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

Abstract

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
a. Input
b. Process
c. Output

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

Logg, Jennifer, The Psychology of Big Data: Developing a “Theory of Machine” to Examine Perceptions of Algorithms (June 15, 2021). Peer Reviewed and Accepted in Matz, S. (Ed.), American Psychological Association Handbook of Psychology of Technology, Available at SSRN: https://ssrn.com/abstract=

Jennifer Logg (Contact Author)

Georgetown University ( email )

Washington, DC
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
90
Abstract Views
236
PlumX Metrics