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DESCRIPTION:Click for Latest Location Information: http://dgiq-aigov2026.da
 taversity.net/sessionPop.cfm?confid=166&proposalid=16932\nGenerative AI can
  produce polished work quickly, but polished does not always mean ready to 
 use. As AI becomes part of everyday work, organizations need a clear way to
  judge what a model produces, what requires human review, and who is respon
 sible for the final result. This session introduces AI Judgment, a practica
 l approach to reviewing AI-assisted work at both the individual and organiz
 ational level. Attendees will examine how to spot unsupported claims, missi
 ng context, weak reasoning, and other signs that an output needs closer rev
 iew. The session then moves from individual review to team practice: settin
 g shared quality standards, placing review points where work changes hands,
  and making ownership clear. Through examples and discussion, attendees wil
 l leave with a simple framework they can use to strengthen review in their 
 own organization. Learning goals from this session include:\n\n
 Define AI Judgment and explain its role in responsible AI use.\n
 Recognize common signs that AI-assisted work needs closer review.\n
 Identify where human review should happen as work moves between people and 
 teams.\n
 Choose a practical first step for strengthening review in their own organiz
 ation.\n
DTSTART:20261118T143000
SUMMARY:Teaching Judgment: Evaluating the Work AI Produces
DTEND:20261118T151459
LOCATION: See Description
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