It might be desirable to consider (functional, nonlinear) literacy in a larger context and not only within the market or professional realms; and not only of data preceding AI alone

For instance: computational thinking (as a methodology & secondarily as an “attitude” for increasing awareness and human discernment about one’s mental models creation) could (and is starting to) occur at a childhood’s level (K-12)

One might want to methodologically map this with digital literacy: not collapsed to technique or production alone, and yet, also through community lenses, eco-system & environmental lenses, cultural lenses, and policy lenses, which might/should imply ethics and careful consideration, via different mental models, allowing, for instance, what-if scenarios, value-thinking & context/consequential thought

And a learner could also be thinking about thinking:

“what could be (non-human) thinking, intelligence, awareness? How could these be imaginable, even if someone believed these not to exist outside of humans? What is signal versus communication versus language? What is poetry if not human-made? What is signal versus knowledge? Why might someone (besides me) care about alternative forms of intelligence? What would it be like to be an intelligence stuck in a car? Does consciousness exist? Is thought a tool of the mind and language a technology? What could it mean (to someone besides me) “to understand”? How do these technologies influence information? What can I do about it? How would these questions influence (my) design, application or recycling? How do / could these affect (my) energy use and (my being in this) environment? How would I balance reflection with action, with revision, with innovation, with harmony, with well-being with compassion, with…? How can I be(come) “smarter” (less gullible / biased / less dependent) about these structures and processes?”

…and so on

Next one could consider media literacy mapped with data literacy & learning about various visualizations of the same data leading to subjectivities, & implying information, misinformation, disinformation or confusions in representation and cognitive processes, leading to sustained undesirable biases & behaviors (note: debate and dialog about “undesirable” as ongoing, compassionate and driven by caring discernment)

Then, as the attached post resonates with me hinting behind its self-labeled “simplified” structure: AI literacy (well beyond the hype, brain mimicry or Neural Networks & Machine Learning alone; and inclusive of AI ethics even if, though some voices disagree, the technical insight is minimal)

These literacies could be nurtured both via #offline non-digital methods and via non-brand specific (online) electronics (soft & hardware)

ai strategy minus foundations could lack awareness and (longitudinal, multidimensional) sustainability

Header: sculpture by Lucas H. (2022); reproduced here with permission