Rethinking algorithmic regulation

Purpose – The history of cybernetics holds important lessons for how we approach present-day problems in such areas as algorithmic regulation and big data. The purpose of this paper is to position Project Cybersyn as a historical form of algorithmic regulation and use this historical case study as a thought experiment for thinking about ways to improve discussions of algorithmic regulation and big data today. Design/methodology/approach – The paper draws from the author’s extensive research on Cybersyn’s history to build an argument for how cybernetic history can enrich current discussions on algorithmic regulation and the use of big data for governance. Findings – The paper identifies five lessons from the Cybersyn history that point to current data challenges and suggests a way forward. These lessons are: first, the state matters; second, older technologies have value; third, privacy protection prevents abuse and preserves human freedom; fourth, algorithmic transparency is important; and finally, thinking in terms of socio-technical systems instead of technology fixes results in better uses of technology. Research limitations/implications – Project Cybersyn was a computer network built by the socialist government of Salvador Allende under the supervision of the British cybernetician Stafford Beer. It formed part of the government’s program for economic nationalization. Work on the project ended when a military coup brought the Allende government to an early end on September 11, 1973. Since we do not know how the system would have functioned in the long term, parts of the argument are necessarily speculative. Practical implications – The paper uses Cybersyn’s history to suggest ways that the Chilean experience with cybernetic thinking might enhance, improve, and highlight shortcomings in current discussions of algorithmic regulation. Originality/value – The paper provides an original argument that connects one of the most ambitious cybernetic projects in history to present day technological challenges in the area of algorithmic regulation.