reviewACM Computing SurveysSep 4, 2022GREEN OA

Explainable AI (XAI): Core Ideas, Techniques, and Solutions

Netaji Subhas University of Technology · Pandit Deendayal Energy University · +3 more institutions

Indexed incrossref

Abstract

As our dependence on intelligent machines continues to grow, so does the demand for more transparent and interpretable models. In addition, the ability to explain the model generally is now the gold standard for building trust and deployment of artificial intelligence systems in critical domains. Explainable artificial intelligence (XAI) aims to provide a suite of machine learning techniques that enable human users to understand, appropriately trust, and produce more explainable models. Selecting an appropriate approach for building an XAI-enabled application requires a clear understanding of the core ideas within XAI and the associated programming frameworks. We survey state-of-the-art programming techniques…

Citation impact

1,135
total citations
FWCI
127.36
Percentile
100%
References
51
Citations per year

Authors

11

Topics & keywords

Keywords
  • Computer science
  • Taxonomy (biology)
  • Process (computing)
  • Software
  • Artificial intelligence
  • Suite
  • Core (optical fiber)
  • Software deployment
UN Sustainable Development Goals
  • Partnerships for the goals
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