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SUMMARY:AI Center Seminar - AI for Society series - Dr. Alexandra Olteanu 
 - "(Un)rigorous AI"
DTSTART:20261119T133000
DTEND:20261119T143000
DTSTAMP:20261110T014601Z
UID:0bf515f520d083b9cadbe326d72605c23a19e08990a1a16851fd622b
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Alexandra Olteanu\nThe talk is jointly organized by the 
 EPFL AI Center and the CoALA Lab as part of the AI for Society seminar 
 series.\n\nHosting Professor: Prof. Ken Holstein\n\nTitle\n(Un)rigorous AI
 \n\nAbstract\nBeliefs and assumptions about what AI systems can\, will\, o
 r should do abound. Although often unsupported and sometimes highly questi
 onable\, these beliefs and assumptions have had a formative impact on how 
 AI systems are built\, evaluated and described. This in turn impacts how a
 nd in what settings these systems are deployed and used\, and thus when th
 ey fail. However\, foreseeing and addressing the consequences of putting i
 nsufficiently rigorous AI artifacts (e.g.\, models\, systems\, application
 s\, outputs\, data) into practice are often seen as the purview of respons
 ible AI—which is generally seen as separate from rigor\, as it is unders
 tood as more concerned with ethics\, stakeholders\, societal impacts and h
 arms\, and real-world deployment scenarios. I argue that what responsible 
 AI asks researchers and practitioners is to uphold principles of scientif
 ic integrity in their work. Although responsible AI is often seen as out o
 f scope for an AI researcher or practitioner not engaged in that space\, a
 ny scientist and practitioner should see rigor as well within scope. In 
 this talk\, my goal is to provide a useful framework for broadening our co
 llective understanding of what rigorous AI research and practice should en
 tail and\, in doing so\, to help scaffold much-needed dialogue about and s
 crutiny of current AI system development and evaluation practices.\n\nBio\
 nAlexandra Olteanu is a Responsible AI researcher. Until recently she was 
 a principal researcher at Microsoft Research Montreal\, part of the Fairne
 ss\, Accountability\, Transparency\, and Ethics (FATE) Montreal team\; whi
 ch she was a founding member of and later rebuilt. She is also an associat
 e industry member at Mila. Her work routinely unpacks and challenges pract
 ices and assumptions made when designing\, evaluating\, deploying or commu
 nicating about AI systems. Her most recent work focuses on 1) rigor in AI 
 (with a focus on conceptual clarity\, measurement\, and evaluation)\, and 
 2) human agency (with a focus on anthropomorphic AI systems’ design\, be
 havior\, and impact). Before joining Microsoft Research\, Alexandra was a 
 Social Good Fellow at IBM's T.J. Watson Research Center. Alexandra has co-
 organized tutorials/workshops and has served as PC/SPC/AC and in many othe
 r service roles for most major web\, social media\, and responsible AI con
 ferences. She has also served as the inaugural co-chair of the Fairness\, 
 Accountability\, Transparency and Ethics on the Web track @ The 2023 Web C
 onference\, and as the 2024 Program Co-chair for the ACM Conference on Fai
 rness\, Accountability\, and Transparency. Alexandra holds a PhD from Éco
 le Polytechnique Fédérale de Lausanne (EPFL)\, Switzerland.
LOCATION:ELE 117 https://plan.epfl.ch/?room==ELE%20117 https://epfl.zoom.u
 s/j/68619273145?pwd=dKc90MabfoxCnGO643Mbn0Odl39mxe.1
STATUS:CONFIRMED
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