Year: 2025
Type: conference-paper
Abstract: Many Human-AI collaborations are based on task environments in which tasks on controllable assets need to be taken (e.g., to change a route of a truck or to send an informational message to the truck driver) in response to results of monitoring tasks (e.g., changes in customer needs, changes in weather). Human-AI teams need to collaborate effectively and efficiently to generate, assess, and adjust Courses of Actions (COAs) in those environments. RTX BBN Technologies (BBN) has developed multiple AI agents, covering different specific use cases, and is currently deploying Human-AI teams into operational environments. In our work, the most relevant use cases involve an AI agent advising a human on executing complex tasks and human and AI agents handling subtasks usually done by one person. The workshop presentation will focus on overall context, our successes with Human-AI teams in recent years, and specific insights from our work with Human-AI teams performing joint activities in controlled tasking environments.
Authors: Michael Atighetchi, Sedona Thomas, Regan Broderick-Sander, Julia Hiebel
Institution: RTX (United States)
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4410822971