Abstract
More than 100 years ago, Robert Michels (1911) observed that even organizations based on the strongest democratic principles tend to devolve into oligarchy. Leaders will use their authority to serve their own interests, they will cultivate loyalty with a small clique of elites, and they will subvert the mission of the organization. This corruption from the top arises due to the seemingly inescapable concentration of organizational power, hierarchy, and asymmetries in the capacity to monitor and sanction. During the intervening century the widespread misuse of authority across diverse formal organizations has largely proven Michel correct. However, we are no longer limited by the organizational systems of the nineteenth century nor by constraints of face-to-face interaction. Partial examples of alternative organizational structures can be identified among effective contemporary firms, online communities, and large scale collaborative projects. This chapter describes the organizational challenge in terms of the principal-agent problem and identifies the set of attributes necessary for distributed social control in computational institutions. This set of attributes forms an ideal type for identifying problems inherent in extant organizations and for identifying features that can be integrated from current online systems of interaction. In conclusion, this chapter advocates for researchers and designers to propose, develop, and to implement systems that will allow organizations to break the iron law of oligarchy.
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Notes
- 1.
Corruption is sometimes used in a more limited sense where it is applied either to agents of the state, for instance, “using public office for personal gain” (Shah and Huther 2002) or actions of firms as they relate to the state, such as businesses agents bribing state officials to further the interests of their firm.
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Welser, H. (2015). Breaking the Iron Law of Oligarchy: Computational Institutions, Organizational Fidelity, and Distributed Social Control. In: Bertino, E., Matei, S. (eds) Roles, Trust, and Reputation in Social Media Knowledge Markets. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-05467-4_8
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