Decision Topologies in Functionally Differentiated Societies - the cases of projects and AI - [védés előtt]

Kivonat, rövid leírás

This dissertation argues that dominant organisational paradigms provide important but ultimately insufficient foundations for understanding decision-making in contemporary organisations. It shows that action-centred and actor-oriented models rest on implicit assumptions of rationality, hierarchy, and goal-directed agency. As a consequence, they fall short in explaining organisational persistence and how decision dynamics evolve in response to societal volatility. Building on Niklas Luhmann’s social systems theory, a theoretical repositioning of decision-making from individual action to systemic decision communication is proposed, redefining organisations as autonomous social systems constituted through decisions. The research situates organisations within the broader context of a functionally differentiated society, arguing that increasing societal complexity generates rising decision intensity within organisations. To cope with this pressure, organisations stabilise decision-making through structured constellations of interconnected decisions, conceptualised here as decision topologies. Two prominent contemporary decision topologies—projects and artificial intelligence (AI)—are examined in depth. Projects are theorised as differentiated decision systems that can be evaluated through a multi-dimensional project-organisation distinction, and may range from organisation-bound units to autopoietic systems with their own environmental relations. AI is conceptualised not merely as a technological tool, but as a decision topology that reshapes decision premisses, interaction systems, and organisational memory. Thus, the dissertation elaborates how these topologies are not only instrumental but also exert influence on the basic systemic process of the organisation, and through that, on the operation of organisations in society. Methodologically, the dissertation adopts a conceptual, theory-driven approach grounded in an extensive review of Luhmann’s organisational work and relevant project and AI literatures. The main contribution lies in integrating projects and AI into a unified decision-theoretical framework that explains both their stabilising functions and their systemic risks. By advancing the concept of decision topologies, the study offers a near-empirical modelling of organisational dynamics and provides a foundation for future empirical research on decision-making in complex organisational environments