As artificial intelligence increasingly shapes how people learn, work, and communicate, governments and international organizations are prioritizing AI literacy as a central educational objective. Global and national policy initiatives, including UNESCO’s Guidance for Generative AI in Education, the U.S. Executive Order on Advancing AI Education for American Youth, and the National Artificial Intelligence Initiative, reflect a shared recognition that AI literacy is now a critical 21st-century competency for preparing learners to engage responsibly and effectively in an AI-infused world. AI literacy is commonly defined as a set of competencies that enable individuals to critically evaluate, communicate with, and ethically use AI technologies, extending beyond technical knowledge to include awareness of AI’s social, cultural, and ethical implications. As generative AI (GenAI) tools become increasingly embedded in everyday educational and professional practices, the urgency of developing meaningful, developmentally appropriate AI literacy has intensified.
This workshop aims to bring together researchers, educators, industry professionals, and policymakers to explore comprehensive strategies for AI Literacy education that serve non-technical learners, including students and teachers in K-12 and higher education, and the broader workforce. The objectives of the workshop are to explore the design and evaluation of AI literacy programs, examine educational technologies that support AI literacy development, advance approaches to AI literacy assessment, discuss pedagogical strategies for diverse learners, and address issues of diversity, equity, and inclusion in AI literacy.
We particularly invite submissions that:
Investigate frameworks and methodologies for implementing AI literacy, ensuring broad accessibility and meaningful impact across diverse contexts.
Highlight and evaluate emerging tools and platforms that enable hands-on AI experiences and conceptual understanding for non-technical audiences.
Advance new paradigms for measuring AI literacy, including project-based tasks, reflective portfolios, and performance-based evaluations that capture both practical skills and ethical considerations.
Explore inclusive teaching approaches that demystify core AI concepts for K--12 students, educators, and professionals seeking upskilling, regardless of subject-area expertise.
Identify and address systemic and cultural barriers limiting access to AI education, proposing strategies and policies to foster equitable participation and representation in AI-driven fields.
We invite you to submit your original work for presentation and discussion. There will be three types of submissions:
Research Papers (12 pages, including references)
Work-in-progress Papers (6 pages, including references)
Poster (3 pages, including references)
Note: References count towards the page limit. You will select your submission type on EasyChair.
Blinding: All submitted papers should be carefully blinded for review. Take care to remove all authors' names and identifying information (e.g., grant numbers), and refer to any of your prior work in the third person (e.g., "Previously, Smith et al. did ... [1]" rather than "In our prior work [1]").
As we plan to publish all proceedings with CEUR, all submissions must be formatted using the CEURART style, the CEUR Workshop Proceedings format. The files for the CEURART style are available as an Overleaf template (for LaTeX users) and as a downloadable ZIP file (for both Word and LaTeX users, as it includes both LaTex and Word templates).
Submissions are handled via EasyChair: TBD
April 6, 2026: Open Call for Submissions
May 1, 2026: Abstract Deadline for Papers from all tracks
May 8, 2026: Paper Deadline for Papers from all tracks
May 29, 2026: Notification of acceptance for Papers from all tracks
June 12, 2026: Camera-Ready Version Deadline for Papers from all tracks
TBD, 2026: ALIT4ALL: 2nd International Workshop on AI Literacy Education For All
ALIT4ALL proceedings will be published online via CEUR. ALIT4ALL proceedings should be considered semi-archival. This means that the papers are peer-reviewed, published, and citable, but are still appropriate to extend for submission elsewhere. Some venues may expect that work published in a workshop should be revised before republication in a conference or journal, and we expect this should be straightforward to do with the feedback you get by presenting at ALIT4ALL. For example, ACM conferences expect an extension of 25%. Authors retain the copyright to their work when published through CEUR at ALIT4ALL.