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Abstract

KI und Robotik werfen neue Fragen epistemologischer Art auf, die im Kontext einer Philosophie des Geistes wie der Ethik diskutiert werden müssen. Im Hinblick auf eine erste Skizze epistemologischer Art zu möglichen Formen von Intelligenz und Bewusstsein bei KI und Robotern wird aufgezeigt, dass von ihrer Genese und ihrer Struktur, also ihrer Phänomenologie, drei Arten von Intelligenz unterschieden werden müssen, nämlich evolutionär generierte, kulturell-sprachlich eingebettete und technologische, die nicht miteinander identifiziert werden können. Um Intelligenz und Bewusstsein von KI und Robotik im Unterschied zu biologischer und menschlicher Intelligenz verstehen zu können, muss die algorithmische Struktur von KI unter Berücksichtigung der Philosophie des Geistes und des wissenschaftlich-technologischen Forschens im Bereich der Evolution kognitiven und kommunikativen Verhaltens, der Neurowissenschaften und Psychologie und der Menschheitsgeschichte wie der Kulturanthropologie bestimmt werden.

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Abstract

Since Oliver's guide was first published in 2010, thousands of LIS students, records managers, and catalogers and other library professionals have relied on its clear, plainspoken explanation of RDA: Resource Description and Access as their first step towards becoming acquainted with the cataloging standard. Now, reflecting the changes to RDA after the completion of the 3R Project, Oliver brings her Special Report up to date. This essential primer concisely explains what RDA is, its basic features, and the main factors in its development describes RDA's relationship to the international standards and models that continue to influence its evolution provides an overview of the latest developments, focusing on the impact of the 3R Project, the results of aligning RDA with IFLA's Library Reference Model (LRM), and the outcomes of internationalization illustrates how information is organized in the post 3R Toolkit and explains how to navigate through this new structure; and discusses how RDA continues to enable improved resource discovery both in traditional and new applications, including the linked data environment.

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Content

Section 1 Context and purpose of knowledge architecture -- 1 Making the case for knowledge architecture -- 2 The landscape of knowledge assets -- 3 Knowledge architecture and design -- 4 Knowledge architecture reference model -- 5 Knowledge architecture segments -- Section 2 Designing for availability -- 6 Knowledge object modeling -- 7 Knowledge structures for encoding, formatting, and packaging -- 8 Functional architecture for identification and distinction -- 9 Functional architectures for knowledge asset disposition and destruction -- 10 Functional architecture designs for knowledge preservation and conservation -- Section 3 Designing for accessibility -- 11 Functional architectures for knowledge seeking and discovery -- 12 Functional architecture for knowledge search -- 13 Functional architecture for knowledge categorization -- 14 Functional architectures for indexing and keywording -- 15 Functional architecture for knowledge semantics -- 16 Functional architecture for knowledge abstraction and surrogation -- Section 4 Functional architectures to support knowledge consumption -- 17 Functional architecture for knowledge augmentation, derivation, and synthesis -- 18 Functional architecture to manage risk and harm -- 19 Functional architectures for knowledge authentication and provenance -- 20 Functional architectures for securing knowledge assets -- 21 Functional architectures for authorization and asset management -- Section 5 Pulling it all together - the big picture knowledge architecture -- 22 Functional architecture for knowledge metadata and metainformation -- 23 The whole knowledge architecture - pulling it all together

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Date

22. 6.2023 18:25:18