Artificial Intelligence (Ai) Governance and Responsible Use Policy

Melbourne School of Theology (MST) and Eastern College Australia (Eastern) recognise that Artificial Intelligence (AI), including Generative Artificial Intelligence (GenAI), presents significant opportunities and challenges for higher education, theological formation, research, ministry preparation, and organisational operations.

This policy establishes the principles, governance framework, responsibilities, safeguards, and acceptable use requirements for AI across MST and Eastern.

The objectives of this policy are to:

• Promote responsible, ethical, and transparent use of AI
• Protect academic integrity and assessment authenticity
• Safeguard personal, pastoral, organisational, and research information
• Ensure compliance with regulatory, accreditation, legal, and contractual obligations
• Support innovation, learning, teaching, research, ministry formation, and operational effectiveness
• Maintain confidence in the quality, integrity, and reputation of MST and Eastern.

This policy applies to any person acting on behalf of MST or Eastern, whether employed, contracted, or volunteering (collectively referred to in this policy as “staff”). Academic Staff have additional responsibilities under this policy.

This policy applies to:

• Institutionally approved AI systems
• Personally accessed AI systems used for institutional purposes
• AI-generated text, images, audio, video, code, analytics, and other outputs.

Student use of AI is governed by various College policies, including Academic Integrity Policy, Assessment and Grading Policy, Student Code of Conduct and Academic Responsibilities, and any unit-specific or task-specific instructions.

Melbourne School of Theology

MST delivers accredited awards through the Australian University of Theology (AUT).

Accordingly, AI use must be consistent with:

• AUT Academic Regulations
• AUT Artificial Intelligence documentation (forthcoming as of August, 2026)
• AUT Academic Integrity requirements
• Relevant quality assurance requirements
• Applicable provisions of the Higher Education Standards Framework (Threshold Standards) 2021, and subsequent amendments or revisions
• And relevant legislation including Privacy, child safety, gender equality, etc.
• Regulatory oversight such as the Office of Australia Information Commission (OAIC) and eSafety Commission.

Eastern College Australia

Eastern College Australia operates under the regulatory oversight of the Tertiary Education Quality and Standards Agency (TEQSA).

AI use must be consistent with:

• TEQSA guidance
• Institutional academic governance requirements
• Higher Education Standards Framework (Threshold Standards) 2021
• And relevant legislation including Privacy, child safety, gender equality, etc.
• Regulatory oversight such as the Office of Australia Information Commission (OAIC) and eSafety Commission.

Principle of Higher Standard

Where accreditation, regulatory, contractual, or institutional requirements differ, the more stringent requirement applies.

Artificial Intelligence (AI)

The OECD defines an AI system as “a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment.”  (OECD 2024).

Generative Artificial Intelligence (GenAI)

AI systems capable of generating text, images, audio, video, software code, data analysis, or other content in response to user prompts.

Approved AI Tool

An AI system formally approved for institutional use by MST or Eastern, and/or by government agencies and regulators.

Material AI Use

Use of AI that substantially contributes to the creation, modification, analysis, or communication of content.

Sensitive Information

Information requiring heightened protection, including:

• Student records
• Customer Relationship Management and/or Student Management System
• Counselling records
• Pastoral information
• Assessment information
• Human resources information
• Confidential research data
• Disciplinary information
• Financial information
• Donor and stakeholder information
• Legal information

Truth-Oriented Use

AI outputs must be evaluated against reliable evidence, recognised scholarship, institutional standards, and, where relevant, Scripture and theological scholarship.

Human Responsibility

AI may assist human work but does not replace human judgement, discernment, scholarship, leadership, pastoral care, or accountability.

Academic Integrity

The use of AI must support rather than undermine authentic learning, scholarship, and assessment.

Privacy and Stewardship

Information entrusted to MST and Eastern must be protected and managed responsibly.

Transparency

Material AI use should be disclosed where appropriate and required.

Theological Discernment

AI must not function as a theological authority.

Theological claims generated by AI must be critically evaluated against:

• Scripture
• Sound scholarship
• Institutional statements of faith
• Relevant disciplinary standards

Ethical and Lawful Use

AI must be used in ways that are lawful, ethical, respectful, and consistent with the mission, values, and Christian ethos of MST and Eastern.

Institutional Position on AI

MST and Eastern recognise AI as an increasingly important technology affecting higher education, ministry, research, administration, and society. AI may assist our work, but it must never replace our responsibility for truth, pastoral care, academic integrity, scholarship, or wise judgement.

The institutions encourage thoughtful and responsible experimentation with AI where such use:

• Supports research
• Enables innovation
• Improves accessibility
• Enhances learning and teaching
• Improves operational effectiveness

However:

• Responsibility remains with the individual using AI
• AI outputs must not be accepted uncritically
• AI outputs are not inherently accurate
• AI outputs are not authoritative.

AI may assist our work, but it must never replace our responsibility for truth, academic integrity, pastoral care, scholarship, or wise judgement.

Approved AI Tools

Only institutionally approved AI tools may be used for institutional purposes involving institutional information.

Approval considerations include, but are not limited to:

• Risk profile
• Security controls
• Privacy protections
• Cost and sustainability
• Regulatory compliance
• Contractual protections
• Data handling practices
• Organisational administration capabilities.

(The Approved AI Tools Register is maintained in Appendix A)

Staff Operational Use

Staff may use approved AI tools for:

• Project planning
• Preparing reports
• Marketing content
• Meeting summaries
• Policy development
• Drafting correspondence
• Administrative workflows
• Data analysis of non-sensitive information.

All formal outputs must be reviewed by an appropriately authorised staff member before formal organisational use.

Approved users remain accountable for:

• Tone
• Accuracy
• Compliance
• Appropriateness (impact assessment)
• Final implementation.

AI-generated content must not be represented as official institutional positions without appropriate review and editing.

Academic Staff and Faculty Use

Academic staff may use AI to support initial (but not final):

• Learning activity development
• Research planning
• Assessment design
• Teaching resources
• Academic administration
• Curriculum development prior to editing and critical reflection

Academic staff remain responsible for:

• Student learning
• Scholarly quality
• Learning outcomes
• Assessment integrity
• Theological accuracy

AI must not be used as a substitute for scholarly expertise or academic judgement.

Faculty must ensure students are provided meaningful opportunities to demonstrate achievement of learning outcomes independently of inappropriate AI assistance.

Unit-level clarity

Lecturers and unit coordinators should provide clear guidance in unit guides and assessment briefs regarding:

• Whether AI use is permitted
• Whether AI use must be disclosed
• How AI use should be cited or acknowledged
• Which uses are permitted, restricted, or prohibited
• Whether particular assessments prohibit AI assistance.

Assessment Authenticity and Learning Outcomes

MST and Eastern are committed to ensuring that assessment practices validly and reliably demonstrate student achievement of required learning outcomes.

Assessment design, moderation, academic integrity processes and quality assurance methods must recognise and transcend the pervasive disruption from the use of AI.

Assessment Design

Assessment design should, where appropriate:

• Include clear AI-use instructions
• Require engagement with prescribed course materials
• Require students to connect learning to ministry, practice, placement, community, or context where relevant.
• Require students to demonstrate understanding, reasoning, interpretation, application, and reflection
• Include tasks that are difficult to complete through unauthorised AI use alone
• Use oral, practical, reflective, contextual, staged, supervised, or process-based components where appropriate

Authentic Demonstration of Learning

Assessment should enable academic staff to make reasonable judgements about whether the submitted work reflects the student’s own achievement of learning outcomes.

Where concerns arise, Academic Integrity Officers may use appropriate academic integrity processes, including:

• Conducting oral follow-up
• Reviewing drafting history or process evidence
• Comparing work against previous submissions
• Requesting explanation of sources or argument
• Applying relevant academic misconduct procedures.

AI detection tools must not be treated as conclusive evidence on their own.

Moderation and Quality Assurance

Academic governance processes should periodically review:

• Whether academic staff require further training
• The impact of AI on assessment integrity
• Whether students receive adequate guidance
• Whether assessment types remain fit for purpose
• Whether institutional academic integrity controls remain effective.

Research Use

AI may support staff research activities, provided such use is ethical, transparent, accurate, and compliant with applicable requirements.

Permitted Research Uses

Researchers may use approved AI tools to assist with:

• Brainstorming research questions.
• Structuring literature reviews.
• Summarising publicly available sources.
• Improving clarity of expression.
• Planning research workflows.
• Developing coding frameworks.
• Analysing non-sensitive or de-identified data where appropriate.
• Preparing draft abstracts, outlines, or presentations.

Researcher Responsibilities

Researchers remain responsible for:

• Research integrity.
• Accuracy of claims.
• Correct attribution.
• Verification of sources.
• Protection of research data.
• Compliance with ethics approvals.
• Compliance with publisher requirements.
• Disclosure of AI use where required.

Prohibited Research Uses

Researchers must not:

• Rely on AI-generated citations without verification
• Use AI to fabricate data, quotations, sources, or findings
• Use AI in ways that breach research ethics approval conditions
• Present AI-generated analysis as human interpretation without review
• Upload identifiable participant data into AI systems unless specifically approved
• Upload confidential, unpublished, or restricted research material into unapproved AI tools.

Publications and Disclosure

Researchers should comply with journal, publisher, conference, ethics committee, and institutional requirements regarding AI use.

Where AI materially contributes to a research output, disclosure should be made in accordance with relevant disciplinary and publication standards.

Data Protection, Privacy and Confidentiality

AI use must comply with privacy, confidentiality, cybersecurity, contractual, legal, pastoral, and institutional obligations.

Data Minimisation

Users must only provide AI tools with the minimum information necessary for the task.

Where possible, users should:

• Remove names
• Use aggregated data
• Use de-identified data
• Remove identifying details
• Use hypothetical examples
• Avoid uploading full documents where excerpts are sufficient.

Sensitive Information

Sensitive information must not be entered into AI systems unless explicitly authorised through approved institutional arrangements.

Sensitive information includes:

• Student records
• Assessment results
• Unpublished research data
• Personally identifiable information
• Student support information
• Pastoral care information
• Counselling information
• Placement information
• Legal matters
• HR information
• Disciplinary records
• Donor information
• Financial information
• Board or governance papers
• Confidential ministry, church, or community information.

Student and Pastoral Information

Student and pastoral information require particular care because it may involve personal, sensitive, spiritual, family, ministry, wellbeing, or vulnerable-person information.

Users must not enter identifiable student, pastoral, counselling, or ministry-care information into AI tools unless specifically approved or instructed in writing by an authorised staff or faculty representative.

Confidential Institutional Information

Users must not enter confidential institutional information into unapproved AI systems. See Appendix A for approved systems.

This includes:

• Contracts
• Legal advice
• Staff matters
• Risk registers
• Board papers
• Donor information
• Financial forecasts
• Sensitive partnership matters
• Strategic plans not yet public
• Accreditation submissions prior to approval.

AI-Generated Images, Video, Audio and Media

AI-generated media may be used for teaching, learning, internal presentations, communications, marketing, and concept development where appropriate.

All AI-generated media must be critically reviewed against institutional guidance (e.g. policy) before use.

Permitted Uses

Permitted uses may include:

• Marketing drafts
• Concept diagrams
• Draft design concepts
• Accessibility supports
• Teaching illustrations
• Communications assets
• Internal presentation visuals.

Conditions of Use

AI-generated media must:

• Be truthful and not misleading
• Be reviewed by an appropriate human author
• Align with Christian values and institutional ethos
• Comply with branding and communications standards
• Respect cultural, theological, and pastoral sensitivities
• Be disclosed where it could reasonably be interpreted as real.

Prohibited Media Uses

Users must not:

• Create deepfakes or impersonations
• Create misleading or deceptive imagery
• Generate synthetic representations of real people without consent
• Misrepresent historical, theological, ministry, or institutional events
• Use AI-generated media in major public campaigns without approval
• Produce content that is sexually explicit, exploitative, hateful, abusive, or demeaning
• Generate media involving vulnerable persons in inappropriate or misleading ways

High-Risk Media

The following require prior approval from relevant leadership and Communications:

• Fundraising campaigns
• Major public campaigns
• Synthetic images of real or recognisable people
• Content likely to be widely distributed externally
• Sensitive theological, ethical, cultural, or political content
• Depictions of worship, sacraments, pastoral care, trauma, or vulnerable communities

Effective AI governance requires shared responsibility across institutional leadership, academic governance, technology governance, staff, faculty, and students.

Board

The Board provides strategic oversight of institutional risk, compliance, mission alignment, and governance.

Executive Leadership Teams

The Executive Leadership Team is responsible for:

• Allocation of resources
• Approval of major AI initiatives
• Oversight of AI-related organisational risk
• Institutional implementation of this policy
• Ensuring alignment with institutional mission and strategy.

Academic Governance Bodies

Academic governance bodies are responsible for oversight of:

• Research integrity
• Academic integrity
• Learning outcomes
• Curriculum implications
• Assessment authenticity
• Academic quality assurance
• Student-facing academic guidance.

Tech Team / IT

Tech Team is responsible for:

• Supporting incident response
• Advising on cybersecurity risks
• Supporting training and awareness
• Monitoring emerging technology risks
• Maintaining the Approved AI Tools Register
• Managing access controls where appropriate
• Assessing AI tools for privacy, security, and compliance.

Heads of Department and Managers

Heads of Department and managers are responsible for:

• Identifying training needs
• Escalating concerns or breaches
• Supporting compliant AI use within their teams
• Ensuring staff understand relevant requirements
• Ensuring AI use is appropriate to role and context.

Staff

Staff are responsible for:

• Reviewing and verifying AI outputs
• Reporting suspected breaches or risks
• Using AI in accordance with this policy
• Disclosing material AI use where required
• Protecting institutional and personal information
• Ensuring AI does not replace professional responsibility.

Monitoring and Controls

MST and Eastern Tech Team, Academic Integrity staff, or Leadership teams may implement reasonable technical, administrative, and governance controls to manage AI-related risks.

These may include:

• Audit logs
• Staff training
• Web filtering
• Access restrictions
• Endpoint protection
• Approved tool management
• Data loss prevention controls
• Academic integrity processes.

Monitoring must be proportionate, lawful, and consistent with privacy obligations and institutional policies.

Reporting AI-Related Incidents

Users must promptly report suspected AI-related incidents, including:

• Suspected data leakage
• Inappropriate AI-generated media
• Academic misconduct involving AI
• Security or privacy concerns involving AI platforms
• Use of AI to produce misleading institutional content
• AI-generated misinformation used in official contexts
• Sensitive information entered into an unauthorised AI tool.

Reports should be made through the relevant manager, academic leader, or institutional incident reporting process.

Incident Response

AI-related incidents may require involvement from:

• Communications
• Human Resources
• Executive Leadership
• Academic leadership
• Student administration
• Privacy or legal advisers
• Research or ethics committees.

The response should be proportionate to the risk, harm, intent, and institutional impact.

Enforcement

Breaches of this policy may be managed under relevant frameworks, including:

• Staff conduct processes
• Student conduct processes
• Academic integrity processes
• Research misconduct processes.
• Privacy breach response procedures
• Cybersecurity incident response procedures
• Contractual or contractor management processes.

Review and Continuous Improvement

This policy will be reviewed annually, or earlier where required due to:

• Regulatory change
• Material AI-related incident/s
• Accreditation requirements
• Significant technological development
• Changes to institutional systems or strategy
• Updated guidance from AUT, TEQSA, or relevant government agencies.

The Approved AI Tools Register and associated controls should be reviewed at least every six months.

MST and Eastern recognise that AI governance is an evolving area. This policy should therefore be implemented with agility, firmness and humility: establishing clear boundaries while continuing to learn, adapt, and steward emerging technologies wisely.

The Approved AI Tools Register identifies AI tools approved for institutional use.

The Register should be maintained by and reviewed at least every six months.

A1. Approval Categories

AI tools may be classified as:

• Approved for general institutional use.
• Approved for limited use.
• Approved for teaching and learning use.
• Approved for research support.
• Approved for high-confidentiality use.
• Not approved.

A2. Initial Approved Tools

The following tools may be considered for inclusion, subject to institutional review:

A3. Tool Approval Criteria

Before approval, tools should be assessed for:

• Privacy protections.
• Data retention settings.
• Whether user data is used for model training.
• Security controls.
• Enterprise administration.
• Single sign-on availability.
• Audit and access controls.
• Contractual terms.
• Data residency.
• Vendor reputation.
• Regulatory compliance.
• Cost.
• Supportability.
• Risk profile.

End of Appendix A.

Also see MST Eastern AI Governance Policy Appendix suite