[NB. These notes are for a book that might not come out until early 2027 … for the time being I am writing about the GenAI bubble in the past tense – as a lesson to reflect on, rather than something that we will be still taking seriously in two years’ time!]

One of the inconvenient truths of the GenAI bubble was that the actual applications of the technology were not very good (and certainly not as all-powerful as many of its proponents would have us believe). A couple of years after the launch of ChatGPT, Tressie McMillan Cottom felt compelled to call GenAI out as ‘mid tech’ – limited tools capable only of middling, average, mediocre results, all buoyed by a never-ending succession of exaggerated claims and frivolous use cases. 

Cottom’s main observation was simple enough. In reality, people’s experiences of GenAI-assisted tasks were hardly that life-changing, and the amounts of work being done around the technology belied any claims of this being a means of saving time and being effortlessly more efficient:

“Most of us aren’t using AI to save lives faster and better. We are using AI to make mediocre improvements, such as emailing more … AI spits out meal plans with the right amount of macros, tells us when our calendars are overscheduled and helps write emails that no one wants. That’s a mid revolution of mid tasks”

As far as Cottom was concerned, the rise and fall of the GenAI hype bubble during the first half of the 2020s offered an important lesson for educators faced with claims of how AI is set to ‘transform’ education. This is not to deny that other forms of artificial intelligence are impacting, for example, in helping experts model changing climate patterns, identify serious illness and other specialised life-changing use cases. Yet, this is to warn against giving a free pass to far less impressive forms of AI being thrust onto our schools, universities and education systems. Regardless of how AI might be used in cancer research or space exploration, Cottom stressed the importance of acknowledging that educational AI has so far proven to be much less of a ‘game-changer’:

“That tech fantasy [in education]  is running on fumes. We all know it’s not going to work. But the fantasy compels risk-averse universities and excites financial speculators …For now, AI as we know it is just like all of the ed-tech revolutions that have come across my desk and failed to revolutionize much …. They make modest augmentations to existing processes. Some of them create more work. Very few of them reduce busy work” (Cottom 2025)

However, the fact that educational AIs are not very good is not to assume that the technology will not have a significant impact on education. As Cottom pointed out, emerging tech has been used for decades to “justify employing fewer people and ask those left behind to do more with less”. The prospect of a teaching chatbot (however mediocre it might be at teaching) therefore gives every education decision-maker who wants to, the opportunity to cut jobs of real-life teachers. 

So, we need to stay attuned to the politics of educational AI – especially in terms of the politics of educational work and labour. In this current political climate, it is highly unlikely that AI will be used to give teachers more free time. Instead, it is highly likely that we will see instances of AI being used to pile more work onto teachers while getting rid of their colleagues. As Cottom concluded, “[AI] does not have to be transformative to change how we live and work. In the wrong hands, mid tech is an anti-labour hammer”.

Reference

Cottom, T. (2025).  The tech fantasy that powers AI is running on fumes. New York Times, March 29th, www.nytimes.com/2025/03/29/opinion/ai-tech-innovation