Dr. Sarah Whitwell (she / her) is an Educational Developer in the Office of Community Engagement and a Sessional Instructor in the Faculty of Humanities. For the past two years, Dr. Whitwell has taught HUMAN 1DL3: Digital Literacy for the Humanities, a mandatory course for all incoming students in the Faculty of Humanities. The goal of the course is to equip students with digital skills that will support their learning at McMaster and beyond. Given the rapid rise of Generative AI, an important part of the course is teaching students about the uses (and abuses) of Generative AI.
Recognizing that Generative AI plays a critical role in the way we now navigate digital spaces, Dr. Whitwell introduced a new assignment to help students explore the similarities and differences between human-generated and AI-generated content. Both students and instructors have strong opinions about generative AI and its place in academia, and this can make it hard to engage in productive conversations that recognize both challenges and opportunities.
In HUMAN 1DL3, Dr. Whitwell wanted students to understand how Generative AI works. For example, students discussed the technical aspects of the software, how large language models are trained, how content is generated, the environmental impacts of Generative AI usage, and issues related to data privacy breaches, algorithmic bias, and intellectual property theft. Armed with this knowledge, students can then engage in hands-on activities that help them put theory into practice. One tutorial activity, for example, involved comparing photographs and art to identify if they are human-generated or AI-generated. The major assignment, however, is one that Dr. Whitwell playfully titled ‘Humans vs. Generative AI.’
Students begin by writing a short passage (~250 words) about a topic they are passionate about. They might write about their favourite sports team, a favourite movie, or a favourite animal. Students are asked to explain why they are passionate about the topic, writing for an audience that is unfamiliar with their topic.
Students are also tasked with generating a similar passage using a Generative AI tool of their choice (ChatGPT, Google Gemini, Microsoft CoPilot, etc.). For example, a student might ask ChatGPT to explain why the Toronto Blue Jays are their favourite baseball team.
Once students have both a human-generated passage and an AI-generate passage, they are responsible for critically analyzing the two passages. Students might explore the use of examples, tone, and the overall quality of the writing. Students are not graded on the quality of the passages, but based on the quality of their critical analysis, their ability to reflect on the exercise, and their expression.
As a final step, students write a reflection about what they have learned from the exercise. What did they learn about Generative AI? Would they recommend the use of Generative AI for generating text? Are there certain contexts in which Generative AI is particularly useful? Which passage do you think is more compelling?
Download a copy of the rubric.
This assignment provided students with an opportunity to directly compare human-generated and AI-generated content. For some students, this confirmed their existing beliefs about whether Generative AI has a place in academia. For other students, the assignment challenged their understanding of the digital tool.
In the reflective portion of the assignment, many students said that they appreciated the opportunity to develop their own informed opinion about Generative AI. A common conclusion was that Generative AI is impressive in a technical sense, but that it lacks the ability to engage with the human experience and draw on deeply personal examples. In other words, the passages generated by Generative AI never sounded as passionate at those generated by humans.
The ‘Humans vs. Generative AI’ assignment was not without challenges, however, as some students objected to being asked to use Generative AI in any capacity. Some raised environmental concerns, while others objected to the impacts of Generative AI on the labour market and the dangers of cognitive offloading. Dr. Whitwell was prepared for these objections, and had an alternate assignment prepared that allowed students to explore their objections through a written essay.
Since the launch of ChatGPT in November 2022, Humanities education has become something of a battleground. In a recent article in The Conversation, Dr. Johannes Steizinger noted that students and faculty alike believe that Generative AI threatens the purpose of education in many Humanities disciplines, including history and philosophy. And there is merit to this argument, on many fronts, but this doesn’t mean instructors can simply ignore Generative AI, nor should they try to address the problem by AI-proofing their classrooms.
Assignments like ‘Humans vs. Generative AI’ create space for open dialogue. Dr. Whitwell makes sure that students know there are no right or wrong answers, but students do have to support their conclusions with evidence based on the passages they examine. And if students object to using Generative AI, then it’s important to create space for those viewpoints, as well.
Perhaps the biggest challenge with assignments that utilize Generative AI is creating alternate assignments that meet the same intended learning outcomes. While it may be more work for the instructor to create these alternative assignments, Dr. Whitwell believes firmly in student autonomy and allowing them to make decisions about how they engage with course content. She hopes that by the end of HUMAN 1DL3, students feel empowered to use, or not use Generative AI, in ethical ways.
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Whitwell, S. (2026), Humans vs. Generative AI, Teaching in the Age of AI: Examples, Retrieved from Humans vs. Generative AI, Licensed under Creative Commons BY-NC-SA 4.0.
Teaching in the Age of AI