Understanding the Cyber-Physical-Social-Intentional ‘Workforce 4.0’: Conceptual Foundations, Architecture, and Context

Workforce 4.0 as a Cyber-Physical-Social-Intentional System

the VIII Scientific Conference on Modern Concepts and Management Methods: Management 4.0 – Modern Trends in Public, Social and Business Sector • Military University of Technology in Warsaw • December 6, 2018

ABSTRACT: The widespread application of Industry 4.0 technologies relating to social robotics, embodied AI, the Internet of Things (IoT), ubiquitous computing, and advanced human computer interfaces is giving rise to a growing range of “cyber-physical” entities. By building on established definitions and analyses of the cyber-physical system, cyber-physical-social system, cyber-physical society, and cyber-physical-social-thinking space, this text formulates a conceptual framework for understanding the emerging “Workforce 4.0” as a specialized type of “cyber-physical-social-intentional system.” Attention is given to the heterogeneous agency, technological posthumanization, functional decentralization, and planned architectures or spontaneously self-organizing topologies manifested by Workforce 4.0. It is shown how such a workforce is situated within the context of cyber-physical space, a cyber-physical organization, cyber-physical ecosystems, a cyber-physical society, and the larger cyber-physical world.

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A Phenomenological Analysis of the Posthumanized Future Workplace

Impacts of Technological Posthumanization on Future Workplace Architecture

Kwartalnik Nauk o Przedsiębiorstwie 48 (2018), pp. 31-39; MNiSW 2016 List B: 12 points

ABSTRACT: Increasingly, organizations are becoming “technologically posthumanized” through the integration of social robots, AI, virtual reality, and ubiquitous computing into the workplace. Here a phenomenological approach is used to anticipate architectural transformations of the workplace resulting from posthumanization’s challenge to traditional anthropocentric paradigms of the workplace as a space that exists at “human” scale, possesses a trifold boundary, and serves as a spatiotemporal filter.

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Dynamics of Technological Posthumanization: Distinguishing the Anticipated Paths of Developed and Emerging Economies

Differing Paths to Technological Posthumanization

The International Conference on ICT Management for Global Competitiveness and Economic Growth in Emerging Economies (ICTM 2018) • Wrocław • October 22, 2018

ABSTRACT: The processes of “posthumanization” can be understood as those dynamics by which a human organization or society comes to include members other than “natural” biological human beings who contribute to the structure, activities, or meaning of that organization or society. In the world of business, such posthumanization is commonly identified with the growing use of social robots, autonomous AI, and joint human-computer systems to perform work that in earlier eras would have been performed by human beings acting alone. Such “technological” posthumanization is often presented as a new phenomenon occurring largely in those developed economies that are pioneering Industry 4.0 paradigms (e.g., by expanding workplace automation) and that are uniquely positioned to harness such forces to drive economic growth. Here, however, we contend that such emphasis on the novelty of technological posthumanization overlooks forms of non-technological posthumanization that have been at work in human societies for millennia. Such dynamics of non-technological posthumanization have weakened significantly in many developed economies since the mid-20th century; however, they remain relatively strong in emerging economies. In this study, a conceptual framework is developed for identifying and comparing phenomena through which processes of technological or non-technological posthumanization manifest themselves in developed and emerging economies. It is argued that the ongoing and robust experience with non-technological posthumanization possessed by many of the world’s emerging economies may offer them unique and underappreciated psychological, social, and cultural mechanisms for integrating effectively into their enterprises, organizations, and institutions those novel forms of non-human agency that are at work in key Industry 4.0 technologies, like those relating to social robotics, autonomous AI, and advanced human-computer interfaces.

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Enterprise Meta-Architecture for Megacorps of Unmanageably Great Size, Speed, and Technological Complexity

Enterprise Meta Architecture for Megacorps

In Information Systems Architecture and Technology: Proceedings of 39th International Conference on Information Systems Architecture and Technology – ISAT 2018, Part III, edited by Zofia Wilimowska, Leszek Borzemski, and Jerzy Świątek • Springer International Publishing, 2018

ABSTRACT: The discipline of enterprise architecture (EA) provides valuable tools for aligning an organization’s business strategy and processes, IT strategy and systems, personnel structures, and organizational culture, with the goal of enhancing organizational agility, adaptability, and efficiency. However, the centralized and exhaustively detailed approach of conventional EA is susceptible to failure when employed in organizations demonstrating exceedingly great size, speed of operation and change, and IT complexity – a combination of traits that characterizes, for example, some emerging types of “technologized” oligopolistic megacorps reflecting the Industry 4.0 paradigm. This text develops the conceptual basis for a variant form of enterprise architecture that can be used to enact improved target architectures for organizations whose characteristics would otherwise render them “unmanageable” from the perspective of conventional EA. The proposed approach of “enterprise meta-architecture” (or EMA) disengages human enterprise architects from the fine-grained details of architectural analysis, design, and implementation, which are handled by artificially intelligent systems functioning as active agents rather than passive tools. The role of the human enterprise architect becomes one of determining the types of performance improvements a target architecture should ideally generate, establishing the operating parameters for an EMA system, and monitoring and optimizing its functioning. Advances in Big Data and parametric design provide models for enterprise meta-architecture, which is distinct from other new approaches like agile and adaptive EA. Deployment of EMA systems should become feasible as ongoing advances in AI result in an increasing share of organizational agency and decision-making responsibility being shifted to artificial agents.

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