LibGuides: Teaching with Generative AI: Further Reading

Ethics

EU guidelines on ethics in artificial intelligence: Context and implementation
Clearly lays out the seven key EU requirements for ethical Artificial Intelligence:
• human agency and oversight
• robustness and safety
• privacy and data governance
• transparency
• diversity, non-discrimination and fairness
• societal and environmental well-being
• accountability
ENAI Recommendations on the ethical use of Artificial Intelligence in Education
How the right to education is undermined by AI
Young people in education are therefore subject to three distinct threats to their educational rights:

1. So-called predictive AI is used to collect their data, to make unaccountable and discriminatory decisions about their futures, and to surveil and discipline their interactions with educational systems

2. So-called generative AI is used to capture and monopolise cultural and educational content, to advance hegemonic languages and perspectives, and to replace pedagogical relationships with automated agents

3. The narrative of ‘AI futures’ is used to refocus educational outcomes around the automation of intellectual work, stunting the development of young people’s capacities, and preparing them for work that will be precarious, exploitative, and algorithmically disciplined

Resources from Academic Institutions

AI in Education
Thompson Rivers University’s Learning Technology and Innovation team has created this website with support materials, resources, and information made for faculty.
Teaching and Learning with Artificial Intelligence Apps
University of Calgary teaching and learning resource.
Assessment Design in an Era of Generative AI
UBC resources for assessment design.
Generative Artificial Intelligence in the Classroom
University of Toronto guidance on using AI technology in the classroom.
Centre for Research in Assessment & Digital Learning (CRADLE) - Deakin University
The Centre for Research in Assessment and Digital Learning (CRADLE) researches assessment practices in the changing settings of education, which are increasingly embracing digital learning. Our aim is to improve and optimise learning in higher and professional education.
Specific suggestions from CRADLE research
Part of a series of shared research outcomes.

Government Guidelines

Government of Canada Guide on the use of Generative AI
Provides preliminary guidance to federal institutions on their use of generative AI tools. This includes instances where these tools are deployed by federal institutions. It provides an overview of generative AI, identifies challenges and concerns relating to its use, puts forward principles for using it responsibly, and offers policy considerations and best practices.

Outlines the “FASTER” principles:

Fair: ensure that content from these tools does not include or amplify biases and that it complies with human rights, accessibility, and procedural and substantive fairness obligations
Accountable: take responsibility for the content generated by these tools. This includes making sure it is factual, legal, ethical, and compliant with the terms of use
Secure: ensure that the infrastructure and tools are appropriate for the security classification of the information and that privacy and personal information are protected
Transparent: identify content that has been produced using generative AI; notify users that they are interacting with an AI tool; document decisions and be able to provide explanations if tools are used to support decision-making
Educated: learn about the strengths, limitations and responsible use of the tools; learn how to create effective prompts and to identify potential weaknesses in the outputs
Relevant: make sure the use of generative AI tools supports user and organizational needs and contributes to improved outcomes for Canadians; identify appropriate tools for the task; AI tools aren’t the best choice in every situation

Principles for responsible, trustworthy and privacy-protective generative AI technologies
From the Office of the Privacy Commissioner of Canada

Scholarly

Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity
We conduct a randomized controlled trial (RCT) to understand how early-2025 AI tools affect the productivity of experienced open-source developers working on their own repositories. Surprisingly, we find that when developers use AI tools, they take 19% longer than without—AI makes them slower. We view this result as a snapshot of early-2025 AI capabilities in one relevant setting; as these systems continue to rapidly evolve, we plan on continuing to use this methodology to help estimate AI acceleration from AI R&D automation.
Open artificial intelligence platforms in nursing education: Tools for academic progress or abuse?
O’Connor, S. (2023) ChatGPT, Open artificial intelligence platforms in nursing education: Tools for academic progress or abuse? Nurse Education in Practice. V 66. https://doi.org/10.1016/j.nepr.2022.103537.
Educational AI Chatbots for Content and Language Integrated Learning
Mageira, K., Pittou, D., Papasalouros, A., Kotis, K., Zangogianni, P., & Daradoumis, A. (2022). Educational AI chatbots for content and language integrated learning. Applied Sciences, 12(7), 3239. https://doi.org/10.3390/app12073239
Faculty members’ use of artificial intelligence to grade student papers: a case of implications
Kumar, R. Faculty members’ use of artificial intelligence to grade student papers: a case of implications. Int J Educ Integr 19, 9 (2023). https://doi.org/10.1007/s40979-023-00130-7
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?
In this paper, the authors critically examine the rapid growth in the field of Natural Language Processing (NLP), specifically focusing on the development of increasingly larger language models such as BERT, GPT-2/3, Switch-C, and their variants. They question the necessity and inevitability of such models, arguing that researchers must consider the potential risks and costs associated with this direction in NLP research. The authors highlight environmental costs, financial barriers, opportunity costs, and potential harms (e.g., stereotyping, extremist ideology propagation, wrongful arrest) that may arise from the use of these large-scale models.
Assigning AI: Seven Approaches for Students, with Prompts
This paper examines the transformative role of Large Language Models (LLMs) in education and their potential as learning tools, despite their inherent risks and limitations. The authors propose seven approaches for utilizing AI in classrooms: AI-tutor, AI-coach, AI-mentor, AI-teammate, AI-tool, AI-simulator, and AI-student, each with distinct pedagogical benefits and risks.

In the News

The impact of AI on B.C.’s workforce in 2024: An interview with Aaron Hunter, BCIT's Mastercard Chair in Digital Trust

Blog Posts

AI slop and the destruction of knowledge
ScienceDirect features AI generated summaries and definitions that are incorrect and misleading.
“We Couldn’t Generate an Answer for your Question”
Short piece by Jay Singley (Document Delivery and Circulation Desk Manager at North Carolina School of Science and Mathematics) posted on ARCLog, which discusses suppression of 'controversial' topics in Ex Libris' Summon. Seems like its AI-powered Research Assistant is only willing to assist you in finding resources on approved topics.

more... less...

"Despite requests for more information in the same listserv, Ex Libris has not provided a comprehensive response to librarians’ concerns about who the third-party provider is, what the ethical and responsible AI use policies are, whether local control can be made available, what known search terms and topics are obstructed, and more. As one librarian aptly noted, academic users want and need access to information that may be blocked by AI use policies meant for the general public."
6 Tenets of Postplagiarism: Writing in the Age of Artificial Intelligence
Dr. Sarah Elaine Eaton from U of Calgary explores coming implications of AI in academic writing.
Accessibility of AI Interfaces
Review, by Langara Assistive Technologist Luke McKnight, of various AI Chatbots based on their accessibility.
AI Text Generators and Teaching Writing: Starting Points for Inquiry
A list of collected resources that can serve as catalysts for inquiry, discussion, and collaborative research as faculty respond to this major change in the kind of writing assistance available to our students. Last updated February 14, 2023
BCcampus: ChatGPT and Open Education
A nice summary of issues around generative AI technologies and open education. Includes some key questions surrounding copyright. March 6, 2023
BCcampus: Digital Pedagogy Toolbox: Let’s Make Friends with ChatGPT
In this sixth post in our Digital Pedagogy Toolbox blog series, Gwen Nguyen discusses the potential benefits artificial intelligence (AI) tools like ChatGPT can bring to the field of post-secondary education. February 22, 2023
Developing Career-Ready Graduates: The Importance of AI Literacy Across the Curriculum
University of Florida is integrating AI into the undergraduate program. "AI Across the Curriculum," aims to engage students in an interdisciplinary manner that reflects real-world workplace environments. May 2023
How AI Tools Both Help and Hinder Equity
The technology promises to assist students with disadvantages in developing skills needed for success. But AI also threatens to widen the education gap like no tech before it. An overview that touches on many key issues. June 5, 2023
How things are made
An academic's look at the use of ChatGPT, education, and labour. Links at the end to more good resources. February 5, 2023
How to Guide Faculty: Navigating the AI Avalanche in Higher Education as an Academic Administrator
Short and practical post on how to handle the kinds of disruptions in institutions that AI is causing. March 7, 2023
Making ChatGPT detectors part of our education system prioritizes surveillance over trust
George Veletsianos, professor of education and Canada Research Chair in Innovative Learning and Technology at Royal Roads University discusses the harm caused by surveillance. April 27, 2023
On the Automation of “Care”
Dr. Maha Bali discusses ideas around decisions made by people of when to use AI as a shortcut and argues that: "We don’t automate what we care about." February 18, 2023
Prior to (or instead of) using ChatGPT with your students
Autumm Caines provides ideas for what to do before teaching with ChatGPT. January 18, 2023.
Teaching the Machine: Faculty weigh in on AI in the classroom
Recent statistics about AI use from Canadian post-secondary faculty. May 22, 2023

Professional Guidelines

Engineers and Geoscientists BC’s practice advisory Use of Artificial Intelligence (AI) in Professional Practice
provides guidance about using AI appropriately in professional activities.

Creative Commons License

Teaching with Generative AI LibGuide by BCIT Library Services is licensed CC BY-NC, meaning it can be used for non-commercial purposes if attribution is provided. Learn more about Creative Commons licenses on the BCIT Open Education LibGuide.