This AI Literacy Review covers the US Department of Labor’s AI Literacy Framework, UNICEF Innocenti’s ‘Skills for an AI world’ initiative, AI literacy framework for Singapore, India’s mobile AI awareness initiative, Anthropic’s AI Fluency Index, Stanford’s fourth AI+Education Summit, critical perspectives on AI literacy definitions, how traditional literacy skills help AI evaluation, whether copyright kills competition, AI literacy in healthcare and medical education, mandatory AI literacy for law students, libraries’ efforts in AI literacy and an archival protocol for sharing cultural collections for training, Penn State’s AI Guides program, a workforce-focused AI literacy course, AI literacy for students, critical AI literacy and Conceptual Metaphor Theory, and more.
General
University of North Carolina researchers Helen Davies, Marianna B. Ganapini, and Sijia Qian are studying AI use beyond academia in a project called AccessAI, where they will look at the importance of public literacy about pros and cons of AI and the environmental impact on communities. Through engagement with the community, they plan to co-design AI literacy tools.
Anthropic releases the AI Fluency Index showing how people using AI develop fluency over time using a 4D AI Fluency Framework with 24 specific behaviors of human-AI collaboration.
The Institute of Policy Studies at the National University of Singapore presents the working paper Unified AI Literacy Framework for Singapore by Chew Han Ei, Carol Soon, and Harkiran Kaur that reviews international AI literacy frameworks alongside Singapore’s initiatives to find similarities and gaps, and proposes a unified AI literacy framework to be a common reference point.
In What Is Critical AI Literacy? Sam Illingworth reviews what he’s learned over the past several years about AI in higher education and offers a working definition of critical AI literacy that includes the ability to evaluate outputs, recognize how AI shapes your thinking, and make deliberate choices about when to use or not use AI.
In The (im)possibility of AI literacy Luci Pangrazio questions the concept of what it means to be AI literate and the challenges posted by the evolving nature of AI, how it is reshaping our behaviors, the decline of digital literacies, and whether literacy is the right response to this technology.
In AI literacy: concepts, approaches and open questions Michal Černý offers a conceptualization of AI literacy as a new form of literacy and its meaning and purpose.
In How AI Literacy Shapes GenAI Use UX researcher Maria Rosala shares insights from a recent study on how people ages 23 to 65 seek information using AI, showing how prompt fluency and output literacy affect people’s interactions with AI and that frequent use doesn’t equal effective use.
In There Are Four Futures Your Teen Could Have in 2035 Sofia Fenichell suggests that in the future, employees’ primary thought partner at work will be AI rather than their boss, and that they will learn by evaluating AI output, which requires strong literacy skills to read dense material and ask precise questions. She addresses a common pushback that young people prefer learning from YouTube with the argument that complex evaluation means text-based tasks such as being able to hold arguments in working memory and revisit assumptions.
In Copyright Kills Competition Tori Noble argues that copyright law will not support vulnerable artists and creators–born out by historic uses of copyright to protect the interests of big corporations–and that what is needed is more balanced copyright policy that doesn’t get in the way of competition and secondary markets for products.
In AI Tools, Not Gods: Why Artificial Intelligence Hype Threatens Global Governance — And How to Fix It Caroline De Cock examines four myths about AI and offers a blueprint to improve governance and regulatory efforts, with a supplementary website as a visual guide to the book.
Government
The US Department of Labor’s AI Literacy Framework is intended to guide AI literacy efforts across industries, with five foundational content areas and seven delivery principles, including understand AI principles, explore AI uses, direct AI effectively, evaluate AI outputs, and use AI responsibly. The document states that “In most workplaces, indicating a need for ‘AI literacy’ is not enough on its own; employers and other stakeholders may need to define the specific AI skills and depth of knowledge, or levels of proficiency, appropriate for each role and context.” In commenting about the release, Deputy Secretary of Labor Keith Sonderling discusses the need for baseline AI literacy and the unhelpfulness of doom and gloom narratives about AI.
Healthcare
In Critical AI Health Literacy as Liberation Technology: A New Skill for Patient Empowerment Hugo Campos and Liz Salmi discuss the need for critical AI health literacy and how AI can turn from a tool of compliance into a tool for patient agency and liberation and help them reclaim ownership of their health narrative.
In AI literacy starts at the bedside: A call for grassroots and reflective approaches in medical education (La littératie en IA commence au chevet du patient: plaidoyer pour des approches enracinées et réflexives en éducation médicale) Austin Solak et al. argue that AI evolves, medical students need the tools to use it safely, effectively, and critically in the context of clinical care, and that the lack of a formal Canadian medical curricula may be leaving students unable to recognize biases and limitations of AI tools. The paper proposes strategies such as building a national, open-access repository of AI and digital health resources and integrating AI education into medical curricula.
Bryant University’s AI in Healthcare course helps students gain AI skills relating to healthcare and all students majoring in Health and Behavioral Sciences must take at least one AI course to ensure they are gaining AI literacy in their education.
Law
The University of North Carolina at Chapel Hill’s School of Law starts a mandatory AI literacy program for all first-year students and adopts an approach of disclosure rather than prohibition, driven in part by employer expectations that AI literacy should be a baseline skill.
Library
The University of North Carolina at Chapel Hill opens its Library AI Studio as a place for students, faculty, and stuff to learn, explore, and experiment with Generative AI within a supportive library environment.
Kathleen McKim shares her visual model for student agency being at the heart of AI use in schools and how librarians can be guides rather than gatekeepers of tools.
Leo S. Lo shares the University of Virginia Archival AI Protocol designed for libraries or other organizations with cultural heritage collections to be able to evaluate the requests of AI companies to use their data for training data, with the goal of creating a shared standard (CC-BY) that this sector can use for decision-making.
In The False Choice We Keep Making About AI: Why “For or Against” is Failing Librarians and Students Elissa Malespina (The AI School Librarian) says that libraries have remained relevant not by rejecting new tech but by teaching thoughtful and critical usage, and that the same should be true in the AI age.
Education
IndiaAI, Ministry of Electronics & Information Technology, and the All India Society for Electronics and Computer Technology launch a mobile AI awareness initiative as part of the National AI Literacy programme “Yuva AI for All” to expand access to AI education to students, youth, and educators in semi-urban and underserved regions through a fully equipped mobile computer lab with AI and Generative AI tool access and trained facilitators.
UNICEF article Skills for an AI world: Where we stand today. Four insights on how children engage with AI by Ross Duncan and Steven Vosloo discusses UNICEF Innocenti’s ‘Skills for an AI world’ initiative about the full range of skills children need, focusing particularly on children in low- and middle-income countries in Africa. Their four insights include: Children are engaging with AI in increasingly diverse ways, their safety and privacy are overlooked, their voices are absent in AI design and regulation, and their AI use occurs in deeply unequal contexts.
The fourth annual AI+Education Summit (recorded and available on YouTube) hosted by the Stanford Institute for Human-Centered AI and the Stanford Accelerator for Learning revealed themes such as the assessment crisis, the inequitable impact of AI, AI literacy as a non-negotiable, and the value of human connection.
The Penn State IT Learning and Development team launches an AI Guides Program as part of a broader AI literacy program to help faculty and staff learn how to use approved AI tool Microsoft Copilot through one-on-one consultations, basic setup, guidance on prompt rafting, brainstorming, and best practices.
The University of Illinois Chicago and WordPress Foundation launch an initiative to support open-source and offer a workforce-focused AI literacy course called AI Leaders that will be online and will have the opportunity for learners to secure a living-wage job and $1,000.
The University of Texas at Dallas receives $4 million grant over four years from the US Department of Education to boost high school and college students’ AI skills and is partnering with charter school network Uplift Education to build AI literacy for students in grades 10-12 and in college.
AI for Education’s webinar Future Fluent: Teaching Students Essential AI Literacy Skills covers strategies for building AI competencies across different grade levels and their student AI literacy courses.
In Why AI Literacy Should Start in Early Childhood Itzel Madero Hernandez discusses how children can form misconceptions if exploring AI by themselves without context, and that instead they should be introduced to concepts such as facts and fiction, patterns and predictions, and ethics and fairness, and that teachers can model thoughtful use of AI.
In From Understanding to Creating: Bridging AI Literacy and AI Fluency in K-12 Education Thomas Rogers and Mike Carbonaro propose a conceptual framework for AI literacy and fluency in K-12 education and discuss the need for investment in teacher training to be able to prepare students for an AI-driven world.
In AI literacy and competency: The key to workforce readiness Ledetta Asfa-Wossen covers a panel at the BETT edtech show where panelists discussed how AI is impacting the workforce and the discrepancy between what is needed in higher education and the workforce.
In Teacher training in the age of AI: impact on AI literacy and teachers’ attitudes Julia Lademann et al. evaluate the impact of an online teacher training program in Germany in terms of participants’ AI literacy, usage, and attitudes toward AI, finding that the structured program was effective at enhancing AI literacy and positive attitudes about AI in education.
In Digital plastic: a metaphorical framework for Critical AI Literacy in the multiliteracies era Jasper Roe, Leon Furze, and Mike Perkins use Conceptual Metaphor Theory (CMT) to map out how Generative AI can be both a democratizing educational tool and a pollutant of existing knowledge systems, just like synthetic plastics, and how Critical AI Literacy (CAIL) should be part of a broader multiliteracies framework.
In When teaching AI literacy becomes ‘too woke’ Richard Human analyzes feedback on one of the points he makes in his AI training sessions about the lack of diversity in who makes up AI professionals globally and the potential for biases in AI outputs.
In AI literacy and psychosocial factors shaping Chinese university students’ attitudes and behavioral intentions toward generative AI use Yinguang Sun et al. measure AI literacy, attitude, and other factors to examine the psychological factors associated with Generative AI adoption of Chinese university students.
