Making Sense of Recommendations

Michael  Yeomans; Anuj  Shah; Sendhil  Mullainathan; Jon  Kleinberg

Article | Journal of Behavioral Decision Making | October 2019

Making Sense of Recommendations

by Michael Yeomans, Anuj Shah, Sendhil Mullainathan and Jon Kleinberg

Abstract

Computer algorithms are increasingly being used to predict people's preferences and make recommendations. Although people frequently encounter these algorithms because they are cheap to scale, we do not know how they compare to human judgment. Here, we compare computer recommender systems to human recommenders in a domain that affords humans many advantages: predicting which jokes people will find funny. We find that recommender systems outperform humans, whether strangers, friends, or family. Yet people are averse to relying on these recommender systems. This aversion partly stems from the fact that people believe the human recommendation process is easier to understand. It is not enough for recommender systems to be accurate, they must also be understood.

Keywords: recommender systems; artificial intelligence; interpretability; Information Technology; Forecasting and Prediction; Decision Making; Attitudes;

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Yeomans, Michael, Anuj Shah, Sendhil Mullainathan, and Jon Kleinberg. "Making Sense of Recommendations." Journal of Behavioral Decision Making 32, no. 4 (October 2019): 403–414.

When entering into a negotiation, individuals have the choice to enact a variety of communication styles. We test the differential impact of being “warm and friendly” versus “tough and firm” in a distributive negotiation, when first offers are held constant and concession patterns are tracked. We train a natural language processing algorithm to precisely quantify the difference between how people enact warm versus tough communication styles. We find that the two styles differ primarily in length and their expressions of politeness (Study 1). Negotiators with a tough communication style achieved better economic outcomes than negotiators with a warm communication style, both in a field experiment (Study 2) and in a laboratory experiment (Study 3). This was driven by the fact that offers delivered in tough language elicited more favorable counteroffers. We further find that the counterparts of warm versus tough negotiators did not report different levels of satisfaction or enjoyment of their interactions (Study 3). Finally, in Study 4 we document that individuals’ lay beliefs are in direct opposition to our findings: participants believe that authors of warmly worded negotiation offers will be better liked and will achieve better economic outcomes.

Article | Journal of Personality and Social Psychology | December 2019

It Helps to Ask: The Cumulative Benefits of Asking Follow-up Questions

Michael Yeomans, Alison Wood Brooks, Karen Huang, Julia A. Minson and Francesca Gino

In a recent article published in Journal of Personality and Social Psychology (JPSP; Huang, Yeomans, Brooks, Minson, & Gino, 2017), we reported the results of 2 experiments involving “getting acquainted” conversations among strangers and an observational field study of heterosexual speed daters. In all 3 studies, we found that asking more questions in conversation, especially follow-up questions (that indicate responsiveness to a partner), increases interpersonal liking of the question asker. Kluger and Malloy (2019) offer a critique of the analyses in Study 3 of our article. Though their response is a positive signal of engaged interest in our research, they made 3 core mistakes in their analyses that render their critique invalid. First, they tested the wrong variables, leading to conclusions that were erroneous. Second, even if they had analyzed the correct variables, some of their analytical choices were not valid for our speed-dating dataset, casting doubt on their conclusions. Third, they misrepresented our original findings, ignoring results in all 3 of our studies that disprove some of their central criticisms. In summary, the conclusions that Kluger and Malloy (2019) drew about Huang et al. (2017)’s findings are incorrect. The original results are reliable and robust: Asking more questions, especially follow-up questions, increases interpersonal liking. (PsycINFO Database Record (c) 2019 APA, all rights reserved)

Keywords: question-asking; Conversation; Communication; Relationships; Interpersonal Communication;

Citation:

Yeomans, Michael, Alison Wood Brooks, Karen Huang, Julia A. Minson, and Francesca Gino. "It Helps to Ask: The Cumulative Benefits of Asking Follow-up Questions." Journal of Personality and Social Psychology 117, no. 6 (December 2019): 1139–1144. View Details

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