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SUMMARY:Trustworthy AI and Narrow-Scope Models - Philip Nickel
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UID:pretalx-iacap-2026-XDWPNX@pretalx.iacapconf.org
DESCRIPTION:In this paper I conceptualize the narrow scope of some AI mode
 ls from the perspective of trustworthy AI. Trustworthy AI is useful to exp
 lore how different stakeholders can rely on AI models with good reason. It
  is a matter of living up to the commitments and expectations that differe
 nt stakeholders have toward AI.\nI use the example of NAP4DIVE to consider
  a potential barrier to trustworthy AI. This EU project has an ethical aim
 : to develop a complex combination of AI and in vitro models of the blood-
 brain barrier to replace animal models. A relational account of trustworth
 y AI implies that reasonable expectations of AI models should be demonstra
 ted for different stakeholders (e.g.\, regulators) in order for them to ac
 cept and promote replacement of animal models. \nThe narrow scope of such 
 models forms a potential barrier to trustworthy AI. The AI model in NAP4DI
 VE can only be used to predict nanoparticle behaviour across the blood-bra
 in barrier\, and is paired with a specific in vitro model. I distinguish f
 our aspects of its narrow scope: specific socio-technical embedding\, ques
 tion-specificity\, limited system representation\, and narrow validation. 
 In the paper\, I relate and prioritize these aspects from the perspective 
 of trustworthy AI.
LOCATION:Apollo Auditorium
URL:https://pretalx.iacapconf.org/iacap-2026/talk/XDWPNX/
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