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Social Connectivity

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Emerging Technological Risk

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Abstract

Social accounts of technological artefacts and their adoptions by communities of practice highlight the mechanisms of shaping technology. On one hand, looking at classifications and information systems explain how communities of practice identify themselves with adopted technological artefacts. On the other hand, people shape technological artefacts and drive technology evolution , hence technology innovation . However, it is therefore necessary to unveil the mechanisms that make us behave not only just as individuals, but also as societies. Technology has a pivotal role in connecting individuals. It is necessary to move the analysis from the micro, i.e. understanding how individuals or social actors behave with respect to technology, to the macro, i.e. understanding how societies or social groups behave with respect to technology.

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Notes

  1. 1.

    The SHEL model has been adopted in various domains though originally drawn from Avionics and Air Traffic Control (ATC) . The guidelines in [6], for instance, take it as a fundamental conceptual model of human factors . The SHEL model defines any (electronic mediated) productive process performed by a combination of hardware (e.g. any material tool used in the process execution), software (e.g. procedures, rules, practices) and liveware (e.g. end-users, managers) resources embedded in a given environment (e.g. socio-cultural, political). Hence, any productive process may be regarded as an instantiation of the SHEL model for a specific process execution. The SHEL model emphasises that any productive process relies on the different resources, distributed cognition and resource-based modelling. These different aspects of socio-technical systems can be linked together in a sound way [31] . Cognition models, moreover, allow the analysis of dangerous conditions or technology interactions [3] . For instance, simple models representing human understandings with respect to socio-technical systems have stimulated the use of mechanised verification methods in order to identify “automation surprises” [27] . The results encourage further investigations of the use of mechanised tools in order to identify inconsistencies into the design of technology interactions.

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Authors and Affiliations

  1. School of Informatics, The University of Edinburgh, Crichton Street 10, EH8 9AB, Edinburgh, UK

    Stuart Anderson & Massimo Felici

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  1. Stuart Anderson
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  2. Massimo Felici
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Correspondence to Massimo Felici .

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© 2012 Springer-Verlag London Limited

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Anderson, S., Felici, M. (2012). Social Connectivity . In: Emerging Technological Risk. Springer, London. https://doi.org/10.1007/978-1-4471-2143-5_4

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  • DOI: https://doi.org/10.1007/978-1-4471-2143-5_4

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