Team Structure and Team Building Improve Human–Machine Teaming With Autonomous Agents

Author:

Walliser James C.1,de Visser Ewart J.2ORCID,Wiese Eva3,Shaw Tyler H.3

Affiliation:

1. Air Force Nuclear Weapons Center, USA

2. George Mason University, USA and United States Air Force Academy, USA

3. George Mason University, USA

Abstract

Research suggests that humans and autonomous agents can be more effective when working together as a combined unit rather than as individual entities. However, most research has focused on autonomous agent design characteristics while ignoring the importance of social interactions and team dynamics. Two experiments examined how the perception of teamwork among human–human and human–autonomous agents and the application of team building interventions could enhance teamwork outcomes. Participants collaborated with either a human or an autonomous agent. In the first experiment, it was revealed that manipulating team structure by considering your human and autonomous partner as a teammate rather than a tool can increase affect and behavior, but does not benefit performance. In the second experiment, participants completed goal setting and role clarification (team building) with their teammate prior to task performance. Team building interventions led to significant improvements for all teamwork outcomes, including performance. Across both studies, participants communicated more substantially with human partners than they did with autonomous partners. Taken together, these findings suggest that social interactions between humans and autonomous teammates should be an important design consideration and that particular attention should be given to team building interventions to improve affect, behavior, and performance.

Funder

Air Force Office of Scientific Research

Publisher

SAGE Publications

Subject

Applied Psychology,Engineering (miscellaneous),Computer Science Applications,Human Factors and Ergonomics

Cited by 52 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Human control of AI systems: from supervision to teaming;AI and Ethics;2024-05-28

2. An Evaluation of Situational Autonomy for Human-AI Collaboration in a Shared Workspace Setting;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11

3. More than Task Performance: Developing New Criteria for Successful Human-AI Teaming Using the Cooperative Card Game Hanabi;Extended Abstracts of the CHI Conference on Human Factors in Computing Systems;2024-05-02

4. Low-rank human-like agents are trusted more and blamed less in human-autonomy teaming;Frontiers in Artificial Intelligence;2024-04-29

5. The Soul of Work: Evaluation of Job Meaningfulness and Accountability in Human-AI Collaboration;Proceedings of the ACM on Human-Computer Interaction;2024-04-17

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3