final self-review
- Updated Assignment 1 reflection
Show the recommended responsible-use review cycle
- Define the legitimate purpose and affected people.
- Identify assumptions, representation, access, and possible unequal effects.
- Inventory and minimize information.
- Confirm source rights, permissions, and authority.
- Define bounded human and AI roles.
- Verify claims and document contributions.
- Provide correction, contestability, and remedy.
- Disclose material AI use.
- Escalate or stop when authority, evidence, rights, or safeguards are inadequate.
Assessment milestones in Module 3
Assignment 3: Responsible AI Case Analysis
Weight: 20%
Start: Select and bound the case during Unit 7, Week 5
Develop: Across Units 7–9
Recommended submission: After Module 3, at the end of Week 6
Official Moodle due date and time: ____________________
Assignment 1: Journal continues
Record how fairness, accessibility, privacy, source rights, authorship, integrity, contestability, and remedy changed your analysis and personal boundaries.
Recommended final submission: End of Module 6, Week 11
Official Moodle due date and time: ____________________
Choose a manageable case: A focused workflow with identifiable stakeholders, evidence, information, decisions, and remedies will support deeper analysis than a broad topic such as “AI ethics.”
Show the Assignment 3 working-record checklist
- Case and legitimate purpose
- Stakeholders and affected non-users
- AI and human roles
- Fairness and accessibility analysis
- Information inventory and authority
- Source rights, authorship, and disclosure
- Evidence and verification
- Contestability, correction, and remedy
- Escalation and stop conditions
- Residual uncertainty and qualified recommendation
Core learning activities
| Activity | Purpose | Product to retain | Connection |
|---|---|---|---|
| Ethical dilemma analysis | Identify stakeholders, values, responsibilities, alternatives, and remedies. | Structured case analysis | Assignments 1 and 3 |
| Comparative bias audit | Compare assumptions, representation, tone, detail, and recommendations. | Audit table | Assignment 3 |
| Information classification | Classify public, internal, personal, sensitive, confidential, proprietary, and culturally governed information. | Information inventory | Assignments 3, 4, and 6 |
| Privacy-preserving redesign | Remove unnecessary identifying details while preserving the legitimate purpose. | Initial and minimized prompt | Assignments 2, 3, and 4 |
| Permission versus attribution | Distinguish permission, licence compliance, attribution, disclosure, and integrity. | Rights analysis | Assignments 3, 4, and 6 |
| AI-use disclosure workshop | Document AI contributions, verification, revision, and final responsibility. | Disclosure draft | All applicable assignments |
| Case-selection activity | Bound an appropriate case with sufficient evidence and manageable scope. | Case brief | Assignment 3 |
Live AI and non-platform options
Option A: Approved AI
Use an approved system only with synthetic, public, supplied, or explicitly authorized information.
Option B: Supplied outputs
Use supplied prompts, outputs, information inventories, rights scenarios, and disclosure records.
Option C: Non-AI analysis
Complete the same ethical, information, rights, and accountability analysis without operating an AI system.
All options must assess the same human judgment and responsible-use outcomes.
Frameworks introduced in Module 3
FAIRERPROTECTCREATEAccessibilityContestabilityRedressRemedy
FAIRER
Use the exact author-approved expansion in the textbook and course materials. Apply it to fairness, inclusion, accessibility, stakeholder impact, contestability, and remedy.
PROTECT
Use the author-approved framework for purpose limitation, information protection, permissions, retention, security, incidents, and stopping.
CREATE
Use the author-approved framework for copyright, permission, human authorship, attribution, academic integrity, documentation, and disclosure.
Responsible-use boundaries, accessibility, and support
Boundaries
- Do not upload real student, employee, client, patient, applicant, research, legal, financial, or confidential records.
- Do not infer protected characteristics, intent, credibility, diagnosis, or risk from limited information.
- Do not assume public access creates permission.
- Do not treat disclosure as permission or verification.
- Do not permit AI to make consequential decisions or take external action.
Support and escalation
- Contact the course coordinator for assignment and permitted-use questions.
- Use library or copyright support for source and licence questions.
- Contact privacy, security, accessibility, ethics, professional, or community authorities where applicable.
- Use supplied alternatives whenever live AI use is unsuitable or unwanted.