Principles for ethical AI governance practice
This Code outlines expectations that guide how IIAIG-related learning, certification and AI governance themes are approached. It is intended to support responsible, transparent and accountable professional behaviour.
- Provide a shared, high-level reference for ethical behaviour related to IIAIG’s governance themes.
- Set expectations for how learners, educators and organizations engage with IIAIG-aligned content.
- Emphasize responsibility, fairness and integrity when AI systems are discussed, designed or overseen.
Scope and intended use of this code
This Code is a high-level reference for ethical conduct in IIAIG-related learning and AI governance themes. It is not a legal document or regulatory instrument, but a guide that supports responsible behaviour for individuals and organizations engaging with IIAIG curricula and concepts.
Who this code is for
The Code is a reference for:
- Individuals pursuing IIAIG-aligned learning or certifications.
- Educators and academic partners working with IIAIG themes.
- Organizations using IIAIG concepts to inform governance practice.
How it should be read
The Code is conceptual and sits alongside:
- Organizational codes of conduct and HR policies.
- Applicable laws, regulations and institutional requirements.
- IIAIG-aligned documents such as the governance & ethics charter and exam policies.
Core principles in this code
These principles summarize how ethical behaviour is framed in the context of IIAIG’s AI governance themes. They outline orientation, not exhaustive rules.
Integrity
Approach AI governance themes honestly and accurately. Represent skills, experience and contributions truthfully.
Respect
Engage respectfully with learners, educators and colleagues, especially where governance themes involve sensitive societal impact.
Fairness
Consider fairness and non-discrimination where AI may influence decisions about individuals or groups.
Responsibility
Act with care when AI themes intersect with real systems. Understand how governance framing influences risk and oversight.
Expectations for individuals
Individuals engaging with IIAIG-aligned learning or professional contexts are expected to demonstrate conduct consistent with the principles above.
Academic honesty
Approach assessments honestly. Do not misrepresent work done by others as your own, and follow institutional guidelines.
Respect for context
When applying governance concepts in an institution or workplace, respect internal codes of conduct, confidentiality obligations and applicable laws or policies.
Constructive engagement
Engage constructively, accurately and respectfully in discussions, particularly where multidisciplinary perspectives are involved.
Expectations for academic and organizational partners
Partners engaging with IIAIG themes should reflect these principles in their governance, training and oversight conversations.
Alignment with institutional values
Institutions working with IIAIG-aligned content should ensure AI governance themes remain consistent with their academic standards and ethics policies.
Support for responsible use
Organizations using IIAIG concepts should ensure that their internal governance structures and documentation support responsible AI use.
Local accountability
Responsibility for AI-enabled systems remains with the institutions that design or deploy them. The Code is a reference—not a transfer of responsibility.
Raising concerns about conduct
Concerns should be raised through the appropriate channels in the institution where conduct or governance issues arise—such as ethics, compliance or HR processes.
How this Code relates to other IIAIG documents
This Code forms part of a broader group of documents that describe how IIAIG approaches AI governance themes, certifications and learning.
Governance & ethics charter
Provides an overview of IIAIG’s governance model and how ethical perspectives are brought into conceptual discussions.
View charterExam & certification policies
Exam policies describe high-level assessment rules and certification expectations, complementing this Code.
View exam policiesAI governance standards & guidance
As AI governance guidance and practice notes develop, they provide examples of how these ethical themes may connect with day-to-day governance activities.
Explore standards