Understand how artificial intelligence actually works, from first principles to generative models
AI Explained: A Guide for Non-Technical Readers builds understanding of artificial intelligence from first principles rather than diving in at the top. Written by experienced policy and technical experts, the book walks through rules and logic-based approaches, statistical methods, neural networks, machine learning, and generative models in accessible, structured terms.
Each major section concludes with a dedicated use-cases chapter grounding abstract concepts in practical scenarios drawn from healthcare, law, and business. Rather than teaching readers how to build or deploy AI, the book answers a more fundamental question: how do these systems achieve the outcomes they produce? Coverage of AI policy, ethics, and societal impact rounds out the treatment, informed directly by the authors' advisory roles with governments and international bodies. Readers will also find:
- A structured progression from foundational principles through symbolic, statistical, connective, learning, and generative approaches to AI
- Real-world use cases connecting each branch of AI to familiar scenarios in professional and everyday contexts
- Balanced coverage of AI ethics, regulation, and societal impact drawn from direct policy advisory experience
- And more
