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Can You Trust AI-Generated Maps? | Christy Monaco on AI Accountability

Published on: 3rd November, 2026

Can You Trust AI-Generated Maps? | Christy Monaco

What happens when AI-generated information looks authoritative, but the evidence behind it cannot support the decision?

In this episode of The Briefing, Dr. Tuboise Floyd sits down with Christy Monaco, Chief Operating Officer of the Open Geospatial Consortium (OGC), to examine artificial intelligence, geospatial intelligence, open standards, and the accountability required when technology informs consequential decisions.

Drawing on more than three decades of experience across the intelligence community and the geospatial industry, Christy explores a fundamental problem: the difference between having information and having enough confidence in that information to act.

The conversation begins with the intelligence assessments preceding the 2003 Iraq War. Christy discusses how confidence, uncertainty, and underlying evidence shaped consequential judgments, and why the lessons remain relevant as organizations increasingly depend on AI-generated information.

From there, the discussion moves to AI-generated maps, the limitations of large language models in interpreting spatial data, and the difference between technical compliance and factual accuracy.

A map can meet a technical standard and still contain incorrect information. An AI system can generate a convincing answer without providing the evidence necessary to defend a decision.

For leaders approving, procuring, or certifying consequential technology systems, that distinction matters.

IN THIS EPISODE

Intelligence, Evidence, and Confidence

What the intelligence failures surrounding Iraq's weapons of mass destruction teach us about uncertainty, analytical standards, and the danger of overstating confidence.

When AI Gets the Map Wrong

A discussion of a reported incident involving an inaccurate AI-generated map displayed during a government presentation, including where verification should occur and what remains unknown about the internal review process.

Why Geospatial AI Is Difficult

Christy explains why language models can struggle with spatial relationships, coordinates, geographic references, and the underlying data that makes maps reliable.

Standards Do Not Guarantee Accuracy

How open standards establish shared definitions and interoperability while leaving factual verification and consequential judgments to accountable decision-makers.

AI, Flood Evacuations, and Public Safety

A practical scenario involving a city preparing for a flood, where infrastructure data, location information, uncertainty, and human judgment influence emergency response.

Integrity, Provenance, and Trust

Why leaders need to understand where information originated, how it was processed, whether it was independently validated, and what assumptions remain.

Synthetic Imagery and Authentic Evidence

The legitimate use of synthetic images in AI training, the risks of manipulated geographic information, and the importance of distinguishing authentic observations from generated representations.

MUDDI and the UK's National Underground Asset Register

How shared geospatial data models can help organizations combine infrastructure information and reduce costly errors.

Discrete Global Grid Systems and Agentic AI

How OGC's work with DGGS, interoperable data services, and AI-enabled clients is addressing challenges in geographic reasoning and computational scale.

Open Standards and Public Governance

Why Christy favors transparent, consensus-based standards development involving industry, government, academia, and other stakeholders.

THREE QUESTIONS BEFORE YOU SIGN

Christy closes the conversation with three questions every leader should ask before approving an AI system that uses location-based information:

1. Where did the information come from, and how current is it?

2. What was observed versus inferred, and did someone other than the builder or author check it?

3. Who was authorized to act on the information, and what happens if it is wrong?

These questions apply far beyond geospatial technology.

They matter to executives, CIOs, CISOs, AI governance professionals, procurement leaders, public officials, risk officers, and boards responsible for consequential technology decisions.

The central issue is Decision Assurance: Can you follow the evidence, understand the uncertainty, and identify who owns the decision?

ABOUT THE GUEST

Christy Monaco

Chief Operating Officer

Open Geospatial Consortium (OGC)

Christy Monaco brings more than three decades of experience spanning intelligence, national security, technology, and geospatial leadership.

Her career includes senior leadership at the National Geospatial-Intelligence Agency, where she served as Chief Ventures Officer, helping connect government innovation with emerging technologies and industry partners.

Today, as Chief Operating Officer of the Open Geospatial Consortium, she helps advance an international organization dedicated to open geospatial standards, interoperability, and trusted information sharing.

Open Geospatial Consortium:

https://www.ogc.org/

ABOUT THE BRIEFING

The Briefing examines consequential decisions involving artificial intelligence, quantum technology, cybersecurity, governance, risk, and public trust.

Through conversations with leaders, technologists, policymakers, and subject-matter experts, the program explores what happens between technological capability and organizational responsibility.

The Briefing is a Human Signal production.

Find the decision. Follow the evidence. Name who owns it.

PRODUCTION CREDITS

Host and Executive Producer: Dr. Tuboise Floyd

Creative Director: Jeremy Jarvis

Production: Human Signal

Underwriting Partner: MCGlobalTech

The Briefing maintains independent editorial control over its programming. Guest appearances and professional affiliations do not imply endorsement of Human Signal's underwriting partners.