The American Defence Advanced Research Projects Agency (DARPA) is working on building human-machine systems, combining human cognitive strengths and the unique capabilities of smart machines to create intelligent teams adaptive to rapidly changing circumstances.
Modern military operations require infantry squads to carry out their missions simultaneously in the 3-dimensional physical world, the cyber domain, and across the electromagnetic spectrum.
DARPA has announced the Agile Teams program (A-Teams), which sets out to discover, test, and demonstrate predictive and generalisable mathematical methods to enable optimised design of agile hybrid teams. The idea is to challenge the current paradigm of human-intelligent machine systems design by changing the focus from simply using machines for automation and substitution of human capacity to an integrated fabric enabling superior collective problem solving.
“A-Teams is focused not on developing new AI technologies per se, but on developing a framework for optimising the use of smart machines in various roles together with humans to ensure optimal human-machine teamwork for solving dynamic problems,” said John Paschkewitz, DARPA program manager.
“Given an uncertain environment and fluid team structure, how does one best use combined human and machine capabilities to make wise decisions? Are there generalisable mathematical abstractions to capture the dynamic interactions of problem space, team structure, and performance? These are the kinds of questions we intend to answer in the program.”
He says A-Teams results could also apply to team performance in non-combat applications, such as scientific and drug discovery, software engineering, logistics planning, advanced hardware engineering, and intelligence forecasting. Problem solving in these complex environments exceeds the capacity of any individual and is best addressed by teams of people augmented by technology, such as with computer-aided design and collaborative work tools.
The program focus will be on mathematical methods for designing optimal hybrid teams of humans and intelligent machine elements that will be demonstrated and validated in dynamic and complex problem-solving contexts using experimental testbeds. Intelligent machine elements could take a variety of possible forms, including machine agents capable of peer-level interaction with human team members for executing team goals, or as an intelligent problem solving workspace that can coordinate communications and task assignment to optimise team performance.