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Generative Artificial Intelligence (GAI) Overview

Explore this page to learn the basics of GAI, its applications in teaching and learning, its limitations and risks, and Humber’s stance on its use.

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).

Overview

Artificial intelligence (AI) systems have become powerful tools that we use regularly in our professional and personal lives. Spelling and grammar checkers, auto correct with predictive language cues as we text, automatic live captions, or written transcriptions when we livestream are just some of the ways in which artificial intelligence makes our lives and our work faster and easier.

Emerging generative AI (GAI) tools like ChatGPT offer groundbreaking opportunities to harness technology in new and exciting ways. In education, these tools present new possibilities that are challenging the status quo and driving teaching and learning innovation. Given the capabilities of AI applications, we also need to set clear guidelines on how to use AI responsibly, ethically, and productively in academic settings, both to uphold the principles of academic integrity and to prepare learners for AI integration in their future careers.

Test Your Knowledge: Generative AI and Humber GAI Guidelines

Before exploring the content, take a moment to complete this short quiz. This will help you assess your existing knowledge of Generative AI (GAI) and Humber GAI Guidelines.

What Is Generative AI (GAI)?

Generative AI (GAI) is a specialized area within the field of Artificial Intelligence (AI) that incorporates Large Language Models (LLM) and employs algorithms that can replicate human generated text, code, music, images, and multi-media by processing extensive datasets and then predicting an expected output based on human prompts. Tools that employ Generative AI, such as ChatGPT, are becoming increasingly accessible and have already begun to profoundly influence teaching, learning, educational methods, and content.

Humber Polytechnic’s Statement on Generative Artificial Intelligence (GAI)

As GAI continues to evolve, it is essential to establish clear guidelines and best practices to ensure responsible and effective use in academic settings. Understanding Humber Polytechnic’s Statement on Generative Artificial Intelligence is crucial for faculty and learners as it provides a framework for ethical use, academic integrity, and discipline-specific adaptation.

As a community of higher learning, Humber:

  1. Embraces the integration of AI generative tools in ethical, equitable, and constructive ways in support of teaching and learning.
  2. Commits to supporting students to develop digital fluency skills to participate effectively, responsibly, and ethically in AI-enhanced workplaces.
  3. Recognizes that integration of AI will vary across disciplines and will require context-responsive approaches.
  4. Acknowledges that professors have discretion to decide how AI can be applied in a particular course in ways that enhance student learning. This involves the provision of explicit guidance for students in assessment and assignment instructions on how AI tools are to be used and cited.
  5. Contends that un-cited and/or unauthorized use of AI in assessments and assignments constitutes academic misconduct as defined in Humber’s Academic Regulations.
  6. Commits to polytechnic-wide consultation to develop supports for students and professors in the use of AI that is grounded in research/evidence-based best practices.
  7. Will continue to adapt and innovate in response to the rapid changes we will face as artificial intelligence continues to evolve.

How Does GAI Work?

Watch the video below to learn how GAI creates text, images, and more using prompts. It highlights GAI’s potential for learning and creativity while emphasizing responsible use and the importance of checking for accuracy of generated content.

What Can GAI Do?

GAI can generate, improve, and personalize a wide range of content to support both instructors and learners. The list below highlights just a few of its applications. However, users should verify content accuracy as GAI-generated information may be inaccurate and biased.

In 2024, Humber Polytechnic recommends CoPilot for its commercial data protection. If using ChatGPT, consider disabling data collection to prevent prompts and conversation from being collected and stored.

Instructors can use Generative AI to enhance teaching and streamline tasks:

  • Lesson Planning and Content Creation: Generate structured lessons, worksheets, quizzes, presentations, and discussion prompts.
  • Assessment and Feedback: Review learners’ work and offer suggestions, create different types of assessments, and assist with grading.
  • Personalized and Adaptive Teaching: Suggest learning paths, translate content, and convert text to speech or captions for accessibility.
  • Information Processing and Summarization: Simplify complex concepts and generate simple, concise explanations.

Students can use Generative AI responsibly to support their learning:

  • Learning Support and Study Assistance: Generate study guides, provide homework help, and create practice questions.
  • Writing and Research Assistance: Offer feedback on grammar, style, and structure, support with brainstorming, suggest resources, and summarize academic papers.
  • Creativity and Engagement: Assist in brainstorming project ideas and create interactive case studies or role-playing exercises.
  • Study Organization and Time Management: Generate personalized study schedules for effective time management.

What are the Limitations and Risks of GAI?

GAI offers powerful tools for teaching and learning, but it also comes with limitations and ethical challenges. Instructors should help learners understand the risks before integrating it into the classroom. Below are definitions of biases, hallucinations, and disinformation to clarify these concerns.

Biases are systematic errors in AI outputs that unfairly favor or discriminate against certain groups or ideas(IBM, 2023). Biases can come from imbalanced training data, which then reflects societal prejudices or flaws in the AI’s design. For example, an image-generating AI tool can consistently associate certain jobs with specific genders or ethnicities.

Hallucinations occur when an AI system generates false, inaccurate, or misleading information that is not based on its training data or real-world facts (IBM, 2023). Hallucinations can range from minor inconsistencies to completely made-up information. For instance, an AI might confidently provide a nonexistent historical date.

Disinformation refers to false or manipulated information deliberately created or spread using AI tools to cause harm or achieve a specific goal (New Zealand Government, n.d.) GAI can be used to rapidly produce and share large volumes of false content, including fake news articles, manipulated images, or deceptive videos (Deutsche Welle, 2024).

More About General Limitations and Risks of GAI

Generative Artificial Intelligence in Teaching and Learning at McMaster University highlights key limitations and risks, including potential biases, inaccuracies, and ethical concerns. Click on each tab to learn more.

General Limitations and Risks of GAI

Attribution: H5P Activity “General Limitations and Risks of Generative AI” from Generative Artificial Intelligence in Teaching and Learning at McMaster University by Paul R MacPherson Institute for Leadership, Innovation and Excellence in Teaching, eCampusOntario Pressbooks. Used in accordance with Creative Commons Attribution 4.0 International License.

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Want to Learn More About GAI?

Enhance your understanding of GAI with these resources:

Introduction to Generative AI for Educators

This McMaster online module explores generative AI, its capabilities and limitations, practical applications, and its impact on teaching and learning.

ACCESS MODULE

Generative AI Key Terms Definition

This webpage from Humber Polytechnic and University of Guelph-Humber Library provides definitions of GAI-related terms to help you fill in your understanding as you engage with GAI.

ACCESS DEFINITION

AI, Algorithms, and You

This self-paced module, created by the Humber and University of Guelph-Humber Library, offers an introduction to algorithms and AI systems and considerations for their ethical and responsible use at Humber and The University of Guelph-Humber.

ACCESS MODULE
Teaching & Learning with GAI Academic Integrity & Ethics

References

Deutsche Welle. (2024, March 26). Generative AI is the ultimate disinformation amplifier. DW Akademie.https://akademie.dw.com/en/generative-ai-is-the-ultimate-disinformation-amplifier/a-68593890

IBM. (2023). Shedding light on AI bias with real-world examples. IBM Think. https://www.ibm.com/think/topics/shedding-light-on-ai-bias-with-real-world-examples

New Zealand Government. (2025, February 3). Misinformation, hallucinations and GenAI. https://www.digital.govt.nz/standards-and-guidance/technology-and-architecture/artificial-intelligence/responsible-ai-guidance-for-the-public-service-genai/genai-foundations/misinformation-hallucinations

Paul R. MacPherson Institute for Leadership, Innovation and Excellence in Teaching. (2023). Generative artificial intelligence in teaching and learning at McMaster University. https://ecampusontario.pressbooks.pub/mcmasterteachgenerativeai/

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