Unmanned Undersea Systems (UUXs) often operate in communication-limited environments, which require some degree of autonomy in order to operate efficiently and effectively. Current autonomous systems often operate as “black boxes”, which may offer high performance but lack transparency. As such, the use of autonomous systems requires a high degree of trust from the user, which may be difficult to gain. Explainable artificial intelligence (XAI) may offer a way to build user trust in AI systems, by increasing transparency and offering explanations for anomalous behavior. Currently, XAI is used by researchers as an analytic tool to identify poor model performance and improve user interfacing. In this work, we propose that explainability can be transformed into a user-facing tool to foster understanding in both users and developers. We will demonstrate this concept by contextualizing a system’s actions within a restrictive environment, utilizing a simplified scenario with simulated sensor inputs. Success and failure will be defined by creating metrics for the succinctness and relevance of an explanation, including both the salience of provided context and the absence of important information. The
resulting explanations will piece together the environmental conditions, mission, behaviors, and operational status in order to deliver an intuitive explanation of the decisions of an autonomous system.

Exploring Trust and Explainability of Autonomous Systems in an Operational Environment


Group Q&A and panel discussion with authors of talks on Autonomy and Edge Computing

**Moderator:** [Michael Tall](https://www.underline.io/speakers/74376-mike-tall)

**Speakers:**  

[Richard Yang ](https://www.underline.io/speakers/80728-richard-yang)

[Ruriko Yoshida ](https://www.underline.io/speakers/77576-ruriko-yoshida)

[Casey Sapp](https://www.underline.io/speakers/74322-casey-sapp)

[Brad Walls](https://www.underline.io/speakers/77594-brad-walls)

[Alisha Sharma](https://www.underline.io/speakers/77588-alisha-sharma)

[Maj. Larry Wigington](https://www.underline.io/speakers/77627-maj.-larry-wigington)

[Douglas Horner](https://www.underline.io/speakers/81600-douglas-horner)


Autonomy and Edge Computing

technical paper

Naval Information Warfare Center Pacific is partnering with AFCEA San Diego chapter to host the workshop.

The NAML workshop is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team.

The goals of NAML are:

* To spread awareness of current machine learning research relevant to Naval applications

* To connect machine learning researchers with experts in military requirements

* To build and strengthen collaborations within the defense research community

**Watch this video to hear about the AFCEA purpose.**

<iframe width=1280 height=706 frameborder="0" scrolling="no" src="https://screencast-o-matic.com/player/creleVVcvRh?v=6&ff=1&title=0&controls=1" allowfullscreen="true"></iframe>

Richard Yang

1

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Exploring Trust and Explainability of Autonomous Systems in an Operational Environment

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