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Cries for increased “transparency” has become a rallying cry across industries and governments, as consumers and citizens look for more information about what they’re eating, buying, breathing, drinking or how they are being governed. What “does transparency” means, and for whom?

Targeting transparency can have unexpected outcomes, particularly as humans and societies adopt and adapt novel technologies to suit their needs or goals. For instance, research at Northwestern found hospital report cards could actually decrease patient welfare. The dynamics of transparency are complex, given that systems for reporting may reveal corruption, fraud or abuse by powerful interests but can also expose people to retribution or discrimination.

[Radiation plumes in Japan]
[Radiation plumes in Japan]

“The challenge is to create and design transparency policies that actually work for people and don’t just waste time or create a bunch of information that’s difficult to understand or make organizations go through the fairly expensive processes of collecting information that nobody then goes on to use,” said professor Archon Fung, in a recent interview. “The policy challenge has to do with designing transparency policies so that they produce information that is actually highly valuable to people and that people can take action on.”

Many of the perils and promise of transparency have been explored at length in “Full Disclosure,” by the directors of the Ash Center’s Transparency Policy Project, from calorie counts to restaurant inspections. As is so often the case, such research raises as many questions as it answers. When and how do consumers respond to new information? What factors influence whether private companies respond to disclosure mandates by reducing the risks posed to consumers or improving practices? Where and when should policy makers apply disclosure versus other policy tools?

The answers to all of these questions are further complicated by the introduction of networked systems for communication and disclosure, particularly the emergence of powerful mobile devices and social media. The Ash Center is actively looking for examples of socially networked transparency systems that reduce risks and provide new tools for citizens and consumers to navigate the world. Examples of networked transparency include:

  • hospital ratings by individuals that may help other patients avoid the risk of medical error or infections
  • Websites like PatientsLikeMe that may provide earlier warning of drug side effects, safety or effectiveness problems
  • Civic media services like Safecast, which leverage citizen science and public data to inform the public about radiation risks
  • Data sources like Google Flu Trends, where the actions of individuals provide tacit information that can augment existing systems for early warning of outbreaks

In each of these examples, the collective actions of many individuals reporting information based on their experience, aggregations of reliable reports, or sensor data is collected and then disseminated in a way that makes the associated risks to the public risk more visible and transparent. Such networked transparency systems can then be adapted and used to inform individual choices or change behaviors of the entities creating the risks, saving lives or reducing harms.

Over the next several months, the Transparency Policy Project will be looking for more examples of networked transparency, from grassroots efforts created by public laboratories to reporting systems created by governments.

As you’d imagine, the people collaborating on the research (including the fellow writing this post) will be looking for tips, feedback, comments and links from you. Please email your ideas or pointers to alexanderbhoward [at] gmail.com, or reply to @digiphile or @sunshinepolicy on Twitter. Each week, we’ll gather together what we’ve learned to date and share a digest at this blog.

A much talked-about innovation in public policy has been the push to achieve greater transparency and accountability through open government strategies, where the public has access to government information and can participate in co-producing public services. At the Transparency Policy Project we have been investigating the dynamics behind one of the most successful implementations of open government: the disclosure of data by public transit agencies in the United States. In just a few years, a rich community has developed around this data, with visionary champions for disclosure inside transit agencies collaborating with eager software developers to deliver multiple ways for riders to access real-time information about transit.

Transit agencies have long used intelligent systems for scheduling and monitoring the location of their vehicles. However, this real-time information had previously been available only to engineers inside agencies, leaving riders with printed timetables and maps, that, at best, represent the stated intentions of an complex system that can be disturbed by traffic, weather, personnel issues and even riders themselves.

Recognizing the need to be able to access this information on-the-go and in digital format, Bibiana McHugh of Portland’s TriMet agency worked with Google in 2006 to integrate timetable data into Google Maps, eventually becoming Google Transit. McHugh went further, publicly releasing TriMet’s operations data: first the static timetables, and eventually real-time, dynamic data feeds of vehicle locations and arrival predictions. Local programmers have responded with great ingenuity, building 44 different consumer-facing applications for the TriMet system, at no cost to the agency.

Transit Apps and Ridership by City

Other transit agencies have adopted this open data approach with varying outcomes. The most successful agencies work closely with local programmers to understand which data is in demand, troubleshoot and improve the quality of the data feeds. Programmers also make the link between end users and transit agencies by filtering up comments from apps users. This iterative feedback loop relies on a champion within the agency to build strong relationships with the local developer community. Of the five transit agencies we studied, Portland’s TriMet and Boston’s MBTA exemplify this approach and have generated the highest ratio of apps per transit rider (see table). Meanwhile, the most reluctant agency to adopt open data, Washington DC’s WMATA, only has eleven applications serving its customers.

The number of apps built by independent developers is important, indicating the variety of options riders have in selecting which interfaces (mobile, desktop, map-based, text, audio) and platforms best fit their needs to access transit information. As we have learned from our research on what makes transparency effective, simply providing information is not enough. Format and content matter, and should address the needs of a targeted audience. What we have seen in our study of transit transparency is that local programmers have been the critical intermediaries, taking raw data and generating a variety of information tools that transit agencies could not have imagined on their own. For other open government initiatives to spark this level of innovation and public benefit, they must identify their audience of information intermediaries and foster those relationships.

Francisca Rojas, research director – Transparency Policy Project
Original post on Google’s Policy by the Numbers blog (January 27, 2012)