Lang and other experts said they look forward to seeing the results and that they expect the system to be a work in progress.
"Hats off for trying new stuff," said Phillip Atiba Goff, president for the Center for Policing Equity. "There are so many contextual factors that might indicate race and ethnicity that it's hard to imagine how even a human could take that all out."
A 2017 study commissioned by the San Francisco district attorney found "substantial racial and ethnic disparities in criminal justice outcomes." African Americans represented only 6% of the county's population but accounted for 41% of arrests between 2008 and 2014.
The study found "little evidence of overt bias against any one race or ethnic group" among prosecutors who process criminal offenses. But Gascón said he wanted to find a way to help eliminate an implicit bias that could be triggered by a suspect's race, an ethnic-sounding name or a crime-ridden neighborhood where they were arrested.
After it begins, the program will be reviewed weekly, said Maria McKee, the DA's director of analytics and research.
The move comes after San Francisco last month became the first U.S. city to ban the use of facial recognition by police and other city agencies. The decision reflected a growing backlash against AI technology as cities seek to regulate surveillance by municipal agencies.
KQED's Monica Samayoa contributed reporting to this story