Artificial Intelligence (AI)

At its simplest form, artificial intelligence is a field, which combines computer science and robust datasets, to enable problem-solving. It also encompasses sub-fields of machine learning and deep learning, which are frequently mentioned in conjunction with artificial intelligence. These disciplines are comprised of AI algorithms which seek to create expert systems which make predictions or classifications based on input data (IBM, n.d.)

Artificial intelligence is used across all industries and academic subjects. The term is used to describe everything from finding the best route on Apple and Google Maps, self-driving cars, algorithms to display a list in a certain order on a website or in a social media app, and facial recognition software to unlock a smart phone. It is part of our everyday lives, at work, in school and at home (University of Calgary, 2023).

This guide has been created for students and instructors to explore how to responsibly and ethically use AI in their work. There is information about how to critically engage with AI tools, examples and further reading on how students and instructors can use AI tools in their work, and information about current AI news, such as Chat GPT.

As Eaton and Anselmo (2023) described, “If we think of artificial intelligence apps as another tool that students can use to ethically demonstrate their knowledge and learning, then we can emphasize learning as a process not a product.”

The latest generation of Large Language Model (LLM)/ Generative Artificial Intelligence (Gen AI) systems is impacting teaching and learning in many ways, presenting both opportunities and challenges for the ways our instructors and students engage in learning. LLM/Gen AI that can create content such as essays, computer code, and/or images using minimal human prompting, are proliferating, and becoming commonplace. While many LLM/Gen AI systems have recently become available, ChatGPT (the free, online chat system that utilizes the Open AI GPT technology) is currently the most prominent, garnering worldwide attention. The products the LLM/Gen AI tools create are dependent on the quality of the training of the LLM and the prompt given. While some responses may be of good quality, some may have inaccuracies and biases.

At Medicine Hat College (MHC), we remain committed to providing students with exceptional learning experiences and supporting instructors as they adapt their pedagogy in response to this emerging technology. MHC supports instructors in their choice to integrate or not integrate LLM/Gen AI in individual courses, assessments, and with individual students. MHC Academic Regulations clarify that students are expected to follow academic integrity, which is the “moral code of academia and can be defined as the use, generation, and communication of information in an ethical, honest, and responsible manner.” MHC Academic Integrity statements, policies, and procedures are clear in that students must comply with academic integrity as specified by MHC. Due to the rapidly changing LLM/Gen AI landscape, this stance will be periodically reviewed to remain current.

These links are to resources that include background information, such as information about the companies that own popular AI tools, definitions of terms that are often spoken about alongside AI, and basic information on how to use generalised AI tools. 

• A.I. Is Mastering Language. Should We Trust What It Says?

  An article from the New York Times Magazine with an overview of large language models (LLMs) and the history of OpenAI, the company behind Chat GPT-4 and DALL·E 2 (an Art AI tool).

• AI & AI: Exploring the contemporary intersections of artificial intelligence and academic integrity

  A presentation reviewing the issues emerging from the use of artificial intelligence technologies in academic integrity.

• AI Biases: Are We Ready to Be Stereotyped by Robots?

  This article looks at the history of bias in AI and suggestions on how to fix it.

• AI Definitions

  McGill University Libraries created a list of definitions on many of the terms that are mentioned alongside AI.

• Artificial Intelligence Has a Problem With Gender and Racial Bias. Here’s How to Solve It.

  One of the issues with AI is the implicit biases of the people who create them

• The Dawn of AI has Come, and its Implications for Education Couldn’t Be More Significant

  An article from The Conversation on the future of teaching and learning alongside artificial intelligence.

• Glossary of Artificial Intelligence Terms for Educators

  "This glossary was written for educators to reference when hearing and learning about artificial intelligence (AI)."

• A Pragmatic Guide to Conversational AI

  An Ecampus Ontario open pressbook intended to be a pragmatic guide to helping able citizen data scientists to utilize common frameworks and tools to create conversational artificial intelligence experiences for users.

Thank you to the University of Calgary and Bronte Chiang for the information in this guide.