Theory of Machine Book Chapter
The Psychology of Big Data: Developing a “Theory of Machine” to Examine Perceptions of Algorithms

What leads people to make inaccurate judgments?​
​When are they willing to use algorithms to improve their accuracy?

Jennifer M. Logg, Ph.D., is an Assistant Professor of Management at Georgetown University's McDonough School of Business. Prior to joining Georgetown, she was a Post-Doctoral Fellow at Harvard University. Dr. Logg received her Ph.D. from the University of California, Berkeley’s Haas School of Business.

Her research examines why people fail to view themselves and their work realistically. It focuses on how individuals can assess themselves and the world more accurately by using advice and feedback produced by algorithms (scripts for mathematical calculations). 

She calls her primary line of research Theory of Machine. It uses a psychological perspective to examine how people respond to the increasing prevalence of information produced by algorithms. Broadly, this work examines how people expect algorithmic and human judgment to differ. Read more in her book chapter, The Psychology of Big Data: Developing a “Theory of Machine” to Examine Perceptions of Algorithms.

She has spoken on the topic of algorithms with decision-makers in the U.S. Senate, Air Force, and Navy. During her Ph.D., she was a collaborator on the Good Judgment Project, funded by IARPA, Intelligence of Advanced Research Projects Activity, the US intelligence community’s equivalent of DARPA. Currently, she is a Faculty Fellow at Georgetown University's AI, Analytics, and the Future of Work Initiative. She is also also a member of the "Theory of AI Practice" working group, funded by the Rockefeller Foundation through Stanford University's Center for Advanced Study in the Behavioral Sciences.

Awards
Her paper, "Algorithm Appreciation," ranked #1 in 2021 on the list of "Most Cited Organizational Behavior and Human Decision Processes Articles Since 2018."

She received the 2019 Early Career Award for the paper "Is overconfidence a motivated bias?" as judged by the Journal of Experimental Psychology's editors (from five sections).

Poets & Quants listed her as one of the Top 50 Undergraduate Business Professors and she received the Georgetown Career Champion Award (student nominated) in 2022.
Updates:
June 15, 2021
Theory of Machine 
The Psychology of Big Data: Developing a “Theory of Machine” to Examine Perceptions of Algorithms 
American Psychological Association Handbook of Psychology of Technology
Aug. 8, 2019
Algorithms as Magnifying Glasses:
Using Algorithms to Understand the Biases in Your Organization
Harvard Business Review
Oct. 26, 2018
Stop Naming Your Algorithms:
Do People Trust Algorithms More Than Companies Realize?
Harvard Business Review

March 31, 2020
Managing Algorithms
Demystifying Organizations Podcast
Listen on Spotify
May 10, 2019
Harnessing the Wisdom of Crowds:
How Asking Multiple People for Advice Can Backfire 
Harvard Business Review
Nov. 17, 2020
A Social Perspective of a Cognitive Bias:
Overconfidence is Contagious
Harvard Business Review
Upcoming Talks
Talk: Anticipated Preferences vs. Utilization of Algorithmic Advice
ACR Conference 
Denver, CO
October 2022​
​
Past Speaking Engagements
Click links for Talks, Papers, and Programs

Talk: Anticipated Preferences vs. Utilization of Algorithmic Advice
AOM Conference 
Understanding the Future of Work
​with Algorithms, AI, & Automation
Aug 6, 2022

Panel Webcast: Building Social Science into the Foundation of AI Practice
Invited Panelist
Produced by Stanford University's Center for Advanced Study in the Behavioral Sciences
June 14, 2022 @ ​3pm Eastern
Summary
Video
Podcast

Talk: Pre-Registration: Weighing Costs and Benefits for Researchers
Invited Speaker
HEC Montreal Research Day on Replication and Open Science
​April 5, 2022

Talk: Developing a "Theory of Machine"
Harvard University
Lerner Lab
April 8, 2022

Talk: Algorithmic Hiring
APA Conference 
Advancing Human-AI Communication and Interaction Symposium
Invited Speaker
May 2022
​
Invited Panelist
Workshop on AI For Behavior Change

Talk: Developing a "Theory of Machine"
​Invited Talk
Max Planck Institute
May 4, 2021
Talk: www.youtube.com/watch?v=xyDR9kQ5YDk

Talk: Algorithmic Hiring
​Psychology of Technology
Algorithms and Decision-Making Session
Oct. 26, 2020
Talk: https://www.psychoftech.org/rising-stars-data-blitz

Talk: Algorithmic Hiring
Academy of Management
Aug. 10, 2020
Session: Algorithmic Decision Making

Talk: Using Algorithms to Detect Bias
Invited Talk
DC United (MLS Soccer)
July 21, 2020
​
Talk: Using Algorithms to Detect Bias
Invited Talk
Naval Applications of Machine Learning
NIWC Pacific Workshop
Feb. 24, 2020

Invited Interview (Information Collection Stage)
U.S. Senate
Oct. 18, 2019
Consumer Online Privacy Rights Act (COPRA) Bill Introduced 11.26.19
Overview of Bill

 Talk: Algorithm Appreciation
Invited Talk, Postponed
​Harvard University
Science Based Business Initiative
Co-Sponsored by Economics of Science & Engineering and 
Technology & Operations Management