What leads managers to make inaccurate judgments?
When are they willing to use algorithms to improve their accuracy?
Jenn Logg
I am 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 work examines why managers fail to view themselves and their work realistically. My research focuses on how people can make more accurate judgments by using advice and feedback produced by algorithms (scripts for mathematical calculations).
I call my primary line of research, Theory of Machine. In it, I use 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 judgement to differ. Specifically, I examine when people are most likely to leverage the power of algorithmic advice to improve the accuracy of their judgments about the world. In a project on "robo-coaching," I test when people prefer to receive algorithmic feedback on their performance versus feedback from a person.
My second line of research investigates overconfidence, a pervasive bias. My work offers new insights into both the antecedents and consequences of these overly positive self-views. I test the questions: does valuing a particular skill increases people's overconfidence in that skill, is overconfidence socially "contagious," does optimism help performance as much as people expect, and does overconfidence in winning an argument explain why everyone argues but no one is persuaded?
My second line of research investigates overconfidence, a pervasive bias. My work offers new insights into both the antecedents and consequences of these overly positive self-views. I test the questions: does valuing a particular skill increases people's overconfidence in that skill, is overconfidence socially "contagious," does optimism help performance as much as people expect, and does overconfidence in winning an argument explain why everyone argues but no one is persuaded?
