We examine nine commonly cited AI ethical principles and makes the case that what gets labeled "ethical" in AI policy is often a reflection of political perspectives and underlying assumptions rather than genuine consensus. The conversation covers the contested nature of foundational principles like fairness, transparency, and accountability, and why each one dissolves under scrutiny into competing values rather than universal ethics. We discuss the cultural and contextual variability of AI guardrails, the dominance of risk-based ethics in education policy, and feminist Duty of Care theory as a largely overlooked alternative framework.

I am interviewed on the history, present and future of MOOCs by Saffron Mccullough for the MOOC Institute. Topics range from the origin of connectivism, neural networks and what they need to work, and the impact of AI on the future of learning. For more on the MOOC Institute, see https://www.moocinstitute.org/home