Team resilience is emerging as an essential factor in human-autonomy teams (HATs), where humans and AI collaborate. HATs may face various adversities with respect to technology failures, unpredictable situations, and human-AI communication. Team resilience is essential for overcoming such setbacks, enabling HATs to adapt, recover, and accomplish task goals under pressure. Despite growing interest in HAT resilience, existing research lacks a unified framework that integrates the distinct capabilities of humans and AI, their mental models, the various phases of collaboration, and relevant situational factors. We propose a novel framework, drawing from resilience engineering principles, that examines how humans and AI teammates dynamically integrate their capabilities to overcome challenges collectively. Our approach focuses on the distribution of demands between human and AI teammates, recognizing this allocation’s importance to team adaptation and recovery. The framework considers the cross-effects of human and AI resilience components, such as capability and adaptation, within the context of demand distribution and collaborative decision-making to achieve effective and resilient HAT performance. This framework aims to provide a new understanding of the implications of the distribution of demands in HATs and its relation to the team’s resilience.
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