The Institutional Limits of Technical Convergence: Real-Time Market Signals in Algorithmic Market Socialism

Digital platforms coordinate production and exchange through data, prediction and algorithms, while recent work on socialist planning combines computation with consumer feedback. This paper uses a focused conceptual review to assess how far similarities in the use of market signals and computational feedback support claims of convergence between platform capitalism and algorithmic market socialism. It compares information functions, feedback rules, allocation criteria and institutional controls, then applies this framework to a design for real-time social accounting. The comparison yields two results. First, similar data and feedback mechanisms make technical convergence and partial coordination convergence plausible, but they do not establish similar allocations or institutions. Second, social ownership does not necessarily prevent platform-like concentration if data control, objective-setting, audit and appeal remain centralised. Market signals can therefore be used only as revisable inputs alongside non-market evidence. Data and model vintages must also be preserved so that decisions can be reconstructed and challenged. The paper’s contribution is to separate four forms of convergence (technical, coordination, allocation and institutional) and to show why evidence at one level cannot be used as evidence at another.