Publication Type
Journal Article
Version
publishedVersion
Publication Date
1-2023
Abstract
In recent years, AI research has showcased tremendous potential to impact positively 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., commonsense 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.
Discipline
Artificial Intelligence and Robotics
Research Areas
Information Systems and Management
Publication
IEEE Intelligent Systems
First Page
62
Last Page
69
ISSN
1541-1672
Publisher
Institute of Electrical and Electronics Engineers
Citation
CAMBRIA, Erik; MAO, Rui; CHEN, Melvin; WANG, Zhaoxia; and HO, Seng-Beng.
Seven pillars for the future of Artificial Intelligence. (2023). IEEE Intelligent Systems. 62-69.
Available at: https://ink.library.smu.edu.sg/sis_research/8319
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