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Human-Centric AI: The Symbiosis of Human and Artificial Intelligence
Entropy, 23 (2021), 3; 332. https://doi.org/10.3390/e23030332
Horvatić, Davor; Lipić, Tomislav

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Institucijski repozitorij: Repozitorij Prirodoslovno-matematičkog fakulteta

Citirajte ovaj rad

Horvatić, D. i Lipić, T. (2021). Human-Centric AI: The Symbiosis of Human and Artificial Intelligence. Entropy, 23. (3). doi: 10.3390/e23030332

Horvatić, Davor i Tomislav Lipić. "Human-Centric AI: The Symbiosis of Human and Artificial Intelligence." Entropy, vol. 23, br. 3, 2021. https://doi.org/10.3390/e23030332

Horvatić, Davor i Tomislav Lipić. "Human-Centric AI: The Symbiosis of Human and Artificial Intelligence." Entropy 23, br. 3 (2021). https://doi.org/10.3390/e23030332

Horvatić, D. i Lipić, T. (2021) 'Human-Centric AI: The Symbiosis of Human and Artificial Intelligence', Entropy, 23(3). doi: 10.3390/e23030332

Horvatić D, Lipić T. Human-Centric AI: The Symbiosis of Human and Artificial Intelligence. Entropy [Internet]. 11.03.2021. [pristupljeno 22.03.2025.];23(3). doi: 10.3390/e23030332

D. Horvatić i T. Lipić, "Human-Centric AI: The Symbiosis of Human and Artificial Intelligence", Entropy, vol. 23, br. 3, Ožujak 2021. [Online]. Dostupno na: https://urn.nsk.hr/urn:nbn:hr:217:278831. [Citirano: 22.03.2025.]

Za citiranje koristite ovu mrežnu adresu: https://urn.nsk.hr/urn:nbn:hr:217:278831
Podaci o radu
Naslov (engleski)Human-Centric AI: The Symbiosis of Human and Artificial Intelligence
AutorDavor Horvatić
AutorTomislav Lipić
Autorova ustanovaSveučilište u Zagrebu
Prirodoslovno-matematički fakultet
(Fizički odsjek)
Znanstveno / umjetničko
područje, polje i grana		PRIRODNE ZNANOSTI
Fizika
Sažetak (engleski)
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, and speech recognition or strategic board and video games.... Više 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. Despite the outstanding advancements and potential benefits, the concerns about the black-box nature and the lack of transparency behind the behavior of deep learning based AI solutions have hampered their further applications in our society. To fully trust, accept, and adopt newly emerging AI solutions in our everyday lives and practices, we need human- centric explainable AI (HC-XAI) that can provide human- understandable interpretations for their algorithmic behavior and outcomes—consequently enabling us to control and continuously improve their performance, robustness, fairness, accountability, transparency, and explainability throughout the entire lifecycle of AI applications. Following this motivation, the recently emerging trend within diverse and multidisciplinary research communities is based on the exploration of human-centric AI approaches and the development of contextual explanatory models propelling the symbiosis of human intelligence (HI) and artificial intelligence (AI), which forms the basis of the next (third) wave of AI. Sakrij dio sažetka
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Ostalo
Status objaveObjavljen
Vrsta recenzijeRecenziran - međunarodna recenzija
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov časopisaEntropy
Brojčani podacivol. 23, br. 3, 332
e-ISSN1099-4300
DOIhttps://doi.org/10.3390/e23030332
URN:NBNurn:nbn:hr:217:278831
Datum objave publikacije2021-03-11
URL dokumentahttps://www.mdpi.com/1099-4300/23/3/332
Vrsta resursaTekst
Prava pristupaOtvoreni pristup
Uvjeti korištenjaIkona licence Imenovanje 4.0 međunarodna (CC BY 4.0)
Javna napomena© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Received: 2 March 2021. Accepted: 8 March 2021. Published: 11 March 2021.
Datum i vrijeme pohrane2024-09-22 12:22:42
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