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v. t. e. In science, computing, and engineering, a black box is a system which can be viewed in terms of its inputs and outputs (or transfer characteristics ), without any knowledge of its internal workings. Its implementation is "opaque" (black). The term can be used to refer to many inner workings, such as those of a transistor, an engine, an ...
Explainable AI ( XAI ), often overlapping with Interpretable AI, or Explainable Machine Learning ( XML ), either refers to an artificial intelligence (AI) system over which it is possible for humans to retain intellectual oversight, or refers to the methods to achieve this. [1] [2] The main focus is usually on the reasoning behind the decisions ...
Researchers have found that facial recognition AI has concerning failure rates when handling images of Black Americans, especially Black women, either failing to identify a person at all or making ...
Discovery system (AI research) A discovery system is an artificial intelligence system that attempts to discover new scientific concepts or laws. The aim of discovery systems is to automate scientific data analysis and the scientific discovery process. Ideally, an artificial intelligence system should be able to search systematically through ...
This is the 'black box' of AI." The AI algorithms were particularly good at predicting whether a patient would have breast cancer within a year of getting a mammogram, the study showed.
Black Box Corporation. Black Box is an IT company headquartered in Texas, United States. [1] The company provides technology assistance and consulting services to businesses in a variety of sectors including retail, transportation, government, education, and public safety. Black Box operates in 75 locations across 35 countries.
t. e. Black-box testing, sometimes referred to as specification-based testing, [1] is a method of software testing that examines the functionality of an application without peering into its internal structures or workings. This method of test can be applied virtually to every level of software testing: unit, integration, system and acceptance.
Using machine learning to detect bias is called, "conducting an AI audit", where the "auditor" is an algorithm that goes through the AI model and the training data to identify biases. Ensuring that an AI tool such as a classifier is free from bias is more difficult than just removing the sensitive information from its input signals, because ...
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