JUPITER

An AI-based mission planning
framework for Navy operations

An AI-based mission planning framework for Navy operations

Joint User-centered Planning Artificial Intelligence Tools for Effective Mission Reasoning (JUPITER)

JUPITER is an AI-based mission planning framework focused on the effective use of AI across Navy workflows and operational contexts. The Phase II Small Business Technology Transfer (STTR) contract will integrate innovative human AI teaming approaches into Navy operations.

While AI is extremely promising, it needs to be thoughtful and efficiently integrated into operational workflows for the technology to realize its full potential. Simply taking an off-the-shelf AI technology and applying it to a mission critical problem is ill-advised.

“We need to take into account the human dimension when applying AI to critical problem spaces. For example, we must consider the capabilities and limitations of the AI technology, what the risks are, how it changes current workflows, where we should and should not use AI, and how the human and AI elements are going to effectively work together to accomplish overall goals.

Stephanie Kane
Principal Scientist and Principal Investigator on JUPITER

There are many challenges that must be addressed when incorporating AI into different workflows. For example, end users need to understand when and how to distribute tasks across the human AI team, how the AI has arrived at its decisions, and what is needed for effective human AI team coordination and execution.

While developing JUPITER, the team also focused on identifying potential operational scenarios for the Navy that are suitable for incorporating AI technologies, deriving requirements for human AI teaming within these scenarios, and developing methods to evaluate different AI solutions that might work within a human AI team.

JUPITER is not just about identifying tasks that can be offloaded to AI. It also optimizes human AI interactions. The JUPITER framework considers the overall human AI team to cultivate effective interactions across the human end user and AI technologies. “It’s about evaluating their performance as a team and how the human’s work changes with the introduction of AI into the envisioned mission workflow,” Kane says.

Phase I of JUPITER involved understanding where and how AI would most significantly impact the mission planning process. The team established requirements for effective human AI collaboration in targeted operations and created lightweight simulation environments to evaluate concepts and simulate human AI interactions in realistic settings.

In Phase II, the JUPITER team built upon the prior success by identifying additional mission operations where human AI teaming could provide benefit to the Navy, and worked to develop, test, and validate these approaches. JUPITER is currently in a Phase II expansion specifically focused on the transition of the technology to target programs.

The key principles and innovative approaches developed under JUPITER for effective human AI teaming can translate to a number of commercial applications, especially as the interest in AI technologies (including generative AI) has continued to grow.

That’s because JUPITER solves a fundamental problem with technology: overall effectiveness. “We’re deeply looking at the effective use of AI, especially considering the ultimate end users,” Kane says.

JUPITER can be licensed to industries that are working to integrate advanced technologies into workflows. “The commercialization potential of JUPITER is immense, as human AI interaction is a fundamental challenge that numerous companies must address to leverage emerging and cutting-edge AI technologies effectively,” Kane adds.

Contact us to learn more about JUPITER and our capabilities in user interfaces & human-machine teaming and human-centric AI.

This material is based upon work supported by the Naval Air Warfare Center under Contract No. N68335-20-C-0769. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of NAVAIR.

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