Towards Better Trust in Human-Machine Teaming through Explainable Dependability

The human-machine teaming paradigm is increasingly widespread in critical domains, such as healthcare and domestic assistance. The paradigm goes beyond human-on-the-loop and human-in-the-loop systems by promoting tight teamwork between humans and autonomous machines that collaborate in the same phys...

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Veröffentlicht in:International Conference on Software Architecture Companion (Online) S. 86 - 90
Hauptverfasser: Bersani, Marcello M., Camilli, Matteo, Lestingi, Livia, Mirandola, Raffaela, Rossi, Matteo, Scandurra, Patrizia
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.03.2023
Schlagworte:
Analytical models
Autonomous systems
Behavioral sciences
explainable AI
formal analysis
Human in the loop
Human-machine teaming
Medical services
Software architecture
statistical model checking
Teamwork
ISSN:2768-4288
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Beschreibung
Zusammenfassung:The human-machine teaming paradigm is increasingly widespread in critical domains, such as healthcare and domestic assistance. The paradigm goes beyond human-on-the-loop and human-in-the-loop systems by promoting tight teamwork between humans and autonomous machines that collaborate in the same physical space. These systems are expected to build a certain level of trust by enforcing dependability and exhibiting interpretable behavior. We present emerging results in this direction, with a novel framework aiming at achieving better trust in human-machine teaming leveraging formal analysis, as well as eXplainable AI. We illustrate our approach and the emerging results with an example from the healthcare domain.
ISSN:2768-4288
DOI:10.1109/ICSA-C57050.2023.00029