Explore Humber guidelines on the ethical use of AI in education, including academic integrity policies, responsible AI practices, and data privacy considerations.
Note: This is a living document. Humber will continue to adapt this resource as new topics and issues arise due to the rapidly changing landscape of Generative Artificial Intelligence (GAI).
Humber’s Academic Regulation 17.0 (Academic Misconduct) identifies the unauthorized use of artificial intelligence applications and the failure to fully disclose AI use in graded academic work as forms of academic dishonesty.
Humber is committed to ensuring a high-quality academic learning experience, building student success through excellence in teaching and learning, and fostering inclusive environments that promote creativity, innovation, and belonging. This commitment extends to the ethical integration of AI tools in teaching and learning, ensuring that their use aligns with Humber’s values and upholds the integrity of its educational pursuits.
Before exploring the content, take a moment to complete a short quiz to assess your existing knowledge of Humber’s commitment to responsible AI use in teaching and learning. You can choose to complete the interactive quiz or download a PDF version with an answer key.
Interactive Quiz
Alternative PDF Format
Click Test Your Knowledge: Academic Integrity, Ethics and GenAI to download the PDF copy of the quiz.
The integration of AI into teaching and learning provides exciting opportunities to enhance creativity, productivity, and educational outcomes. However, it also requires a steadfast commitment to academic integrity to ensure that AI use supports rather than undermines Humber’s mission to develop highly skilled, adaptable citizens who lead with integrity.
Academic integrity develops critical skills like research, critical thinking, and communication, essential for professional success. In an AI-driven world, using AI tools responsibly ensures they enhance learning without replacing genuine effort. By accrediting sources and upholding ethical standards, you build the adaptability and trustworthiness needed to thrive in both academic and professional environments.
As AI becomes more integrated into education, it is equally important to consider its ethical implications, data privacy concerns, and compliance with regulations like FIPPA.
It is essential to consider ethics, data privacy, and security to protect students and uphold institutional integrity. Ethical use of AI in educational setting requires:
By proactively addressing these ethical, legal, and privacy concerns, educators can harness AI's potential while maintaining trust, compliance, and responsible innovation in the classroom.
New artificial intelligence (AI) tools and large language models (LLM) (e.g., ChatGPT, Google Bard, Bing Chat) interact in a conversational way and have many uses, but they also present ethical challenges. Some key issues for educators related to AI-generated information are:
These ethical concerns highlight the need for transparency, critical evaluation of AI-generated content, and proper citation when using AI in academic work.
Maintaining student privacy is essential. Instructors should carefully check technology signup requirements and terms of use before adopting AI tools in the classroom. To maintain privacy (and meet FIPPA requirements) instructors must ensure AI tools do not collect student data (e.g., phone number, email address, age) without proper safeguards. If an AI tool does not meet privacy requirements, its use must be voluntary, and alternatives should be provided to students. By prioritizing student privacy and compliance, instructors can integrate AI responsibly while protecting learners.
Generative AI companies collect personal information from the time that a user visits the site to their completion of using their services. At minimum, account data includes enough information to associate the individual with their account to login (this is usually name and email address). Sometimes setting up accounts includes providing additional demographic data that is either optional or mandatory. For services that require payment, the transaction directly links the user's payment details to their account and activity, making it difficult to remain anonymous or use an alias. These data collection practices raise privacy concerns, as stored information could be misused, shared, or accessed without authorization. By understanding these risks, instructors can make informed decisions when incorporating AI into teaching and learning while ensuring that privacy remains a top priority.
This work was adapted from Durham College for the Humber context, and is licensed under a Creative Commons
Attribution-NonCommercial-ShareAlike 4.0 International License.
The intention of these guiding resources is to offer a starting point for instructors to consider the potential uses of generative AI in teaching and learning prior to the start of teaching courses at Humber Polytechnic. More importantly they provide an opportunity to think about and reflect on how we teach. The resources below will help guide you in this new era of teaching with AI. Explore key considerations and strategies to enhance your teaching practice and support effective student learning.