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ORGANIZER;CN=Daniele Quercia:mailto:[email protected]
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[email protected]:mailto:[email protected]
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artdata.polito.it:mailto:[email protected]
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r-nexa.polito.it:mailto:[email protected]
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municazione:mailto:[email protected]
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=Alberto T
enconi:mailto:[email protected]
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=Nicola Pe
droni:mailto:[email protected]
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=Andrea Ca
rpignano:mailto:[email protected]
ATTENDEE;ROLE=OPT-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=Stefano Tr
averso:mailto:[email protected]
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anesi:mailto:[email protected]
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esco Di Tano:mailto:[email protected]
ATTENDEE;ROLE=OPT-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=Luca Colo
mba:mailto:[email protected]
ATTENDEE;ROLE=OPT-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=Luca Gioa
cchini:mailto:[email protected]
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ni:mailto:[email protected]
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efano:mailto:[email protected]
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carini:mailto:[email protected]
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Fiori:mailto:[email protected]
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Vaccarino:mailto:[email protected]
ATTENDEE;ROLE=OPT-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=Martino T
revisan:mailto:[email protected]
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Cappelluti:mailto:[email protected]
ATTENDEE;ROLE=OPT-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=Fulvio Co
rno:mailto:[email protected]
ATTENDEE;ROLE=OPT-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=Emilio Pa
olucci:mailto:[email protected]
DESCRIPTION;LANGUAGE=en-US: Title: When Abstraction Fails: Navigating Uncer
tainty in High-Stakes Systems\n Join the meeting<https://teams.microsoft.c
om/l/meetup-join/19%3ameeting_YzczNmM0YWUtNWU4ZC00NDg5LThiNzYtY2UyZTk5YTE4
MDIx%40thread.v2/0?context=%7b%22Tid%22%3a%225d471751-9675-428d-917b-70f44
f9630b0%22%2c%22Oid%22%3a%221e405340-2229-4554-b37f-b193c118d70e%22%7d>\n\
n\nAbstract: With high-stakes systems\, safety and security engineering de
pends heavily on abstractions — models\, simulations\, bench tests — t
hat stand in for the system itself. But these abstractions have limits. Th
ey inevitably rely on imperfect assumptions: simplifications that hold unt
il they don’t\, especially under conditions of novelty\, extremity\, or
scale. In systems that push the boundaries of performance\, therefore\, ab
straction becomes brittle\, and the pretense of total foresight becomes a
liability. This talk examines what happens when engineers reach the limits
of their abstractions. Focusing on testing and modeling under conditions
of extremity\, I explore how ‘rational’ accidents can arise from the l
imits of what can be known\, tested\, or anticipated in advance. From ther
e I examine how one domain — civil aviation — manages these accidents
by leveraging decades of accumulated operational experience. The talk is a
n invitation to reconsider what counts as credible knowledge in high-conse
quence engineering\, and to value operational experience not as a fallback
when models fail\, but as a foundation for safety and security when they
inevitably do.\n\n<https://arxiv.org/abs/2407.02191>Bio: John Downer is As
sociate Professor of Science and Technology Studies at the University of B
ristol. He has written extensively about the idiosyncrasies of technoscien
tific knowledge\, the limits of proof\, and their implications for technol
ogy governance. His 2024 monograph ‘Rational Accidents: Reckoning with C
atastrophic Technologies\,’ examines the logical dilemmas of establishin
g ‘ultra-high’ reliabilities in highly complex systems such as jetline
rs and reactors\, and unpacks the practical ramifications of those dilemma
s. His broader work looks at epistemological and regulatory issues in a ra
nge of technological domains\, from civil aviation and nuclear\, to autono
mous systems and artificial intelligence. He has a PhD in Science and Tech
nology Studies (STS) from Cornell University\, and prior to joining Bristo
l he held positions at Kings College London\, the London School of Economi
cs (LSE)\, and Stanford University. He is currently a visiting researcher
at the Centre for the Governance of Artificial Intelligence (GovAI) in Oxf
ord.\n\n\n\n
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010000000A96594759DCEDC4EB87FAE4C3F7D5A73
SUMMARY;LANGUAGE=en-US:[Responsible AI] When Abstraction Fails: Navigating
Uncertainty in High-Stakes Systems
DTSTART;TZID=GMT Standard Time:20250512T153000
DTEND;TZID=GMT Standard Time:20250512T163000
CLASS:PUBLIC
PRIORITY:5
DTSTAMP:20250512T075553Z
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STATUS:CONFIRMED
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