I was recently told that AI literacy is a problem rather than a solution, that it distracts education from its democratic purposes and amounts to a surrender to technology.
My first objection concerns the very nature of AI literacy. Far from being a form of capitulation to technology, AI literacy can help demystify it. It enables learners to understand how systems actually work, what their limitations and underlying assumptions are. It also permits the deconstruction of the hype and the deterministic discourses promoted by industry actors. Understanding AI is precisely what allows individuals not to surrender to it.
AI literacy also helps learners see that generative AI represents only a small part of the broader AI field. Important issues related to machine learning, automation, decision-making systems, computer vision, predictive analytics, and robotics receive far less public attention, even though they are no less critical to our democratic societies.
This wider view matters because AI raises distinct challenges across sectors: in healthcare, journalism, education, finance, justice, public administration, and the military, its uses, limitations, possibilities, and risks are not the same. Ethical discussion about AI cannot be meaningful without a basic understanding of these specificities. AI literacy provides the foundation for critical engagement with issues such as bias, discrimination, surveillance, accountability, environmental impact, and human autonomy. It likewise allows learners to understand regulatory frameworks and to engage with them critically.
AI literacy provides individuals with the relevant tools that help to decide whether to engage with technologies, how to engage with them, and when to resist them. In this sense, it fosters responsible and critical use of pervasive technologies rather than passive adoption.
It also helps learners understand the wider digital environment in which AI operates, such as platforms, algorithms, social media, and search engines. Therefore, it favours the understanding of how these shape access to information, participation in public life, and the construction and dissemination of knowledge.
AI literacy is certainly not a panacea, and it should not become the ultimate goal of education. On this point I agree. But if AI literacy is excluded, what exactly remains as a response to socio-technical systems that are now deeply embedded in everyday life and increasingly involved in decision-making that affects individuals and societies?
McLuhan argued that the challenge is not only how technologies are used but also how they shape environments. Building on this insight, AI literacy can be understood as a means of identifying, framing, analysing, and critiquing these environmental effects, whether social, cultural, or perceptual. Education is precisely where such learning should take place.
Nevertheless, AI literacy need not be conceived as yet another literacy added to an already crowded list. It can rather be understood as a convergence of existing literacies, such as digital, media, information, critical, ethical or civic literacy. Understood this way, it does not displace but serves the broader human purposes of democratic education.
