ON A RECENT episode of Inside Learning, the podcast from our Trinity College-based technology centre Learnovate, host Aidan McCullen shared a story he’d heard from a chief operating officer.

A colleague had sent the COO a lengthy report, and he duly read it carefully and gave detailed feedback. Then he asked the colleague for his thoughts on the report. The reply? He had generated it using Gen AI and hadn’t formed any personal thoughts. No doubt the report was well written, neatly structured and perfectly plausible. Yet the colleague had never even read it, let alone struggled to understand what it said. So how could he stand over it?

This is the quiet risk in the age of AI – we are producing more while understanding less. Understanding can’t be generated on our behalf. It’s built slowly by expending effort and enduring frustration.

Learning requires the uncomfortable internal work of fitting new ideas into what our brains and bodies already know or believe. This is how we come to learn and through which our understanding becomes our own. AI can help us work through that pain, or it can allow us to bypass it entirely. Which we choose, and our children choose, has consequences for our capacity as human beings to think, judge and understand.

Everything becoming same same

You have no doubt noticed that while AI-generated emails, posts and reports are polished, well-structured and perfectly reasonable, they are also somehow interchangeable. When researchers, led by the University of Washington, put tens of thousands of open-ended questions to AI models, the kind with no single right answer, they found the models gave strikingly similar responses as described in the paper Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond). Even when systems were built by different companies, they arrived at the same ideas.

The researchers named this effect the Artificial Hivemind. There’s a simple reason for this. AI is designed to produce the most likely answer, the one that best fits the patterns in everything it has learned from. That makes it amazingly useful, but it also means it pulls inevitably and persistently toward a homogenised centre.

In the same way that cosmetic surgery is producing a convergence of........

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