Opportunity Information: Apply for W911NF 17 S 0003 ADVANCED AI AA ANALYTIC
The Department of Defense (U.S. Army Materiel Command), through DEVCOM’s Data and Analysis Center (DEVCOM DAC) and under the Army Research Laboratory (ARL) Broad Agency Announcement W911NF-17-S-0003, issued a Special Notice seeking proposals focused on "Advanced AI/AA Analytics." The core purpose of the opportunity is to fund applied research that builds a rigorous analytical and simulation-based framework the Army can use to properly assess, test, and evaluate artificial intelligence and assistive automation (AI/AA) systems before and during integration into Army operations. In practical terms, the Army is looking for a credible, repeatable way to understand how AI-enabled or automation-enabled capabilities perform, what they are good at, where they fail, and how they affect overall mission outcomes when paired with human operators.
A central requirement is that the proposed framework cover live, virtual, and constructive (LVC) simulation approaches. That means the effort should not be limited to one type of modeling or test environment. Instead, it should be able to represent AI/AA systems in realistic Army operational situations across a spectrum: live testing where feasible, virtual simulations that replicate platforms and environments, and constructive simulations where forces and behaviors are represented computationally at scale. The government’s intent is to create a toolset and methodology that can model the AI/AA system inside operational contexts that matter to the Army, rather than evaluating algorithms in isolation. This emphasis reflects a need to examine the full technology-human operator ensemble, including how people interact with AI/AA, how trust and workload shift, and how performance changes under stress, uncertainty, and mission complexity.
The desired framework is meant to directly support a range of analysis types that DEVCOM DAC performs for Army leaders. Specifically, the framework should enable direct measurement of system behavior and outcomes, trade-off analyses (for example, comparing alternative AI/AA designs, levels of autonomy, or sensor/compute configurations), and performance and effectiveness analyses that translate technical performance into operational value. It should also produce data suitable for feeding higher-level force-on-force models, which are often used to explore campaign-level or large-unit outcomes. Additionally, the Army highlights sustainability analysis, signaling interest in understanding not only how AI/AA performs in ideal conditions, but also how it can be supported over time, including implications for maintenance, updates, data requirements, retraining, logistics, and operational readiness.
A major deliverable embedded in the notice is the development and delivery of metrics, along with the underlying variables that drive those metrics. The government is not just asking for generic scorecards; it is asking for experimental, calculated, or modeled measures that have high explanatory value. In other words, the metrics should meaningfully capture the most important determinants of performance and effectiveness for AI/AA technologies when used by human operators in realistic scenarios. This suggests an expectation that proposers will define what "good" looks like in operational terms, connect those outcomes to measurable drivers (such as decision accuracy, timeliness, robustness to degraded data, operator workload, error rates, mission success contributions, resilience under adversarial conditions, and similar factors), and provide a defensible method for measuring or estimating them within LVC environments.
From a funding and administrative perspective, the opportunity is categorized as discretionary and uses a cooperative agreement instrument, which typically implies substantial government involvement during performance (for example, collaboration, iterative reviews, or shared technical direction consistent with the award’s terms). The listing indicated an award ceiling of $45,000,000 with an expectation of a single award, pointing to a large, integrated effort rather than a collection of small independent projects. The CFDA number provided is 12.431 (a defense R&D-related assistance listing). The posting dates in the source data show it was created March 10, 2021 with an original closing date of April 12, 2021.
In summary, this Special Notice targets an applied research effort to build an Army-relevant evaluation ecosystem for AI and assistive automation: a comprehensive LVC-enabled analytical and simulation framework, backed by well-defined, high-value metrics, that allows DEVCOM DAC and senior decision makers to quantify performance, compare alternatives, understand operational impacts, generate inputs for broader force models, and make more confident choices about integrating AI/AA systems into Army organizations and missions.Apply for W911NF 17 S 0003 ADVANCED AI AA ANALYTIC
- The Department of Defense, Dept of the Army -- Materiel Command in the science and technology and other research and development sector is offering a public funding opportunity titled "SPECIAL NOTICE FOR ADVANCED AI/AA ANALYTICS" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 12.431.
- This funding opportunity was created on Mar 10, 2021.
- Applicants must submit their applications by Apr 12, 2021. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Each selected applicant is eligible to receive up to $45,000,000.00 in funding.
- The number of recipients for this funding is limited to 1 candidate(s).
- Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).
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Frequently Asked Questions (FAQ) - Advanced AI/AA Analytics (DEVCOM DAC / ARL BAA W911NF-17-S-0003 Special Notice)
1) Who is offering this grant opportunity?
This opportunity is issued by the Department of Defense (U.S. Army Materiel Command) through DEVCOM's Data and Analysis Center (DEVCOM DAC) under the Army Research Laboratory (ARL) Broad Agency Announcement (BAA) W911NF-17-S-0003.
2) What is the focus area of the Special Notice?
The Special Notice seeks proposals focused on "Advanced AI/AA Analytics," centered on evaluating artificial intelligence and assistive automation (AI/AA) systems in Army-relevant operational contexts.
3) What is the main purpose of the effort being funded?
The purpose is to fund applied research that builds a rigorous analytical and simulation-based framework the Army can use to assess, test, and evaluate AI/AA systems before and during their integration into Army operations.
4) What problem is the Army trying to solve with this effort?
The Army is seeking a credible, repeatable way to understand how AI-enabled or automation-enabled capabilities perform, what they do well, where they fail, and how they impact mission outcomes when paired with human operators.
5) Is this opportunity about evaluating AI algorithms in isolation?
No. The government intent is to model and evaluate AI/AA systems within operational contexts that matter to the Army, rather than evaluating algorithms alone.
6) What does "AI/AA" mean in this notice?
In this notice, AI/AA refers to artificial intelligence and assistive automation systems, including AI-enabled and automation-enabled capabilities used in Army operations.
7) What kind of framework is the Army asking proposers to build?
The Army is asking for an analytical and simulation-based evaluation framework (a toolset and methodology) that can represent AI/AA systems in realistic operational situations and support repeatable assessment across relevant Army mission contexts.
8) What does LVC mean, and why is it required?
LVC stands for live, virtual, and constructive simulation. The framework is required to cover LVC approaches so the Army can represent AI/AA systems across a spectrum of environments: live testing where feasible, virtual simulations that replicate platforms and environments, and constructive simulations that model forces and behaviors computationally at scale.
9) Does the framework need to include all three simulation approaches (live, virtual, and constructive)?
Yes. A central requirement is that the proposed framework cover live, virtual, and constructive simulation approaches, rather than being limited to only one type of modeling or test environment.
10) What is meant by evaluating AI/AA in "realistic Army operational situations"?
It means evaluating AI/AA systems inside operational contexts relevant to Army missions, including conditions involving stress, uncertainty, and mission complexity, and accounting for how the system performs as part of a broader operational scenario rather than in a lab-only setting.
11) Is human interaction with AI/AA part of the evaluation scope?
Yes. The notice emphasizes examining the full technology-human operator ensemble, including how people interact with AI/AA, how trust and workload change, and how performance shifts under stress and uncertainty.
12) What types of analyses should the framework support?
The framework is intended to support analysis types that DEVCOM DAC performs for Army leaders, including direct measurement of system behavior and outcomes, trade-off analyses, and performance and effectiveness analyses that translate technical performance into operational value.
13) What are "trade-off analyses" in the context of this notice?
Trade-off analyses include comparisons between alternative AI/AA designs and configurations, such as different levels of autonomy or differing sensor/compute configurations, to understand how choices affect performance and operational outcomes.
14) What does "performance and effectiveness" analysis mean here?
It refers to analyses that connect technical performance (how the AI/AA system behaves) to operational effectiveness (the mission value and impact of that behavior in realistic scenarios).
15) Does the notice mention generating outputs for larger force-on-force or campaign-level models?
Yes. The framework should produce data suitable for feeding higher-level force-on-force models that are used to explore larger-unit or campaign-level outcomes.
16) What is meant by "sustainability analysis" in this opportunity?
Sustainability analysis signals interest in understanding how AI/AA can be supported over time, not just how it performs in ideal conditions. The notice specifically points to implications for maintenance, updates, data requirements, retraining, logistics, and operational readiness.
17) Are metrics a major deliverable of the effort?
Yes. A major deliverable is the development and delivery of metrics and the underlying variables that drive those metrics.
18) What kind of metrics does the Army want?
The Army is not asking for generic scorecards. The notice calls for experimental, calculated, or modeled measures with high explanatory value that capture key determinants of performance and effectiveness for AI/AA technologies when used by human operators in realistic scenarios.
19) Does the notice describe examples of metric drivers or variables?
Yes. It suggests connecting operational outcomes to measurable drivers such as decision accuracy, timeliness, robustness to degraded data, operator workload, error rates, contribution to mission success, resilience under adversarial conditions, and similar factors.
20) Do proposed metrics need to be measurable within LVC environments?
Yes. The notice implies metrics should have a defensible method for measurement or estimation within live, virtual, and constructive simulation environments.
21) What funding mechanism (award instrument) is expected?
The opportunity uses a cooperative agreement instrument.
22) What does a cooperative agreement imply for how the project will be run?
A cooperative agreement typically implies substantial government involvement during performance, such as collaboration, iterative reviews, or shared technical direction consistent with the terms of the award.
23) Is this a discretionary funding opportunity?
Yes. The listing categorizes the opportunity as discretionary.
24) What is the award ceiling mentioned in the notice?
The listing indicates an award ceiling of $45,000,000.
25) Does the notice expect one award or multiple awards?
The source information indicates an expectation of a single award, suggesting a large, integrated effort rather than multiple smaller independent projects.
26) What is the CFDA number associated with this opportunity?
The CFDA number provided is 12.431 (a defense R&D-related assistance listing).
27) What were the posting and closing dates listed for this notice?
The source data shows the notice was created on March 10, 2021, with an original closing date of April 12, 2021.
28) What is DEVCOM DAC expected to use the resulting framework for?
The framework is meant to support DEVCOM DAC analyses for Army leaders and senior decision makers, including quantifying performance, comparing alternatives, understanding operational impacts, generating inputs for broader models, and making more confident decisions about integrating AI/AA into Army organizations and missions.
29) What is the practical end state described by the notice?
The end state is an Army-relevant evaluation ecosystem for AI and assistive automation: an LVC-enabled analytical and simulation framework supported by well-defined, high-value metrics that can be used to assess, test, and evaluate AI/AA systems in operational contexts.
30) Is the opportunity positioned as basic research or applied research?
The notice describes it as an applied research effort focused on building a usable evaluation framework and associated metrics for operationally grounded assessment.
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