AI Literacy for Adult Learners

Team: Maalvika Bhat, Charlotte Li

We are exploring how to design both general and profession-specific AI literacy interventions for adult audiences.

AI Literacy for Journalists

This project seeks to find out about the existing practices in journalism for producing journalistic pieces around the topic of Artificial Intelligence (AI) and how might designed interventions help journalists promote AI literacy for the general public through published materials. By conducting interview studies and co-design research,  we hope to gain insight on emerging journalistic practices surrounding researching and communicating about AI to the public, and we will develop design considerations and interventions to promote AI literacy in journalistic communications, as well as areas for potential future work. 

Explainable AI Tools

As AI becomes increasingly embedded in everyday life, understanding its underlying principles is crucial, yet educational resources for non-experts remain scarce. To address this, Bhat and Dr. Long developed three interactive web-based tools designed to demystify core AI concepts — edge detection, confidence thresholds, and sensitivity — through hands-on, engaging experiences.

Each tool was crafted using user-centered and learning sciences principles, allowing users to interact directly with complex AI processes. For example, “The Art of Edge Detection” visually explains how AI recognizes boundaries in images, while the “Confidence Calibration Explorer” and “Toggling Sensitivity” tools introduce users to the concepts of reliability in AI decision-making and algorithmic trade-offs. These tools empower users to adjust parameters, offering real-time feedback that helps deepen their understanding of AI’s strengths, limitations, and ethical implications.

In a study involving 42 adult participants, Bhat and Long found that engagement with these tools increased participants’ familiarity and confidence in discussing AI concepts. A mixed-methods evaluation highlighted interaction patterns like critical thinking, ethical considerations, and real-world application, showcasing how adult learners actively make sense of AI technologies.

This project not only contributes new educational tools to the AI and XAI communities but also provides valuable insights into designing effective, transparent, and learner-centered AI interfaces. The tools are accessible online, supporting a more inclusive AI literacy framework and encouraging ethical, informed AI engagement across diverse user backgrounds.

Bhat, M., & Long, D. (2024, July). Designing Interactive Explainable AI Tools for Algorithmic Literacy and Transparency. In Proceedings of the 2024 ACM Designing Interactive Systems Conference (pp. 939-957).

Bhat, M. (2024, June). Creative Explainable AI Tools to Understand Algorithmic Decision-Making.  In Proceedings of the 16th Conference on Creativity & Cognition (pp. 10-16).