A Storm in an IoT Cup: The Emergence of Cyber-Physical Social Machines

Abstract

The concept of 'social machines' is increasingly being used to characterise various socio-cognitive spaces on the Web. Social machines are human collectives using networked digital technology which initiate real-world processes and activities including human communication, interactions and knowledge creation. As such, they continuously emerge and fade on the Web. The relationship between humans and machines is made more complex by the adoption of Internet of Things (IoT) sensors and devices. The scale, automation, continuous sensing, and actuation capabilities of these devices add an extra dimension to the relationship between humans and machines making it difficult to understand their evolution at either the systemic or the conceptual level. This article describes these new socio-technical systems, which we term Cyber-Physical Social Machines, through different exemplars, and considers the associated challenges of security and privacy.

Artificial intelligence and machine learning in dynamic cyber risk analytics at the edge

“…This needs task-specific human machine interfaces [44], for self-aware machines and component prognostics and health management [45].…”

Design of a dynamic and self-adapting system, supported with artificial intelligence, machine learning and real-time intelligence for predictive cyber risk analytics in extreme environments – cyber risk in the colonisation of Mars

“…The development of such cognitive engine and its application, would undoubtedly bring multiple benefits and would enable deeper understanding of the impact of cyber risk at the edge. Nonetheless, IoT networks represent complex coupled systems (D. De Roure et al 2019), that can be described as cyber-physical social machines (Madaan et al 2018) and social machines (David De Roure et al 2015) should be observed in practice (Shadbolt et al 2019). Given that IoT is considered as critical enabler (Lee et al 2019a) of value creation (Lee et al 2019b), the findings of this study would probably be best verified when observed in practice.…”

Artificial Intelligence, Machine Learning and Real-time Probabilistic Data for Cyber Risk (Super) -forecasting: Red Teaming the Connected World (RETCON)

“…However, the AI/ML infrastructure in the communications network and the relevant cyber security technology must evolve in an ethical manner that humans can understand, while maintaining maximum trust and privacy of the users. IoT networks represent complex coupled systems [40], that can be described as cyber-physical social machines [41] and social machines [42] should be observed in practice [43]. Given that IoT is considered as critical enabler [44] of value creation [45], the findings of this study would probably be best verified when observed in practice.…”