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DTSTAMP:20260516T152807Z
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DTSTART;TZID=America/Indiana/Indianapolis:20260604T173000
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DESCRIPTION:Join IEEE Women in Engineering for an insightful webinar on bui
 lding trustworthy AI systems—a critical challenge as AI moves from exper
 imentation to real-world\, high-stakes applications.\n\nThis session bring
 s together two experienced speakers who will share practical perspectives 
 on why many AI systems fail to gain trust and how we can design systems th
 at are reliable\, safe\, and transparent by design.\n\nThrough real-world 
 case studies and research-backed frameworks\, you’ll explore how to buil
 d AI systems that not only perform well but also know their limits\, commu
 nicate uncertainty\, and prevent critical failures. Topics will include pr
 oduction challenges in AI deployment\, reliability and explainability\, an
 d safety mechanisms for high-impact environments such as healthcare.\n\nWh
 ether you’re a student\, engineer\, or industry professional\, this webi
 nar will equip you with actionable insights\, practical frameworks\, and k
 ey questions to evaluate and build trustworthy AI systems.\n\nSpeaker(s): 
 Anusha Kovi\, Latha Iyer\n\nAgenda: \nSession 1 (45 minutes)\n\nTalk: From
  Demo to Durable: How to Ship AI Systems People Actually Trust\nSpeaker: A
 nusha\, Business Intelligence Engineer\, Amazon\n\n- Presentation (30 minu
 tes)\n- Why most AI pilots fail in production\n- Real-world case study of 
 an AI system failure\n- A practical five-layer framework: policy\, retriev
 al\, reasoning\, verification\, and explanation\n- Key questions and red f
 lags when building trustworthy AI systems\n\n- Q&amp;A (15 minutes)\n---------
 ------------------------------------------------------\n\nSession 2 (45 mi
 nutes)\n\nTalk: When AI Says “I Don’t Know”: Building Safety Alerts 
 for High-Stakes Systems\nSpeaker: Latha Iyer\, Applied AI Researcher\n\n- 
 Presentation (30 minutes)\n- Risks of overconfident AI in critical environ
 ments\n- Introduction to Adaptive Confidence Circuit Breaker (ACCB)\n- Rea
 l-world validation using healthcare data\n- Designing AI systems that reco
 gnize and communicate uncertainty\n\n- Q&amp;A (15 minutes)\n\nVirtual: https:
 //events.vtools.ieee.org/m/557290
LOCATION:Virtual: https://events.vtools.ieee.org/m/557290
ORGANIZER:hinagandhi@ieee.org
SEQUENCE:64
SUMMARY:IEEE Women in Engineering Webinar on Trustworthy AI Systems
URL;VALUE=URI:https://events.vtools.ieee.org/m/557290
X-ALT-DESC:Description: &lt;br /&gt;&lt;p data-start=&quot;125&quot; data-end=&quot;315&quot;&gt;Join IEEE 
 Women in Engineering for an insightful webinar on building trustworthy AI 
 systems&amp;mdash\;a critical challenge as AI moves from experimentation to re
 al-world\, high-stakes applications.&lt;/p&gt;\n&lt;p data-start=&quot;317&quot; data-end=&quot;53
 2&quot;&gt;This session brings together two experienced speakers who will share pr
 actical perspectives on why many AI systems fail to gain trust and how we 
 can design systems that are reliable\, safe\, and transparent by design.&lt;/
 p&gt;\n&lt;p data-start=&quot;534&quot; data-end=&quot;914&quot;&gt;Through real-world case studies and
  research-backed frameworks\, you&amp;rsquo\;ll explore how to build AI system
 s that not only perform well but also know their limits\, communicate unce
 rtainty\, and prevent critical failures. Topics will include production ch
 allenges in AI deployment\, reliability and explainability\, and safety me
 chanisms for high-impact environments such as healthcare.&lt;/p&gt;\n&lt;p data-sta
 rt=&quot;916&quot; data-end=&quot;1121&quot;&gt;Whether you&amp;rsquo\;re a student\, engineer\, or i
 ndustry professional\, this webinar will equip you with actionable insight
 s\, practical frameworks\, and key questions to evaluate and build trustwo
 rthy AI systems.&lt;/p&gt;&lt;br /&gt;&lt;br /&gt;Agenda: &lt;br /&gt;&lt;h3 data-section-id=&quot;q4f0no&quot;
  data-start=&quot;310&quot; data-end=&quot;342&quot;&gt;&lt;span style=&quot;color: rgb(0\, 0\, 0)\;&quot; rol
 e=&quot;text&quot;&gt;Session 1 (45 minutes)&lt;/span&gt;&lt;/h3&gt;\n&lt;p data-start=&quot;343&quot; data-end=
 &quot;485&quot;&gt;&lt;strong data-start=&quot;343&quot; data-end=&quot;352&quot;&gt;Talk:&lt;/strong&gt; &lt;em data-star
 t=&quot;353&quot; data-end=&quot;421&quot;&gt;From Demo to Durable: How to Ship AI Systems People
  Actually Trust&lt;/em&gt;&lt;br data-start=&quot;421&quot; data-end=&quot;424&quot;&gt;&lt;strong data-start
 =&quot;424&quot; data-end=&quot;436&quot;&gt;Speaker:&lt;/strong&gt; Anusha\, Business Intelligence Eng
 ineer\, Amazon&lt;/p&gt;\n&lt;ul data-start=&quot;487&quot; data-end=&quot;813&quot;&gt;\n&lt;li data-section
 -id=&quot;e1q29n&quot; data-start=&quot;487&quot; data-end=&quot;787&quot;&gt;&lt;strong data-start=&quot;489&quot; data
 -end=&quot;518&quot;&gt;Presentation (30 minutes)&lt;/strong&gt;\n&lt;ul data-start=&quot;523&quot; data-e
 nd=&quot;787&quot;&gt;\n&lt;li data-section-id=&quot;ogln4o&quot; data-start=&quot;523&quot; data-end=&quot;564&quot;&gt;Wh
 y most AI pilots fail in production&lt;/li&gt;\n&lt;li data-section-id=&quot;b8yd9p&quot; dat
 a-start=&quot;567&quot; data-end=&quot;616&quot;&gt;Real-world case study of an AI system failure
 &lt;/li&gt;\n&lt;li data-section-id=&quot;1wa1act&quot; data-start=&quot;619&quot; data-end=&quot;716&quot;&gt;A pra
 ctical five-layer framework: policy\, retrieval\, reasoning\, verification
 \, and explanation&lt;/li&gt;\n&lt;li data-section-id=&quot;n84tqa&quot; data-start=&quot;719&quot; dat
 a-end=&quot;787&quot;&gt;Key questions and red flags when building trustworthy AI syste
 ms&lt;/li&gt;\n&lt;/ul&gt;\n&lt;/li&gt;\n&lt;li data-section-id=&quot;gxnydi&quot; data-start=&quot;789&quot; data-
 end=&quot;813&quot;&gt;&lt;strong data-start=&quot;791&quot; data-end=&quot;811&quot;&gt;Q&amp;amp\;A (15 minutes)&lt;/s
 trong&gt;&lt;/li&gt;\n&lt;/ul&gt;\n&lt;hr data-start=&quot;815&quot; data-end=&quot;818&quot;&gt;\n&lt;h3 data-section
 -id=&quot;zmswjb&quot; data-start=&quot;820&quot; data-end=&quot;852&quot;&gt;&lt;span role=&quot;text&quot;&gt;Session 2 (
 45 minutes)&lt;/span&gt;&lt;/h3&gt;\n&lt;p data-start=&quot;853&quot; data-end=&quot;991&quot;&gt;&lt;strong data-s
 tart=&quot;853&quot; data-end=&quot;862&quot;&gt;Talk:&lt;/strong&gt; &lt;em data-start=&quot;863&quot; data-end=&quot;94
 0&quot;&gt;When AI Says &amp;ldquo\;I Don&amp;rsquo\;t Know&amp;rdquo\;: Building Safety Alert
 s for High-Stakes Systems&lt;/em&gt;&lt;br data-start=&quot;940&quot; data-end=&quot;943&quot;&gt;&lt;strong 
 data-start=&quot;943&quot; data-end=&quot;955&quot;&gt;Speaker:&lt;/strong&gt; Latha Iyer\, Applied AI 
 Researcher&lt;/p&gt;\n&lt;ul data-start=&quot;993&quot; data-end=&quot;1294&quot;&gt;\n&lt;li data-section-id
 =&quot;18xwo88&quot; data-start=&quot;993&quot; data-end=&quot;1268&quot;&gt;&lt;strong data-start=&quot;995&quot; data-
 end=&quot;1024&quot;&gt;Presentation (30 minutes)&lt;/strong&gt;\n&lt;ul data-start=&quot;1029&quot; data-
 end=&quot;1268&quot;&gt;\n&lt;li data-section-id=&quot;76k38r&quot; data-start=&quot;1029&quot; data-end=&quot;1083
 &quot;&gt;Risks of overconfident AI in critical environments&lt;/li&gt;\n&lt;li data-sectio
 n-id=&quot;1l5vaj8&quot; data-start=&quot;1086&quot; data-end=&quot;1148&quot;&gt;Introduction to Adaptive 
 Confidence Circuit Breaker (ACCB)&lt;/li&gt;\n&lt;li data-section-id=&quot;y5wert&quot; data-
 start=&quot;1151&quot; data-end=&quot;1198&quot;&gt;Real-world validation using healthcare data&lt;/
 li&gt;\n&lt;li data-section-id=&quot;1isssnz&quot; data-start=&quot;1201&quot; data-end=&quot;1268&quot;&gt;Desig
 ning AI systems that recognize and communicate uncertainty&lt;/li&gt;\n&lt;/ul&gt;\n&lt;/
 li&gt;\n&lt;li data-section-id=&quot;gxnydi&quot; data-start=&quot;1270&quot; data-end=&quot;1294&quot;&gt;&lt;stron
 g data-start=&quot;1272&quot; data-end=&quot;1292&quot;&gt;Q&amp;amp\;A (15 minutes)&lt;/strong&gt;&lt;/li&gt;\n&lt;
 /ul&gt;
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END:VCALENDAR