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ORGANIZER;CN=Daniele  Quercia:mailto:[email protected]
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 artdata.polito.it:mailto:[email protected]
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DESCRIPTION;LANGUAGE=en-US:Format: 35 min talk + 25 min Q&A\n\n\nThe System
 ic Risks of Mismatched Uncertainty: Why Professional AI Needs More Than Be
 tter Calibration\n\n\n\nJoin the meeting<https://teams.microsoft.com/l/mee
 tup-join/19%3ameeting_NzY3NmJlZjYtZjdiOS00OGU1LTlhYmYtODg0N2Q3YzM5OWZh%40t
 hread.v2/0?context=%7b%22Tid%22%3a%225d471751-9675-428d-917b-70f44f9630b0%
 22%2c%22Oid%22%3a%221e405340-2229-4554-b37f-b193c118d70e%22%7d>\n\n\nAI sy
 stems deployed in healthcare\, education\, and law face a critical challen
 ge: many forms of professional uncertainty resist the probabilistic quanti
 fication that current systems privilege. A physician pondering whether to 
 document suspected domestic abuse faces uncertainties about appropriate in
 quiry\, patient safety risks\, and trauma-informed care that cannot meanin
 gfully be reduced to confidence scores. When diagnostic systems express hi
 gh algorithmic confidence while failing to communicate these contextual un
 certainties\, the resulting mismatch between expressed and actual uncertai
 nty creates cascading systemic risks. This talk examines why technical imp
 rovements in uncertainty quantification (while valuable) cannot address th
 e fundamental epistemological mismatch between algorithmic confidence and 
 professional judgment.\n\n\nDrawing on my recent analysis of healthcare an
 d judicial contexts\, I show how this mismatch risks eroding professionals
 ' capacity to refine the tacit\, experience-based judgment that distinguis
 hes expert from novice performance: precisely the forms of situated knowin
 g that depend on engaging with uncertainty rather than resolving it premat
 urely. The solution requires shifting from designer-centric to genuinely p
 articipatory approaches: building technical architectures that enable prof
 essional communities to iteratively refine how systems communicate uncerta
 inty\, treating uncertainty expression itself as evolving professional kno
 wledge rather than a fixed algorithmic problem.\n\n\n\nFurther reading:\n\
 n1.    Delacroix\, S.\, Robinson\, D.\, Bhatt\, U.\, Domenicucci\,
  J.\, Montgomery\, J.\, Varoquaux\, G.\, Ek\, C.H.\, Fortuin\, V.\, He\, Y
 .\, Diethe\, T. and Campbell\, N.\, 2025.  ‘Beyond Quantification: Navig
 ating Uncertainty in Professional AI Systems’\, RSS: Data Science and Ar
 tificial Intelligence\, 1(1)\, p.udaf002.\n\n2.    Delacroix\, S.\
 , 2025.  'Designing with uncertainty: LLM interfaces as transitional space
 s for democratic revival'. Minds and Machines\, 35(4)\, p.41.\n\n3.  
   Delacroix\, S.\, 2025. ‘Moral Perception and Uncertainty Expressio
 n in LLM-Augmented Judicial Practice’\, Minds and Machines\, 35 (44)\n\n
 4.    Fraile Navarro\, D.\, Lewis\, M.\, Blease\, C.\, Shah\, R.\,
  Riggare\, S.\, Delacroix\, S.\, Lehman\, R.\, 2025. 'GenAI and the changi
 ng dynamics of clinical consultations'\, British Medical Journal\, 391:e08
 5325\n\n\n\nSylvie Delacroix’s work focuses on data & machine ethics. Sh
 e is the Inaugural Jeff Price Chair in Digital Law at King's College Londo
 n\; and also the founding Director of the Centre for Data Futures and a vi
 siting professor at the Centre for Language AI research at Tohoku Universi
 ty (Japan). Her work has always been animated by a commitment to bridge th
 e gap between theory and practice. This has led to launch or be involved i
 n a variety of ethics and public policy initiatives. She is currently work
 ing on agency-enhancing uncertainty communication features for LLMs deploy
 ed in morally loaded contexts. She is also considering the social sustaina
 bility of the data ecosystem that makes generative AI possible.\n\n\n\n\nS
 ubscribe to future talk announcements: Anyone outside Bell Labs can receiv
 e talk announcements by subscribing to the mailing list. To subscribe\, se
 nd an empty email with the subject line "Subscribe RAI” to daniele.querc
 [email protected]\n\n\n\n\n\n
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 0100000005182EEB1A8F9D840B97E9CED39A2F989
SUMMARY;LANGUAGE=en-US:[Responsible AI] The Systemic Risks of Mismatched Un
 certainty\, Sylvie Delacroix\, King's College
DTSTART;TZID=GMT Standard Time:20251215T153000
DTEND;TZID=GMT Standard Time:20251215T163000
CLASS:PUBLIC
PRIORITY:5
DTSTAMP:20251209T100417Z
TRANSP:OPAQUE
STATUS:CONFIRMED
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