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What Is Explainable AI (XAI)? Explainable AI refers to a set of processes and methods that aim to provide a clear and human-understandable explanation for the decisions generated by AI and machine learning models.
Oct 24, 2022 · As artificial intelligence (AI) becomes more complex and widely adopted across society, one of the most critical sets of processes and methods is explainable (AI), sometimes referred to as XAI. Explainable AI can be defined as: A set of processes and methods that help human users comprehend and trust the results of machine learning algorithms. […]
Oct 5, 2021 · The Explainable AI (XAI) program aims to create a suite of machine learning techniques that: Produce more explainable models, while maintaining a high level of learning performance (prediction ...
Feb 12, 2024 · Methodologies of Explainable AI (XAI) Explainable AI offers tools and processes to explain different characteristics of both simply explainable ML models and the black box ones. For explainable models like linear and logistic regression, a lot of information can be obtained from the value of coefficients and parameters.
What is explainable AI, or XAI? Explainable AI is a set of processes and methods that allows users to understand and trust the results and output created by AI’s machine learning (ML) algorithms.
Explainable AI—especially explainable machine learning—will be essential if future warfighters are to understand, appropriately trust, and effectively manage an emerging generation of artificially intelligent machine partners. The Explainable AI (XAI) program aims to create a suite of machine learning techniques that:
Jan 16, 2023 · 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 ...
