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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 ...
How deep learning is a subset of machine learning and how machine learning is a subset of artificial intelligence (AI) The deep learning revolution started around CNN- and GPU-based computer vision. Although CNNs trained by backpropagation had been around for decades and GPU implementations of NNs for years, [ 97 ] including CNNs, [ 98 ] faster ...
Right to explanation. In the regulation of algorithms, particularly artificial intelligence and its subfield of machine learning, a right to explanation (or right to an explanation) is a right to be given an explanation for an output of the algorithm. Such rights primarily refer to individual rights to be given an explanation for decisions that ...
Less than a year ago, Anthropic was founded by former OpenAI VP of research Dario Amodei, intending to perform research in the public interest on making AI more reliable and explainable. Its $124 ...
The second overarching factor when considering explainable AI is assessing the trade-offs of “true explainable and transparent AI.”. Currently there is a trade-off in some tasks between ...
Trinity College Dublin. Occupation. Computer scientist. Employer. Technological University Dublin. Luca Longo is an Italian computer scientist specializing in Explainable artificial intelligence [1], Deep Learning and Argumentation theory with research in the areas of Human performance modeling. As the founder and general chair of the World ...
Liang Zhao is a computer scientist and academic. He is an associate professor in the Department of Compute Science at Emory University. [1]Zhao's research focuses on data mining, machine learning, and artificial intelligence, with particular interests in deep learning on graphs, societal event prediction, interpretable machine learning, multi-modal machine learning, generative AI, and ...
Yixin Chen is a computer scientist, academic, and author. He is a professor of computer science and engineering at Washington University in St. Louis. [1] Chen's research interests are focused on computer sciences, with a particular focus on the fields of machine learning, deep learning, and data mining. [2]