Explainable AI: current status and future directions

• URL: http://arxiv.org/abs/2107.07045v1
• Date: Mon, 12 Jul 2021 08:42:19 GMT
• Title: Explainable AI: current status and future directions
• Authors: Prashant Gohel, Priyanka Singh and Manoranjan Mohanty
• Abstract summary: Explainable Artificial Intelligence (XAI) is an emerging area of research in the field of Artificial Intelligence (AI) XAI can explain how AI obtained a particular solution and can also answer other "wh" questions. This paper provides an overview of these techniques from a multimedia (i.e., text, image, audio, and video) point of view.
• Score: 11.92436948211501
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Explainable Artificial Intelligence (XAI) is an emerging area of research in the field of Artificial Intelligence (AI). XAI can explain how AI obtained a particular solution (e.g., classification or object detection) and can also answer other "wh" questions. This explainability is not possible in traditional AI. Explainability is essential for critical applications, such as defense, health care, law and order, and autonomous driving vehicles, etc, where the know-how is required for trust and transparency. A number of XAI techniques so far have been purposed for such applications. This paper provides an overview of these techniques from a multimedia (i.e., text, image, audio, and video) point of view. The advantages and shortcomings of these techniques have been discussed, and pointers to some future directions have also been provided.

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