How might we track complex issues in our cities without watching them?

I’ve used my JSK Fellowship to tackle a need I found in running a local news operation whose small staff was trying to cover civic issues in a large city (Bangalore). I wanted to figure out how newsrooms could systematically collaborate the community to track ongoing public issues and proceedings. I was both looking for way to arm reporters with collective wisdom on an issue ahead of the reporting process, and also an “early warning system” for civic  stories. I felt that if done well, this could lower discovery costs (more stories for the same budget), deepen and diversify storytelling and also strengthen community engagement.

Learnings and accomplishments

  • I came to the conclusion that a public-facing tracking solution that serves both journalists and active citizens will empower both groups of people. I had originally imagined that it might be better to solve the tracking problem only within local newsrooms. Building this out as a community asset accessible to both groups, emerged from interviews and discussions.
    • I also broke the problem of asynchronous tracking into parts in a business school class, using a decomposition technique. This cut down the number of moving parts and allowed focus on sub-problems. It was very helpful because it split the city civic process tracking work into 4 sub-problems:
      • Crowdsourcing documents and insights from the community around a local newsroom on specific local concerns
      • Monitoring a city’s calendar events
      • Monitoring a city’s open documents
      • Monitoring a city’s open data sets

Tracking slide

  • I discovered some data journalism and civic tech groups that were already working on the sub-problems of a similar nature. In principle those code modules are open source and can be leveraged for a new prototype to integrate multiple functionalities into one system. I am familiar with how to do this due to my software engineering background.
  • My choice of analogy — ‘radar screen’ — does transfer to the city sphere. It translated to the idea of a ‘civic radar screen’.

Flightradar24 is a website powered by amateur aviation enthusiasts that tracks most planes in the sky above any city or region worldwide. You can log in, and type a city name and see the planes above your rooftop on the screen, with flight path, make and model, takeoff, landing and more. It is crowdsourced and data driven.

Imagine a civic process in a city — whether it is city council decision on new housing, a permit process for a new crematorium — is a plane. It has a takeoff, a journey and a landing. During the journey there can turbulence, problems, or a good cruise. It could also be hijacked (special interests) or delayed. It could land smoothly or circle several times and then land. It could also run out fuel or crash. I am proposing that a civic radar screen be built for a few key US cities to track civic processes in public for journalists and citizens.

Citizens and journalists can specify their interests (keywords, patterns) to this tracker and let it alert them when a match was found along with the associated document or data set. This rich alert could also simply be stored in a newsroom’s database so that it became part of institutional memory. Journalists can use this to detect or scan for newsworthiness, surface deeper and more diverse stories sooner, and citizens can use the same tool for more relevant access to city data sets and documents.

The latest data and document analysis, crowdsourcing and visualization techniques could be used to build such a system.

I am also proposing that like freeways, public transit and airports, this become part of a city’s digital infrastructure, driven by journalists, citizens and open data/documents.

  • For crowdsourcing, I wanted to test a hypothesis on whether active citizens, experts and activists will share insights (and documents) with trusted local newsrooms when the latter does a call-out. The call-out is an article with questions on a specific local concern and a deadline. We are currently doing one experiment in San Francisco (KALW 91.7) and early results were a success. The newsroom is currently going to use this approach for more local topics to help gather insights ahead of the reporting process. This result tells me that ‘deep crowdsourcing’ on local concerns is possible and it could built up as a standard operating procedure in newsrooms for any issues on which multiple ongoing stories are done. The same crowdsourcing can done by the organization (or partnership of newsrooms) that might run a civic radar screen, so the lessons are portable.
  • One key learning is that despite the widespread recognition of the word ‘crowdsourcing’ in U.S. media, only a handful of newsrooms remain leaders in the practice. The vast majority of local newsrooms need help to get started and there is a major opportunity to add this as a ‘capacity’ aligned with the community engagement/social media editor’s role.

Next steps

  • During June-September I will be working on a prototype civic radar screen for a set of narrow use cases (for journalists and citizen/activists) using data sets and documents from the San Francisco city government. I will be developing some new code, as well as leveraging open source tools already built by others for individual end-uses, and using visualization tools.  
  • I will also complete more experiments in crowdsourcing both in U.S. cities and Bangalore, and produce a document to address ‘what is deep crowdsourcing’ in a local newsroom context — the opportunity, the benefits, the really low investment needed, and how can a newsroom get started.
  • I will also develop an idea for the organizational structure needed to run and sustain a civic radar screen for a major city. My starting point is that it be a partnership of multiple local newsrooms, NGOs and civic tech players.
  • During this time I will be a visiting scholar attached to the H-STAR Institute at Stanford.