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An Agile New Research Framework for Hybrid Human-AI Teaming: Trust, Transparency, and Transferability

Authors :
Sabrina Caldwell
Penny Sweetser
Nicholas O’Donnell
Matthew J. Knight
Matthew Aitchison
Tom Gedeon
Daniel Johnson
Margot Brereton
Marcus Gallagher
David Conroy
Source :
ACM Transactions on Interactive Intelligent Systems. 12:1-36
Publication Year :
2022
Publisher :
Association for Computing Machinery (ACM), 2022.

Abstract

We propose a new research framework by which the nascent discipline of human-AI teaming can be explored within experimental environments in preparation for transferal to real-world contexts. We examine the existing literature and unanswered research questions through the lens of an Agile approach to construct our proposed framework. Our framework aims to provide a structure for understanding the macro features of this research landscape, supporting holistic research into the acceptability of human-AI teaming to human team members and the affordances of AI team members. The framework has the potential to enhance decision-making and performance of hybrid human-AI teams. Further, our framework proposes the application of Agile methodology for research management and knowledge discovery. We propose a transferability pathway for hybrid teaming to be initially tested in a safe environment, such as a real-time strategy video game, with elements of lessons learned that can be transferred to real-world situations.

Details

ISSN :
21606463 and 21606455
Volume :
12
Database :
OpenAIRE
Journal :
ACM Transactions on Interactive Intelligent Systems
Accession number :
edsair.doi...........1195ad70eeedef84ca4c6eec8e1f8845