Human-Centric AI: The Symbiosis of Human and Artificial Intelligence

Well-evidenced advances of data-driven complex machine learning approaches emerging within the so-called second wave of artificial intelligence (AI) fostered the exploration of possible AI applications in various domains and aspects of human life, practices, and society. Most of the recent success i...

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Main Authors: Davor Horvatić, Tomislav Lipic
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/23/3/332
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spelling doaj-7e3c6bf86ec74db8a4c8fed4a3ae4e8a2021-03-12T00:06:01ZengMDPI AGEntropy1099-43002021-03-012333233210.3390/e23030332Human-Centric AI: The Symbiosis of Human and Artificial IntelligenceDavor Horvatić0Tomislav Lipic1Department of Physics, Faculty of Science, University of Zagreb, Bijenička Cesta 32, 10000 Zagreb, CroatiaDivision of Electronics, Ruđer Bošković Institute, Bijenička Cesta 54, 10000 Zagreb, CroatiaWell-evidenced advances of data-driven complex machine learning approaches emerging within the so-called second wave of artificial intelligence (AI) fostered the exploration of possible AI applications in various domains and aspects of human life, practices, and society. Most of the recent success in AI comes from the utilization of representation learning with end-to-end trained deep neural network models in tasks such as image, text,<br>and speech recognition or strategic board and video games. By enabling automatic feature engineering, deep learning models significantly reduce the reliance on domain-expert knowledge, outperforming traditional methods based on handcrafted feature engineering and achieving performance that equals or even supersedes humans in some respects.https://www.mdpi.com/1099-4300/23/3/332artificial intelligencedeep neural networksinterpretabilityexplainabilityfairnessaccountability
collection DOAJ
language English
format Article
sources DOAJ
author Davor Horvatić
Tomislav Lipic
spellingShingle Davor Horvatić
Tomislav Lipic
Human-Centric AI: The Symbiosis of Human and Artificial Intelligence
Entropy
artificial intelligence
deep neural networks
interpretability
explainability
fairness
accountability
author_facet Davor Horvatić
Tomislav Lipic
author_sort Davor Horvatić
title Human-Centric AI: The Symbiosis of Human and Artificial Intelligence
title_short Human-Centric AI: The Symbiosis of Human and Artificial Intelligence
title_full Human-Centric AI: The Symbiosis of Human and Artificial Intelligence
title_fullStr Human-Centric AI: The Symbiosis of Human and Artificial Intelligence
title_full_unstemmed Human-Centric AI: The Symbiosis of Human and Artificial Intelligence
title_sort human-centric ai: the symbiosis of human and artificial intelligence
publisher MDPI AG
series Entropy
issn 1099-4300
publishDate 2021-03-01
description Well-evidenced advances of data-driven complex machine learning approaches emerging within the so-called second wave of artificial intelligence (AI) fostered the exploration of possible AI applications in various domains and aspects of human life, practices, and society. Most of the recent success in AI comes from the utilization of representation learning with end-to-end trained deep neural network models in tasks such as image, text,<br>and speech recognition or strategic board and video games. By enabling automatic feature engineering, deep learning models significantly reduce the reliance on domain-expert knowledge, outperforming traditional methods based on handcrafted feature engineering and achieving performance that equals or even supersedes humans in some respects.
topic artificial intelligence
deep neural networks
interpretability
explainability
fairness
accountability
url https://www.mdpi.com/1099-4300/23/3/332
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