Ethical, Practical, and Policy Challenges of AI in Teaching Einsteinian Physics

The integration of artificial intelligence (AI) into the instruction of Einsteinian physics offers transformational possibilities with significant ethical, pedagogical, and policy concerns. AI-driven tools can improve students' understanding of intricate topics such as spacetime curvature, gravitational time dilation, and relativistic motion by providing adaptive feedback, simulations, and tailored learning environments. Nevertheless, their implementation prompts significant apprehensions over educator autonomy, epistemic legitimacy, algorithmic prejudice, data confidentiality, and disparate access to technology. The assumption of functions historically occupied by professors by AI systems poses a risk of dehumanizing physics education, transitioning from inquiry and dialogue to automated instruction. Moreover, AI-generated explanations may be scientifically erroneous or epistemically superficial, thus perpetuating errors instead of fostering profound comprehension. The digital divide exacerbates disparities between well-resourced and underprivileged schools, restricting equitable access to AI-enhanced education. Sustainable integration necessitates policies that guarantee transparency, data protection, teacher training, and curriculum reform that properly incorporates Einsteinian physics into scientific education. AI should function not as a substitute for educators but as a cognitive and pedagogical ally that enhances human instruction, fosters reflective thinking, and democratizes access to contemporary physics. This study advocates for a comprehensive paradigm that integrates technological innovation with ethical accountability, epistemological precision, and social equity.