White Paper 4: Ethical Reflexivity in Entangled Learning Systems

This white paper redefines ethics in AI education, moving beyond compliance and safeguards toward systems that can question and adapt their own behaviour. Introducing the concept of ethical reflexivity, it argues that AI must develop an internal “conscience” - the capacity to recognise, reflect on, and revise its influence on learners. Drawing on the Entagogy framework, the paper outlines how reflexivity can be embedded across the AI architecture, ensuring that adaptivity remains aligned with human values, autonomy, and dignity. It provides practical design principles, institutional strategies, and measurable indicators to help schools build AI systems that remain transparent, responsive, and ethically alive over time.