When AI Becomes the Reader, Structure Becomes Authority
When AI systems process government information, they can’t always tell if a policy is current or even if it’s official. Structure provides the clues.
Artificial Intelligence
Tennessee Sees Governance as Key to Agentic Success
Agentic AI has the potential to transform how government responds to constituent needs — but state and local officials aren’t getting caught in the hype. Hear how Tennessee’s CIO explains her state’s careful, responsible path to incorporating agentic AI into state systems.
Confronting Bias in Artificial Intelligence
An AI system recently admitted to a featured contributor that it “flows downstream on a river of human bias” and rarely gets corrected. That should change how leaders use these tools. If you rely on AI for decisions, learn three practical ways to push back on AI bias and redirect the current.
The Rise of Human-AI Decision Teams in Government
AI is reshaping decision-making across government, creating hybrid human-AI decision teams that combine machine speed and pattern recognition with human judgment, accountability, and context. Such collaboration can deliver faster and more effective mission outcomes, risk detection, and other benefits.
Strategies for Modernizing the Grant Lifecycle
In this video interview, Roth and Ryan Alcorn, Principal, AI Strategy at Euna Solutions, discuss how agencies can better manage the full grant lifecycle.
Why Public Information Officers Are Confronting a New Problem: AI Attribution
As AI increasingly becomes an intermediary between government organizations and the public, the structure of information begins to matter as much as the content itself. It is not a shift in messaging — it is a shift in how data is read.
AI in Government Starts With Trust in Data, but Is Built With People
AI is embedded in government operations, and agencies need a proactive approach to data governance in order to mitigate risk — and foster trust.
Privacy in the Enterprise-AI Age: Strategic Implications Across Government and Key Infrastructure
As government organizations make greater use of AI, their privacy risks are expanding beyond traditional data protection. Critical infrastructure sectors must address new challenges related to data aggregation and accountability for AI-assisted decisions, among other concerns. To navigate this landscape successfully, organizations must enforce strong privacy protections to sustain innovation while maintaining public trust.
AI Data Centers: An Additional Consideration
RDMA is a fascinating approach to “sharing memory” without having to burden a CPU. Learn why, and why AI data centers and cloud vendors use it.
Why Trustworthy AI Is Not Good Enough
In this video interview, John Chao, Director of Federal Products at Seekr, discusses how agencies can achieve defensible AI and adopt AI with greater confidence.