About this episode

The episode discusses the importance of trustworthy data in AI deployment for public safety and national security, featuring insights from technology leaders.

One common theme among technology leaders discussing AI deployment is the need for a "definitive source." Without trusted data, none of AI's conclusions are truly actionable. This week on Feds At the Edge, two technology leaders share practical strategies for building trustworthy AI environments while strengthening security and compliance. Jared Pane from Elastic discusses why organizations can't blindly trust AI outputs, highlighting both familiar data quality issues and emerging threats like hidden "white-space text" embedded in datasets that can carry malicious code into AI repositories. Meanwhile, Chris Bunton from Texas Dept of Agriculture, explains how automation can simplify security and compliance, including the implementation of a policy bot that provides employees with 24/7 guidance on compliance best practices. Tune in on your favorite podcasting platform for practical advice for agencies beginning their AI journey: start small, solve clear problems, and build a collaborative culture that supports long-term success.

People in this episode

Guests: Jared Pane, Chris Bunton

Topics covered

• AI deployment
• data quality
• public safety
• national security
• automation
• security compliance

Keywords

• AI
• data quality
• public safety
• national security
• automation
• compliance
• security
• malicious code

Mentioned in this episode

Organizations: Elastic, Texas Dept of Agriculture

More episodes of Feds at the Edge

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• Ep. 254 The Future of 6G · June 24, 2026 · 1h 1m
• Ep. 253 Meeting the AI Implementation Challenge – Securely · June 17, 2026 · 1h 2m
• Ep. 252 Addressing Security Holes in Air Gapped Environments. · June 10, 2026 · 60 min

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