Air Force: ~$14.54M for "explainable AI and autonomy" research (HAARDCORE) — a federal contract with the University of Dayton (USAspending)
The U.S. Air Force awarded about $14.54M ($14,535,633, as of 2026-09-08) for operationally relevant, explainable AI and autonomy R&D (HAARDCORE). Recipient: the University of Dayton. University research centered on AI that can explain why it reached a decision.
Contract key facts
- RecipientUNIVERSITY OF DAYTON
- Contract value$14,535,633 (≈$14.5M)
- Awarding agencyDepartment of Defense
- Awarding sub-agencyDepartment of the Air Force
- Award typeDEFINITIVE CONTRACT
- Period of performance2025-08-25 〜 2028-02-24
- Contract ID (PIID)FA239125CB010
Contract scope (original)
HYBRID ARTIFICIAL INTELLIGENCE AND AUTONOMY RESEARCH AND DEVELOPMENT CONSIDERED OPERATIONALLY RELEVANT AND EXPLAINABLE (HAARDCORE)
Key points
- Air Force funded explainable AI and autonomy R&D (HAARDCORE)
- AI that can explain "why" is essential to trust in high-stakes settings
- "Operationally relevant" — mindful of usefulness in real operations
- Value ~$14.54M, period August 2025–February 2028; recipient University of Dayton
- Echoes the "trustworthy AI" concern (FAITH-MD) from our separate article
- Two conditions are written into the programme name: explainable, and operationally relevant.
1What explainable means here
"Explainable" refers to AI whose reasoning for a conclusion a human can understand. Using AI and autonomous systems in high-stakes settings requires being able to trust and verify their outputs — a concern that echoes the Air Force's "trustworthy AI" framework (FAITH-MD) covered in our separate article. The phrase "operationally relevant" indicates research mindful of usefulness in real operations, not just theory.
2A university as the performer
3Two conditions written into the programme name
The name HAARDCORE carries two conditions placed on the research. What is written into the name is not the performance of the technology but the properties it has to satisfy.
Neither is a condition asking for an AI that gets more answers right. Both are conditions seen from the user's side: that a correct answer can be traced to a reason, and that the work reaches actual operation. No specific methods or deliverables appear in the source.
Why it matters
An example of public funding for AI explainability and operational fit, not just raw performance. Useful for reading trustworthy-AI/autonomous-systems research and the breadth of university-performed military AI research.
FAQ
What is "explainable AI"?
Why would the military research explainability?
Sources (primary)
This article is an independent organization based on the U.S. official spending data below. Verify the exact, latest details with the official source.
- USAspending (award details)
- Contract ID (PIID)：FA239125CB010