By Jayden Kyryluk, BA (JD Candidate 2026)
Sam Altman, the co-founder of OpenAI (the company behind ChatGPT) declared on June 10, 2025, “We are past the event horizon; the takeoff has started. Humanity is close to building digital superintelligence…”[1] Just like that, with a snap of a finger, artificial intelligence (“AI”) has taken over public discourse and has enmeshed itself in nearly aspect of modern life. As industries scramble on how to adapt, one question must be asked: how will AI affect one of our most important institutions—education?
What is Artificial Intelligence?
AI refers to the development of computer systems that can perform tasks traditionally requiring human intelligence, such as reasoning, learning, problem-solving, and even creativity.[2] From large language models like ChatGPT to image generators, automated tutors, and predictive analytics, AI has become a daily reality for professionals, students, educators, and the public at large. Like any tool, AI is neither inherently good nor bad. Much like the printing press in the 16th century, AI is something that can revolutionize the world, but only if it is used wisely.
Looking ahead, Sam Altman, who maintains a positive outlook on AI, stated “2025 has seen the arrival of agents that can do real cognitive work;…2026 will likely see the arrival of systems that can figure out novel insights. 2027 may see the arrival of robots that can do tasks in the real world.”[3] This acceleration of AI forecasted by Altman is striking, especially considering that ChatGPT, the most well-known language model and catalyst for bringing AI into mainstream consciousness, was only released on November 30, 2022.[4] In less than three years, AI has gone from an experimental novelty to societal force. With any revolution, though, something must give.
How is AI Affecting Education?
AI takes on many forms in education. Tools like Grammarly or ChatGPT assist with writing. Apps like Khanmigo or ScribeSense grade assignments or tutor students in real time.[5] Universities use AI to streamline their administrative processes, as a research support tool, or to personalize teaching and learning.[6] Even though AI may make education more efficient and accessible, it also has the potential to fragment critical thinking and the very nature of learning, in turn leaving many in doubt about the future of education itself.
According to an October 2024 study by KPMG, six in ten Canadian students reported using generative AI for their schoolwork.[7] Students are primarily using AI to assist them with “generating ideas (46 per cent), research (41 per cent) and editing and reviewing assignments (38 per cent).”[8]
At its best, AI democratizes knowledge. It offers real-time tutoring to students who may be underserved, translates materials across languages, and provides support for students with disabilities, such as text-to-speech, speech-to-text, and AI-driven sign language avatars.[9] Almost like a personal Khan Academy, AI can help students in understanding course content, build practical skills such as financial literacy, and even incentivize teachers to further embrace social interaction through non-AI tasks such as group projects, presentations, or small-group discussions.
But at its worst, AI poses a threat to academic integrity, critical thinking, and the student-teacher relationship. The most obvious disruption has been in writing and assessment. Students are using AI to draft essays, answer exam questions, or even generate entire assignments.[10] While three quarters of Canadian students say generative AI tools have improved the quality of their schoolwork, two thirds admit they are not learning or retaining as much knowledge.[11]
AI does not think, it predicts. Large language models, for example, generate content based on patterns in existing data, not truth or understanding, both of which are essential to the development of a growing mind.[12] When students rely on AI to think for them, they risk losing the very capacities education is supposed to develop: reasoning, originality, and critical thinking. This is especially true in disciplines that require ethical judgment, historical awareness, or interpretive nuance, such as law, history, philosophy, or political science. Even in scientific fields like math or physics, complex problems are easily solved by AI.[13]
The result is confusion. Universities have no idea how to respond to AI. In Canada, some professors are moving towards in-person written exams, while others are trying out oral exams or finding ways to incorporate AI.[14] Students receive mixed signals about what is allowed, and teachers feel disempowered. All the while, the public, seeing ChatGPT doing very well on standardized tests like the LSAT or writing essays in a snap of the finger, may begin to question the value of a degree altogether.[15]
What Are Some of the Solutions?
AI is neither inherently positive nor negative as its value lies in how it is used. With seven in 10 students saying they are turning to generative AI for help rather than their professors, it’s crucial that post-secondary institutions adapt to AI rather than deny it.[16] As with any technological revolution, the likely solution is not to fear AI, nor blindly embrace it. It is to reimagine education in light of it. If AI can automate surface-level thinking, then education must dig deeper.
1. Return to In-Person Assessment
One immediate remedy is to revive methods that AI cannot easily replicate: oral examinations, handwritten essays, and seminar-style evaluations. Before the age of standardized testing, students were assessed through conversation and performance. These methods were pioneered by Socrates, formalized by the Jesuits, and used by most of the pre-digital world. They test real understanding and make impersonation difficult. Oral examinations, for instance, offer students the opportunity to bring their knowledge to life through spontaneous reasoning and discussion. While these methods are certainly more labour intensive than standardized tests, a return to these forms would reassert the value of quick, critical thinking.
2. Collective Learning
Education can shift away from standardized testing and toward evaluating the collective learning process. This includes peer review, drafts, group projects, reflective journals, collaborative learning, or increased lab time in the sciences. Incentivizing face-to-face interaction among students not only aids in producing non-AI products but helps students in developing their socialization skills that have been slowly declining since the advent of phones and social media.[17] Assessing the intellectual journey by promoting collective learning protects against taking shortcuts with AI.
3. Teach AI Literacy, Not Just AI Use
Students must learn how AI works, not just how to use it. This means integrating AI ethics, algorithmic bias, and digital epistemology into curricula. Just as literacy once meant reading and writing, in today’s world it could include understanding the tools shaping our thoughts. Education on AI could ideally begin in elementary or high school, teaching students to be active users and (or critical active users/collaborators) critics of AI rather than passive users.
4. Use AI as a Learning Partner
After teaching students AI literacy, educational institutions can utilize AI as a learning partner, not an assignment doer, by encouraging students to use AI for certain things. For example, students can use AI to personalize their learning experience; some students are visual learners, others are auditory learners—AI can cater to both. AI tools like ChatGPT, Midjourney or DALL-E can help spark an idea or prompt a conversation in the classroom, in turn helping students see problems differently.[18] AI can also provide instant feedback to a student’s work or answer questions quickly and easily in a way they understand. These facets can all be used and embraced by educational institutions to use AI for what it is: a tool.
5. Establish Clear Institutional Guidelines
Universities and schools should set clear and transparent AI policies. Students should know what is acceptable, and teachers should receive training on how to use it and detect and respond to misuse. Blanket bans, for instance, are unenforceable, while unregulated AI use is equally problematic. A balanced approach, grounded in the principle of subsidiarity, can be taken. Instructors should have the autonomy to incorporate AI into their courses where appropriate, within the framework of a consistent, student-focused institutional policy. Canadian students are confused; 65 per cent say they feel that they are cheating when they use generative AI.[19] A clear policy is required to put everyone’s mind at ease.
Conclusion
Education has always been about the formation of persons, not just the transmission of information. If AI can do the latter faster, educational institutions must double down on the former. This means framing AI as an opportunity to improve education rather than destroy it. After all, crisis invites growth.
[1] Sam Altman, “The Gentle Singularity” (10 June 2025), online: <https://blog.samaltman.com/the-gentle-singularity> [Altman].
[2] Oxford English Dictionary (2023) sub verbo “Artificial Intelligence”.
[3] Altman, supra note 1.
[4] OpenAI, “Introducing ChatGPT” (30 November 2022), online: <https://openai.com/index/chatgpt/>.
[5] Fredrik Filipsson, “What is ScribeSense and How Does it Use AI?”, Redress Compliance (8 February 2025), online: <https://redresscompliance.com/what-is-scribesense-and-how-does-it-use-ai/>.
[6] University of Bridgeport, “How is AI Technology Used in Higher Education?” (24 October 2023), online: <https://www.bridgeport.edu/news/how-is-ai-technology-used-in-higher-education/>.
[7] KPMG, “Students using generative AI confess they’re not learning…” (21 October 2024), online: https://kpmg.com/ca/en/home/media/press-releases/2024/10/students-using-gen-ai-say-they-are-not-learning-as-much.html [KPMG Survey].
[8] Ibid.
[9] Deepranjani Foundation, “Assistive Technology: A Game Changer for Neurodiverse Learners” (18 February 2025), online: <https://www.deepranjani.com/insight-detail/assistive-technology-game-changer-neurodiverse-learners>.
[10] Kevin Maimann, “Canadian universities grapple with evaluating students amid AI cheating fears”, CBC News (8 June 2025), online: <https://www.cbc.ca/news/canada/university-ai-exams-1.7551617> [Maimann].
[11] KPMG Survey, supra note 7.
[12] John Nosta, “The Truth About LLMs and Their Evolving Capabilities”, Psychology Today (16 October 2025), online: <https://www.psychologytoday.com/us/blog/the-digital-self/202410/the-truth-about-llms-and-their-evolving-capabilities>.
[13] Will Douglas Heaven, “What’s next for AI and math”, MIT Technology Review (4 June 2025), online: <https://www.technologyreview.com/2025/06/04/1117753/whats-next-for-ai-and-math/>.
[14] Maimann, supra note 10.
[15] J.D. Capelouto, “Here’s how GPT-4 scored on the GRE, LSAT, AP English, and other exams”, SEMAFOR (15 March 2023), online: <https://www.semafor.com/article/03/15/2023/how-gpt-4-performed-in-academic-exams>.
[16] KPMG Survey, supra note 7.
[17] Effective School Solutions, “The Decline of Teenage Social Skills” (26 April 2024), online: <https://effectiveschoolsolutions.com/teenage-social-skills/>.
[18] Digital Marketing Institute, “5 Ways Universities & Colleges Can Embrace AI in The Classroom” (4 March 2024), online: <https://digitalmarketinginstitute.com/blog/5-ways-universities-colleges-can-embrace-ai-in-the-classroom>.
[19] KPMG Survey, supra note 7.
The views and opinions expressed in the blogs and case reporter are the views of their authors, and do not represent the views of the Desautels Centre for Private Enterprise and the Law, the Faculty of Law, or the University of Manitoba. Academic Members of the University of Manitoba are entitled to academic freedom in the context of a respectful working and learning environment.