Pete Rai – författare

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 AIReal-world use cases connecting each branch of AI to familiar scenarios in professional and everyday contextsBalanced coverage of AI ethics, regulation, and societal impact drawn from direct policy advisory experienceClear explanations of how neural networks, machine learning algorithms, and large language models produce their resultsAn approachable foundation suited equally to cross-disciplinary university courses and independent professional developmentWritten for lawyers, business leaders, policymakers, healthcare professionals, educators, journalists, and other non-technical professionals who need to understand AI rather than build it, this book replaces confusion with structured knowledge of how artificial intelligence systems operate across the full scope of the field. So if you are curious but not confident, informed but not technical, or simply trying to make sense of the rapid changes around you – if you’ve ever felt like AI is something happening to you rather than something you can actively engage with – then this book is for you.

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 Clear explanations of how neural networks, machine learning algorithms, and large language models produce their results An approachable foundation suited equally to cross-disciplinary university courses and independent professional development Written for lawyers, business leaders, policymakers, healthcare professionals, educators, journalists, and other non-technical professionals who need to understand AI rather than build it, this book replaces confusion with structured knowledge of how artificial intelligence systems operate across the full scope of the field. So if you are curious but not confident, informed but not technical, or simply trying to make sense of the rapid changes around you if you ve ever felt like AI is something happening to you rather than something you can actively engage with then this book is for you.