Seven pillars for the future of Artificial Intelligence

• Main Authors: CAMBRIA, Erik, MAO, Rui, CHEN, Melvin, WANG, Zhaoxia, HO, Seng-Beng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Artificial Intelligence and Robotics
• Online Access: https://ink.library.smu.edu.sg/sis_research/8319; https://ink.library.smu.edu.sg/context/sis_research/article/9322/viewcontent/Seven_pillars_for_the_future_of_artificial_intelligence_Final.pdf
• Institution: Singapore Management University

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.