Anti-Eviction Mapping Project

The Anti-Eviction Mapping Project (AEMP) is a San Francisco Bay Area–based data-visualization, critical-cartography, and multimedia-storytelling collective documenting dispossession and resistance upon gentrifying landscapes. Founded in 2013 by Erin McElroy, Manon Vergerio, and Sam Raby at the height of San Francisco's tech-boom displacement wave, AEMP operates as an all-volunteer collective with fiscal sponsorship through Independent Arts & Media and has since expanded to chapters in Los Angeles and New York City. Its primary contribution to the make-AI-good corpus is the Landlord Tech Watch — a sustained research programme tracking the deployment of property technology (proptech) against tenants: facial-recognition door systems, biometric building access, algorithmic rent-setting software, and AI-driven tenant-screening services.

Founding and structure

AEMP emerged from San Francisco's second tech boom, a period in which Ellis Act no-fault evictions, Airbnb-driven short-term-rental conversion, and speculative acquisition by institutional landlords rapidly displaced long-term low-income tenants, disproportionately Black and Latino households. McElroy holds a Feminist Studies doctorate from UC Santa Cruz; Vergerio came from tenant organising in Brooklyn and San Francisco; Raby brought cartography and data-science expertise. The founding coalition partnered with the San Francisco Tenants Union and the direct-action collective Eviction Free San Francisco, grounding the data work inside active organising campaigns from the outset.

AEMP operates as an all-volunteer, non-hierarchical collective through Independent Arts & Media fiscal sponsorship rather than as a free-standing nonprofit — structurally analogous to Detroit Community Technology Project's Allied Media Projects arrangement — drawing on institutional back-office capacity while preserving collective decision-making. A New York City chapter was established in August 2017; a Los Angeles chapter followed.

Mapping, oral history, and EvictorBook

AEMP's four output modes — digital mapping and software tools, narrative multimedia and oral history, research reports, and murals and public events — each orient housing-displacement data toward on-the-ground organising. The Narratives of Displacement and Resistance oral-history initiative documents displaced tenants' experiences in their own voices, attaching life histories to eviction-address point data so the maps carry human texture alongside statistical pattern. The more recent (Dis)location: Black Exodus project, supported by a 2022–23 California Arts Council grant, extends this methodology to the documented displacement of Black San Franciscans, combining oral histories, creative cartography, archival materials, and art.

EvictorBook is an interactive database linking landlord names and building addresses to eviction histories, consolidating publicly available but deliberately fragmented assessor, property-ownership, and unlawful-detainer records. Its analytical move is the exposure of corporate-landlord networks that obscure ownership through multiple limited-liability-company shell structures: a single investor group operating dozens of properties becomes legible as a network at the database level. The NYC chapter's Worst Evictors project builds on the same approach using Right to Counsel coalition and JustFix.nyc data.

Landlord tech and AI-in-housing work

AEMP's most direct contribution to the make-AI-good movement is its sustained documentation of property technology — AI and algorithmic systems embedded in the landlord-tenant relationship. The collective defines landlord tech as technology that increases the power of landlords while disempowering tenants and those seeking shelter: facial-recognition entry systems tracking tenant movement and visitors; predictive algorithms generating automated eviction notices; algorithmic rent-setting software coordinating pricing across large institutional portfolios; and tenant-screening data services that bar applicants with past eviction records.

The Landlord Tech Watch, directed by McElroy at the University of Washington through the Anti-Eviction Lab with AEMP as a partner organisation, combines a crowdsourced tenant-reporting map with academic research and community workshops. In 2022, AEMP and the AI Now Institute co-produced Landlord Technologies of Gentrification: Facial Recognition and Building Access Technologies in New York City Homes — documenting how biometric "digital doorman" facial-recognition systems were installed in majority-tenant-of-colour buildings under a safety framing while disproportionately misidentifying tenants of colour and functioning as a gentrification accelerant. The 2023 San Francisco Landlord Tech Report extended the methodology to the Bay Area market.

Place in the movement

AEMP is the corpus's first entity anchoring the landlord-tech accountability strand of the make-AI-good movement — the organised tenant-side response to AI deployment inside residential housing. Where Oakland Privacy works the municipal-ordinance path and the Stop LAPD Spying Coalition works the policing-and-surveillance path, AEMP operates in the housing-and-property lane, where much of the day-to-day AI deployment affecting low-income urban communities occurs but where dedicated civil-society infrastructure is comparatively thin. Its counter-cartography methodology — and the philosophy of tools produced with rather than about communities — constitutes a distinct approach among corpus entities doing AI-adjacent data and mapping work.