AI explainability remains an important preoccupation - enough so to earn the shiny acronym of XAI. There are notable developments in AI explainability and interpretability to assess. How much progress ...
The definitions of interpretability and explainability are not at all simplistic to those working directly in the field of artificial intelligence. They tend to be very domain and application specific ...
A practical review of explainable AI examines how transparency and interpretability improve trust in high-stakes ...
Two of the biggest questions associated with AI are “why does AI do what it does”? and “how does it do it?” Depending on the context in which the AI algorithm is used, those questions can be mere ...
Machine learning is taking the world by storm, helping automate more and more tasks. As digital transformation expands, the volume and coverage of available data grows, and machine learning sets its ...
This talk will attempt to demystify, for a non-technical audience, the current state of neural network explainability and interpretability, as well as trace the boundaries of what is in principle ...
To many AI practitioners and consumers, explainability is a precondition of AI use. A model that, without showing its work, tells a doctor what medicine to prescribe may be mistrusted. No experienced ...
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