
- 239 pages
- English
- PDF
- Available on iOS & Android
About this book
Implement AI and big data at your organization using principles from behavioral economics
In Behavioral AI: Unleash Decision Making with Data, behavioral economist Dr. Rogayeh Tabrizi delivers an intuitive roadmap to help organizations disentangle the complexity of their data to create tangible and lasting value. The book explains how to balance the multiple disciplines that power AI and behavioral economics using a combination of the right questions and insightful problem solving.
You'll learn why intellectual diversity and combining subject matter experts in psychology, behavior, economics, physics, computer science, and engineering is essential to creating advanced AI solutions. You'll also discover:
- How behavioral economics principles influence data models and governance architectures and make digital transformation processes more efficient and effective
- Discussions of the most important barriers to value in typical big data and AI projects and how to bring them down
- The most effective methodology to help shorten the long, wasteful process of "boiling the ocean of data"
An exciting and essential resource for managers, executives, board members, and other business leaders engaged or interested in harnessing the power of artificial intelligence and big data, Behavioral AI will also benefit data and machine learning professionals.
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Information
Table of contents
- Cover
- Title Page
- Copyright Page
- Contents
- Preface
- Chapter 1 Magic Happens at the Intersections
- Chapter 2 It Is All Connected: Behavioral Economics, Decision-Making, Biases, and Heuristics
- Chapter 3 Minimal Data, Maximal Impact: From Big Data to Minimum Viable Data
- Chapter 4 Building Intelligence: AI and ML Essentials, Transforming Data into Intelligence
- Chapter 5 Real-World Impact: Harnessing AI and ML for Practical Solutions
- Chapter 6 Decoding Complexity: Leveraging Systems Thinking in Modern Organizations
- Chapter 7 Unlocking Scale: Overcoming Operational and Organizational Complexity in Scaling AI Projects
- Epilogue
- Notes
- Additional Reading
- Bibliography
- Acknowledgments
- About the Author
- Index
- EULA