A landscape of havoc and fracture
The last paragraph of this post by Julian Stodd, which I discovered via OLDaily, points to something emancipatory about generative AI that I think some people may have missed:
An interesting feature of the Generative AI revolution is that whilst the technologies themselves are monumental, both in terms of complexity and physical energy and scale, it may well be individuals, at scale, who drive the true change. Not a single technology that breaks in, but rather people breaking out. Breaking out of restrictive and constrained structure.
Stodd is part of a doctoral programme, and (with no lack of hyperbole) discusses how his cohort is likely to be “the last to really read books… to really write for myself… to be confused and lost in thought.” He calls this a “landscape of havoc and fracture” and points to four dimensions of this shift:
Dialogic Engines – synchronous iteration and exploration of ideas, warping legacy ideas of trust, self doubt, foolishness, failure, and curiosity. As we wrote in ‘Engines of Enagement’, Generative AI makes high quality dialogue a commodity, but not simply as a service – it shifts the social context of such. So we can be in dialogue as a solo feature, removing all social judgement of curiosity and ignorance, if we dare.
Agentic Retrieval – not just a search engine, but a context setting system. These tools can shift the boundaries of context – not telling us what we asked for, but giving us what we may need. And from a perspective of virtually unbounded knowledge. We can factor this into our dialogue – asking for breadth and challenge to our thinking – or we may find it just lands. I think that systems shifting context is highly significant, as the fracture and evolution of context is a key part of insight and even paradigmatic change.
Trans-disciplinarity as the norm: our taxonomies of knowledge are not natural, but rather shaped by legacy mechanisms of need, discovery, ownership, and understanding. We have tended to segment our knowledge and hence structures of learning (as well as power, status, and identity) vertically around these themes. So we have engineers and poets, but not many poetic engineers. I think Generative AI changes this in significant ways, if we allow it to: permits a broadening of vocabulary and conception, a translation engine if you like, but also a provocative one – if we ask or if it offers.
The Primacy of Sense Making: I’ve said for some time that knowledge itself is shifting in the context of the Social Age, and Generative AI scales this change. The latest GenAI tools are Engines of Synthesis, reflection and contextualisation, leaving us in a radically broadened landscape of sense making as individual and collective feature. And I don’t think sense making per se is at threat of absorption by technology. Not that the Engines cannot make sense, just that our act of consumption is inherently linked to re-contextualisation and insight. In other words, if the technology has already chewed it over, we will chew it over again. It just broadens the space and foundations for us to do so.
I’ve been using GPT-4o for my MSc and it’s so much better and deeper to learn with an assistant than to rely on what’s provided to you as a student, and what you can discover by just wading through books and articles.
Source: Julian Stodd’s Learning Blog