Datalism and Data Monopolies in the Era of A.I.: A Research Agenda
The increasing use of data in various parts of the economic and social systems is creating a new form of monopoly: data monopolies. We illustrate that the companies using these strategies, Datalists, are challenging the existing definitions used within Monopoly Capital Theory (MCT). Datalists are pursuing a different type of monopoly control than traditional multinational corporations. They are pursuing monopolistic control over data to feed their productive processes, increasingly controlled by algorithms and Artificial Intelligence (AI). These productive processes use information about humans and the creative outputs of humans as the inputs but do not classify those humans as employees, so they are not paid or credited for their labour. This paper provides an overview of this evolution and its impact on monopoly theory. It concludes with an outline for a research agenda for economics in this space.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Measuring the Volatility of the Political agenda in Public Opinion and News Media
Recent election surprises, regime changes, and political shocks indicate that political agendas have become more fast-moving and volatile. The ability to measure the complex dynamics of agenda change and capture the natu…
Aggregating Credences into Beliefs: Agenda Conditions for Impossibility Results
Binarizing belief aggregation addresses how to rationally aggregate individual probabilistic beliefs into collective binary beliefs. Similar to the development of judgment aggregation theory, formulating axiomatic requir…
BinarizationNegationTopic Is Not Agenda: A Citation-Community Audit of Text Embeddings
Vector search and retrieval-augmented generation (RAG) rest on the assumption that cosine similarity between text embeddings reflects conceptual relatedness. We measure where this assumption breaks. We build an augmented…
A Meta-Learning Algorithm for Interrogative Agendas
Explainability is a key challenge and a major research theme in AI research for developing intelligent systems that are capable of working with humans more effectively. An obvious choice in developing explainable intelli…
Meta-LearningOutlier DetectionA Research Agenda on Agents and Software Engineering: Outcomes from the Rio A2SE Seminar
The rise of agentic AI is reshaping software engineering in two intertwined directions: agents are increasingly applied to support software engineering tasks, and Agentic AI systems themselves are complex systems that re…