Add to ORKGWe characterize three notions of explainable AI that cut across research fields: opaque systems that offer no insight into its algo- rithmic mechanisms; interpretable systems where users can mathemat- ically analyze its algorithmic mechanisms; and comprehensible systems that emit symbols enabling user-driven explanations of how a conclusion is reached. The paper is motivated by a corpus analysis of NIPS, ACL, COGSCI, and ICCV/ECCV paper titles showing differences in how work on explainable AI is positioned in various fields. We close by introducing a fourth notion: truly explainable systems, where automated reasoning is central to output crafted explanations without requiring human post processing as final step of the generative process
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
We characterize three notions of explainable AI that cut across research fields: opaque systems that...
We characterize three notions of explainable AI that cut across research fields: opaque systems that...
We characterize three notions of explainable AI that cut across research fields: opaque systems that...
We characterize three notions of explainable AI that cut across research fields: opaque systems that...
AbstractExplainability in Artificial Intelligence (AI) has been revived as a topic of active researc...
Explainable artificial intelligence and interpretable machine learning are research fields growing i...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
We characterize three notions of explainable AI that cut across research fields: opaque systems that...
We characterize three notions of explainable AI that cut across research fields: opaque systems that...
We characterize three notions of explainable AI that cut across research fields: opaque systems that...
We characterize three notions of explainable AI that cut across research fields: opaque systems that...
AbstractExplainability in Artificial Intelligence (AI) has been revived as a topic of active researc...
Explainable artificial intelligence and interpretable machine learning are research fields growing i...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a...