ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

Advances in Psychological Science ›› 2022, Vol. 30 ›› Issue (12): 2619-2627.doi: 10.3724/SP.J.1042.2022.02619

• Conceptual Framework •     Next Articles

Human-agent collaborative decision-making in intelligent organizations: A perspective of human-agent inner compatibility

HE Guibing(), CHEN Cheng, HE Zetong, CUI Lidan, LU Jiaqi, XUAN Hongzhou, LIN Lin   

  1. Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310028, China
  • Received:2021-12-31 Online:2022-12-15 Published:2022-09-23
  • Contact: HE Guibing E-mail:gbhe@zju.edu.cn

Abstract:

The era of artificial intelligence has already arrived. With the rapid development of intelligent technology, more and more companies are adopting this technology into their business processes to enhance their core competitiveness. Subsequently, human-agent collaborative work is becoming common, and human-agent collaborative decision-making (HACDM) is evolving as a new form of organizational decision-making. However, evidence shows that HACDM still faces challenges, such as low trust and controllability toward agents, low transparency of agents, and low collaboration between humans and agents. Therefore, how these challenges can be overcome to improve the decision quality, decision efficiency, and user experience of HACDM is crucial to the field of organizational decision-making.
This project suggests that human-agent compatibility, especially human-agent inner compatibility (HAIC) which consists of cognitive, affective, and value compatibility, might be the fundamental factor affecting the performance of HACDM. Following the perspective of HAIC theory and using the multi-disciplinary methods from psychology, cognitive science, and organizational behavior, we intend to 1) reveal the existing problems within HACDM; 2) explore the impact of HAIC on the process and performance of HACDM; 3) propose methods to improve the performance of HACDM. Thus, this project consists of three studies. Study 1 aims to investigate real-world intelligent organizations to uncover the current usage of agents, the willingness of human employees and managers to collaborate with agents, and the possible problems within HACDM. Based on the findings of study 1, study 2 adopts HAIC theory as its framework and explores the influence of cognitive, affective, and value compatibilities on the process and performance of HACDM. Finally, study 3 tests the effectiveness of the several methods suggested by HAIC theory for improving HACDM, such as increasing the transparency of agents’ decisions and providing decision feedback to human employees.
This project’s findings will contribute both theoretically and practically. Theoretically, this project examines the components of HAIC (i.e., cognitive, affective, and value compatibilities) and investigates their influence on HACDM. Thus, it will contribute to the further development of human-agent compatibility theory and human-agent collaboration theory. Practically, the project proposes several methods that can effectively improve the performance of HACDM. Therefore, it will improve the performance of intelligent organizations and promote the intelligentization progress of HACDM.

Key words: intelligent organization, human-agent collaborative decision-making, human-agent inner compatibility, cognitive compatibility, affective compatibility, value compatibility

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