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Human-Centered Artificial Intelligence: Advanced Lectures 1st ed. 2023 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 429 pages, height x width: 235x155 mm, weight: 676 g, 91 Illustrations, color; 20 Illustrations, black and white; XII, 429 p. 111 illus., 91 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Artificial Intelligence 13500
  • Izdošanas datums: 04-Apr-2023
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 303124348X
  • ISBN-13: 9783031243486
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Human-Centered Artificial Intelligence: Advanced Lectures 1st ed. 2023Palielināt
  • Formāts: Paperback / softback, 429 pages, height x width: 235x155 mm, weight: 676 g, 91 Illustrations, color; 20 Illustrations, black and white; XII, 429 p. 111 illus., 91 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Artificial Intelligence 13500
  • Izdošanas datums: 04-Apr-2023
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 303124348X
  • ISBN-13: 9783031243486
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783031243486.html
Keywords:
The 18th European Advanced Course on AI (ACAI) took place in Berlin on 11-15 October 2021, organized by the European project Humane-AI Net in collaboration with the European AI Association (EURAI). The school included tutorials on different topics, which were selected through an open call to top European AI researchers. In addition, the school also included 4 invited talks, a student poster presentation, and a mentorship program.





This volume contains 21 tutorial chapters organized according to the following themes: human-centered AI; human-centered machine learning; explainable AI; ethics, law, and the societal aspects of AI; argumentation; and social simulation. The contributions include learning objectives, reading lists, and links to further resources.

The Advanced Course on Human-Centered AI: Learning Objectives.- Conceptual Foundations of Human-Centric AI.- Machine Learning With Neural Networks.- Generative Networks and the AutoEncoder.- Convolutional Neural Networks.- Transformers in Natural Language Processing.- Vision and Multi-Modal Transformers.- Transformers in Automatic Speech Recognition.- Interactive Robot Learning: An Overview.- Explainable Machine Learning for Trustworthy AI.- Why and How Should We Explain AI.- Artificial Visual Intelligence: Perceptual Commonsense for Human-Centred Cognitive Technologies.- An Introduction to Ethics and AI.- Law for Computer Scientist.- Mythical Ethical Principles for AI and How to Attain Them.- Operationalising AI Ethics: Conducting Socio-Technical Assessment.- Writing Science Fiction as an inspiration for AI research and Ethics Dissemination.- Argumentation in AI.- Computational Argumentation Cognitive AI.- Agent-based Social Simulation for Policy Making.- Towards a Social Artificial Intelligence.

Mohamed ChetouaniSorbonne University, France Virginia DignumUmea University, Sweden Paul LukowiczGerman Research Center for Artificial Intelligence, Germany Carles SierraArtificial Intelligence Research Institute (IIIA-CSIC), Spain