Commonsense AI in the History of the Web

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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Published
2025-05-08
DOI
https://doi.org/10.1145/3701716.3716841
Primary Topic
Image Processing and 3D Reconstruction
Type
article
Field-Weighted Citation Impact
0.00

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article

Commonsense AI in the History of the Web

Deborah L. McGuinness, Henry Lieberman, Mayank Kejriwal
Image Processing and 3D Reconstruction
article

Commonsense AI in the History of the Web

Deborah L. McGuinness, Henry Lieberman, Mayank Kejriwal
article en

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.

University of Southern California (US), Rensselaer Polytechnic Institute (US), Massachusetts Institute of Technology (US)
University of Southern California, Defense Advanced Research Projects Agency, Air Force Office of Scientific Research
Openalex Percentile: Top 90%
Image Processing and 3D Reconstruction
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Commonsense AI in the History of the Web — Deborah L. McGuinness, Henry Lieberman, et al. · (2025) | TGRS Research Map | TGRS