BARBiE’s interactive, rule-based, and API-only design makes it a useful solution for explaining black-box models in enterprise settings, and it receives higher ratings for informativeness, understanding, trust, and satisfaction than all baselines.
This work explored powerful explainers which use rules, where explanation instability stemming from training data becomes more apparent, and found that the rule-based method employed, BARBE, sharply increased in fidelity and stability when trained with the modified process, making BARBE+PBC which exceeded other methods...
A structured framework in which every resemblance claim specifies the human reference class, the AI system and version, the task and context, the property compared, the measurement relation, the perturbations considered, the uncertainty of the estimate and the inference that the evidence permits is proposed.
Peng Wang, E. Law, Li-Ye Zou et al.· Physics of Life Reviews· 0 citations
Domain modeling is inherently interpretive: the same textual description may yield solutions that differ in structure, abstraction, and scope. Not all such differences constitute errors. Some reflect legitimate alternative representations and well-justified modeling decisions, while others stem from misconceptions or m...
Iris Reinhartz-Berger, Maxim Bragilovski, Arnon Sturm· Proceedings of the ACM/IEEE...· 0 citations
This work conducts a controlled human study of six reasoning formats across tasks of varying complexity, supported by a web-based framework that randomizes task domains, problem instances, and representation order.
An analytical model is developed that incorporates the defining features of human and machine intelligence, capturing the limited but flexible nature of human cognition with imperfect machine recommendations, and represents how AI-based explanations influence the DM’s belief in the algorithm’s predictive quality.
T. Boyacı, Caner Canyakmaz, Francis de Véricourt· Management Sciences· 0 citations
It is suggested that the notion of the experimenters’ regress (ER) in scientific instruments is useful to understand the situation of XAI, and a new variant of ER is identified in the design and application of XAI algorithms: the validity of XAI algorithms and the workings of black-box models cannot be secured without...
Si-Yu Yao· Synthese· 0 citations
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