MOC
OB
CTO
Sophia Pink
The Wharton School, U. of Pennsylvania
William Brady
Kellogg School of Management, Northwestern U.
Jennifer Logg
Georgetown U., United States
Rafael Batista
U. of Chicago Booth School of business
Sophia Pink
The Wharton School, U. of Pennsylvania
Organizations are increasingly using algorithms to aid with decision-making. However, these algorithms often ignore human psychology, which can lead to both biased algorithms and missed opportunities. The first set of presentations focuses on how algorithms learn from human behavior data. They show how training algorithms on human behavior data without taking psychology into account can lead to unintended consequences, such as discrimination in resume screening or distorted social perceptions fueled by social media algorithms. The latter talks study how employees learn from algorithms. They uncover insights into how people leverage algorithmic advice in real-world situations versus hypothetical scenarios, and present a method for using algorithms to generate novel hypotheses about behavior.
Author: Sophia Pink – The Wharton School, U. of Pennsylvania
Author: Sendhil Mullainathan – U. of Chicago Booth School of business
Author: Katherine Milkman – U. of Pennsylvania
Author: William Brady – Kellogg School of Management, Northwestern U.
Author: Joshua Jackson – Northwestern Kellogg School of Management
Author: Silvan Baier – Kellogg School of Management, Northwestern U.
Author: Joseph Abruzzo – Kellogg School of Management, Northwestern U.
Author: Rafael Batista – U. of Chicago Booth School of business
Author: James Ross – U. of Chicago Booth School of business
Author: Sendhil Mullainathan – U. of Chicago Booth School of business
Author: Jens Ludwig – U. Of Chicago
Author: Jennifer Marie Logg – Georgetown U.
Author: Rachel Schlund – Cornell U.