Solving the trust equation

17 Mar 2015

Socially intelligent computers can turn difficult online negotiations into win−win situations through tactical information disclosure

Online negotiations can be improved if computer programs take social values, such as honesty and trust into account when bargaining with human counterparts.

Online negotiations can be improved if computer programs take social values, such as honesty and trust into account when bargaining with human counterparts.

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Programming fundamental ‘social intelligence’ skills into software agents can make humans substantially more trusting of online negotiations, which can lead to superior outcomes in e-commerce transactions, finds an A*STAR-led team of technology researchers, business experts and cognitive scientists.

Automated software agents that bargain for the best deals on the Internet are widely used for business-to-business sales and processes. However, as people are naturally skeptical of negotiations lacking face-to-face contact, engineers are seeking ways to make such software less intimidating.

Yinping Yang from the A*STAR Institute of High Performance Computing explains that it is challenging to create a computerized negotiator with enough social skills to put people at ease. “These agents have to elicit cooperative behavior such as making concessions while maintaining the negotiation goals,” says Yang. “This requires transdisciplinary knowledge of business and social communications as well as careful computational coding of social-psychological rules.”

Yang and her collaborators from academia and industry realized that one way for computers to gain the trust of human negotiators was to proactively share certain information. For example, the software agent could express that its priority is distribution and offer one price for immediate delivery of merchandise and a lower one for delivery in two weeks — a flexibility that signals a willingness to search for mutual benefits.

To test their theory, the team gave 54 MBA students the opportunity to bargain with software designed to simulate the real-world purchasing of laptop computers. They instructed the students to negotiate with an online agent over four key factors — price per unit, quantity, service level and delivery terms — while keeping in mind that their top priority should be obtaining a low unit price.

After an initial round of bargaining, the researchers’ proactive agent offered to find a joint solution by sharing that if the participant ordered in large quantities, it was willing to make concessions in other areas. The agent then invited the student to reciprocate by divulging their priority. As a control, some students negotiated with a non-proactive agent that simply presented counteroffers without offering additional information.

The results were striking: 80 per cent of the negotiations using the proactive agent were successful, whereas only half of the control group had agreeable outcomes. Surprisingly, even students whose personalities tested positive for cynical, ‘Machiavellian’ traits felt more trusting about the online negotiations. According to Yang, this finding suggests that even self-interested individuals can be steered toward cooperative approaches with the right social clues.

The A*STAR-affiliated researchers contributing to this research are from the Institute of High Performance Computing. For more information about the team’s research, please visit the Social and Cognitive Computing Department webpage.

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Yang, Y., Falcao, H., Delicado, N. & Ortony, A. Reducing mistrust in agent-human negotiations. IEEE Intelligent Systems 29, 36–43 (2014). | article

About the Researcher

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Yinping Yang

Principal Investigator

Institute of High Performance Computing
Yinping Yang is a social technologist who has a passion for advancing human communication and decision-making. She currently leads the affective computing group at A*STAR’s Institute of High Performance Computing (IHPC). Her team drives A*STAR’s digital emotion and empathy machine programme which aims to build emotion-level understanding and empathy in next-generation intelligent systems. Her research has spanned multiple subject areas, including automated negotiation, emotion recognition and sentiment analysis, disease surveillance and ground sensing, and science and technology foresight. Besides research, Yang works extensively on applied industry and public sector projects and is an advisor consulted for deep tech start-ups. Her work has won numerous research and technology innovation awards from prestigious organizations, including a best paper award from the IEEE system sciences conference and a connect + develop open innovation award on digital insights from The Procter and Gamble Company. In 2020, she was named in the inaugural 100 Singapore women in tech list as a female leader recognized in Singapore’s tech sector, and was among 53 outstanding women featured in GovInsider’s special report. She obtained her PhD in Information Systems in 2008 from the School of Computing, National University of Singapore.

This article was made for A*STAR Research by Nature Research Custom Media, part of Springer Nature