What is explainable AI?
What is Explainable AI (XAI)? - IBM
Explainable artificial intelligence (XAI) allows human users to comprehend and trust the results and output created by machine learning algorithms.
What is Explainable AI? - SEI Blog
Explainable AI refers to the set of processes and methods that allows human users to comprehend and trust the results and output created by machine learning ...
Explainable artificial intelligence - Wikipedia
XAI aims to explain what has been done, what is being done, and what will be done next, and to unveil which information these actions are based on.
Introduction to Vertex Explainable AI - Google Cloud
Vertex Explainable AI offers Feature-based and Example-based explanations to provide better understanding of model decision making.
What is Explainable AI? Benefits & Best Practices - Qlik
Explainable AI (XAI) refers to a set of techniques and processes that help you understand the rationale behind the output of a machine learning algorithm.
What is explainable AI? | Definition from TechTarget
XAI is artificial intelligence (AI) that's programmed to describe its purpose, rationale and decision-making process in a way that the average person can ...
What is Explainability? | C3 AI Glossary Definition
Explainability (also referred to as “interpretability”) is the concept that a machine learning model and its output can be explained in a way that “makes sense ...
Explainable Artificial Intelligence (XAI): What we know and what is ...
The study starts by explaining the background of XAI, common definitions, and summarizing recently proposed techniques in XAI for supervised machine learning.
What Is Explainable AI? - YouTube
Explainable AI allows users to understand how an AI model makes predictions or comes to results. Learn more about what explainable AI is, ...
Why businesses need explainable AI—and how to deliver it
Explainability is the capacity to express why an AI system reached a particular decision, recommendation, or prediction. Developing this ...
What Is Explainable AI (XAI)? - Palo Alto Networks
XAI aims to make AI systems transparent and interpretable, allowing users to understand how these systems arrive at their decisions or predictions.
What is Explainable AI (XAI)? | Juniper Networks US
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 ...
EXPLAINABLE ARTIFICIAL INTELLIGENCE
Interpretable AI models allow humans to estimate what a model will predict given an input, and understand when the model has made a mistake. Explainability is ...
What is Explainable AI (XAI) and Why Does It Matter? - Medium
XAI techniques provide the means to try to unravel the mysteries of AI decision-making, helping end users easily understand and interpret model predictions.
Explainable Artificial Intelligence (XAI) (Archived) - Darpa
XAI is one of a handful of current DARPA programs expected to enable “third-wave AI systems”, where machines understand the context and environment in which ...
The importance of explainability in AI decision-making | Algolia
Explainability is the capacity to express why an AI system reached a particular decision, recommendation, or prediction.
What Is Explainable AI? | Built In
Explainable AI makes artificial intelligence models more manageable and understandable. This helps developers determine if an AI system is working as intended ...
Explainable vs. Interpretable Artificial Intelligence - Splunk
In this article, we will explore the differences between explainable and interpretable artificial intelligence.
Explainable Artificial Intelligence - an overview | ScienceDirect Topics
Explainable Artificial Intelligence (XAI) is a strategy for developing AI systems that tries to give explicit and intelligible explanations for the AI model's ...
What Is Explainable AI (XAI)? - NVIDIA Blog
Explainable AI, or XAI, is a set of tools and techniques that help people understand the math inside AI models to provide greater ...