{"title":"机器人的公平性对人机合作团队中人类奖惩行为和信任的影响","authors":"Jiajia Cao, Na Chen","doi":"10.1177/00187208221133272","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Based on social exchange theory, this study investigates the effects of robots' fairness and social status on humans' reward-punishment behaviors and trust in human-robot interactions.</p><p><strong>Background: </strong>In human-robot teamwork, robots show fair behaviors, dedication (altruistic unfair behaviors), and selfishness (self-interested unfair behaviors), but few studies have discussed the effects of these robots' behaviors on teamwork.</p><p><strong>Method: </strong>This study adopts a 3 (the independent variable is the robot's fairness: self-interested unfair behaviors, fair behaviors, and altruistic unfair behaviors) × 3 (the moderator variable is the robot's social status: superior, peer, and subordinate) experimental design. Each participant and a robot completed the experimental task together through a computer.</p><p><strong>Results: </strong>When robots have different social statuses, the more altruistic the fairness of the robot, the more reward behaviors, the fewer punishment behaviors, and the higher human-robot trust of humans. Robots' higher social status weakens the influence of their fairness on humans' punishment behaviors. Human-robot trust will increase humans' reward behaviors and decrease humans' punishment behaviors. Humans' reward-punishment behaviors will increase repaired human-robot trust.</p><p><strong>Conclusion: </strong>Robots' fairness has a significant impact on humans' reward-punishment behaviors and trust. Robots' social status moderates the effect of their fair behavior on humans' punishment behavior. There is an interaction between humans' reward-punishment behaviors and trust.</p><p><strong>Application: </strong>The study can help to better understand the interaction mechanism of the human-robot team and can better serve the management and cooperation of the human-robot team by appropriately adjusting the robots' fairness and social status.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":" ","pages":"1103-1117"},"PeriodicalIF":4.7000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Influence of Robots' Fairness on Humans' Reward-Punishment Behaviors and Trust in Human-Robot Cooperative Teams.\",\"authors\":\"Jiajia Cao, Na Chen\",\"doi\":\"10.1177/00187208221133272\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Based on social exchange theory, this study investigates the effects of robots' fairness and social status on humans' reward-punishment behaviors and trust in human-robot interactions.</p><p><strong>Background: </strong>In human-robot teamwork, robots show fair behaviors, dedication (altruistic unfair behaviors), and selfishness (self-interested unfair behaviors), but few studies have discussed the effects of these robots' behaviors on teamwork.</p><p><strong>Method: </strong>This study adopts a 3 (the independent variable is the robot's fairness: self-interested unfair behaviors, fair behaviors, and altruistic unfair behaviors) × 3 (the moderator variable is the robot's social status: superior, peer, and subordinate) experimental design. Each participant and a robot completed the experimental task together through a computer.</p><p><strong>Results: </strong>When robots have different social statuses, the more altruistic the fairness of the robot, the more reward behaviors, the fewer punishment behaviors, and the higher human-robot trust of humans. Robots' higher social status weakens the influence of their fairness on humans' punishment behaviors. Human-robot trust will increase humans' reward behaviors and decrease humans' punishment behaviors. Humans' reward-punishment behaviors will increase repaired human-robot trust.</p><p><strong>Conclusion: </strong>Robots' fairness has a significant impact on humans' reward-punishment behaviors and trust. Robots' social status moderates the effect of their fair behavior on humans' punishment behavior. There is an interaction between humans' reward-punishment behaviors and trust.</p><p><strong>Application: </strong>The study can help to better understand the interaction mechanism of the human-robot team and can better serve the management and cooperation of the human-robot team by appropriately adjusting the robots' fairness and social status.</p>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":\" \",\"pages\":\"1103-1117\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2024-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1177/00187208221133272\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/10/11 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1177/00187208221133272","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/10/11 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
The Influence of Robots' Fairness on Humans' Reward-Punishment Behaviors and Trust in Human-Robot Cooperative Teams.
Objective: Based on social exchange theory, this study investigates the effects of robots' fairness and social status on humans' reward-punishment behaviors and trust in human-robot interactions.
Background: In human-robot teamwork, robots show fair behaviors, dedication (altruistic unfair behaviors), and selfishness (self-interested unfair behaviors), but few studies have discussed the effects of these robots' behaviors on teamwork.
Method: This study adopts a 3 (the independent variable is the robot's fairness: self-interested unfair behaviors, fair behaviors, and altruistic unfair behaviors) × 3 (the moderator variable is the robot's social status: superior, peer, and subordinate) experimental design. Each participant and a robot completed the experimental task together through a computer.
Results: When robots have different social statuses, the more altruistic the fairness of the robot, the more reward behaviors, the fewer punishment behaviors, and the higher human-robot trust of humans. Robots' higher social status weakens the influence of their fairness on humans' punishment behaviors. Human-robot trust will increase humans' reward behaviors and decrease humans' punishment behaviors. Humans' reward-punishment behaviors will increase repaired human-robot trust.
Conclusion: Robots' fairness has a significant impact on humans' reward-punishment behaviors and trust. Robots' social status moderates the effect of their fair behavior on humans' punishment behavior. There is an interaction between humans' reward-punishment behaviors and trust.
Application: The study can help to better understand the interaction mechanism of the human-robot team and can better serve the management and cooperation of the human-robot team by appropriately adjusting the robots' fairness and social status.
期刊介绍：
ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications.
The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.
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