Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/173446
Title: Seven pillars for the future of artificial intelligence
Authors: Cambria, Erik
Mao, Rui
Chen, Melvin
Wang, Zhaoxia
Ho, Seng-Beng
Murugesan, San
Keywords: Computer and Information Science
Issue Date: 2023
Source: Cambria, E., Mao, R., Chen, M., Wang, Z., Ho, S. & Murugesan, S. (2023). Seven pillars for the future of artificial intelligence. IEEE Intelligent Systems, 38(6), 62-69. https://dx.doi.org/10.1109/MIS.2023.3329745
Journal: IEEE Intelligent Systems
Abstract: In recent years, artificial intelligence (AI) research has showcased tremendous potential to positively impact humanity and society. Although AI frequently outperforms humans in tasks related to classification and pattern recognition, it continues to face challenges when dealing with complex tasks such as intuitive decision making, sense disambiguation, sarcasm detection, and narrative understanding as these require advanced kinds of reasoning, e.g., common-sense reasoning and causal reasoning, which have not been emulated satisfactorily yet. To address these shortcomings, we propose seven pillars that we believe represent the key hallmark features for the future of AI, namely, multidisciplinarity, task decomposition, parallel analogy, symbol grounding, similarity measure, intention awareness, and trustworthiness.
URI: https://hdl.handle.net/10356/173446
ISSN: 1541-1672
DOI: 10.1109/MIS.2023.3329745
Schools: School of Computer Science and Engineering 
School of Humanities 
Rights: © 2023 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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