AI for Scaling Legal Reform: Mapping and Redacting Racial Covenants in Santa Clara County

Faiz Surani*, Mirac Suzgun*, Vyoma Raman, Christopher D. Manning, Peter Henderson, Daniel E. Ho
Stanford University · Princeton University
*Equal Contribution · Corresponding Author: deho [at] stanford [dot] edu

Warning: This website contains offensive racial terms from historical deed documents.

Example of a racial covenant document

Abstract

Legal reform can be challenging in light of the volume, complexity, and interdependence of laws, codes, and records. One salient example of this challenge is the effort to restrict and remove racially restrictive covenants, clauses in property deeds that historically barred individuals of specific races from purchasing homes. Despite the Supreme Court holding such racial covenants unenforceable in 1948, they persist in property records across the United States. Many jurisdictions have moved to identify and strike these provisions, including California, which mandated in 2021 that all counties implement such a process. Yet the scale can be overwhelming, with Santa Clara County (SCC) alone having over 24 million property deed documents, making purely manual review infeasible. We present a novel approach to addressing this pressing issue, developed through a partnership with the SCC Clerk-Recorder's Office. First, we leverage an open large language model, fine-tuned to detect racial covenants with high precision and recall. We estimate that this system reduces manual efforts by 86,500 person hours and costs less than 2% of the cost for a comparable off-the-shelf closed model. Second, we illustrate the County's integration of this model into responsible operational practice, including legal review and the creation of a historical registry, and release our model to assist the hundreds of jurisdictions engaged in similar efforts. Finally, our results reveal distinct periods of utilization of racial covenants, sharp geographic clustering, and the disproportionate role of a small number of developers in maintaining housing discrimination. We estimate that by 1950, one in four properties across the County were subject to racial covenants.

Findings

Figure 7: Clusters of racial covenants on an interactive map of modern-day Santa Clara County. Some of the largest and most notable racially restricted developments are shown in red. Dots represent individual subdivisions and are scaled in proportion to the number of racial covenants within the subdivision. You can also explore a map which counts the number of lots covered by racial covenants here.

Distribution of racial covenants over time Distribution of racial covenants over time

Figure 8: Top: Number of property deeds with restrictive covenants from 1905--1974, divided by whether specific racial groups were excluded or only white/Caucasian individuals were permitted. Most pre-1915 covenants specifically exclude Black and Asian individuals, but the vast majority of later covenants are white-only. The small number of restrictive covenants matched after 1970 consists largely of older deeds filed for reference, rather than new restrictive covenants being introduced. Bottom: The number of occurrences of specific racial groups in covenants that exclude specific groups. East Asian and Black were by far the most commonly excluded demographics, but some covenants targeted other groups, such as Italian, Portuguese, Indian, and Mexican individuals.

Acknowledgments

We thank Nikita Bhardwaj and Helen Gu for research assistance; Gina Alcomendras, Louis Chiaramonte, Robert Fannion, Greta Hansen, Margaret Pula, Anthony Serafica, and Genevieve Singh-Hanzlick for the collaboration; Ananya Karthik and Allison Casasola for labeling assistance; and Greg Ablavsky, Michael Corey, Kirsten Delegard, Sarah DeMott, Dan Jurafsky, Gideon Lichfield, Varun Magesh, Erin Maneri, Derek Ouyang, Claire Lazar Reich, Kit Rodolfa, Kyle Swanson, and Andrea Vallebueno for helpful feedback and comments.

For other commendable efforts to map racial covenants, see the National Covenants Research Coalition.

BibTeX

@article{suranisuzgun2024,
  title={AI for Scaling Legal Reform: Mapping and Redacting Racial Covenants in Santa Clara County},
  author={Surani, Faiz and Suzgun, Mirac and Raman, Vyoma and Manning, Christopher D. and Henderson, Peter and Ho, Daniel E.},
  journal={Stanford RegLab Working Paper},
  year={2024}
  url={https://dho.stanford.edu/wp-content/uploads/Covenants.pdf}
}