I wrote this article for the most recent APA Technology Division Newsletter, which we sent out this week. Other articles include city apps, water quality mapping, TOD database, a VMT estimation tool, and online participation.
The expansion of the Internet has made possible amazing examples of the collaboration of large groups of people, a phenomenon often called crowdsourcing. Projects like Wikipedia and OpenStreetMap have created new types of encyclopedias and maps. Other projects have coordinated thousands of volunteers to perform major outreach events, such as cleaning up garbage in Estonia or coordinating relief efforts for disasters such as the earthquake in Haiti.
As examples have proliferated, city planners have begun to explore whether the web can be used to tackle urban planning problems. Reviewing some well-known crowdsourcing examples with a focus on urban planning, I will describe four distinct models of crowdsourcing. Understanding these different models and their relative merits is required to integrate successful models of public sector crowdsourcing. The four types are crowdsourcing are:
- Soliciting solutions to problems
- Coordinating many individuals to achieve “collective intelligence”
- Novel combinations of incentives, processes, and staffing to achieve organizational goals
- Peer production of public goods
Some projects have used crowdsourcing as a way of soliciting innovative designs to a problem online. In Salt Lake City’s Next Stop Design project, Thomas Sanchez and Daren Brabham led a team which held an online design competition for a bus stop in Salt Lake City. In a recent article for the journal Planning Theory, Brahbam argues crowdsourcing should be viewed as a new type of public participation. He cites as an example the company InnoCentive, which operates a website where corporations post technical problems and “solvers” compete to win cash prizes for the best solution. “In essence, any urban planning project is predicated on a problem.” Brahbam writes, “Typically that problem is how best to accommodate changing populations with different infrastructure, all while considering the interests of residents, developers, business owners, and the environment. If a problem can be framed clearly, and if all the data pertaining to a problem can be made available, then that problem can be crowdsourced.”
In Melbourne, Australia, Mark Elliott and a team of collaborators took quite a different approach to crowdsourcing for a project completed in 2008. Partnering with an official city planning process, Elliot’s group created a wiki so the plan could be written in the same way as Wikipedia is – through the contributions of hundreds of different authors. In his doctoral dissertation, Elliott proposed a theory of “stigmergic collaboration.” Stigmergy is a theory developed in the natural sciences for a “mechanism of indirect coordination between agents,” such as the ways ant colonies can work in highly coordinated ways without a central authority. Elliott argues this type of cooperation and collaboration is made possible through technologies that create a “localized site of individualistic engagement” that reduces demands placed on participants.
A recent paper by MIT researchers argued crowdsourcing projects should be viewed as innovative arrangements of components, what they call a genome. Through a detailed analysis of the organizations Linux, Wikipedia, InnoCentive, and Threadless, the authors conclude each share a common set of ingredients which fall into four categories: the goal to be achieved, the structure or process of achieving the goal, incentives, and staffing. They observe these projects combine the components in different ways. For example, in the case of Linux, the crowd contributes new software code through collaboration for recognition, but only a small group decides which modules are included in each release through a hierarchy. In the case of Wikipedia, although the crowd creates articles, but the website uses voting and administrators for other decisions, such as whether to delete an article.
Finally, many have speculated that crowdsourcing should move beyond the realm of ideas. Citing examples of massive cleanups and emergency relief efforts, they argue city governments should use technology to crowdsource the production of public services. Instead of the government being the sole provider of certain public services, such as filling potholes or cleaning graffiti, could they simply coordinate citizens to help each other? I am skeptical of such claims for a number of reasons. Governments are subject to unique political and institutional arrangements which make collaborating with citizens difficult. Even if these barriers can be overcome, the flexibility of purely private organizations may be required for a successful project. However, even if governments can’t crowdsource their core functions, there may still be a need for a different approach in this new world. Bas Kotterink, a researcher in the Netherlands, argued in a lecture last summer that the expansion of private crowdsourcing may mean governments should take on expanded roles facilitating innovation, monitoring, and enforcing basic values such as privacy.
Although sharing similarities, each of these models contains distinct assumptions and approaches. Successfully using crowdsourcing for urban planning may require another approach entirely, taking into account the unique characteristics of each city and project. By describing some of the diverse approaches used thus far, I hope this article will help provoke ideas and innovation.
Originally written for APA Planning and Technology Today