AIML publications and perspectives support its educational mission by making technical, scientific, and ethical questions more understandable to students, partners, and the broader public.
A research manuscript examining objective drift in large-language-model-assisted education, with emphasis on student agency, structured planning, acceptance criteria, and human oversight in computer science learning.
A public-facing essay on why human-in-the-loop approaches may better preserve human agency, practical judgment, and alignment with community needs than fully autonomous systems.