Theory of Machine Book Chapter
The Psychology of Big Data: Developing a “Theory of Machine” to Examine Perceptions of Algorithms
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?
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Jennifer M. Logg, Ph.D.
I am an Assistant Professor of Management at Georgetown University's McDonough School of Business. Prior to joining Georgetown, I was a Post-Doctoral Fellow at Harvard University. I received my Ph.D. from the Management of Organizations department at the University of California, Berkeley’s Haas School of Business. My research examines why people fail to view themselves and their performance realistically. My primary line of research examines how people respond to advice and feedback from algorithms (scripts for mathematical calculations), which can help them improve their accuracy. Read more about this research here and in my book chapter. I have been invited to speak on algorithms with decision-makers in the U.S. Senate, Air Force, and Navy. During my Ph.D., I 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, I am a core member of a working group based at Stanford University's Center for Advanced Study in the Behavioral Sciences and funded by the Rockefeller Foundation called, "Theory of AI Practice." I am a Faculty Fellow at Georgetown University's AI, Analytics, and the Future of Work Initiative. |
Updates:
- Top 50 Undergraduate Business Professors by Poets & Quants (2022)
- Chapter: The Psychology of Big Data: Developing a “Theory of Machine” to Examine Perceptions of Algorithms (2021)
- Paper: Algorithm Appreciation
- Ranked #1 on list of "Most Cited Organizational Behavior and Human Decision Processes Articles Since 2018" (2021)
- Talk: Algorithmic Hiring, Psychology of Technology's Early Career Researchers Data Blitz (2020)
- Paper: Is overconfidence a motivated bias?
- Early Career Award as judged by the Journal of Experimental Psychology's editors (from five sections; 2019)
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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 |
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Aug. 8, 2019
Algorithms as Magnifying Glasses: Using Algorithms to Understand the Biases in Your Organization Harvard Business Review |
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Oct. 26, 2018
Stop Naming Your Algorithms: Do People Trust Algorithms More Than Companies Realize? Harvard Business Review |
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May 10, 2019
Harnessing the Wisdom of Crowds: How Asking Multiple People for Advice Can Backfire Harvard Business Review |
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Nov. 17, 2020
A Social Perspective of a Cognitive Bias: Overconfidence is Contagious Harvard Business Review |
Upcoming Talks
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: Anticipated Preferences vs. Utilization of Algorithmic Advice
APA Conference
Advancing Human-AI Communication and Interaction Symposium
Invited Speaker
May 2022
Past Speaking Engagements
Click links for Talks, Papers, and Programs
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
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: Anticipated Preferences vs. Utilization of Algorithmic Advice
APA Conference
Advancing Human-AI Communication and Interaction Symposium
Invited Speaker
May 2022
Past Speaking Engagements
Click links for Talks, Papers, and Programs
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