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Table of Contents
Intro
Preface
Acknowledgments
Contents
Part I: Received Wisdom
Chapter 1: Rational Decision and Risk Analysis and Irrational Human Behavior
Introduction
Extending Classical Decision Analysis (DA) with AI/ML Ideas
Decision Analysis for Realistically Irrational People
Two Decision Pathways: Emotions and Reasoning Guide Decisions
We All Make Predictable Mistakes
Marketers, Politicians, Journalists, and Others Exploit Our Systematic Mistakes
People Respond to Incentives and Influences in Groups, Organizations, and Markets
Moral Psychology and Norms Improve Cooperative Risk Management
We Can Learn to Do Better
The Rise of Behavioral Economics
Beyond Behavioral Economics and Rational Choice: Behaving Better in a Risky World
Review of Behave: The Biology of Humans at Our Best and Worst
12 Rules for Life: An Antidote to Chaos
Comments on Behave and 12 Rules
Review of Morality: Restoring the Common Good in Divided Times
References
Chapter 2: Data Analytics and Modeling for Improving Decisions
Introduction
Forming More Accurate Beliefs: Superforecasting
Learning About the World Through Data Analysis: The Art of Statistics
Using Models to Interpret Data: The Model Thinker
Overview of Contents
Comments on The Model Thinker
Responding to Change Strategically: Setting Goals and Acting Under Uncertainty
Using Data to Discover What Works in Disrupting Poverty
Conceptual Framework: Uncertain Risks and Rewards and Poverty Traps
Extending and Applying the Framework: How Risk and Perceptions Strengthen Poverty Traps
Escaping Poverty Traps: Weakly Held Beliefs and Credible Communication
How Can Analysis Help Reduce Health Risks and Poverty?
References
Chapter 3: Natural, Artificial, and Social Intelligence for Decision-Making
Introduction
Biological Foundations of Thought: Cognitive Neuroscience
Thinking and Reasoning
Computational Models of Nondeliberative Thought: Deep Learning (MIT Press, 2019)
Computational Models of Deliberative Thought: Artificial Intelligence: A Very Short Introduction (Oxford University Press, 201...
Communities of Knowledge
Factfulness: Ten Reasons Weŕe Wrong About the World-and Why Things Are Better Than You Think
Aligning AI-ML and Human Values: The Alignment Problem
Conclusions
References
Part II: Fundamental Challenges for Practical Decision Theory
Chapter 4: Answerable and Unanswerable Questions in Decision and Risk Analysis
Introduction: Risk Analysis Questions
Some Models and Methods for Answering Risk Analysis Questions
The Simplest Causal Models: Decision Tables and Decision Trees
Fault Trees, Event Trees, Bayesian Networks (BNs) and Influence Diagrams (IDs)
Markov Decision Processes (MDPs) and Reinforcement Learning (RL)
Preface
Acknowledgments
Contents
Part I: Received Wisdom
Chapter 1: Rational Decision and Risk Analysis and Irrational Human Behavior
Introduction
Extending Classical Decision Analysis (DA) with AI/ML Ideas
Decision Analysis for Realistically Irrational People
Two Decision Pathways: Emotions and Reasoning Guide Decisions
We All Make Predictable Mistakes
Marketers, Politicians, Journalists, and Others Exploit Our Systematic Mistakes
People Respond to Incentives and Influences in Groups, Organizations, and Markets
Moral Psychology and Norms Improve Cooperative Risk Management
We Can Learn to Do Better
The Rise of Behavioral Economics
Beyond Behavioral Economics and Rational Choice: Behaving Better in a Risky World
Review of Behave: The Biology of Humans at Our Best and Worst
12 Rules for Life: An Antidote to Chaos
Comments on Behave and 12 Rules
Review of Morality: Restoring the Common Good in Divided Times
References
Chapter 2: Data Analytics and Modeling for Improving Decisions
Introduction
Forming More Accurate Beliefs: Superforecasting
Learning About the World Through Data Analysis: The Art of Statistics
Using Models to Interpret Data: The Model Thinker
Overview of Contents
Comments on The Model Thinker
Responding to Change Strategically: Setting Goals and Acting Under Uncertainty
Using Data to Discover What Works in Disrupting Poverty
Conceptual Framework: Uncertain Risks and Rewards and Poverty Traps
Extending and Applying the Framework: How Risk and Perceptions Strengthen Poverty Traps
Escaping Poverty Traps: Weakly Held Beliefs and Credible Communication
How Can Analysis Help Reduce Health Risks and Poverty?
References
Chapter 3: Natural, Artificial, and Social Intelligence for Decision-Making
Introduction
Biological Foundations of Thought: Cognitive Neuroscience
Thinking and Reasoning
Computational Models of Nondeliberative Thought: Deep Learning (MIT Press, 2019)
Computational Models of Deliberative Thought: Artificial Intelligence: A Very Short Introduction (Oxford University Press, 201...
Communities of Knowledge
Factfulness: Ten Reasons Weŕe Wrong About the World-and Why Things Are Better Than You Think
Aligning AI-ML and Human Values: The Alignment Problem
Conclusions
References
Part II: Fundamental Challenges for Practical Decision Theory
Chapter 4: Answerable and Unanswerable Questions in Decision and Risk Analysis
Introduction: Risk Analysis Questions
Some Models and Methods for Answering Risk Analysis Questions
The Simplest Causal Models: Decision Tables and Decision Trees
Fault Trees, Event Trees, Bayesian Networks (BNs) and Influence Diagrams (IDs)
Markov Decision Processes (MDPs) and Reinforcement Learning (RL)