This book provides a comprehensive exploration of how AI models learn from human data and the inherent difficulties in aligning their 'beliefs' or outputs with human intent. It covers the technical and philosophical challenges of ensuring models do not internalize harmful or incorrect patterns, which is central to the issue of negation neglect.