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Human-machine design considerations in advanced machine-learning systems

Human-machine design considerations in advanced machine-learning systems

Keates, S. ORCID: 0000-0002-2826-672X, Varker, P. and Spowart, F. (2011) Human-machine design considerations in advanced machine-learning systems. IBM Journal of Research and Development, 55 (5). 4:1-4:10. ISSN 0018-8646 (doi:10.1147/JRD.2011.2163274)

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Abstract

This paper explores issues related to human–computer interaction with the new class of machine-learning systems that represent an exciting development on the frontiers of information technology. These systems represent a significant breakthrough in humanity's decades-long endeavor to build computers that are “more like us”—fundamentally designed to map to and support human abilities and where the needs of people are central to the design process. This paper examines the human aspects of developing such new technology, with a focus on question-and-answer machine-learning systems. Considerations such as how human behavior should be addressed in the design and development of such systems are presented, followed by a series of potential application domains for the new technology.

Item Type: Article
Additional Information: [1] Copyright: © 2011 by International Business Machines Corporation. Copying in printed form for private use is permitted without payment of royalty provided that (1) each reproduction is done without alteration and (2) the Journal reference and IBM copyright notice are included on the first page. The title and abstract, but no other portions, of this paper may be copied by any means or distributed royalty free without further permission by computer-based and other information-service systems. Permission to republish any other portion of this paper must be obtained from the Editor.
Uncontrolled Keywords: Human machine design considerations, advanced machine-learning systems, Behavioral science, Global Positioning System, Human computer interaction, Knowledge based systems, Machine learning, User interfaces, Web search
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Faculty / Department / Research Group: Faculty of Engineering & Science
Related URLs:
Last Modified: 14 Oct 2016 09:29
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/12653

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