Birth of Industry 5.0: Making Sense of Big Data with Artificial Intelligence, “The Internet of Things” and Next-Generation Technology Policy

Abstract

Driverless cars with artificial intelligence (AI) and automated supermarkets run by collaborative robots (cobots) working without human supervision have sparked off new debates: what will be the impacts of extreme automation, turbocharged by the Internet of Things (IoT), AI, and the Industry 4.0, on Big Data and omics implementation science? The IoT builds on (1) broadband wireless internet connectivity, (2) miniaturized sensors embedded in animate and inanimate objects ranging from the house cat to the milk carton in your smart fridge, and (3) AI and cobots making sense of Big Data collected by sensors. Industry 4.0 is a high-tech strategy for manufacturing automation that employs the IoT, thus creating the Smart Factory. Extreme automation until "everything is connected to everything else" poses, however, vulnerabilities that have been little considered to date. First, highly integrated systems are vulnerable to systemic risks such as total network collapse in the event of failure of one of its parts, for example, by hacking or Internet viruses that can fully invade integrated systems. Second, extreme connectivity creates new social and political power structures. If left unchecked, they might lead to authoritarian governance by one person in total control of network power, directly or through her/his connected surrogates. We propose Industry 5.0 that can democratize knowledge coproduction from Big Data, building on the new concept of symmetrical innovation. Industry 5.0 utilizes IoT, but differs from predecessor automation systems by having three-dimensional (3D) symmetry in innovation ecosystem design: (1) a built-in safe exit strategy in case of demise of hyperconnected entrenched digital knowledge networks. Importantly, such safe exists are orthogonal-in that they allow "digital detox" by employing pathways unrelated/unaffected by automated networks, for example, electronic patient records versus material/article trails on vital medical information; (2) equal emphasis on both acceleration and deceleration of innovation if diminishing returns become apparent; and (3) next generation social science and humanities (SSH) research for global governance of emerging technologies: "Post-ELSI Technology Evaluation Research" (PETER). Importantly, PETER considers the technology opportunity costs, ethics, ethics-of-ethics, framings (epistemology), independence, and reflexivity of SSH research in technology policymaking. Industry 5.0 is poised to harness extreme automation and Big Data with safety, innovative technology policy, and responsible implementation science, enabled by 3D symmetry in innovation ecosystem design.

Socio-Technical Perspectives on Smart Working: Creating Meaningful and Sustainable Systems

“…While Industry 4.0 has been concerned with creation of 'smart factories' through application of robotics and virtualisation in production systems, Industry 5.0 is more concerned with synergistic relationships between such systems and people, including socio-democratic and ethical considerations (Özdemir and Hekim 2018). It is suggested that Industry 5.0 will be characterised by human intelligence working in tandem with cognitive computing to produce more value-added products and goods.…”

“…Its deployment requires a socio-technical perspective in which inter-human and inter-system interactions are considered carefully in conjunction with contextual dependencies, going beyond first-order cybernetic considerations. Özdemir and Hekim (2018) point out a need for careful design in order to secure this: 'Industry 5.0 is poised to harness extreme automation and Big Data with safety, innovative technology policy, and responsible implementation science, enabled by 3D symmetry in innovation ecosystem design ' (2018, p.65).…”

Digging Deeper into Precision/Personalized Medicine: Cracking the Sugar Code, the Third Alphabet of Life, and Sociomateriality of the Cell

“…Timing is not the only consideration, however, for responsible governance of innovations. The types of methodologies we deploy to map the human values, politics, and power asymmetries related to emerging technologies also matter (Balmer et al, 2015;Lopez and Lunau, 2012;Ö zdemir and Hekim, 2018;Williams, 2006). For example, in the second half of the 20th century and after 1980s in particular, attempts for innovation governance have tended to employ conceptual frames based on technological determinism and market efficiency, focusing narrowly on specific technologies to uncritically enable their transition to products, rather than targeting grand societal challenges or wicked social problems, and with little consideration for the opportunity costs of investing in a given technology or alternative futures (Editorial, 2015;Ö zdemir and Springer, 2018).…”

The Role of Digital Connectivity in Supply Chain and Logistics Systems: A Proposed SIMPLE Framework

“…• Provide integration and real-time interaction with key SCM members: for an organization to achieve effective connectivity integration through its SCM operations, it should resort to cutting-edge technologies like blockchain to enhance realtime interaction and visibility [29,30]. • Create integration and leverage interplay between robots and humans: smart concepts are built on SCM activities only when robots and humans work in symbiosis [31]. To this effect, humans should develop their own education and skills to maximize operations with robots [32].…”