Igor Perko
Faculty of Economics and Business, University of Maribor, Slovenia
Biography
Igor Perko is an Associate Professor at the Faculty of Economics and Business, University of Maribor, Slovenia, and Co-Director General of the World Organisation of Systems and Cybernetics (WOSC). His early academic and professional work focused on the design and implementation of business intelligence, predictive analytics, and risk management systems, particularly in financial contexts. This work addressed decision support, default prediction, information asymmetry, and data sharing in inter-organisational environments. His research evolved toward systems thinking and cybernetics, integrating multimedia, collective intelligence, and Hybrid Reality into a coherent CyberSystemic perspective. Within this framework, he investigates how socio-technical systems operate across physical, digital, and artificial domains, with particular attention to ethics, governance, and social responsibility. His current research concentrates on interactions as the primary unit of analysis, advancing interaction observation as a CyberSystemic methodology for analysing complex systems, including AI-supported learning, organisational decision-making, and academic publishing. He has authored and edited numerous journal articles, monographs, special issues, and edited volumes in the fields of systems science, cybernetics, information systems, and social responsibility.
Sessions
CyberSystemic Model Creation Protocol: AI-energy-climate-health governance case
This paper proposes the CyberSystemic Model Creation Protocol as a methodological approach for developing governance-oriented models in multi-domain transformation problems. It addresses situations in which technological, social, ecological, institutional, economic, and ethical issues interact and require traceable, revisable, and accountable governance support. A recursive six-phase protocol consisting of governance problem framing, model requirements extraction, interaction-interface specification, methodology allocation, model construction, and conceptual evaluation is proposed. The first three phases are elaborated and illustrated through the case of AI-energy-climate-health governance. The case examines AI both as a governed system that increases electricity, cooling, water, grid, investment, and regulatory pressure, and as a governance-supporting system for forecasting, coordination, scenario inquiry, and decision support. Findings: The illustrative application shows how a broad governance problem can be translated into a governance frame, governance goals, model requirements, and interaction-interface specifications. The interaction-interface phase uses the five viable-system model functions to identify interfaces for operations, coordination, control, intelligence, and policy. Each interface is linked to a required body of knowledge and to a knowledge-status assessment that distinguishes available, partial, weak, assumed, missing, and contested knowledge. The protocol contributes a methodological pathway from observing system properties toward designing governance-supporting CyberSystemic models. It helps avoid false holism by identifying knowledge gaps, weak evidence, assumptions, and contested areas visible before model construction. The paper is conceptual and illustrative. Further research should elaborate, implement, and validate the later protocol phases in empirical governance settings, especially methodology allocation, model construction, and conceptual evaluation across cases and contexts.