AI Literacy
Overview
AI literacy studies the knowledge and judgment people need to understand how AI works, use it effectively, recognize its limitations, and make informed choices about its social effects. Common approaches include scaffolded courses, project-based and no-code activities, prompting instruction, simulations, and exercises that expose learners to AI errors; studies assess these through experiments, surveys, classroom artifacts, and analysis of human-AI interactions. Work spans K–12 and higher education as well as professional settings, with growing attention to trust, privacy, environmental costs, equity, and governance. A central tension is that familiarity or confidence using AI does not guarantee sound understanding or calibrated reliance, while extensive assistance can support immediate performance yet bypass learning or widen differences between users.
Latest papers
43 papers1 paper in the last four weeks, down 83% on the four weeks before. 0.0% of all new papers.