AI Literacies review

General claims:

• “Literacy” is often used in imprecise or very general ways. Often “literacy” is used as a synonym for a collection of skills or competencies, without any internal structure.

• Why is the term “literacy” used at all? There is a recognition of other “literacies,” particularly reading/writing and mathematics. So the connotation is just that of an important skillset. “Similar to classic literacy which includes reading/writing and mathematical abilities, AI literacy has emerged as a new skill set in response to this new era of intelligence.” (@ng2021, p. 504)

• The computational literacies framework [@kafai2021] is helpful for how it contrasts the state of CS education with that of AI education: most CS education heavily emphasizes cognitive learning, while AI education almost entirely avoids cognitive learning.

  • Also could provide some clarity around “AI ethics.” Usually not characterized–are we talking about ethics in terms of individual morality? In terms of what constitutes a just society?

• This argument that the idea of literacy is under-developed is congruent with the idea that lots of people have already figured out powerful ways to use AI in education, but that we really don’t have a clear paradigm for what students should learn about AI.

• @casal-otero2023:

  • Two approaches to defining AI literacy: “learning experience and theoretical perspective” (p. 1).
    • Parallels to @wilkerson2020’s argument for practice-driven understandings of CT
  • Fuzzy operationalization of “Literacy.”
    • “some researchers believe that AI education should be considered as important as literacy in reading and writing” (p. 2)
    • “The highly interdisciplinary character is also another factor to consider.” (p.2)
    • “AI literacy can be defined as a set of skills that enable a solid understanding of AI through three priority axes: learning about AI, learning about how AI works, and learning for life with AI”

@ng2021:

• Coded for four “AI literacies:”
  • “know and understand AI”
  • “apply AI”
  • “evaluate and create AI”
  • “AI ethics” This is just Bloom’s taxonomy, with ethics thrown in. If we wanted to taxonomize the modes of AI understanding, it would be more suitable to

@wiggins2005’s facets of understanding

In any case, this is not what is meant by literacy. When New Literacies scholars pluralize the term, they refer to distinct forms of social meaning-making, distinguished by different cultures and distinct media.

• @burgsteiner2016 take a very different approach, organizing their learning goals as an introduction to subfields of AI, which could be the subject of later specialized coursework. This approach, reminiscent of Bruner’s [-@bruner1960] “spiral curriculum” by which “any subject can be taught in an intellectually honest form to any child at any stage of development” (p. 33), is quite different from other conceptualizations of what K12 students ought to learn about AI.

@kandlhofer2016 also uses an approach like @burgsteiner2016, focusing on introducing subfields. Their definition of literacy does include a developmental trajectory.

Reflections on AI4K12. What do I make of this? It seems a bit unrealistic. For example, when the framework says 9-12 grade students should be able to explain