Stanford researchers map ‘White-Only’ properties using AI

Racially restrictive covenants are clauses in property deeds that ban individuals of a particular race from buying a home.

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( ) — Researchers at Stanford University and Princeton University have teamed up with the County of Santa Clara to attempt to map and redact racial covenants around the county by using artificial intelligence. Racially restrictive covenants are clauses in property deeds that ban individuals of a particular race from buying a home. Despite the U.

S. Supreme Court setting laws barring racial covenants, researchers say they persist in national property records. When Dan Ho purchased a home in Palo Alto, he recounts, “We had to sign papers that said that the ‘property shall not be used or occupied by any person of African, Japanese or Chinese or any Mongolian descent,’ except for the capacity of a servant to a Caucasian person.



” “It was a stunning testament to housing discrimination in the area, and it’s been constitutionally unenforceable since 1948,” said Ho, the William Benjamin Scott and Luna M. Scott Professor of Law, Director of RegLab, and Senior Fellow at Stanford University HAI. Study In 2021, California mandated that all counties should implement to identify and strike these provisions.

According to the SCC Clerk Record’s Office, however, Santa Clara County has over 24 million property deed documents, making manual review of these documents unfeasible. “Prior to this collaboration, our team manually read close to 100,000 pages over weeks to identify racial covenants,” Assistant County Clerk-Recorder Louis Chiaramonte said, “and it was a challenging undertaking.” In partnership with the SCC Clerk Recorder’s Office, researchers created an “open large language model” to detect racially restrictive covenants around the county.

Researchers estimate that this language model system “reduces manual efforts by 86,500 person-hours," which they believe would cost “less than 2% of the cost for a comparable off-the-shelf closed model.” Once the model detects a racial covenant through language, it then illustrates the logs on a map, including a legal review of the history of when the document was created. Results Results show a “distinct period” of the use of racial covenants and geographic clustering.

“We estimate that by 1950, properties across the County were subject to racial covenants,” researchers said. The map above shows the clusters of racial covenants around Santa Clara County. Some of the largest and most notable racially restricted developments are shown in red, with dots representing smaller subdivisions.

The interactive version of the map can be found . According to the figure shown above, the largest groups facing racial discrimination were “by far” Black and East Asian populations, with “Other Asian” groups coming in third, researchers said. Latino and European populations experienced the least racial discrimination.

Despite a large number of covenants barring particular races, research shows that the largest type of property deed with restrictive covenants was “White-Only” properties, mainly distributed throughout the 1920s. Some covenants targeted other groups, such as Italian, Portuguese, Indian, and Mexican individuals, researchers said. Moving Forward “The County of Santa Clara has been proactively going through millions of documents to remove discriminatory language from property records,” said Chief Operating Officer Greta Hansen.

“We’re grateful for our partnership with Stanford, which has helped the County substantially expedite this process, saving tax-payer dollars and staff time.” Researchers said they have hopes of joining other jurisdictions attempting to do the same thing. Other efforts mapping racial covenants can be found .

The study itself can be found . To remove this article -.