AI literacy – my current position statement

Recently, most of my work has been focused on AI in education, particularly genAI. There’s a lot to be said and a lot to be done and I’m hoping to get back into some blog action and start posting somewhat regularly here.

First up is what I would essentially call a position statement. I’ve been teaching courses on AI literacy. I like the concept of AI literacy as it encourages us to focus on the specific competences that are needed to navigate contemporary info landscapes. However, I’m not fond of the idea of introducing “yet, another literacy” to the vast, and overly complex, array of literacies that have emerged in recent years (I partly blame PISA for this). The notion that every little thing constitutes a “literacy” creates endless layers of complexities as each one seems to require a new curriculum to add to the already full plate of curricula. So, obviously, the question has come up (far too often for my liking), whether we now need a new AI literacy curriculum, in addition to the technology literacy, information literacy, media literacy, etc. curricula that we already have in most educational systems? I say, no.

AI literacy should not be approached as an additional or parallel literacy, but rather, understood as the contemporary expression of technology, information and media literacy in an environment shaped by increasingly autonomous and generative systems. The rapid integration of AI into everyday tools, platforms and information flows does not create a wholly new domain of competence. Instead, it transforms the conditions under which established literacies are practiced. Interacting with predictive models, navigating algorithmically curated information and engaging with synthetic media all build on long-standing literacies that now operate within a qualitatively different technological landscape.

I feel that this perspective supports a more coherent and less fragmented understanding of literacy in education. Rather than expanding the literacy vocabulary with yet another category, it highlights how AI reshapes the core practices of accessing, evaluating and producing information. It also clarifies that educational responses should focus on adapting existing literacy traditions to AI-mediated contexts instead of developing isolated AI modules. In my view, this offers a far more robust conceptual foundation for curriculum design and professional development because it situates AI within the broader ecology of digital competence and underscores the continuity of literacy development across technological shifts.

A fair amount of work has been done to develop AI literacy frameworks and all that work is indeed very helpful. It helps us to identify the ways that our increasingly AI-populated environment differs from previous technological environments. What we need to do now is to re-examine existing technology and information literacy frameworks to make space for those differences. For example, to take an obvious element, existing frameworks are based on the assumption that all information can be traced to a human origin, i.e. when evaluating information tidbit X, we look for who first said X and the context in which X was said. Now we have to be open to the possibility that, actually, no one (i.e. no human) said X, but rather it was “said” by an AI. That in itself doesn’t necessarily mean that it’s invalid – we still need to evaluate the context and premises. This is a concrete example of a necessary competence change. But, under which heading do we make the necessary changes? Does this call for a change in our information literacy frameworks or should it be unique to our emerging AI literacy frameworks? To me, the obvious answer here is that our AI literacy needs change our information literacy frameworks.

So, the gist of what I’m saying is this. We need to develop AI literacy frameworks but not for the sole purpose of generating new frameworks. Rather, emerging AI literacy frameworks should be used to re-examine and reconfigure existing literacy frameworks.