I am very clear what will be the future of learning, but less sure of “learning”. I go home by two days at the technology apprenticeship conference, where the question of change is in the mind of each. Change through technology, methodology, social context, etc. With of course.
In a neurological sense, learning will continue to be what has always been: our main adaptation mechanism, the thing that allows us to make new mistakes, instead of dying of the ancients. We are, in the soul, both learning and narration creatures.
Learning, in the structural sense, is invented: areas, technologies and approaches to codify specific results on the scale, to stimulate consistency and conformity, replicability, quality, scale. Learning activity, learning systems. And these, of course, change. Or should be.
Of course, as with all that humans create, it is maintained in the human context, and in this case, they are contexts of power, knowledge, influence, control, law, religion, etc. Awareness is controlled, as is learning.
Navigating this dynamic: the change due to technologies and social contexts is difficult, but familiar. Blee on the context of social age, and the emergence of Genai on a large scale, and ease, and you find that many structures which nest around codified learning are, themselves, fragmenting.
More a question of “change in a system”, but of change of the system itself. And not from “certainty” to “certainty”, but rather ambiguity. Or rather, we must seek ambiguity and uncertainty.
Radical connectivity and various social age technologies (even before we superimpose in AI) are fracture and emergence characteristics. There is no clear “truth”, but rather a potentially precious workforce.
It talks about our individual need to explore and our organizational need to adapt. For me, it is naive to see AI without seeing it in the social context. Both in terms of the way this context shapes AI and on the way in which the AI fragments the aspects of our Social context.
My current work around this – which can shape a series of engagement engines – is to consider both “strategic AI” and the “social context of AI”.
#Workingoutloud on learning and AI
