I just had a really nice email from a high school student in South Africa saying that he’d read one of my blog posts and it had inspired him in his own school-based research. He was chancing his arm a bit and wondering whether he could interview me. But, he appears to be someone rather like I was when I was his age, and left it to the last minute and wanted to interview me today! I offered to speak to him on Monday, but that was a little bit too late for him. Nevertheless, what it did was make me think: my God, I haven’t written anything on my blog for months. So I had a look and the last entry was in May. How is that even possible? I know we had a hot summer but it feels now like it lasted about 5 minutes.

Anyway, it made me think, firstly, why am I not writing on my blog? And on that question I refer you to my calendar, my grey hair and the anguished look behind my eyes. But it also made me think about where everything is going. Because even though I don’t really have that much time to get my thoughts onto paper, doing so actually really helps me. It helps me cohere ideas and learn for myself exactly what it is that I’m thinking, particularly when it’s messy and messy is a word that captures not only the World but a lot of HE right now.

I might not be writing much (beyond completing a couple of chapters and doing a few reviews; nearly forgot about those) but I  do nevertheless still read a lot of controversial posts, especially on LinkedIn where expatriates of Twitter now seem to have gone to argue and share pictures of their dinners (or is that just my algorithm?). It’s especially grim in the AI and education space. The digs and the jibes from all ‘sides’, the over exhuberant ‘influencer’ language effusiveness from others. The horror at our imminent destruction. The bafflement that we’re not taking it seriously enough, or not using it well enough. Everybody’s going to be stupid within the next five years! No, everybody will be able to do super-intelligent things within the next five years with all their free time! No, actually AI will kill us all!  All of this kind of stuff. Actually it gets to me quite a bit.  Some of it is certainly ill-informed. But even when it isn’t ill-informed, it is very often incredibly bile-filled and increasingly acrimonious. Like a mirror to the polarised political car crash unfolding across the world we just don’t seem to have preserved or value reasoned debate.

I say this all the time but we have to be a little bit more nuanced, particularly from the perspective of those of us working in academia. This is unlike any phenomenon that has come before. And I increasingly find myself wanting to find a language for talking about it. A language of compromise, perhaps. A language of mutual respect. A language that enables us to take some of the heat out of the vitriolic, the dismissive, the scornful, the abusive. The shouting prevents people from allowing themselves the space to ask questions that they worry might be perceived as stupid. It makes people pick a side. And, while here I am picking the fence/ shelf/ tightrope (select preferred metaphor), I’m increasingly convinced that picking sides is one of the least useful things we can do.

A lot and not very much has happened since I last posted. One thing I think has genuinely shifted is that the big tech companies have recognised the necessity of, at least superficially, challenging the very real threat of overdependence, cognitive dependency or excessive cognitive offloading. And cognitive offloading is an interesting example of precisely the problem I’m talking about. As many people with superior intellects to mine have pointed out, we have been cognitively offloading in all sorts of ways, and with all sorts of tools, since the dawn of civilisation. Whether it was chipping symbols into rocks to keep tabs on stock or to confirm contracts, all the way through to everything we have done in the digital era and continue to do now. Cognitive offloading isn’t inherently a bad thing; it’s a thing humans do. It is the way in which you do it, when you do it and the tools with which you do it that are the issue. And even that relatively simple discrimination, that simple distinction, seems sometimes to have been lost on people who are very, very intelligent themselves and very well educated and should know bloomin’ better.

Yes, the big tech companies are obviously doing their best to muscle in on the learning space. There has been a noticeable reframing of AI away from the idea of the glorified search engine, which it never was anyway, and the quick-answer machine, towards the idea of the learning machine. Something that can supposedly support cognitive development rather than replace it. Whether that is actually having much impact on student behaviour is another matter.I suspect it is having limited, perhaps minimal, impact so far. All the evidence I see seems to suggest that sophisticated workflows are still very much in the minority. Relatively simplistic uses and applications of free versions of tools remain the norm. And that, I think, is where some of the work now lies. Can we properly help students understand where the affordances lie and where the issues lie?

We have some brilliant colleagues here at UEL doing fantastic work around defining, or helping define for students, what it means to be an AI critic. And the more we can do of that, the better. But we also increasingly need to acknowledge that there are a lot of students who are either vocally taking a stand against AI or, if not exactly taking a stand, are reluctant in their compliance when asked to use AI tools. And often quite cynical and sneery about it.

My own daughter is 15 and talks about AI slop, AI garbage, AI propaganda and AI misinformation. Its rep is poor amongst the youth, I think it is fair to say. That matters because while all of this is going on, AI itself is changing. Big tech is steering towards learning utilities framings – from beyond that idea of a quick-answer machine towards something that can supposedly help develop synaptic firing and the cognitive development. At the same time, we have the increasingly agentic functions of new tools, the vibe-coding potential, the creating-things potential and everything else that is emerging.

It’s  particularly complex for those people who have still refused to really engage with or touch these technologies in any meaningful way, or who abandoned them early on because they thought, ‘Yeah, this isn’t for me’, or ‘this is killing the planet’, or for any of the other perfectly legitimate reasons people have for resisting. Meanwhile, people in roles like mine are trying to work out how we can best get people up to speed, whether they be staff or students, whilst continuing to acknowledge the very many valid reasons why people might push back, resist or reject. And, increasingly, I think all of this has to connect to the bigger questions about higher education. It’s still all about:

What is education for?

What is assessment for?

What is it that we are actually trying to judge?

What is it that we need to teach?

What is it that we want to evaluate?

And how well do our current structures, pedagogies and assessment designs actually enable us to do those things? Which is perhaps the funny thing about looking back at what I was writing in May. The technology has moved on an the tools are faster and more capable. The rhetoric has become louder and with that the polarisation is greater. The arguments about dependency, cognition, authenticity, assessment and human capability have become more urgent. But the questions underneath it all haven’t really changed. What are we trying to achieve through education, and which bits of that should technology help us with?

And perhaps, somewhere between the evangelists telling us that everything has changed and the uber sceptics telling us that everything is being destroyed, there is still some space for the rest of us to work that out, without shouting at each other like hecklers and snarly, stick wielding pensioners at a reform rally, sorry, conference.