# Agent Teaming Situation Awareness (ATSA): A Situation Awareness Framework for Human-AI Teaming

arXiv: https://arxiv.org/abs/2308.16785 · HTML: https://mlsanity.com/paper/2308.16785/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 114 references that are in the map.
- First posted on arXiv 31 Aug 2023.

## Builds on (most cited first, 8 of 8)

- [Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy](https://mlsanity.com/paper/2002.04087/) (2020)
- [Embodied Intelligence via Learning and Evolution](https://mlsanity.com/paper/2102.02202/) (2021)
- [Hybrid Intelligence](https://mlsanity.com/paper/2105.00691/) (2021)
- [Transitioning to human interaction with AI systems: New challenges and opportunities for HCI professionals to enable human-centered AI](https://mlsanity.com/paper/2105.05424/) (2021)
- [CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models](https://mlsanity.com/paper/2109.01401/) (2021)
- [Who/What is My Teammate? Team Composition Considerations in Human-AI Teaming](https://mlsanity.com/paper/2105.11000/) (2021)
- [Human-AI Symbiosis: A Survey of Current Approaches](https://mlsanity.com/paper/2103.09990/) (2021)
- [Modeling Engagement in Long-Term, In-Home Socially Assistive Robot Interventions for Children with Autism Spectrum Disorders](https://mlsanity.com/paper/2002.02453/) (2020)

## Built on by (most cited first, 3 of 3)

- [What Types of Human-AI Teams Exist?](https://mlsanity.com/paper/2607.02198/) (2026)
- [Human-Centered Human-AI Collaboration (HCHAC)](https://mlsanity.com/paper/2505.22477/) (2025)
- [From Retrieving Information to Reasoning with AI: Exploring Different Interaction Modalities to Support Human-AI Coordination in Clinical Decision-Making](https://mlsanity.com/paper/2601.22338/) (2026)

## Abstract (arXiv)

The rapid advancements in artificial intelligence (AI) have led to a growing trend of human-AI teaming (HAT) in various fields. As machines continue to evolve from mere automation to a state of autonomy, they are increasingly exhibiting unexpected behaviors and human-like cognitive/intelligent capabilities, including situation awareness (SA). This shift has the potential to enhance the performance of mixed human-AI teams over all-human teams, underscoring the need for a better understanding of the dynamic SA interactions between humans and machines. To this end, we provide a review of leading SA theoretical models and a new framework for SA in the HAT context based on the key features and processes of HAT. The Agent Teaming Situation Awareness (ATSA) framework unifies human and AI behavior, and involves bidirectional, and dynamic interaction. The framework is based on the individual and team SA models and elaborates on the cognitive mechanisms for modeling HAT. Similar perceptual cycles are adopted for the individual (including both human and AI) and the whole team, which is tailored to the unique requirements of the HAT context. ATSA emphasizes cohesive and effective HAT through structures and components, including teaming understanding, teaming control, and the world, as well as adhesive transactive part. We further propose several future research directions to expand on the distinctive contributions of ATSA and address the specific and pressing next steps.