![San Jose city street](/sites/g/files/omnuum10826/files/styles/hwp_21_9__1920x825/public/2026-08/San%20Jose%20FFN%20picture.png?itok=orv5iExF) # Fellowship Field Notes: San José’s First 90 Days As part of The Responsive Cities Network, funded by the John S. and James L. Knight Foundation and led by Data-Smart City Solutions at the Bloomberg Center for Cities at Harvard Universitythis series features learnings, insights, and reflections from the three Service Innovation Fellows embedded in Boulder, Philadelphia, and San Jose. August 20, 2026 [ Ala'a Kolkaila ](/people/alaa-kolkaila) A few weeks ago, I relocated from Boston to San José -- the Capital of Silicon Valley. Almost immediately, technology became part of the backdrop of my everyday life. Food delivery robots share the sidewalks, autonomous vehicles navigate the streets, and now I find myself working just a few miles away from some of the companies building the transformational technologies that are reshaping our world. I joined the city of San José as a [Service Innovation Fellow](/responsive-cities-network "The Responsive Cities Network"), part of a new initiative funded by the [John S. and James L. Knight Foundation](https://knightfoundation.org/) and led by Data-Smart City Solutions at the Bloomberg Center for Cities at Harvard University. I work closely with the Information Technology department and the Mayor’s Office, which gives me the opportunity to work across City Hall, explore how AI and innovation can improve San José’s service delivery while ensuring that community voices are heard and their needs are addressed. ## The Work This Month Object detection is the first use case I started exploring as part of the city’s broader effort to move from a reactive to more proactive service delivery model. Through cameras equipped with AI technology, San José can identify a wide array of conditions such as potholes, graffiti, and illegal dumping before residents need to submit service requests. On the surface, the proposition seems straightforward: if the city can identify problems earlier, it can respond without placing the burden on residents to report them first. But shortly, it became evident that beneath what appeared to be a technological solution was a much broader service delivery challenge, one that touches on operational workflows, back-end integration, departmental ownership and information dissemination across the teams. Illegal dumping and junk pick-up offer an interesting example; they both look alike on camera, however they both follow different downstream service processes. Thus, it is essential to think through how a detection is interpreted, routed, and ultimately translated into the right service request. Beyond these operational questions lie an even more fundamental one: how can the city ensure that what it chooses to detect reflects the community’s need? For example, potholes may be a priority in one neighborhood while illegal dumping may have a much greater impact somewhere else. Other communities may identify concerns that are not among the first conditions the city prioritized their detection, potentially undermining the very purpose of proactive identification. To better understand that question, I began by examining the historical trends of service requests on San José 311 portal. The data shows us where residents are reporting problems. However, this does not necessarily tell us where all the problems are occurring. Reporting generally depends on someone noticing the issue, knowing how to report it and deciding to take the time to do so. This distinction becomes particularly important when thinking about proactive service delivery, as some community needs may be underrepresented or entirely absent from complaint-driven data. ## What I Found: That realization pushed the work beyond data analysis and into community engagement. If proactive service delivery is meant to reduce the burden on residents, it should not reduce their role inshaping what the city pays attention to. This is now shaping a broader citywide engagement plan focused on understanding community needs, how residents prioritize the different services object detection can support, and what additional conditions they would value having identified earlier. For instance, during the city’s recent Responsive Cities Network Kickoff, residents highlighted uneven sidewalks, bike-lane obstructions, and overgrown vegetation as issues where earlier detection could make a meaningful difference. These conversations are helping broaden the scope of the work from what technology is currently capable of detecting to what residents themselves believe would improve their neighborhoods and their experience of city services. ## Reflections and Road Forward: That experience reinforced a broader lesson for me. Cities are often eager to adopt emerging tools, demonstrate innovation, and position themselves as [testbeds for new](https://unhabitat.org/sites/default/files/2021/11/centering_people_in_smart_cities.pdf) [technologies](https://unhabitat.org/sites/default/files/2021/11/centering_people_in_smart_cities.pdf), sometimes before fully examining their social, operational, or distributive consequences. In San José, where new technologies and potential partners are constantly within reach, that tension is especially visible. Grounding [the work with a problem-first](https://datasmart.hks.harvard.edu/rethinking-gov-2026) [approach](https://datasmart.hks.harvard.edu/rethinking-gov-2026), helps ensure that technology responds to a clearly defined challenge; this is where true innovation begins. In the first 90 days of my journey with the city of San José, I came to appreciate that proactive government requires a different posture, not just a different tool. This has reinforced for me the importance of understanding the need, the context, and the challenge of the service before deciding where technology can genuinely add value. As I move forward, I am asking myself: - What does it actually take to move from proactive detection to proactive service delivery? - How can community priorities shape what the city chooses to detect rather than only reacting to what technology already makes possible? - Where can AI remove friction for residents and staff, and where are the underlying problems really about process, data, or organizational design? - How can we communicate to our residents the services we are proactively detecting? - How can we create feedback loops that tell us not only whether an issue was detected and closed, but whether residents experienced a meaningful improvement? - And where can connecting departments create as much value as deploying new technology? ## About the Author ### Ala'a Kolkaila ![Ala'a Kolkaila headshot](/sites/g/files/omnuum10826/files/styles/hwp_1_1__100x100_scale/public/2026-06/headshot_AK.jpeg?itok=C-_42RKu) Ala'a Kolkaila (she/her) is a Service Innovation Fellow at the Bloomberg Center for Cities at Harvard University, where she works within the Office of the Mayor in San José to shape how artificial intelligence is applied across city operations and public services. A strategic advisor and economist with over a decade of experience, she has built a career at the intersection of public policy, digital transformation, and economic development. Ala'a earned her Master in Public Administration from Harvard Kennedy School in 2024 as a Mason Fellow, followed by an MBA from MIT Sloan School of Management in 2025 as a Sloan Fellow. During that time, she also served as a Fellow at Harvard's Belfer Center, where she advanced research on emerging technology, and cryptocurrency , and as a Millennium Leadership Fellow at the Atlantic Council. See also:- [ Artificial Intelligence ](/topics/artificial-intelligence) - [ Civic Engagement ](/topics/civic-engagement) - [ Human-Centered Design ](/topics/human-centered-design) - [ Innovation ](/topics/innovation) - [ Operations ](/topics/operations) - [ Performance Measurement ](/topics/performance-measurement) Share on:- [ Facebook ](#) - [ Twitter ](#) - [ Linkedin ](#)