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PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
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TZID:America/New_York
BEGIN:DAYLIGHT
DTSTART:20260308T030000
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DTSTART:20251102T010000
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BEGIN:VEVENT
DTSTAMP:20260106T200716Z
UID:861BB719-1491-495D-91A5-A088AC0E3E3E
DTSTART;TZID=America/New_York:20260112T190000
DTEND;TZID=America/New_York:20260112T200000
DESCRIPTION:The widespread deployment of Artificial Intelligence in decisio
 n-intensive and safety-critical applications introduces complex challenges
  related to governance\, ethics\, and accountability. This examines techni
 cal and organizational mechanisms for AI governance\, including risk asses
 sment\, bias identification\, fairness constraints\, model transparency\, 
 auditability\, and lifecycle monitoring. Governance-oriented practices suc
 h as dataset documentation\, evaluation pipelines\, approval workflows\, a
 nd post-deployment monitoring are presented as integral components of reli
 able AI system design. Emphasis is placed on embedding governance and ethi
 cal controls directly into AI development and deployment workflows rather 
 than treating them as post-hoc considerations.\n\nSpeaker(s): \, Sree\n\nV
 irtual: https://events.vtools.ieee.org/m/531583
LOCATION:Virtual: https://events.vtools.ieee.org/m/531583
ORGANIZER:anushanerella@ieee.org
SEQUENCE:19
SUMMARY:WIE Speaker Series 2026:AI Governance and Ethics: Building Accounta
 ble and Trustworthy Systems
URL;VALUE=URI:https://events.vtools.ieee.org/m/531583
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;The widespread deployment of Artificial In
 telligence in decision-intensive and safety-critical applications introduc
 es complex challenges related to governance\, ethics\, and accountability.
  This examines technical and organizational mechanisms for AI governance\,
  including risk assessment\, bias identification\, fairness constraints\, 
 model transparency\, auditability\, and lifecycle monitoring. Governance-o
 riented practices such as dataset documentation\, evaluation pipelines\, a
 pproval workflows\, and post-deployment monitoring are presented as integr
 al components of reliable AI system design. Emphasis is placed on embeddin
 g governance and ethical controls directly into AI development and deploym
 ent workflows rather than treating them as post-hoc considerations.&lt;/p&gt;
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