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Marvin Minsky et al. raised the issue that AI can function as a form of surveillance, with the biases inherent in surveillance, suggesting HI (Humanistic Intelligence) as a way to create a more fair and balanced "human-in-the-loop" AI. [61] Explainable AI has been recently a new topic researched amongst the context of modern deep learning.
The field of Explainable AI seeks to provide better explanations from existing algorithms, and algorithms that are more easily explainable, but it is a young and active field. [ 18 ] [ 19 ] Others argue that the difficulties with explainability are due to its overly narrow focus on technical solutions rather than connecting the issue to the ...
Explainable Artificial Intelligence in the context of black box machine learning models: Saliency maps are a prominent tool in XAI, [6] providing visual explanations of the decision-making process of machine learning models, particularly deep neural networks. These maps highlight the regions in input images, text, or other types of data that ...
Empowerment (artificial intelligence) Enterprise cognitive system; Environmental impacts of artificial intelligence; Epistemic modal logic; Evolutionary developmental robotics; Explainable artificial intelligence; Extremal optimization
This has led to advocacy and in some jurisdictions legal requirements for explainable artificial intelligence. [68] Explainable artificial intelligence encompasses both explainability and interpretability, with explainability relating to summarizing neural network behavior and building user confidence, while interpretability is defined as the ...
If 2023 was a year of wonder about artificial intelligence, 2024 was the year to try to get that wonder to do something useful without breaking the bank. There was a “shift from putting out ...