New findings from Canada suggest that artificial intelligence (AI) is becoming part of everyday life, which is a foundation for postplagiarism. Questions remain about academic integrity, transparency, and responsible use and using a postplagiarism framing, we talk about how to use AI ethically.
This is the first of two blog posts discussing the Association for Canadian Studies’ recent report, AI and Chat Use: Lessons Learned, published in July 2026. The study was led by the Association for Canadian Studies in collaboration with the Diversity Institute and the Future Skills Centre – Centre des Compétences futures. The Future Skills Centre is funded by the Government of Canada’s Future Skills program. This study was conducted through a web-based survey among Canadians aged 18 and older. A total of 1,700 respondents completed the survey, including a booster sample of 200 individuals with an immigration background.
AI use is becoming common
Almost half of Canadians reported using AI tools such as ChatGPT or Copilot at least weekly. Among people under 45, the figure rose to about 60%. AI use also varied by background: 77% of newcomers reported using AI tools, compared with 45% of non-newcomers. These findings suggest that AI is becoming part of how Canadians learn and work, although adoption differs across groups.
Human-AI co-creation: Who does the work?
The first tenet of postplagiarism, developed by Dr. Sarah Elaine Eaton, recognizes the growing role of human-AI co-creation. People may use AI to generate ideas, edit writing, or produce parts of a final product. The report found that 25% of AI users said AI did most or almost all of the work, while 18% said they and AI contributed about equally. Another 27% said they did most of the work with AI assistance, and 30% said they did almost all the work themselves. These findings show that AI involvement varies considerably. However, recognizing human-AI collaboration does not mean every use is appropriate. A key question is not whether AI was used, but how it was used and whether the human contributor remains responsible.
When does AI use become cheating?
Canadians expressed strong concerns about AI producing final answers. Overall, 64% considered it cheating when AI produced most of a final answer, and 51% said the same when it produced part of the answer. By comparison, 27% considered generating ideas or editing and improving work to be cheating. Younger respondents were particularly concerned about AI-generated answers: 79% of those aged 18–24 considered it cheating when AI produced most of the final answer. These findings challenge the assumption that younger people automatically accept every form of AI use. They also show why educators should distinguish between using AI to support learning and using it to replace learning.
Disclosure and clear rules matter
Three in four Canadians (75%) believed AI use should be disclosed in schoolwork and academic assignments. For work-related tasks, 61% supported disclosure. Yet only 32% said they acknowledge their own AI use in a document at work or school. Another 34% said they did not, and 34% were unsure. This gap highlights the need for clear expectations. Disclosure helps teachers and readers understand how a piece of work was produced. Institutions should explain what students may use AI for, when disclosure is required, and how to acknowledge its contribution.
Dependence, trust, and unclear rules
One in three Canadians (34%) said they were becoming more dependent on AI. Among those aged 18–24, the figure was 52%. Meanwhile, only 33% trusted AI-generated information most of the time or completely. The survey also found that 47% considered current AI rules unclear, compared with 20% who considered them clear. However, 45% of respondents aged 18–24 said the rules were clear. These results raise important questions for educators and policymakers. People need guidance on responsible AI use, but they also need to learn how to verify information and make decisions independently.
Moving forward
The findings present a mixed picture: AI use is widespread, yet concerns about cheating, dependence, and transparency remain. Postplagiarism provides a way to discuss human-AI collaboration without abandoning academic integrity. The goal should not be to reject AI or accept every use without question. Instead, we need clear rules that support responsible collaboration, human judgment, and meaningful learning.
The second post examines new Canadian findings on AI translation, language learning, workplace communication, and the limits of machine translation.
References
Eaton, S. E. (2023). Postplagiarism: Transdisciplinary ethics and integrity in the age of artificial intelligence and neurotechnology. International Journal for Educational Integrity, 19(1), 1–10. https://doi.org/10.1007/s40979-023-00144-1
Jedwab, J., & Cukier, W. (2026, July). AI and chat use: Lessons learned. Association for Canadian Studies. https://acs-metropolis.ca/en/library/ai-and-chat-use-lessons-learned
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About the Authors
Sarah Elaine Eaton, PhD, is a Professor and the Director of the Postplagiarism Research Lab in the Werklund School of Education, University of Calgary.
Fuat Ramazanov, EdD, is a management educator and researcher whose work focuses on artificial intelligence in education, human–AI co-creation, creativity, and emerging technologies.
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