Generative artificial intelligence (AI) uses machine learning to generate new content, ideas or solutions by training models on large datasets from diverse sources.
This technology enables us to develop intelligent systems capable of generating text, images, videos, code and interactive simulations, paving the way for more personalized and engaging educational content. Already, Laurier is exploring the opportunities and challenges of generative AI’s use in academia.
Generative AI tools hold immense promise to revolutionize traditional teaching methods and enhance the learning experience. It is becoming deeply integrated in all aspects of our lives, and universities are key institutions for teaching how to use generative AI responsibly and critically.
At Wilfrid Laurier University, we support faculty members in critically considering the adoption of generative AI in their courses where it aligns with how the technology is changing the way in which the world interacts with it.
We embrace generative AI as a tool for student learning while also being mindful of uses of this technology that can diminish agency, creativity, expression, curiosity, authenticity, critical thinking, and deep and meaningful learning.
The generative AI committee stands as an institution-wide collaboration at the forefront of exploration and ethical considerations of artificial intelligence. Comprised of experts from diverse fields across Laurier, this committee will explore ways generative AI is transforming the landscape of teaching and learning to equip students, faculty and staff with the knowledge and skills needed to harness the use of AI in education.
The committee will provide recommendations on the impacts posed by generative AI on teaching, research and operational activities at Laurier and will also offer recommendations about changes in policy and practice. With a mission to drive interdisciplinary dialogue, the committee fosters a collective understanding of the implications and opportunities of AI technology.
In its initial year, the committee will meet monthly in September, October and November 2023 to discuss generative AI in the context of teaching, research and operational activities. During these meetings the committee will set the mandate for the subcommittees, including deliverables and timelines. The subcommittees will meet through the fall 2023 and winter 2024. The committee will reconvene in March 2024 to receive the recommendations from the subcommittees.
In subsequent years the committee will meet twice annually, in the fall and the winter, to review and reassess guidelines from the perspective of a) how they have worked to date and b) changes needed based on experience and updates to generative AI.
Generative AI tools have not been assessed against Laurier’s privacy and security requirements. The University is awaiting the outcome of the joint investigation by the federal and provincial privacy commissioners. At this time, all cloud-based generative AI technologies that are used by faculty and staff in any aspects of their work may only be used with Type 1 information (e.g., general queries and specific subject matter, etc.). Do not upload any personal information, potentially identifying information, or intellectual property (i.e. submitted work for a course) of any faculty or staff member or student. Type 2 and Type 3 data cannot be uploaded to a cloud-based gen AI system, as once it has been uploaded individual loses control over their personal data and/or intellectual property. See Policy 10.4 Records Management for definitions of information types.
Explore the possibilities of generative AI in teaching and learning. This comprehensive guide on the integration of artificial intelligence in education outlines its potential to enhance teaching experience and elevate learning outcomes. It examines how generative AI is revolutionizing traditional educational approaches and offers insights into how educators at Laurier can leverage the technology to create more interactive and engaging learning environments.
The resource for students in teaching roles outlines opportunities and challenges of generative AI tools in academia for students in teaching roles. It delves into the dynamic landscape of integrating AI-powered tools into educational settings and addresses the unique challenges it brings.
This guide on citing artificial intelligence sources helps navigate the intricacies of referencing AI-related materials. Whether you're a student, researcher or professional, this resource offers instructions on citing AI sources effectively.
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