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DTSTAMP:20260909T102821Z
DESCRIPTION:Click for Latest Location Information: http://dgiq-aigov2026.da
 taversity.net/sessionPop.cfm?confid=166&proposalid=16718\nMove beyond princ
 iples to practice—learn how to validate the trustworthiness of an AI 
 system with a proven evaluation that operationalizes governance principles 
 into measurable evaluations across responsible AI.\n\nAs organizations rapi
 dly deploy Generative AI and Agentic AI systems—from conversational a
 ssistants to autonomous agents—a critical governance question emerges
 : How do you validate that these systems are trustworthy before exposing th
 em to users or sensitive data? Unlike traditional models, Gen AI systems in
 troduce unique risks: prompt injection attacks, hallucinated outputs, jailb
 reaking attempts, context manipulation, bias amplification, and unpredictab
 le emergent behaviors.\n\nThis session introduces a comprehensive framework
  specifically designed for Generative AI governance that transforms abstrac
 t principles into concrete validation protocols to ensure the AI systems ar
 e trusted.
DTSTART:20261118T083000
SUMMARY:Building Trust at Scale: In the Era of Responsible AI
DTEND:20261118T091459
LOCATION: See Description
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