Tag Archives: U.S. Army Combat Capabilities Development Command

University Of Maryland Will Investigate AI Limitations Via Army Research Grant

COLLEGE PARK, MD: University of Maryland College of Information Studies (UMD iSchool) researchers, led by principal investigator Dr. Susannah Paletz, have been awarded a three-year $616,700 usd grant funded by the Army Research Office (ARO), overseen by ARO Program Manager Dr. Edward Palazzolo. This project examines how teams of intelligence analysts can work together and with artificial intelligence (AI). AI has the potential to support intelligence analysts in reviewing potentially hundreds of thousands of source documents, pulling out key findings, and assembling them into actionable intelligence. AI can also aid in the flow of information and projects among members of the intelligence team, improving the efficiency and accuracy of their work.

“AI-driven technology has sometimes been touted as a replacement for human intelligence,” said Dr. Adam Porter, the project’s co-principal investigator, professor at the UMD Department of Computer Science, and Executive and Scientific Director of the Fraunhofer USA Center for Experimental Software Engineering (CESE). “In practice, however, AI doesn’t always work, or gives limited or biased answers. Human oversight is still required, and it’s therefore critical that we deeply understand how humans and AI can work best together.”

The Human-Agent Teaming on Intelligence Tasks project coordinated through the iSchool will focus on two particular research areas; 1.) how interactive AI agents, such as chatbots, have the ability to mitigate or exacerbate the communication and coordination problems that can occur with shift handovers of intelligence work, such as inaccuracy blindness and overlooking potentially relevant information, and 2.) examining how humans could potentially deal with these blind spots, biases, or inaccuracies. 

The research team plans to develop an experimental infrastructure to help test team cognition challenges within the work completed by intelligence analysts consisting of task-relevant input materials, such as mission descriptions and source documents, activity recording tools, experimental monitoring capabilities, and different AI supports for human analysts, such as chatbots offering advice on a particular task. 

“We want to develop a task that can raise the problems with asynchronous team cognition in intelligence tasks, but is simple enough to be used by research participants with minimal training,” said Dr. Susannah B.F. Paletz, research professor at the UMD iSchool, and affiliate at the UMD Applied Research Laboratory for Intelligence and Security (ARLIS). 

Susannah Paletz
Dr. Susannah B.F. Palletz


This task will substantially increase insight into the strengths and weaknesses of AI technology to support intelligence tasks, help shed light on how and when human analysts can safely place their trust in AI technology, and how they can proactively identify problems in AI-generated input. It will also aid teams of humans, including asynchronous teams, working together in situations that include AI-generated input.

“This basic research is an important step in the early process of learning how humans and agents can collaboratively become a single team with considerably greater capacity and productivity than human only teams,” Palazzolo said. “Moreover, this research has broad implications into the work of many teams focused on knowledge work and information management such as medical teams involved in shift work, collaborative software development teams, and research teams.”

In addition to Porter, the Fraunhofer USA team also includes Dr. Madeline Diep, Senior Scientist, and Jeronimo Cox, Software Developer, at Fraunhofer USA CESE. The Fraunhofer USA team will lead the effort to create configurable AI agents used in the experimental tasks, and a data collection and analysis infrastructure for capturing and understanding participant behaviors.

The UMD iSchool team includes graduate students Tammie Nelson, a fourth year PhD student, Melissa Carraway, incoming first year PhD student, and Sarah Valhkamp, incoming first year PhD, in Information Science.

The grant proposal team includes UMD Office of Research Administration Contract Manager, Stephanie Swann; iSchool Business Manager, Jacqueline Armstrong; and former iSchool Business Manager, Lisa Geraghty.

Outside of UMD, Dr. Aimee Kane, the Harry W. Witt Faculty Fellow and an Associate Professor of Management in the Palumbo-Donahue School of Business at Duquesne University, will be a consultant and an intellectual contributor on this project.

ARO is an element of the U.S. Army Combat Capabilities Development Command’s (CCDC) Army Research Laboratory. The Human-Agent Teaming on Intelligence Tasks project (grant no. W911NF-20-1-0214) is slated to run through June 30, 2023. For the Silo, Mia Hinckle.

Autonomous Vehicles Now Able To Stop Safely

Mendon, Utah – Autonomous Solutions, Inc. (ASI) has received Phase I funding from the U.S. Army Combat Capabilities Development Command Ground Vehicles Systems Center (formerly TARDEC) to improve the way heavy vehicles stop while operating autonomously. 

“Bringing large autonomous vehicles to a safe stop in varying environments can be challenging,” said Jeff Ferrin, CTO of ASI. “Having additional funding from the Army to further develop this technology will help us make autonomous vehicles safer, which is always our number-one priority.” 

The objective of the Army in awarding this grant is to develop and demonstrate a system that can be operated remotely and considers both the dynamics of the vehicle, as well as the environment, to optimally and safely bring a large ground vehicle to a complete stop despite the terrain.

“ASI has been working on terrain characterization with the Army since 2014,” said Ferrin. “This project will use similar technology to make sure the vehicle is aware of the terrain around it. This model of the terrain will then be used by the vehicle to ensure a safer stop is completed.”

A significant focus of this intelligent urgent stop initiative is machine learning. This improved technology will continuously monitor the interaction between a vehicle and its surroundings and update the internal model that is used to properly halt the vehicle. This process will allow the vehicle to learn and adapt as the terrain and environment change.

As the advanced solution is developed, tested and proven, it can be used by ASI’s autonomous vehicles across all the company’s multiple industries, including agriculture, automotive, construction haulage, mining, facility robotics and more.

According to Ferrin, “The system can be used with any drive-by-wire vehicle. It will interface with the brakes and steering to bring the vehicle to a safe, controlled stop.”

Details of the Phase I stage awarded to ASI include development of a concept design using commercial-off-the-shelf (COTS) sensors to perform safe deceleration of a large ground vehicle. A concept design report and performance analysis report are required deliverables before Phase II can be awarded. For the Silo, Brandon Taylor.

About ASI

Autonomous Solutions, Inc. (ASI) is a world leader in industrial vehicle automation. ASI serves clients across the world in the mining, agriculture, automotive, government, and manufacturing industries with remote control, teleoperation, and fully automated solutions from its headquarters and 100-acre proving ground in northern Utah.