语义百科全书和布尔梦

A. Provo
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引用次数: 0

摘要

当元数据成为知识时,多样性的机会和伤害和排斥的风险就会出现。随着GLAM机构对语义网的贡献,我们必须注意参与的含义。虽然语义网是在20世纪90年代蓬勃发展的网络技术中发展起来的,但认识到它的根源是经典/符号人工智能(被称为老式人工智能,或GOFAI),特别是专家系统和知识表示,这鼓励了一些关键问题,如:语义网从知识表示和专家系统中继承了哪些问题?GOFAI的失败是真正的失败,还是修辞和实践之间的差距指向了生成的可能性(其中一些现在可以在语义网计划中看到)?我们能从人工智能的批评者、女权主义的方法和对百科全书中立性的揭露中学到什么?这篇研究文章将探讨对AI专家系统和Cyc(一个正在进行的创建常识知识库的项目)的批评如何应用于像Wikipedia、Wikidata、DBpedia和Schema.org这样的语义网络。
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Semantic Encyclopedias and Boolean Dreams
When metadata becomes knowledge, opportunities for multiplicity and risks of harm and exclusion arise. As GLAM institutions contribute to the Semantic Web, we must pay attention to the implications of participation. While the Semantic Web grew out of the flourishing of web technologies in the 1990s, recognizing its roots in classical/symbolic AI (referred to as Good Old Fashioned Artificial Intelligence, or GOFAI)—in particular, expert systems and knowledge representation—encourages critical questions like: which problems from knowledge representation and expert systems does the Semantic Web inherit? Are GOFAI failures really failures, or does the gap between rhetoric and practice point to generative possibilities (some of which can now be seen in Semantic Web initiatives)? What can we learn from AI critics, feminist approaches, and the unmasking of encyclopedic neutrality? This research article will explore how critiques of AI expert systems and Cyc, an ongoing project to create a common sense knowledge base, might apply to Semantic Webefforts like Wikipedia, Wikidata, DBpedia, and Schema.org.
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