Open AccessBeating Common Sense into Interactive Applications
Author(s) -
Lieberman Henry,
Liu Hugo,
Singh Push,
Barry Barbara
Publication year - 2004
Publication title -
ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v25i4.1785
Subject(s) - commonsense knowledge , commonsense reasoning , common sense , computer science , interface (matter) , inference , dream , artificial intelligence , human–computer interaction , data science , knowledge based systems , epistemology , psychology , philosophy , bubble , maximum bubble pressure method , neuroscience , parallel computing
A long‐standing dream of artificial intelligence has been to put commonsense knowledge into computers—enabling machines to reason about everyday life. Some projects, such as Cyc, have begun to amass large collections of such knowledge. However, it is widely assumed that the use of common sense in interactive applications will remain impractical for years, until these collections can be considered sufficiently complete and commonsense reasoning sufficiently robust. Recently, at the Massachusetts Institute of Technology's Media Laboratory, we have had some success in applying commonsense knowledge in a number of intelligent interface agents, despite the admittedly spotty coverage and unreliable inference of today's commonsense knowledge systems. This article surveys several of these applications and reflects on interface design principles that enable successful use of commonsense knowledge.