Comparing the Impacts on Team Behaviors Between Artificial Intelligence and Human Process Management in Interdisciplinary Design Teams
| Autor: | Joshua T. Gyory, Kenneth Kotovsky, Christopher McComb, Jonathan Cagan |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Journal of Mechanical Design. 144 |
| ISSN: | 1528-9001 1050-0472 |
| DOI: | 10.1115/1.4054723 |
| Popis: | This brief extends prior research by the authors on studying the impacts of interventions provided by either a human or an artificial intelligence (AI) process manager on team behaviors. Our earlier research found that a created AI process manager matched the capabilities of human process management. Here, these data are studied further to identify the impact of different types of interventions on team behaviors and outcomes. This deeper dive is done via two unique perspectives: comparing teams’ problem-solving processes before and after interventions are provided, and through a regression analysis between intervention counts and performance. Results show overall mixed adherence to the provided interventions, and that this adherence also depends on the intervention type. The most significant impact on the team process arises from the communication frequency interventions. Furthermore, a regression analysis identifies the interventions with the greatest correlation with team performance, indicating a better selection of interventions from the AI process manager. Paired together, the results show the feasibility of automated process management via AI and shed light on the effective implementation of intervention strategies for future development and deployment. |
| Databáze: | OpenAIRE |
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