More data has been produced in the 21st century than all of human history combined. Yet, are we making better decisions today than in the past? How many poor decisions result from the absence of data? The existence of an overwhelming amount of data has affected how we make decisions, but it has not necessarily improved how we make decisions. To make better decisions, people need good judgment based on data literacy―the ability to extract meaning from data.
Including data in the decision-making process can bring considerable clarity in answering our questions. Nevertheless, human beings can become distracted, overwhelmed, and even confused in the presence of too much data. The book presents cautionary tales of what can happen when too much attention is spent on acquiring more data instead of understanding how to best use the data we already have. Data is not produced in a vacuum, and individuals who possess data literacy will understand the environment and incentives in the data-generating process. Readers of this book will learn what questions to ask, what data to pay attention to, and what pitfalls to avoid in order to make better decisions. They will also be less vulnerable to those who manipulate data for misleading purposes.
Author(s): Michael Jones
Publisher: Palgrave Macmillan
Year: 2022
Language: English
Pages: 160
City: Cham
Preface
Acknowledgments
Contents
List of Figures
1 Introduction
What Just Happened?
Data Literacy
The OODA Loop
Judgment in the Digital Economy
Notes
2 Know Your Limits
Information Overload
Ignorance Is Bliss
Fooling Yourself
Notes
3 See the Unseen
Lack of Privacy
Deadly Serious
Trying to Hide
Notes
4 Unintended Consequences
Local Optimization
Metric Fixation
Quitting
Vicious Circle
Good Intentions
Notes
5 When More Is Better
More Accurate Predictions
More Informed Decisions
Minimize Conflicts of Interest
Promote Better Behavior
More Efficient Markets
Notes
6 Everything Has a Price
Acquisition and Storage Costs
Data Preparation Costs
Consider the Risks
Unintended Consequences
Notes
7 Map the Environment
Identify All the Variables
Estimate Second-Order Effects
Include Markets and Institutions
Ignore Irrelevant Data
Notes
8 Establish a Theory
Theory as Models
Causal Explanations
Engineering Solutions
Notes
9 Conclusion
Defense Against Gaslighting
Wicked Problems
Cultivating Data Literacy
Notes
Appendix A: A Case Study of Data Literacy During Covid-19
When More Data Is Better
The Data-Generating Process
Misleading Data
False Data
Appendix B: Data Literacy Checklist
Appendix C: Academic Journal Bibliography
Index
