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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 [1][2]. Its implementation is "opaque" (black). The term can be used to refer to many inner workings, such as those of a transistor, an engine ...
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.
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 or ...
Black box attacks in adversarial machine learning assume that the adversary can only get outputs for provided inputs and has no knowledge of the model structure or parameters. [ 17 ] [ 85 ] In this case, the adversarial example is generated either using a model created from scratch, or without any model at all (excluding the ability to query ...
Fuzzing. In programming and software development, fuzzing or fuzz testing is an automated software testing technique that involves providing invalid, unexpected, or random data as inputs to a computer program. The program is then monitored for exceptions such as crashes, failing built-in code assertions, or potential memory leaks.
The AI code of practice will not be legally binding when it takes effect late next year, but it will provide firms with a checklist they can use to demonstrate their compliance.
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