Challenges in interpretability of additive models

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Abstract

We review generalized additive models as a type of ‘transparent’ model that has recently seen renewed interest in the deep learning community as neural additive models. We highlight multiple types of nonidentifiability in this model class and discuss challenges in interpretability, arguing for restraint when claiming ‘interpretability’ or ‘suitability for safety-critical applications’ of such models.
Original languageEnglish
Publication statusPublished - 2024
MoE publication typeNot Eligible
EventWorkshop on Explainable Artificial Intelligence - Virtual, Online
Duration: 14 Aug 202415 Aug 2024
https://sites.google.com/view/xai2024/

Workshop

WorkshopWorkshop on Explainable Artificial Intelligence
Abbreviated titleXAI
CityVirtual, Online
Period14/08/202415/08/2024
Internet address

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