图书简介
Revealing the limitations of human decision-making, this book explores how Artificial Intelligence (AI) can be used to optimize decisions for improved business outcomes and efficiency, as well as looking ahead to the significant contributions Decision Intelligence (DI) can make to society and the ethical challenges it may raise.From the theories and concepts used to design autonomous intelligent agents to the technologies that power DI systems and the ways in which companies use decision-making building blocks to build DI solutions that enable businesses to democratize AI, this book presents an impressive framework to integrate artificial and human intelligence for the success of different types of business decisions.Replete with case studies on DI applications, as well as wider discussions on the social implications of the technology, Decision Intelligence: Human–Machine Integration for Decision Making appeals to both students of AI and data sciences and businesses considering DI adoption.
List of Acronyms
Preface
Acknowledgements
Chapter 1 Decision Intelligence – Introduction and Overview
Introduction to DI
Defining Decision Intelligence
DI Evolution and Landscape
Why We Need DI
DI to Optimize Decisions
DI for Improved Business Outcomes and Efficiency
How DI Works and How It Looks
Types of Business Decisions
Decision Making Process
DI Forms
Decision Assistance
Decision Support
Decision Augmentation
Decision Automation
Infrastructure Design – Data Architecture for DI
State of DI Adoption
Factors Affecting DI Adoption Decisions
Conclusion
Case Study: AI-Powered Recommendation System Delivering Consistent Energy Saving at Google Data Centers
Questions for Discussion
References
Chapter 2 Humans Vs. Machines in Decision-Making
Humans in Decision-Making
Behavioral Economics of Decision-Making
Neuroscience and Neuroeconomics Perspectives
Computers in Decision-Making
Basic Programming Methods
The Evolution of AI-Powered Decision-Making
Machine Learning
Supervised Machine Learning
Unsupervised Machine Learning
Reinforcement Learning
Classical Machine Learning
Neural Networks and Deep Learning
Human Vs. Computer – Who is Better at Decision-Making?
Conclusion
Case Study: John Hopkins Manages Patient Flow During Covid-19 With AI Powered Capacity Command Center
Questions for Discussion
References
Chapter 3 Systems and Technologies for Decision-Making
Organization as a System
Decision Making System in the Organization
Decision Making Environments
Human Agents
Trade Policy 买家须知
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