Using Algorithms to Understand the Biases in Your Organization

“Using Algorithms to Understand the Biases in Your Organization“
Speaker: Logg, J. (Georgetown University)
Date: 6 December 2019
Speaker Session Preview
SMA hosted a speaker session presented by Dr. Jennifer Logg (Georgetown University) as a part of its SMA General Speaker Series. During her brief, Dr. Logg discussed how organizations can leverage algorithms (i.e., sequences of mathematical calculations) to improve their decision making accuracy and predictions. To begin, she explained why algorithms are such powerful tools for decision making. She stated that the accuracy of algorithms is far greater than that of humans, and despite organizations’ willingness to invest resources in algorithmic advice produced by big data, researchers know little about whether individuals are willing to listen to it. This motivated Dr. Logg to conduct her empirical research, which determined that average citizens rely more on identical advice when they think it comes from an algorithm than from other people. Paradoxically, a sample of national security professionals who made forecasts on a regular basis relied less on algorithmic advice than these average citizens did, and doing so negatively impacted their accuracy and predictions. Next, Dr. Logg discussed the recent backlash concerning algorithms that produce biased output. She argued that labeling algorithmic output as “algorithmic bias” and “machine bias” produces major consequences that will ultimately impair the quality of organizational decision-making. Moreover, she explained that because algorithms make decisions based off of input data, it is the input data that is often times biased rather than the algorithm itself. Consequently, people should not direct their backlash at the algorithms but rather the people making the decisions. Dr. Logg then outlined three consequences of blaming algorithms for biases. Decision makers 1) fail to acknowledge the bias present in the input data fed into the algorithm, 2) forego learning from “failure,” and 3) tend to revert back to human judgement, despite its lesser accuracy. To conclude, Dr. Logg explained how organizations can best leverage algorithms to improve their decision-making. She explained that organizations can use algorithms to purposely magnify potential biases in their decision-making with the goals of 1) identifying bias and 2) addressing the causes of bias. Organizations can also use the process of creating algorithms to clarify goals for decisions and predictions.
Speaker Session Audio Recording
To access an audio recording of the session, as well as Prof. Logg’s slides, please email Ms. Nicole Omundson (nomundson@nsiteam.com).
Dr. Jennifer M. Logg (Behavioral Scientist)
Dr. Jennifer M. Logg is an Assistant Professor of Management at Georgetown University’s McDonough School of Business.  Her primary line of research focuses on how individuals can assess themselves and the world more accurately.  Her work tests when people are most likely to leverage the power of algorithms to improve their accuracy.  She has created a program of work that examines how people expect algorithmic and human judgment to differ (a theoretical framework she calls Theory of Machine, a twist on the classic “theory of mind”).  
In a secondary line of work, she examines when people assess their performance more favorably than reality warrants and whether optimism improves performance as much as people think it does.  She received the prestigious 2019 Early Career Award from the Journal of Experimental Psychology's editors (from five sections) for the paper "Is overconfidence a motivated bias?"
Prior to Georgetown, Dr. Logg was a Post-Doctoral Fellow at Harvard University (Harvard Business School and then Harvard Kennedy School) and received her Ph.D. from the Haas School of Business at the University of California at Berkeley.  In graduate school, she was a Pre-doctoral Fellow with the Good Judgment Project, funded by the Intelligence of Advanced Research Projects Activity (IARPA).  Prior to graduate school, she conducted research on decision making at Columbia University at the Center for Research on Environmental Decisions (CRED), funded by the National Science Foundation (NSF).  Her work has been published in academic journals including the Journal of Personality and Social Psychology, Journal of Experimental Social Psychology, and Journal of Behavioral Decision Making, and 
Website: www.jennlogg.com
