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

Author:

Caldwell Sabrina1,Sweetser Penny1ORCID,O’Donnell Nicholas2,Knight Matthew J.3,Aitchison Matthew1,Gedeon Tom1,Johnson Daniel2,Brereton Margot2,Gallagher Marcus4,Conroy David2

Affiliation:

1. Australian National University, Canberra, ACT, Australia

2. Queensland University of Technology, Brisbane City, QLD, Australia

3. Defence Science and Technology, Edinburgh, SA, Australia

4. University of Queensland, St Lucia, QLD, Australia

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.

Funder

Defence Science and Technology Group

Defence Science Partnerships

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Human-Computer Interaction

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