Article by Bloomberg Cities Network: “…The following three lessons from Ho’s work offer practical guidance for local leaders interested in realizing this potential.
Inserting AI at key moments to unlock action.
Most city leaders already know about the more common applications of AI. But Ho argues that being more ambitious with the technology doesn’t always mean developing a new “end-to-end solution,” as he describes them. In fact, sometimes, local leaders can achieve massive impact when they insert the technology in a strategic way at a critical point in a complex workflow. And that, in turn, can create space for civil servants to deliver what people need.
For example, as part of a partnership with California’s Santa Clara County, Ho and his team at Stanford RegLab adapted a large language model so it could quickly parse through millions of records. The objective? Identifying property deeds containing discriminatory language that was intended, decades ago, to limit who could purchase certain homes. Doing so manually could consume nearly 10 years of staff time. The new tool did an initial analysis with near-perfect accuracy in just a few days. And while that work still calls for human review, the lesson for Ho is that this sort of approach can help ensure civil servants aren’t so consumed with bureaucracy that they are unavailable for frontline service delivery.
“If you are expending your time on these internal tasks, there are other services that necessarily have to take a hit,” Ho explains. Instead, tools such as this one can help ensure local leaders have capacity to maintain adequate staffing at frontline service counters that provide everything from birth certificates to public benefits.
Creating space for human discretion.
Ho cautions against relying on AI to independently manage some of local government’s most sensitive responsibilities, public benefits chief among them. But even in these complex areas, he argues, AI can play a valuable supporting role by streamlining delivery workflows and freeing up civil servants to focus on the human side of service….
Triggering conversations about how to improve policies.
Ho’s work isn’t only showing how cities can free teams from red-tape tasks. It’s also demonstrating how cities can get to the root of those problems: by improving over-complicated policies and programs for the long term.
As part of his team’s collaboration focused on San Francisco’s municipal code, the city has been using a search system developed by RegLab to identify every case where legislation requires agency personnel to produce potentially time-consuming reports. Some of the findings would be comical if they weren’t in danger of using precious capacity, such as the rule calling for regular updates on the state of city newspaper racks that no longer exist…(More)”
