The Psychology of Big Data: Developing a “Theory of Machine” to Examine Perceptions of Algorithms
Peer Reviewed and Accepted in Matz, S. (Ed.), American Psychological Association Handbook of Psychology of Technology
37 Pages Posted:
Date Written: June 15, 2021
Table of Contents
1. Introduction: Data Analytics Needs Psychology
a. Current work
2. Data Analytics’ Last Mile Problem
3. The Power of Algorithms
a. Algorithmic accuracy
b. How people respond to algorithmic advice is an open question.
c. Presenting algorithms as a threat rather than a tool.
d. Boundaries to algorithmic capabilities.
4. The Psychology of Big Data
5. Theory of Machine
6. Theory of Machine and Decision Context (Prediction, Assessment, Feedback)
a. Context of error: Expectations of learning and alternatives.
7. Using Psychology to Create Better Algorithms
a. Preparing to Build the Algorithm
b. Building the Algorithm
c. Interpreting Output from the Algorithm
8. Differentiation from Innovation, Anthropomorphism, and Robots
9. Conclusion: Algorithms are Tools
Keywords: Big Data, Algorithms, Psychology, Decision Making, Theory of Machine
Suggested Citation: Suggested Citation