Designing Socio-Technical Systems for Collaboration: Trends and Future Implications of Mathematics

Dear Colleagues,

This Special Issue is to provide a platform to discuss implications of socio-technical collaboration. This kind of system has become increasingly prevalent due to the ongoing advancements in technology, especially artificial intelligence and machine learning. Additionally, the focus of automation has shifted progressively from replacing humans to complementing them. This new vision stretches the very concept of collaboration in many ways, and research in new paradigms, methods, and tools seems to offer broader implications to understand and promises a huge impact in the future.

Browsing through the most recent literature on this topic, we have found a lot of unanswered questions that can be categorized into the following lines of research:

Task allocation: models, algorithms, and approaches to find the right level of workload for workers and to exploit advantages from both machines and humans;

Human performance improvement: models, algorithms, and approaches to avoid human error coming with socio-technical systems (complacency or human bias, out-of-the loop, etc.);

Social challenges: models, algorithms, and approaches to improve social interaction between humans and machines and to measure/evaluate the impacts of individual factors (such as trust, acceptance, usability) on human performance;

Safety issues: models, algorithms, and approaches to ensure the best level of safety for humans collaborating with machines.

Dr. Maria Elena Nenni
Dr. Valentina Di Pasquale
Dr. Raffaele Iannone
Guest Editors

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• managing the human factors in socio-technical systems
• implementing safety issues in socio-technical systems
• data science for socio-technical systems
• simulation and mathematical modelling of socio-technical systems
• formalization and applications of domain knowledge
• decision making
• machine learning techniques for socio-technical systems
• artificial intelligence applications for socio-technical systems
• empirical studies conducted in socio-technical systems using quantitative, qualitative and mixed methods