About This Textbook
Welcome From Fermi the Ferret
Hello everyone! Welcome to the interactive intelligent textbook
A Skeptic’s Guide to Quantum Computing. My name is Fermi the
ferret, and I will be your guide throughout this book. I will
introduce each chapter, ask tough questions about the evidence,
and give you tips and encouragement along the way. But does the
math check out? Let’s find out together!
Why This Book
Over $100 billion has been invested in quantum computing worldwide, yet no company has produced a single dollar of positive return on investment from quantum computing products or services. Proponents routinely assert that economic viability is "just a few years away" — a claim that has been made, and missed, repeatedly since the 1990s.
Despite this track record, most coverage of quantum computing remains relentlessly optimistic. Press releases become breathless headlines. Incremental laboratory results are presented as transformative breakthroughs. Consulting firms project hundreds of billions in future market value based on assumptions that require multiple simultaneous physics breakthroughs — none of which are guaranteed.
This book exists because investors, policymakers, students, and curious citizens deserve a clearly written, evidence-based resource that examines quantum computing through the lens of economic viability, physics constraints, cognitive bias, and the sociology of technology hype. It is not anti-quantum — it is pro-evidence. Where quantum technologies deliver real value (such as quantum sensing), we say so. Where the gap between claims and reality is wide, we document it rigorously.
The 17 chapters cover the full landscape: what quantum computing is and is not, the history of broken promises, the fundamental physics barriers, the economics of investment, the cognitive biases that sustain hype, systems thinking models of why investment perpetuates itself, better alternative investments, and a practical toolkit for critical thinking about any emerging technology claim.
How to Use This Book
This textbook is designed for self-paced study. Each chapter builds on previous material, so reading in order is recommended. The book includes several types of resources:
- 17 Chapters covering physics, economics, psychology, and critical thinking
- Interactive MicroSims embedded in chapters — browser-based simulations you can manipulate to explore concepts like error correction overhead, investment expected value, and hype dynamics
- Quizzes at the end of each chapter to test your understanding
- Annotated References for each chapter linking to Wikipedia articles, authoritative books, and research papers
- Glossary with 241 defined terms
- FAQ with 93 questions and answers
- Learning Graph visualizing concept dependencies across the course
- Search available from any page using the search bar in the top navigation
The Learning Graph visualizes how concepts connect across chapters. If you want to explore non-linearly or check prerequisites for a specific topic, start there.
About the Author
Dan McCreary is a semi-retired AI researcher, solution architect, and educator who has spent more than three decades helping Fortune 100 organizations reason over massive datasets. At Optum he founded the Generative AI Center of Excellence and led the team that built one of the world’s largest healthcare knowledge graphs — spanning over 25 billion vertices — to unify member, provider, and patient insights. Dan’s deep background in knowledge representation and systems thinking underpins the precise learning graphs and intelligent textbook workflows used throughout this course.
He is the co-author of Making Sense of NoSQL (Manning Publications), the founding chair of the NoSQL Now! conference, and a frequent keynote speaker on semantic search, ontology strategy, and AI hardware. Beyond industry, Dan has mentored students as a STEM volunteer since 2014 and now applies the same rigor to building open educational resources. You can visit the Intelligent Textbooks Case Studies to see over 71 textbooks that Dan has created or co-created with other authors.
Selected Credentials
- B.A. in Physics and Computer Science from Carleton College
- M.S.E.E. from the University of Minnesota
- MBA coursework at the University of St. Thomas
- Patent holder in semantic search and ontology management techniques
- Advocate for large-scale Enterprise Knowledge Graph adoption across healthcare and education
- Long-time promoter of accessible, low-cost AI-powered learning experiences
How to Cite This Book
APA (7th edition)
McCreary, D. (2025). A skeptic's guide to quantum computing: Why it may never be economically viable. https://dmccreary.github.io/quantum-computing/
Chicago (17th edition)
McCreary, Dan. 2025. A Skeptic's Guide to Quantum Computing: Why It May Never Be Economically Viable. https://dmccreary.github.io/quantum-computing/.
MLA (9th edition)
McCreary, Dan. A Skeptic's Guide to Quantum Computing: Why It May Never Be Economically Viable. 2025, dmccreary.github.io/quantum-computing/.
BibTeX
1 2 3 4 5 6 7 | |
To cite a specific chapter, append the chapter number and title — for example:
McCreary, D. (2025). Chapter 11: Cognitive biases in quantum computing investment. In A skeptic's guide to quantum computing: Why it may never be economically viable. https://dmccreary.github.io/quantum-computing/chapters/11-cognitive-biases/