Difference between revisions of "PCS"

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(Physical-Cyber-Social Computing: An Early 21st Century Approach to Computing for Human Experience)
(Physical-Cyber-Social Computing: An Early 21st Century Approach to Computing for Human Experience)
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=Physical-Cyber-Social Computing: An Early 21st Century Approach to Computing for Human Experience=
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=Physical-Cyber-Social Computing: <br/> An Early 21st Century Approach to Computing for Human Experience=
  
 
Visionaries and scientists from the early days of computing and electronic communication have discussed the proper role of technology to improve human experience. Technology now plays an increasingly important role in facilitating and improving personal and social activities and engagements, decision making, interaction with physical and social worlds, generating insights, and just about anything that a human, as an intelligent being, seeks to do.  We have used the term Computing for Human Experience (CHE) [1] to capture this essential role of technology in a human centric vision. CHE emphasizes the unobtrusive, supportive and assistive role of technology in improving human experience, so that technology “takes into account the human world and allows computers themselves to disappear in the background” (Mark Weiser [2]). This can be distinguished from Licklider’s vision of human-computer collaboration [5], Eglebert’s vision of augmenting human intellect [16], and McCarthy’s definition of intelligent machines [11].
 
Visionaries and scientists from the early days of computing and electronic communication have discussed the proper role of technology to improve human experience. Technology now plays an increasingly important role in facilitating and improving personal and social activities and engagements, decision making, interaction with physical and social worlds, generating insights, and just about anything that a human, as an intelligent being, seeks to do.  We have used the term Computing for Human Experience (CHE) [1] to capture this essential role of technology in a human centric vision. CHE emphasizes the unobtrusive, supportive and assistive role of technology in improving human experience, so that technology “takes into account the human world and allows computers themselves to disappear in the background” (Mark Weiser [2]). This can be distinguished from Licklider’s vision of human-computer collaboration [5], Eglebert’s vision of augmenting human intellect [16], and McCarthy’s definition of intelligent machines [11].
  
 
In this article, we present a vision of the future of computing, called physical-cyber-social (PCS) computing. PCS computing is a holistic treatment of data, information, and knowledge from physical, cyber, and social worlds to integrate, understand, correlate, and provide contextually relevant abstractions to humans.  PCS computing takes ideas from, but goes significantly beyond, the current progress in cyber-physical systems, socio-technical systems and cyber-social systems to support CHE [3].  We will exemplify future CHE application scenarios in healthcare and traffic management that are supported by (a) a deeper and richer semantic interdependence and interplay between sensors and devices at physical layers, (b) rich technology mediated social interactions, and (c) the gathering and application of collective intelligence characterized by massive and contextually relevant background knowledge and advanced reasoning in order to bridge machine and human perceptions.  We will share an example of PCS computing using semantic perception [4], which converts low-level, heterogeneous, multimodal and contextually relevant data into high-level abstractions that can provide insights and assist humans in making complex decisions.  The key challenge for PCS computing requires moving away from traditional data processing to multi-tier computation along a data-information-knowledge-wisdom dimension, which supports reasoning to convert data into abstractions that are more familiar, accessible, and understandable by people.
 
In this article, we present a vision of the future of computing, called physical-cyber-social (PCS) computing. PCS computing is a holistic treatment of data, information, and knowledge from physical, cyber, and social worlds to integrate, understand, correlate, and provide contextually relevant abstractions to humans.  PCS computing takes ideas from, but goes significantly beyond, the current progress in cyber-physical systems, socio-technical systems and cyber-social systems to support CHE [3].  We will exemplify future CHE application scenarios in healthcare and traffic management that are supported by (a) a deeper and richer semantic interdependence and interplay between sensors and devices at physical layers, (b) rich technology mediated social interactions, and (c) the gathering and application of collective intelligence characterized by massive and contextually relevant background knowledge and advanced reasoning in order to bridge machine and human perceptions.  We will share an example of PCS computing using semantic perception [4], which converts low-level, heterogeneous, multimodal and contextually relevant data into high-level abstractions that can provide insights and assist humans in making complex decisions.  The key challenge for PCS computing requires moving away from traditional data processing to multi-tier computation along a data-information-knowledge-wisdom dimension, which supports reasoning to convert data into abstractions that are more familiar, accessible, and understandable by people.

Revision as of 19:17, 9 January 2013

Physical-Cyber-Social Computing:
An Early 21st Century Approach to Computing for Human Experience

Visionaries and scientists from the early days of computing and electronic communication have discussed the proper role of technology to improve human experience. Technology now plays an increasingly important role in facilitating and improving personal and social activities and engagements, decision making, interaction with physical and social worlds, generating insights, and just about anything that a human, as an intelligent being, seeks to do. We have used the term Computing for Human Experience (CHE) [1] to capture this essential role of technology in a human centric vision. CHE emphasizes the unobtrusive, supportive and assistive role of technology in improving human experience, so that technology “takes into account the human world and allows computers themselves to disappear in the background” (Mark Weiser [2]). This can be distinguished from Licklider’s vision of human-computer collaboration [5], Eglebert’s vision of augmenting human intellect [16], and McCarthy’s definition of intelligent machines [11].

In this article, we present a vision of the future of computing, called physical-cyber-social (PCS) computing. PCS computing is a holistic treatment of data, information, and knowledge from physical, cyber, and social worlds to integrate, understand, correlate, and provide contextually relevant abstractions to humans. PCS computing takes ideas from, but goes significantly beyond, the current progress in cyber-physical systems, socio-technical systems and cyber-social systems to support CHE [3]. We will exemplify future CHE application scenarios in healthcare and traffic management that are supported by (a) a deeper and richer semantic interdependence and interplay between sensors and devices at physical layers, (b) rich technology mediated social interactions, and (c) the gathering and application of collective intelligence characterized by massive and contextually relevant background knowledge and advanced reasoning in order to bridge machine and human perceptions. We will share an example of PCS computing using semantic perception [4], which converts low-level, heterogeneous, multimodal and contextually relevant data into high-level abstractions that can provide insights and assist humans in making complex decisions. The key challenge for PCS computing requires moving away from traditional data processing to multi-tier computation along a data-information-knowledge-wisdom dimension, which supports reasoning to convert data into abstractions that are more familiar, accessible, and understandable by people.