Commonsense AI in the History of the Web
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Authors
Kejriwal, Mayank
McGuinness, Deborah L.
Lieberman, Henry
Issue Date
2025-05-08
Type
Article
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Abstract
Machine common sense (MCS)-the challenge of enabling computers to grasp everyday human knowledge-has been a grand challenge in Artificial Intelligence (AI) since the 1950s. While recent advances in large language models have led to impressive progress, there is still no consensus on how much common sense today's AI actually possesses. In this brief review, we revisit the historical development of MCS in the context of the Web, examining how the Web's evolution-from early knowledge representation efforts to knowledge graphs, the Semantic Web, and crowdsourcing-has shaped MCS research. We argue that key breakthroughs in Web technologies were instrumental in addressing longstanding challenges of scale and coverage in commonsense reasoning. At the same time, MCS research has influenced the development of core Web applications, including intelligent agents, plausibility-based reasoning, and robust evaluation of black-box AI systems.
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Full Citation
Mayank Kejriwal, Deborah L. McGuinness, and Henry Lieberman. 2025. Commonsense AI in the History of the Web. In Companion Proceedings of the ACM on Web Conference 2025 (WWW '25). Association for Computing Machinery, New York, NY, USA, 837–840. https://doi.org/10.1145/3701716.3716841
Publisher
Association for Computing Machinery