Best of both worlds: Human autonomy teaming for effective decision making
Up to $1.2M in phased development funding to propel technology forward
The Department of National Defence and the Canadian Armed Forces (DND/CAF) are seeking innovative solutions to provide effective and trusted Human-Autonomy Teaming (HAT) support for the analysis and management of information received from disparate data sources to support decision making in NORAD’s (North American Aerospace Defense Command) Command and Control (C2) Operations.
What IDEaS provides
Funding of up to $200,000 will be provided for innovative solutions to help advance this defence challenge over a performance period of up to 6 months. There is a potential opportunity for further funding of up to $1 million for a performance period of up to a year should the solution be found successful and promising by DND/CAF.
What innovators bring
Solutions that demonstrate effective Human-Autonomy Teaming (HAT) in NORAD C2 operations that result in timely responses and trusted and verifiable AI decisions. Proposed solutions must focus on advanced training systems and/or after-action analysis functionalities in the context of continental surveillance.
Background and context
In the context of future battle management for missile and air defense in NORAD operations, systems will invariably involve human operators working closely with autonomous systems to ensure effective C2 through enhanced situational awareness and efficient threat response. The C2 effectiveness depends on the timely response, which, under the ever-growing sources of data, can exceed the capacity of the most experienced human operators. Inevitably, Artificial intelligence (AI)-enabled decision support tools will be critical to compensate for human limitations and help enable and ensure HAT capabilities. However, many AI-enabled systems operate in environments that are not specifiable a priori. There will also always be environments in which data come from multiple sources, including new or partially unreliable ones, and where the integrity of data sources and AI processes and outputs cannot be fully trusted. To achieve the full HAT potential for C2 operations, there is the need for mutual trust between human operators and AI-enabled decision aids in the context of wide area surveillance, advanced training systems, and after-action analysis. With such trusted partnership, a persistent and reliable HAT decision support capability will help achieve information dominance and decision superiority.
Proposed solutions must provide trustworthy tools that demonstrate effective HAT in NORAD C2 operations that results in timely responses and trusted and verifiable AI decisions. Proposed solutions focus on advanced training systems and/or after-action analysis functionalities in the context of continental surveillance.
Proposed solutions that focus on advanced training systems and/or after-action analysis functionalities in the context of continental surveillance should support NORAD human operators for the test, evaluation, and audit of AI enabled decisions related to continental surveillance.
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