Artificial Intelligence Needs Open-Access Knowledgebase Contents

A substantial knowledgebase is an important part of many A.I. applications as well as (arguably) in any system that is claimed to implement broad-range intelligence. Although this has been an accepted view in our field since very long, little progress has been made towards the establishment of large and sharable knowledgebases. Both basic research projects and applications projects have found it necessary to construct special-purpose knowledgebases for their respective needs. This is obviously a problem: it would save work and speed up progress if the construction of a broadly sharable and broadly useful knowledgebase could be a joint undertaking for the field. In this article I wish to discuss the possibilities and the obstacles in this respect. I shall argue that the field of Knowledge Representation needs to adopt a new and very different paradigm in order for progress to be made, so that besides working as usual on logical foundations and on algorithms, we should also devote substantial efforts to the systematic preparation of knowledgebase contents. The article is based on the author’s experience from the ongoing development of the Common Knowledge Library (⁀http://piex.publ.kth.se/ckl/), CKL. This is an open-access resource for modules of knowledge and facts, presently containing more than 70,000 entities with their associated attributes and values.