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Causal Artificial Intelligence: The Next Step in Effective Business AI 1st Edition
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Discover the next major revolution in data science and AI and how it applies to your organization
In Causal Artificial Intelligence: The Next Step in Effective, Efficient, and Practical AI, a team of dedicated tech executives delivers a business-focused approach based on a deep and engaging exploration of the models and data used in causal AI. The book’s discussions include both accessible and understandable technical detail and business context and concepts that frame causal AI in familiar business settings.
Useful for both data scientists and business-side professionals, the book offers:
- Clear and compelling descriptions of the concept of causality and how it can benefit your organization
- Detailed use cases and examples that vividly demonstrate the value of causality for solving business problems
- Useful strategies for deciding when to use correlation-based approaches and when to use causal inference
An enlightening and easy-to-understand treatment of an essential business topic, Causal Artificial Intelligence is a must-read for data scientists, subject matter experts, and business leaders seeking to familiarize themselves with a rapidly growing area of AI application and research.
- ISBN-101394184131
- ISBN-13978-1394184132
- Edition1st
- PublisherWiley
- Publication dateOctober 3, 2023
- LanguageEnglish
- Dimensions5.9 x 0.9 x 8.9 inches
- Print length384 pages
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From the Back Cover
Explore the next major revolution in data science and artificial intelligence: causal AI
In Causal Artificial Intelligence: The Next Step in Effective Business AI, a team of distinguished AI and analytics professionals delivers an incisive and comprehensive exploration of the models and data of causal inference and causal artificial intelligence. Authors Judith Hurwitz and John Thompson offer the technical detail―explained clearly and accessibly―necessary to understand the underlying technologies, as well as the business context that frames causal AI from a perspective of daily business operations.
You’ll discover meaningful and practical insights into what causality is and how it can benefit your organization and understand the critical differences between correlation-based approaches to AI and causality-based approaches. The book also includes easy-to-understand use cases and examples that demonstrate the value of causality for solving business problems.
Perfect for data scientists, subject matter experts in a variety of fields, as well as managers, executives, and other business leaders, Causal Artificial Intelligence is a one-of-a-kind resource designed to open eyes and minds to the incredible possibilities of casual AI and its implications for businesses of all kinds.
About the Author
JUDITH S. HURWITZ is the chief evangelist at Geminos Software, a causal AI platform company. For more than 35 years she has been a strategist, technology consultant to software providers, and a thought leader having authored 10 books in topics ranging from augmented intelligence, data analytics, and cloud computing.
JOHN K. THOMPSON is an international technology executive with over 37 years of experience in the fields of data, advanced analytics, and artificial intelligence (AI). John is responsible for the global AI function at EY. He has previously led the global Artificial Intelligence and Rapid Data Lab teams at CSL Behring and is the bestselling author of three books on data analytics.
Product details
- Publisher : Wiley; 1st edition (October 3, 2023)
- Language : English
- Paperback : 384 pages
- ISBN-10 : 1394184131
- ISBN-13 : 978-1394184132
- Item Weight : 7.4 ounces
- Dimensions : 5.9 x 0.9 x 8.9 inches
- Best Sellers Rank: #338,306 in Books (See Top 100 in Books)
- #381 in Business Decision Making
- #620 in Artificial Intelligence & Semantics
- #663 in Decision-Making & Problem Solving
- Customer Reviews:
About the authors
Judith S. Hurwitz is Chief Evangelist at Geminos Software, a causal AI platform intended to help business leaders collaborate to understand the cause and effect of business problems and how to address these complex issues. Judith has multiple decades of experience as a software thought leader, book author on emerging technology topics, strategy consultant and developer. She has started three companies focused on emerging software technologies including:
• President, Hurwitz & Associates, a technology consulting firm focused on AI/ML, cloud services, security, and software development.
* Founder of CycleBridge, a consulting firm focused on applying advanced technologies to the Biotech market
*Hurwitz Group, an analyst and research firm focused on emerging technologies.
She worked as an internal consultant and developer at a variety of firms including John Hancock Insurance and Apollo Computer.
Hurwitz is a graduate of Boston University with both BS and MS degrees. She is on the College of Arts & Sciences (CAS) Dean's advisory board. She also serves as a mentor for students starting technology businesses.
Her best selling books include:
Augmented Intelligence: The Business Power of Human-Machine Collaboration (2021, CRC Press),
Cognitive Computing and Big Data Analytics (2015, John Wiley & Sons)
Smart or Lucky? How Technology Leaders Turn Chance into Success. (2015,Jossey Bass)
Cloud Computing for Dummies (2020, John Wiley & Sons, 2nd edition,)
Big Data for Dummies (2011, John Wiley & Sons)
Hybrid Cloud for Dummies (2012, John WIley & Sons)
Service Management for Dummies (2009, John WIley & Sons)
Cloud Computing for Dummies (first edition, 2010, John Wiley & Sons)
Service Oriented Architectures for Dummies (first edition, 2007, John WIley & Sons)
Service Oriented Architectures for Dummies (second edition, 2009)
John is an international technology executive with over 38 years of experience in the fields of data, advanced analytics and artificial intelligence (AI).
Most recently, John was responsible for the AI functions and operations at EY on a global basis. Previously, he led the global advanced analytics and AI function at a leading biopharmaceutical company where he and his team that developed and deployed over 25 analytical applications in 4.5 years. John was an Executive Partner at Gartner, where he was management consultant to market leading companies in the areas of digital transformation, data monetization and advanced analytics. Before Gartner, John was responsible for the advanced analytics business unit of the Dell Software Group.
John is the author of the bestselling books:
- The Path to AGI: Artificial General Intelligence: Past, Present, and Future. When most people talk about AI, they are talking about Generative AI (GenAI). GenAI is useful and valuable and will drive significant value, but the field of AI is much more than GenAI. AI has been under active development for over 70 years. Read all about the nuances and differences in each of the three areas of AI. As AI moves towards larger and more comprehensive applications and solutions, we will see an evolution of all three areas of AI, and, at the same time, we will see a convergence of the three areas toward Composite AI. Composite AI will be the state of the art for many years and possibly even decades. Composite AI will grow and evolve into Artificial General Intelligence (AGI). While AGI is an exciting theme for science fiction movies, it will not arrive in the next few years. The path to AGI will be long and challenging. In the book we discuss the pragmatic and practical path in detail. Business leaders and technologists need to understand where AI is moving. The book outlines one of the most probable paths unfolding over the next few decades as we move toward AI being embedded in all systems and operations. AI will become a utility like electricity and water, but we have a long road of sophisticated development to navigate before we arrive at that point. The Path to AGI is a reference book and guide for those interested in all types of AI and how these types will merge, integrate, and evolve into one of the most consequential technologies the world has ever seen.
- Causal Artificial Intelligence: The Next Step in Effective Business AI. Has been written for technology and business professionals to provide and introduction to the topic of Causal AI. The book’s discussions include both accessible and understandable technical detail and business context and concepts that frame causal AI in familiar business settings. The book contains clear and compelling descriptions of the concept of causality and how it can benefit your organization. As well as detailed use cases and examples that vividly demonstrate the value of causality for solving business problems. An enlightening and easy-to-understand treatment of an essential business topic, Causal Artificial Intelligence is a must-read for data scientists, subject matter experts, and business leaders seeking to familiarize themselves with a rapidly growing area of AI application and research.
- Data for All: Is intended for all people who are interested in, and possibly concerned, about the data that they are continuously creating as a by-product of almost all activities of their everyday life. The book delves into what commercial companies, governments, academic institutions, market research firms, data syndication companies, and other interested parties are doing with the data they collect about you, your children, your spouse, your parents, and everyone that you know…and everyone that you do not know as well. In this book, we discuss your data and the changes related to your data that are coming in the next few years. You will want to know what to do, and this book tells you in detail what you can do.
– Analytics Teams: Harnessing analytics and artificial intelligence for business improvement. The book was published in June 2020 and outlines how to hire and manage high performance advanced analytics teams. The book outlines how to engage with executives and senior managers. How to select and undertake analytics projects that change and improve how a business operates.
– Analytics: How to win with Intelligence, which debuted on Amazon as the #1 new book in Analytics in 2017. Analytics is a book that guides non-technical executives through the journey of creating an analytics function, funding initiatives and driving change in business operations through data and applied analytical applications.
Mr. Thompson’s technology expertise includes all aspects of advanced analytics and information management including – descriptive, predictive and prescriptive analytics, artificial intelligence, analytical applications, deep learning, cognitive computing, big data, data warehousing, business intelligence systems, and high-performance computing.
One of John’s primary areas of focus and interest has been to create innovative technologies to increase the value derived by organizations around the world.
John has built start-up organizations from the ground up and he has reengineered business units of Fortune 500 firms to reach their potential. He has directly managed and run - sales, marketing, consulting, support and product development organizations.
He is a technology leader with expertise and experience spanning all operational areas with a focus on strategy, product innovation, growth and efficient execution.
Thompson holds a Bachelor of Science degree in Computer Science from Ferris State University and a MBA in Marketing from DePaul University.
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Simple decision - Buy buy buy!
Top reviews from the United States
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- Reviewed in the United States on September 22, 2023Few authors – if any – have the ability to take highly technical innovations and breakthroughs in AI, and translate them into the “big picture”: What is it good for, how can I use it to improve my organization and its processes, and what should I do next? The authors of this book, Hurwitz and Thompson, are masters of this skill.
As is widely known, AI is transformational, and critical for success in a competitive business environment, to optimize manufacturing processes, identify effective medical interventions, or just understand and interact with complex and challenging reality. UCLA Professor Judea Pearl’s recent work on causal AI has been recognized by experts as a breakthrough w/r to the application of Artificial Intelligence and Big-Data-Analytics, in order to understand and solve real-world problems. Professor Pearl was awarded the prestigious Turing Award for this work. Hurwitz and Thompson now deliver the key insights of Pearl’s leading-edge work to practitioners in this book.
The fact that “correlation does not equal causation” is widely known and taught to be a key tenet of how to interpret and draw inferences from data. But: This is only part-of-the-story! In reality, in complex systems, effects can be direct or indirect, mediated, suppressed or augmented, reciprocal, etc. And modern analytic techniques can provide the tools to untangle the “knowledge graphs” to deliver insight into the causal relationships between measured and latent (non-observed, but inferred) variables and constructs. In Causal Artificial Intelligence, Hurwitz and Thompson provide an overview of the approach to Causal AI, explain critical terminology and definitions, how to go about retrieving the right info and data, where to find the right (e.g., Python) tools, and how to implement it. Practitioners will particularly appreciate the recipes and examples for success, based on the authors’ extensive real-world experience (and prior publications).
So in sum, a must-read book for anyone who wants to stay on-top of critical developments in AI, and how they are rapidly changing all aspects of our world!
(PS: Causal AI and Judea Pearl’s work is also briefly discussed in our recent book on Practical Data Analytics for Innovation in Medicine -- see: https://www.amazon.com/Practical-Data-Analytics-Innovation-Medicine. Hurwitz and Thompson’s book is a dedicated introduction for practitioners that I can highly recommend.)
- Reviewed in the United States on August 4, 2024I was excited to read this book after an endorsement from the author of “The Book of Why”. It was more superficial than I hoped for and failed to work through real business examples to completion as the book went along.
- Reviewed in the United States on February 8, 2024I found this book extremely good. As a long time product manager and marketing exec in the AI space, I learned a ton about the future of AI for business, and gained highly valuable insights into how business leaders should be looking at the era of digital reinvention driven by AI. Today's AI is very much in its infancy. While generative AI is top of mind, it will not be long before Causal AI becomes to focus area. It's one thing to understand WHAT is occurring, yet another to understand HOW, but the value is in the WHY. This book is written for both technologies and "mere mortal" business leaders to understand what to be pushing for in AI systems. The notion of "if this, then what", true AI explainability, cause and effect, etc are explored in the context of real use cases. The value of AI will ultimately evolve to an interactive experience to explore various approaches to problem solving and without causal inferencing, you can only do so much. I view this as a must read for c-suite leaders that are involved in driving business transformation involving AI. It will decode a ton of concepts and future applications AI. Finally, it's very well written book and easy to consume.
- Reviewed in the United States on August 8, 2024John and Judith knock it out of the park with this book. Much like “Building Analytics Teams,” this book speaks to the technical business professionals looking to sharpen their skills.
Just today, I picked up this book to address a current modeling scenario, and it didn’t disappoint.
Practical advise & easy reading, I buy these books sight unseen based on their consistent quality and expert insights.
5.0 out of 5 starsJohn and Judith knock it out of the park with this book. Much like “Building Analytics Teams,” this book speaks to the technical business professionals looking to sharpen their skills.Simple decision - Buy buy buy!
Reviewed in the United States on August 8, 2024
Just today, I picked up this book to address a current modeling scenario, and it didn’t disappoint.
Practical advise & easy reading, I buy these books sight unseen based on their consistent quality and expert insights.
Images in this review
- Reviewed in the United States on October 25, 2023Having picked up Judith Hurwitz and John Thompson's collaborative work "Causal Artificial Intelligence, The Next Step In Effective Business AI" from Amazon midweek, I expected to do a run of it over a weekend. The more time I spent with it, the more I wanted to slow down and think through the implications of a pivot from the correlation perspective to the causal one.
The work offers a very readable and practical resource for anyone interested in the next phase of AI. It bridges the gap between theoretical understanding and practical application nicely, presenting a clear-eyed view of the domain of Causal AI. The authors' passion for the subject and commitment to ensuring the material is accessible make this book an essential addition to the library of data and AI professionals in leadership and practitioner roles. It is a good read for those who want to stay at the forefront of AI innovation and harness the potential of causal artificial intelligence.
5.0 out of 5 starsHaving picked up Judith Hurwitz and John Thompson's collaborative work "Causal Artificial Intelligence, The Next Step In Effective Business AI" from Amazon midweek, I expected to do a run of it over a weekend. The more time I spent with it, the more I wanted to slow down and think through the implications of a pivot from the correlation perspective to the causal one.Clear headed view on where we go next with Artificial Intelligence
Reviewed in the United States on October 25, 2023
The work offers a very readable and practical resource for anyone interested in the next phase of AI. It bridges the gap between theoretical understanding and practical application nicely, presenting a clear-eyed view of the domain of Causal AI. The authors' passion for the subject and commitment to ensuring the material is accessible make this book an essential addition to the library of data and AI professionals in leadership and practitioner roles. It is a good read for those who want to stay at the forefront of AI innovation and harness the potential of causal artificial intelligence.
Images in this review
- Reviewed in the United States on April 12, 2024Unfortutanely the book is a shallow and superficial attempt, it keeps making the same pitches over and over.
- Reviewed in the United States on November 24, 2023I highly recommend “Causal Artificial Intelligence” by Hurwitz and Thompson as a must-read for both AI practitioners and, perhaps more importantly, business leaders seeking deeper insights into driving successful AI projects. Cause AI emphasizes the importance of understanding the principles of causation (not just correlation) in real world AI scenarios by forming hybrid teams with data experts, business leaders, and subject matter experts. The authors demystify complex AI concepts to ensure that both seasoned AI professionals and business leaders can understand the concepts and harness the power of Causal AI. As a business executive I found the book at about the right level and very helpful in terms of providing specific guidance on different approaches to successful projects.
5.0 out of 5 starsI highly recommend “Causal Artificial Intelligence” by Hurwitz and Thompson as a must-read for both AI practitioners and, perhaps more importantly, business leaders seeking deeper insights into driving successful AI projects. Cause AI emphasizes the importance of understanding the principles of causation (not just correlation) in real world AI scenarios by forming hybrid teams with data experts, business leaders, and subject matter experts. The authors demystify complex AI concepts to ensure that both seasoned AI professionals and business leaders can understand the concepts and harness the power of Causal AI. As a business executive I found the book at about the right level and very helpful in terms of providing specific guidance on different approaches to successful projects.A must-read book for business leaders seeking deeper insights into driving successful AI projects
Reviewed in the United States on November 24, 2023
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