Ethical Use and Consideration
Privacy, Copyright, Indigenous Knowledge and Inclusive Learning
On this page:
1.
Respecting Indigenous Knowledge and Cultural Protocols
We recognize the importance of upholding Indigenous rights, data sovereignty, and cultural integrity. GenAI tools can risk misrepresenting, misappropriating, or exploiting Indigenous knowledge systems, especially when trained on scraped internet data without appropriate context, permission, or protocols. To ensure ethical AI practices:
Engage Indigenous voices in AI policy development and implementation.
Avoid using GenAI tools to generate or replicate Indigenous stories, designs, or cultural content without explicit permission.
Acknowledge and respect the First Nations Principles of OCAP (Ownership, Control, Access, and Possession) in any use of data or knowledge related to Indigenous communities.
Commitment to Equity, Diversity, and Inclusion
Generative AI (GenAI) use must reflect our commitment to equity, diversity, and inclusion (EDI). Ethical AI practices help create safe, inclusive learning environments and guard against reinforcing systemic bias or discrimination. AI tools may draw on datasets that contain limited or unbalanced perspectives, so instructors and students are encouraged to critically assess outputs and seek diverse viewpoints, while being mindful that access to technology and representation in digital spaces are uneven.
These barriers can be especially significant for Indigenous peoples, racialized communities, women, and people with disabilities. Embedding an EDI lens throughout AI use—from course design to data selection—strengthens our commitment to championing equity, diversity, and inclusion across all teaching, learning, and workplace practices.
Privacy and Data Ethics
Generative AI (GenAI) tools rely on vast amounts of data—often collected without transparency. It’s important to advocate for the ethical handling of personal and sensitive information:
Do not input proprietary, personal, or confidential information into AI tools.
Understand that GenAI systems are often "black boxes"—users typically don’t know how data is used, stored, or shared.
Consider risks of data theft, re-identification, and unauthorized profiling.
Prioritize student and staff awareness of data privacy rights and digital safety practices when using GenAI.
Copyright Infringement and Intellectual Property
Generative AI (GenAI) tools learn by analyzing large amounts of information—some of which may be copyrighted. This means the content they produce could accidentally break copyright rules. It’s important to understand how to use it responsibly, including what you can share and how to use its outputs without violating copyright.
Use tools trained on open or public domain data whenever possible to reduce the risk of copyright infringement.
Cite and acknowledge AI-generated content when it is used to support learning or research.
Do not use GenAI to replicate, modify, or transform copyrighted material unless you have the appropriate permissions or licenses.
Understand Creative Commons licenses and how they apply to both source content and AI-generated outputs.
Discuss intellectual property rights with students when assigning creative projects involving GenAI tools.
Furthermore, uploading or submitting content to generative AI platforms—such as asking them to summarize an article or edit text—may constitute copyright infringement if you do not have the legal right to share that material. This includes:
Content or materials from library-licensed databases (e.g., journal articles, eBooks).
Course materials that are protected by copyright.
Student work submitted without their explicit consent.
To avoid copyright violations:
Do not upload third-party content unless it is openly licensed, in the public domain, or you have explicit permission to use it.
Always review the terms of service and privacy policies of any GenAI platform you use.
Respect copyright to protect intellectual property and support ethical academic practices.