Physical-Cyber-Social Computing: An Early 21st Century Approach

Abstract

insight generation, and just about anything that humans, as intelligent beings, seek to do. We've used the term computing for human experience (CHE) 1 to capture technology's human-centric role. CHE emphasizes the unobtrusive, supportive, and assistive part technology plays in improving human experience; here, technology "takes into account the human world and allows computers themselves to disappear in the background." 2 We can distinguish this from Licklider's vision of human-computer collaboration, Eglebert's vision of augmenting human intellect and-more recently-ambient intelligence, and Vannever Bush's and McCarthy's machine-centric vision of making computing more intelligent so that it thinks and behaves like humans.Here, we present an emerging paradigm called physical-cyber-social (PCS) computing. It encompasses a holistic treatment of data, information, and knowledge from the PCS worlds to integrate, correlate, interpret, and provide contextually relevant abstractions to humans. We view PCS as the next phase of computing systems, building on current progress in cyber-physical systems, sociotechnical systems, and cyber-social systems to support CHE. PCS incorporates deeper and richer semantic interdependence and interplay between sensors and devices at physical layers; richer technology-mediated social interactions; and the gathering and application of collective intelligence characterized by massive and contextually relevant background knowledge and advanced reasoning to bridge machine and human perceptions.PCS computing requires that we move away from traditional data processing to multitier computation along the data-information-knowledge-wisdom (DIKW) dimension, which supports reasoning to convert data into abstractions that are more familiar, accessible, and understandable to humans.We illustrate PCS computing for healthcare with a focus on semantic perception, 3 which converts low-level, heterogeneous, multimodal, and contextually relevant data into higher-level abstractions that can provide insights and assist humans in making complex decisions. Case StudyConsider the case of Ram, a 60-year-old Asian male, who receives a blood pressure screening from his doctor and discovers that the reading is slightly higher than expected (90 diastolic, measured in mmHg). Let's look at two questions that Ram might have: What is the normal blood pressure of an Asian male of his age? What is the best way to manage a diastolic blood pressure of 90? To answer these questions, we need access to physiological observations obtained from other people with similar characteristics and demographics (physical). We should also consider the ethnic, social, cultural, and economic background for similarity (social). Moreover, in addition to expert knowledge, the knowledge and experience of similar people dealing with the same health issue are important (cyber). Neither an average doctor nor current cyber-physical systems can answer these questions, but PCS computing can address them in a holistic manner. Patient empowerment and p...

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