Artificial Intelligence For Dummies, published by Wiley, is a general-audience introduction now in its third edition (2024), written by John Paul Mueller, Luca Massaron, and Stephanie Diamond. It runs 368 pages in six parts and 20 chapters, moving from definitions, data, and algorithms to machine learning, generative AI, medicine, robots, drones, self-driving cars, and the limits of the technology. This page describes what the book covers using the publisher's contents pages and its chapter 1 excerpt; it is a guide to the book's scope, not a verdict on every chapter.
Key takeaways
- Three editions exist: March 2018 (336 pages), October 2021 (368 pages), and the 2024 edition, where Stephanie Diamond joined as a third author.
- The 2024 edition has a full part on how AI works, with a chapter on machine learning and a chapter on deep learning that covers the perceptron and backpropagation.
- Chapter 8 of the 2024 edition addresses generative AI for text and images, so it is the part of the book that dates fastest.
- Some positions in the book are the authors' own framing, such as rating AI's simulation of creative intelligence as "None" in a chapter 1 table, and should be read as one view.
- Any introductory AI book should be checked against its publication date, because product names and capabilities change faster than printed editions.
Three editions, three different books
The title has been revised twice. Wiley lists the first edition as published in March 2018, with 336 pages and the authors John Paul Mueller and Luca Massaron. The second edition followed in October 2021 at 368 pages with the same two authors. The third edition appeared as an e-book in October 2024 and as a paperback in November 2024, again at 368 pages, with Stephanie Diamond added. Her listed background is marketing and a book on writing AI prompts, which fits the new material on generative tools.
The dates matter for a practical reason. The 2018 edition came before large language model chatbots reached the public, so a reader who buys an older copy gets the foundations but not the tools now in daily news. The publisher's page for the third edition describes it as covering how AI systems work, including hardware, software, and the role of data, along with current trends and ethical use of generative AI.
What the third edition covers, part by part
The table below follows the printed contents of the 2024 edition. Page numbers are the start of each part.
| Part | Chapters | Topics listed in the contents |
|---|---|---|
| 1. Introducing AI (page 5) | 1 to 4 | Defining AI and its history, the role of data, algorithms, specialized hardware such as GPUs and TPUs |
| 2. Understanding How AI Works (page 79) | 5 to 7 | Data analysis, supervised, unsupervised, and reinforcement learning, probabilities, decision trees, neural networks and backpropagation, convolutions |
| 3. Everyday interaction with AI (page 135) | 8 to 11 | Generative AI for text and images, AI in applications, automating processes, human interaction |
| 4. AI Applied in Industries (page 203) | 12 to 15 | Medical needs, robots, drones, the AI-driven car and its six levels of autonomy |
| 5. Getting Philosophical About AI (page 275) | 16 to 18 | Where AI will not work, AI winters, human endeavors, AI in space |
| 6. The Part of Tens (page 321) | 19 and 20 | Ten contributions of AI to society and ten ways AI has failed |
What chapter 1 argues, and where readers may disagree
Chapter 1 opens by saying the book takes a middle-of-the-road view, neither echoing the hype of proponents nor the negativity of detractors. It then sorts definitions of AI into four groups: acting humanly, thinking humanly, thinking rationally, and acting rationally. It also uses a four-type scheme credited to Arend Hintze, running from reactive machines through limited memory and theory of mind to self-awareness. A section on hype, with the five "tribes" of machine learning, closes the chapter's conceptual material.
A few statements are the authors' judgments rather than settled facts. A table of the kinds of human intelligence rates a computer's potential to simulate creative intelligence as "None," even though the same book later has a section on attempts to mimic human creativity in generative AI. Researchers measure creativity in different ways, and the question is still debated. A reader should treat such ratings as a framing device and check them against current studies.
Questions to ask of any introductory AI book
- When was this edition published, and which tools and models does it name?
- Does the contents page include limits and failures, or only uses?
- Are claims about what AI cannot do supported by cited research, or stated as opinion?
- Do the authors define terms such as machine learning, deep learning, and generative AI separately?
- Does the book say which parts are likely to age, such as product names and benchmark results?
- Is there a way to check examples, such as references, links, or companion files?
FAQ
Is the third edition different enough from the second to matter?
The publisher lists both at 368 pages, but the third edition adds a third author and, per its printed contents, a full chapter on generative AI for text and images. The publisher's description of the 2021 edition covers drones, robots, vehicles, space, and medicine and does not mention generative AI.
Does the book teach programming or math?
The contents pages show explanatory chapters on algorithms, probability, and neural networks, not a programming course. The publisher describes it as a jargon-free starting point for readers who want a deeper understanding of how AI works.
Who are the authors?
Wiley describes Luca Massaron as a data scientist and Google Developer Expert in AI and machine learning, and Stephanie Diamond as a marketing professional who has written or contributed to over two dozen books. John Paul Mueller is described as a long-time technology author whose credits include earlier editions and other For Dummies titles.
Is this a full review of the book?
No. It draws on the publisher's contents pages, the chapter 1 excerpt, and catalog data. It does not assess every chapter or compare the book with other textbooks.
Related reading
- AI and deep learning compared
- Another AI textbook, Artificial Intelligence: A Modern Approach
- The impact of AI on society
- How GPT chatbots work
More in AI Basics.
Last verified: October 2026
Sources
- Artificial Intelligence For Dummies, 3rd Edition (product page, front matter, and chapter 1 excerpt), John Wiley & Sons, 2024
- Artificial Intelligence For Dummies, 2nd Edition (product page), John Wiley & Sons, 2021
- Artificial Intelligence For Dummies (product page), John Wiley & Sons, 2018