This chapter presents a conceptual model of a stigmergic information system network for social sustainability data. It recognizes the omnipresence of technology in contemporary society and acknowledges the dynamic landscape of society. The interaction between humans and systems can be harmonized, leveraging collective intelligence to foster social sustainability. The Conceptual Model for a Stigmergic Information System Network for Social Sustainability proposes a structure that unifies and leverages social sustainability data from diverse societal activities to support alleviating social problems by design. This base model considers predictive, corrective, and retrospective analytics with system dynamic feedback loops applied against control module parameters to act as systemic thermostats for social stability, reduce perception bias, and monitor exploitative effects. The distributed architecture operates with self-organizing communication micro-processes. It introduces the capacity for increased transparency, data comparability, and social information sharing. The intended audience includes academics, business managers, policymakers, computer scientists, and sustainability practitioners, indicating the proposed concepts’ diverse applicability and relevance.

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From Concepts to Coherence: Modeling Social Impact Data for Societal Systemic Alignment

  • Carol Aebi

摘要

This chapter presents a conceptual model of a stigmergic information system network for social sustainability data. It recognizes the omnipresence of technology in contemporary society and acknowledges the dynamic landscape of society. The interaction between humans and systems can be harmonized, leveraging collective intelligence to foster social sustainability. The Conceptual Model for a Stigmergic Information System Network for Social Sustainability proposes a structure that unifies and leverages social sustainability data from diverse societal activities to support alleviating social problems by design. This base model considers predictive, corrective, and retrospective analytics with system dynamic feedback loops applied against control module parameters to act as systemic thermostats for social stability, reduce perception bias, and monitor exploitative effects. The distributed architecture operates with self-organizing communication micro-processes. It introduces the capacity for increased transparency, data comparability, and social information sharing. The intended audience includes academics, business managers, policymakers, computer scientists, and sustainability practitioners, indicating the proposed concepts’ diverse applicability and relevance.