Disruptive, Infrastructural, and Speculative: Rental Housing in Berlin under Post-Platform Urbanism

• Applicant: Dr. Niloufar Vadiati, Ph.D.
• Subject Area: Human Geography ; Methods in Artificial Intelligence and Machine Learning ; City Planning, Spatial Planning, Transportation and Infrastructure Planning, Landscape Planning
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 573963572

This proposal sets out a three-year research plan to investigate how digital housing platforms are reshaping Berlin’s rental housing sector through three interrelated dynamics: disruption, infrastructure, and speculation. These dimensions are examined under the conceptual lens of “Post-Platform Urbanism,” which captures the evolving role of digital platforms as they move beyond basic, user-driven tools toward increasingly automated, AI-powered systems. In this context, digital housing platforms are no longer neutral intermediaries; they function as active agents in shaping how urban residents access, navigate, and experience housing. The project focuses on platforms such as ImmoScout24, Wunderflats, and Nestpick—each of which integrates algorithmic features that mediate access to housing through automated search matching, pricing, filtering, and recommendation systems. These technological systems contribute not only to the optimisation of rental processes but also to the reconfiguration of social relations, housing markets, and urban space. As digital infrastructures, they influence who gets to live where, under what conditions, and at what cost—often bypassing traditional forms of regulation, including rent caps and tenancy protections. In a city like Berlin, where housing remains a contentious political and social issue, these changes raise urgent questions about inequality, accessibility, and algorithmic governance. The project develops a conceptual framework that draws on platform studies, urban theory, digital geography, and urban ethnography to analyse how post-platforms operate simultaneously as disruptive market forces, as infrastructures embedded in daily life, and as speculative systems shaping future urban living. Methodologically, the research employs a mixed-methods approach. This includes algorithmic audits (e.g., content analysis, expert interviews, and “black-box” testing of platform behaviours), spatial data analysis using public and scraped platform datasets, and ethnographic fieldwork involving interviews with tenants, platform users, and housing activists. The aim is to produce a multi-scalar and empirically grounded account of how AI- and ML-powered housing platforms mediate access to urban space, reshape tenant experiences, and influence the organisation of housing markets in Berlin. The research contributes to urban and digital geography by theorising housing platforms not merely as tools of market efficiency but as socio-technical infrastructures with political, spatial, and economic agency. In doing so, the project addresses a growing gap in scholarship on digital platforms in urban contexts and supports the development of critical methodologies to study automation, algorithmic governance, and platform-mediated inequalities in housing.

• DFG Programme: Research Grants