Designing for human-AI complementarity in K-12 education

Abstract: Recent work has explored how complementary strengths of humans and artificial intelligence (AI) systems might be productively combined. However, successful forms of human-AI partnership have rarely been demonstrated in real-world settings. We present the iterative design and evaluation of Lumilo, smart glasses that help teachers help their students in AI-supported classrooms by presenting real-time analytics about students' learning, metacognition, and behavior. Results from a field study conducted in K-12 classrooms indicate that students learn more when teachers and AI tutors work together during class. We discuss implications for the design of human-AI partnerships, arguing for participatory approaches to research in this area, and for principled approaches to studying human-AI decision-making in real-world contexts. Artificial intelligence (AI) systems are increasingly used to support human work in deeply social contexts such as education, healthcare, social work, and criminal justice. In these contexts, AI can automate routine parts of practitioners' work, while freeing up their time for activities they find more meaningful (17, 28, 39).