Daniel Greene
Associate Professor, College of Information
University of Maryland
Daniel Greene is an associate professor in the College of Information at the University of Maryland. His ethnographic, historical, and theoretical research explores how the future of work is built and who is included in and excluded from that future. His first book, The Promise of Access: Technology, Inequality, and the Political Economy of Hope, was published by MIT Press in 2021. It received the McGannon Prize for the best book of the year on media and activism.
Area of Expertise: Technology and Work
-
Greene, D. (2022). Landlords of the internet: Big data and big real estate. Social Studies of Science, 52(6), 904-927.
Who owns the internet? It depends where you look. The physical assets at the core of the internet, the warehouses that store the cloud’s data and interlink global networks, are owned not by technology firms like Google and Facebook but by commercial real estate barons who compete with malls and property storage empires. Granted an empire by the US at the moment of the internet’s commercialization, these internet landlords shaped how the network of networks that we call the internet physically connects, and how personal and business data is stored and transmitted. Under their governance, internet exchanges, colocation facilities, and data centers take on a double life as financialized real estate assets that circle the globe even as their servers and cables are firmly rooted in place. The history of internet landlords forces a fundamental reconsideration of the business model at the base of the internet. This history makes clear that the internet was never an exogenous shock to capitalist social relations, but rather a touchstone example of an economic system increasingly ruled by asset owners like landlords.
Full Article -
Greene, D., & Mawii, Z. (2025). Gigs North and South. Social Media + Society, 11(2).
This commentary investigates platformization in global south and global north labor markets, arguing they are linked via a process of uneven and combined development. Focusing on platformization in India and the United States, we briefly describe long-standing patterns of formal and informal labor in the United States and India, which prepare the ground for the 21st-century explosion of gig platforms. We conclude by returning to the global scale of uneven and combined development, drawing on contemporary Indian Marxists to explain the global spread of gig platforms post-2008 as a global financial response to the political problem of surplus workers within premature deindustrialization.
Full Article -
Greene, D. (2021). The promise of access: Technology, inequality, and the political economy of hope. mit press.
Abstract: Why do we keep trying to solve poverty with technology? What makes us feel that we need to learn to code--or else? In The Promise of Access, Daniel Greene argues that the problem of poverty became a problem of technology in order to manage the contradictions of a changing economy. Greene shows how the digital divide emerged as a policy problem and why simple technological solutions to complex social issues continue to appeal to politicians and professionals who should (and often do) know better.
Full Book -
Stark, L., Greene, D., Hoffmann, A.L. (2021). Critical Perspectives on Governance Mechanisms for AI/ML Systems. In: Roberge, J., Castelle, M. (eds) The Cultural Life of Machine Learning. Palgrave Macmillan, Cham.
Abstract: This chapter provides a critical overview of proposed mechanisms for the ethical design and governance of contemporary artificial intelligence (AI) and machine learning (ML) systems. We describe various proposed mechanisms for AI/ML governance, paying particular attention to the possibilities and limits of these mechanisms for realizing truly just and equitable societal outcomes. In doing so we argue each category of intervention has reinforced and supported the broader regimes of corporate and state power under which AI/ML technologies are being developed, and that reformist initiatives relying on these mechanism risk cooptation and failure. We conclude by highlighting the abolitionist approach to AI-driven surveillance technology taken by the Movement for Black Lives and the workplace democracy approach taken by the #TechWontBuildIt technology workers campaign as alternative paradigms for AI/ML governance.