Last updated: 18 Jul 2024 · This standard defines mandatory and optional requirements and constraints that need to be satisfied for an AI method, algorithm, application or system t...
Public attention towards explainability of artificial intelligence (AI) systems has been rising in recent years to offer methodologies for human oversight. This has translated into...
The joint ISO (International Organization for Standardization) and IEC (International Electrotechnical Commission) committee on Artificial Intelligence (AI), SC 42, is playing a cr...
Explainability in artificial intelligence (AI) is crucial for ensuring transparency, accountability, and risk mitigation, thereby addressing digital responsibility, social, ethical...
IEEE strengthens global AI governance by contributing 100+ standards to the new International AI Standards Exchange, fostering innovation and interoperability
The quest to open black box artificial intelligence (AI) systems evolved into an emerging phenomenon of global interest for academia, business, and society and brought about the ri...
Recent advancements in Explainable Artificial Intelligence (XAI) aim to bridge the gap between complex artificial intelligence (AI) models and human understanding, fostering trust ...
Explainability is a quality sometimes required in the context of Artificial Intelligence (AI). The European’s proposed AI Act will probably contain obligations for some AI systems ...
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