• he OECD offers its current definition of Media & AI Literacy as “the set of competencies to interact with digital content and platforms effectively, ethically and responsibly.”
• By mixing media literacy and AI literacy, the OECD has set itself a significant challenge.
• Media educators, for example, have long sought to position media literacy in terms of the “3Cs” of consumption, creation, and critique
• And in the current political context, AI is not simply a “tool” for new forms of creativity and consumption, but a profoundly political technology requiring particular critical literacies.
• The illusion of understanding—the belief that being able to prompt a chatbot effectively constitutes deep knowledge—may be more dangerous than ignorance.

• It is now, through the AI literacy test, exerting its political authority over how AI skills are to be defined and valued.

  Its aim is to produce a globally standardized definition of AI literacy that is likely to erase nuance and diversity in approaches
• It will require AI literacy to be broken down into a series of measurable units which can feature as testable items

• As such, the assessment is not expected to be a conventional test, but organized as simulations making use of accessible existing “tools.” It will mobilise such tools to test a specifically defined “model” of AI literacy and its componentized “competencies.”

• AI literacy must become AI literacy-as-numbers, subject to techniques of metrology and amenable to comparison.
• It’s not hard to imagine there being eventual winners in the AI literacy rankings
• As with all OECD tests, the significance of the AI literacy assessment is not necessarily the quantitative results it will produce in more than half a decade’s time. It’s the activity that it incites in education systems in anticipation of the assessment. The existence of a test animates significant efforts to prepare students to take it.
• Audrey Watters argues that the kind of AI literacy promoted by the order serves governmental and commercial interests, but is likely to lack any criticality due to the US administration’s hostility to ideas about bias and discrimination.

• the AI literacy framework may focus centrally on skills of AI use (“learning to prompt” as the new “learning to code”) than any critical engagement with AI as a social and public problem.
• AI literacy can appear as a kind of technical training in efficient AI use—what I’ve elsewhere called “pedagoGPT” courses and classes
• digital literacy has become a powerful way of governing both teachers and students in schools.
• Educators and leaders may feel compelled to act on the OECD/EC/code.org framework in order to perform effectively on the test.
• AI literacy-as-numbers could make acting on AI a central preoccupation of schooling systems
• The OECD’s efforts should be understood as an attempt at infrastructuring AI literacy. Infrastructuring AI literacy means building, maintaining and enacting a testing and measurement system that will not only enumerate AI competencies, but make AI literacy into a central concern and objective of schooling systems

• They would have to perform to the measurement standards embedded in the infrastructure, following the prescriptions of the AI literacy framework, in order to “count.”

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