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AI Explained: A Guide for Non-Technical Readers

by Pete Rai

A structured introduction to how AI works

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AlbakiReads Editorial

A structured introduction to how AI works

Pete Rai’s guide traces artificial intelligence from rule- and logic-based systems through statistical methods, neural networks, machine learning and generative models. Its progression is designed to explain how systems produce their outcomes, not to teach readers to build or deploy them. Practical use-case sections connect technical ideas with examples from healthcare, law and business, while additional coverage considers AI policy, ethics, regulation and societal effects. The book brings together foundational concepts and professional contexts, making the subject legible without requiring a technical starting point.

Good fit for readers who enjoy

  • Non-technical professionals seeking to understand AI systems rather than build them
  • Readers interested in AI’s applications across healthcare, law and business
  • Those seeking an introduction that also covers AI policy, ethics and societal impact

Themes

Artificial intelligence foundations and methodsGenerative AI and large language modelsPractical applications of AIAI policy, ethics and societal impact

Based on publisher information and book metadata.

Book overview

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.

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Customer reviews

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Malaika Taylor

I highly recommend to for anyone looking for inner clarity

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Great service and fast service

Great shopping experience! The book arrived quickly, was well packaged, and matched the description perfectly. I would definitely shop with you again

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