A few years ago, I posted about my progress learning and adopting generative artificial intelligence as an educator. While writing the post, Climbing Up and Sliding Down the AI Slope of Enlightenment, I thought that within a few months and committed effort, I would achieve confidence and control of GenAI and its potential. How naive I was! In order to clarify my journey, a basic understanding of Gartner’s Hype Cycle is necessary.
Gartner’s Hype Cycle & ChatGPT
Gartner’s Hype Cycle provides the five steps of acceptance of new technologies in a marketplace. This is graphically explained in section 2.1 in Prinsloo (2017). In our case, the market is the Canadian LINC and ESL sector. As a practitioner in the LINC sector, I revisted my experience with ChatGPT and the Hype Cycle, since the original post in late 2023. All of us are experiencing this adaptation differently and the following is my experience.
The Gartner’s Hype Cycle stages are:
1 Innovation trigger — ChatGPT released October 2022
2 Peak of Inflated Expectations – January 2023 (imagining a candy store for educators)
3 Trough of Disillusionment – June 2023 (flaws, challenges, ethical issues, plagiarism)
4 Slope of Enlightenment – Off and on late 2023
3 Trough of Disillusionment – March 2024 until now (this is intentionally repeated)
5 Plateau of Productivity – Not there yet
Reasons for Disillusionment?
I find myself in the Trough of Disillusionment despite an extensive engagement with pioneering education technologies. These included, Computer-Assisted Language Learning tools and practices with personal computers in separate rooms, Compact Disc with rich media and interaction, email, the visual Internet, learning management systems, MOOCs (online learning), streaming audio and video services, 3D virtual worlds, laptops and handheld portable devices. Of course, none of these were as disruptive as GenAI, but they were considered revolutionary at the time.
From the Slope of Enlightenment to the Trough of Disillusionment
During my climb up the Slope of Enlightenment, I was keen to become a more efficient and effective educator and have that translate to better learning pathways for students. What happened? There is no way I can provide details in this short blog post, so this list of challenges speaks for itself:
- Periodic GenAI hallucinations or inaccurate information.
- Inordinate amount of time checking GenAI creations for possible inaccuracies.
- Potential for plagiarism on both sides of the classroom.
- Danger of reduced learning due to student and educator reliance on GenAI.
- Danger that bias and stereotypes in large language models (LLMs) can be transferred to materials and human attitudes.
- Increase in digital inequality between the haves and the have-nots.
- Intellectual property and copyright uncertainty of AI-generated media and source content.
- Potential loss of authentic communication between educator and learner due to overuse of GenAI.
- Professional guilt associated with using GenAI.
- Professional reputation issues stemming from public works labelled “made with AI.”
- Privacy issues resulting from learners over sharing identity details with GenAI tools.
Daily consumption of AI information through social media, traditional media outlets, books, articles, and peer exchanges has led to confusion. Cheerleaders of AI tout it as the miracle that will change our world for the better in all fields, from engineering to medicine, and in our case, education. On the other hand, posts and reports of identity acquisition, security breaches and environmental damage warn us to become more educated consumers of AI.
Educators are presently looking upwards for guidance. Teachers really want a “do and don’t” list. Governments, international organizations, and educational institutions down to individual departments do provide direction. However, there are some legal issues that have to be resolved as to who owns what. It is difficult to write policies and provide specific guidance in this state. A relevant document that was not written for educators but provides some GenAI usage strategies is the Government of Canada’s Guide on the Use of Generative Artificial Intelligence.
To dig deeper into our GenAI perspectives, Jen Artan and I co-facilitated a series of seven GenAI Conversation webinars to inform, share and learn about our GenAI experiences with our language teaching and settlement peers on the Tutela network. The webinars were based on the guide’s FASTER framework (Fair, Accountable, Secure, Transparent, Educated and Relevant) for considering GenAI in a professional setting. Through these sessions, we learned that the GenAI education field is dynamic, and we have much to learn. We must stay abreast of the trends and develop new strategies to address the frequent changes being implemented by the AI-tech companies.
Final thoughts
To this point, I still am not sure if or to what degree I should be using GenAI. From the FASTER framework, I think the best strategy for me to inch back up the Slope of Enlightenment may be to stay educated with GenAI in our field and to communicate frequently with my peers to learn innovations to become a confident and skilled user of GenAI
Resources
Allan, J. (2023). Climbing Up and Sliding Down the AI Slope of Enlightenment, https://blog.teslontario.org/climbing-up-and-sliding-down-the-ai-slope-of-enlightenment. TESL Ontario Blog.
Allan, J, (2025). Consider the Government of Canada’s Guide on the Use of Generative Artificial Intelligence. https://blog.teslontario.org/consider-the-government-of-canadas-guide-on-the-use-of-generative-artificial-intelligence
Allan, J. (2026). Instructors, Let’s Talk About GenAI — FASTER conversations. https://blog.teslontario.org/instructors-lets-talk-about-genai-faster-conversations
Jen Artan LinkedIn Profile, https://www.linkedin.com/in/jen-artan-0541b290
Prinsloo, T. (2017). Using the Gartner Hype Cycle to Evaluate the Adoption of Emerging Technology Trends. In T.-C. Huang, R. Lau, Y.-M. Huang, M. Spaniol, & C.-H. Yuen (Eds.), Emerging Technologies for Education (Lecture Notes in Computer Science, Vol. 10676). Springer, Cham. Retrieved June 22, 2026, from https://repository.up.ac.za/items/8681be1e-3e43-45f7-8eea-6c8e9fc26d71
Treasury Board of Canada Secretariat. (2024, February 12). Generative AI in your daily work or Concise Guide summary, https://www.canada.ca/en/government/system/digital-government/digital-government-innovations/responsible-use-ai/generative-ai-your-daily-work.html

2 Comments
As shared in Linkedin,
Beautifully written, John Allan —I think we have been derailed by the hype and blink of this Rabbit 🐇 hole 🕳️
All of a sudden, we can do without human connections because we can go “trough” AI —but not all that shines is gold… ‘kind of like’ the ROM’s psychedelic exhibit happening now, where is this experiment taking us?
But, but, but… it’s got electrolytes. (Kudos if you get the reference).
John – I am with you here in the mighty trough, trench, or as Cecilia calls it, the rabbit hole. At least with a rabbit hole, you have an idea what may be at the end of the tunnel; hopefully you’ll find a cute fuzzy bunny, and not the Monty-Python Rabbit of Caerbannog. (It was not a nice rabbit.)
Generative “artificial intelligence” has been over-hyped by the hype-masters, the hyper-scalers, the venture-capitalists who’ve massively over-inflated their actual worth while at the same time attempting to convince the world that we cannot live without it, that there’s no use fighting it (inevitabilism), and that anyone arguing against its use in EVERY aspect of life has some kind of undercover Luddite agenda.
Here, in the trough, you’ll find good company. You’ll find educators questioning the value of the tool, raising concerns about necessary and proportionate use of “GenAI” especially when it comes to data-centre expansion and the impact these are having on the environment (read Karen Hao, Kate Campbell, Timnit Gebru, Naomi Klein, and many others).
Here, in the trough, you will find educators wondering about “ethical” use. You’ll find colleagues asking about the labour practices of the “big tech” companies, especially in less affluent areas (Global South). You’ll find people asking about privacy, about the security of our data, about the role that Big Tech is taking in our everyday lives.
Here, in the trough, you’ll find educators wondering why OpenAI did not act sooner (or at all) when it had pretty convincing evidence about the Tumbler Ridge shooter.
Here, in the trough, you’ll find educators struggling with the very concept of a tool that at its very core is paper-mache, pulled together from artists, content creators, writers, without consent claiming “fair use”. (And occasionally winning based on this argument.)
Here, in the trough, you’ll find good company. I know that there is value to “GenAI”; that it’s ability to analyze reams of data in no time flat, and based on that data, produce text that’s decent. Plausible.
So, John – you’re not alone in the trough. I believe machine learning in other contexts can produce some pretty amazing advancements (AlphaFold – Nobel prize); but at this moment in time, I have questions about GenAI. And I’m working hard trying to find some answers (reading both sides of the debate).
Keep asking the questions, keep blogging!
Some references…
Dickson, C. (2026). B.C. Preparing Legal Action Against OpenAI in the Wake of Tumbler Ridge. CBC. Retrieved from: https://www.cbc.ca/news/canada/british-columbia/bc-attorney-general-legal-options-tumbler-ridge-9.7261071.
Doctorow, C. (2026). The Reverse Centaur’s Guide to Life After AI.
Lynskey, D. (2026) The Guardian. Review: The Reverse Centaur’s Guide to Life after AI by Cory Doctorow. Retrieved from: https://www.theguardian.com/books/2026/jun/22/the-reverse-centaurs-guide-to-life-after-ai-by-cory-doctorow-review-the-real-price-of-artificial-intelligence
Zitron, E. (2026). The AI Industry is Losing. Retrieved from https://www.wheresyoured.at/the-ai-industry-is-losing/