Nov 28, 2019 · Explainable artificial intelligence (XAI) is a set of processes and methods that allows human users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, …

Explainable AI (XAI), often overlapping with interpretable AI, or explainable machine learning (XML), is a field of research within artificial intelligence (AI) that explores methods that provide humans with the ability of intellectual oversight over AI algorithms.

Dec 5, 2023 · Explainable artificial intelligence (XAI) refers to a collection of procedures and techniques that enable machine learning algorithms to produce output and results that are understandable and reliable for human users.

Nov 1, 2023 · Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated applications, but the outcomes of many AI models are challenging to comprehend and trust due to their black-box nature. Usually, it is essential to understand the reasoning behind an AI model’s decision-making.

Feb 14, 2025 · As the "black-box" problem creates challenges for AI, explainable AI can help reshape business-to-business operations by fostering trust and improving decision making.

2 days ago · Explainable AI is more than just a technical enhancement—it represents a cultural shift in how organizations engage with technology. By integrating XAI strategies: • Transparency is increased.

Explainable AI not only builds trust with users but also facilitates debugging, compliance, and improved performance in AI systems [8]. It addresses the fundamental question: How can we trust a system that we do not understand?

Oct 19, 2024 · Explainable AI (XAI) aims to address this challenge by providing tools and methodologies that make AI models more transparent, interpretable, and understandable for humans. XAI focuses on ensuring that AI systems can be trusted, accountable, and compliant with regulatory standards.

Feb 7, 2025 · Artificial Intelligence (AI) has played an increasingly significant role in using data collected from diverse sources such as social media, sensors, education, multimedia, and text data, to make necessary decisions that have helped humans [67,68,69].Explainable Artificial Intelligence (XAI) stems from the increasing integration of AI models in a way that allows humans to understand, interpret ...

Apr 6, 2020 · Explainable AI is a key element of trustworthy AI. As part of NIST’s efforts to provide foundational tools, guidance, and best practices for AI-related research, NIST released a draft report, Four Principles of Explainable Artificial Intelligence, for public comment. Inspired by comments received, this workshop delved further into developing ...