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DTSTART:20251102T020000
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DESCRIPTION:Yu-Che Chen\, University of Nebraska at Omaha\, will present "A
  Multi-level Collaborative Governance Framework for Designing Accountable 
 AI Systems" as part of the CPR Seminar Series.Abstract:How do we design ac
 countable artificial intelligence (AI) systems? Our NSF-funded project tea
 m takes an interdisciplinary approach to develop and implement a multi-lev
 el governance design framework to answer the question. The public policy a
 nd service context is collaborative emergency management between tribal na
 tions and U.S. governments. We implement a co-design of a custom-built AI 
 chatbot for emergency management in indigenous communities and study the i
 mpact of such co-design on accountability. We strive for a culturally resp
 onsible way to engage with indigenous people for the AI chatbot co-design 
 and research. We follow an interpretive approach in collecting and analyzi
 ng data. The project's preliminary findings suggest the importance of cult
 urally responsible engagement\, embedded multi-level governance\, tribal s
 overeignty\, participatory design\, and explainable AI in designing a more
  accountable AI system.
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DTSTAMP:20260514T043509Z
DTSTART:20241205T203000Z
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SUMMARY:A Multi-level Collaborative Governance Framework for Designing Acco
 untable AI Systems
UID:RFCALITEM639143157098470140
X-ALT-DESC;FMTTYPE=text/html:<p>Yu-Che Chen\, University of Nebraska at Oma
 ha\, will present "A Multi-level Collaborative Governance Framework for De
 signing Accountable AI Systems" as part of the CPR Seminar Series.</p><p><
 strong>Abstract:</strong></p><p>How do we design accountable artificial in
 telligence (AI) systems? Our NSF-funded project team takes an interdiscipl
 inary approach to develop and implement a multi-level governance design fr
 amework to answer the question. The public policy and service context is c
 ollaborative emergency management between tribal nations and U.S. governme
 nts. We implement a co-design of a custom-built AI chatbot for emergency m
 anagement in indigenous communities and study the impact of such co-design
  on accountability. We strive for a culturally responsible way to engage w
 ith indigenous people for the AI chatbot co-design and research. We follow
  an interpretive approach in collecting and analyzing data. The project's 
 preliminary findings suggest the importance of culturally responsible enga
 gement\, embedded multi-level governance\, tribal sovereignty\, participat
 ory design\, and explainable AI in designing a more accountable AI system.
 </p>
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