All competencies under one factor: recognizing AI understanding intelligence understanding knowledge representation building decision trees understanding decision-making recognizing generative AI recognizing supervised learning understanding ML processes understanding AI learns from…
Organized into 5 "facets:" 1) understanding AI’s nature, 2) recognizing AI’s capabilities, 3) grasping AI’s underlying mechanisms, 4) discerning appropriate AI utilization, and 5) comprehending public perceptions of AI.
Use & apply AI Know & understand AI Detect AI AI ethics AI self-efficacy (problem solving) AI self-competency (persuasion literacy, emotion regulation)
Technical understanding Critical appraisal Practical application
Recognizing AI Interdisciplinarity Understanding intelligence General vs. narrow AI’s strengths & weaknesses Representations Decision-making ML steps Human role in AI Programmability Data literacy Learning from data Critically interpreting data Ethics