Empirical Impacts of Independent and Collaborative Training on Task Performance and Improvement in Human-AI Teams

Author:

Flathmann Christopher1ORCID,Schelble Beau G.2ORCID,Galeano Anna1

Affiliation:

1. Clemson University, Clemson, SC, USA

2. The University of Tennessee, Knoxville, TN, USA

Abstract

With improving AI technology, human-AI teams are becoming increasingly common in research. Within these teams, humans and AI can work collaboratively to complete shared tasks. However, continuing research efforts highlight that humans are ill-prepared to work in human-AI teams. As such, recent efforts have called for training to become a greater focus in the. This paper reports on an empirical in-person experiment that explored the impact of individual and collaborative task-focused training in human-AI teams. Participants were tasked with either training together or separately prior to collaborative working in a human-AI team. Results show that having humans train together prior to joining a human-AI team can negatively impact their performance and ability to improve at a task when they begin working in a human-AI team. As such, results suggest that human-AI teams need to identify ideal ways to collaboratively train humans on task-related skills in human-AI teams.

Publisher

SAGE Publications

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