Data on the Human Versus artificial intelligence process management experiment

被引:4
|
作者
Zurita, Nicolas F. Soria [1 ,2 ]
Gyory, Joshua T. [3 ]
Balon, Corey [4 ]
Martin, Jay [4 ]
Kotovsky, Kenneth [5 ]
Cagan, Jonathan [3 ]
McComb, Christopher [3 ]
机构
[1] Penn State Univ, Sch Engn Design Technol & Profess Programs, University Pk, PA 16802 USA
[2] Univ San Francisco Quito, Colegio Ciencias & Ingn, Diego Roblesy Via Interocean, Quito, Ecuador
[3] Carnegie Mellon Univ, Dept Mech Engn, Pittsburgh, PA 15213 USA
[4] Penn State Univ, Appl Res Lab, University Pk, PA 16802 USA
[5] Carnegie Mellon Univ, Dept Psychol, Pittsburgh, PA 15213 USA
来源
DATA IN BRIEF | 2022年 / 41卷
关键词
Artificial intelligence; Collaborative design; Design teams; Engineering design; Human-computer interaction; Process management; Complex engineering systems;
D O I
10.1016/j.dib.2022.107917
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Human subject experiments are performed to evaluate the influence of artificial intelligence (AI) process management on human design teams solving a complex engineering problem and compare that to the influence of human process management. Participants are grouped into teams of five individuals and asked to generate a drone fleet and plan routes to deliver parcels to a given customer market. The teams are placed under the guidance of either a human or an AI external process manager. Halfway through the experiment, the customer market is changed unexpectedly, requiring teams to adjust their strategy. During the experiment, participants can create, evaluate, share their drone designs and delivery routes, and communicate with their team through a text chat tool using a collaborative research platform called HyForm. The research platform collects step-by-step logs of the actions made by and communication amongst participants in both the design team's roles and the process managers. This article presents the data sets collected for 171 participants assigned to 31 design teams, 15 teams under the guidance of an AI agent (5 participants), and 16 teams under the guidance of a human manager (6 participants). These data sets can be used for data-driven design, behavioral analyses, sequence-based analyses, and natural language processing. (C) 2022 The Author(s). Published by Elsevier Inc.
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页数:10
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