Our research on crowdsourcing government has generated six lessons for designing crowdsourcing to generate effective policies and services (Liu 2017). However, one thing that needs to be emphasized more is the experience that has been gained by implementing crowdsourcing. Studies show that government officials become reluctant to continue to adopt crowdsourcing when experiencing the following situations: (1) information overload, (2) low-quality inputs, or (3) political risk due to unexpected content. Meanwhile, studies also show that citizens will not participate or sometimes show increased distrust of governments’ efforts when they experience (1) counterfeit information, (2) lack of interest in their contribution, or (3) no consequent follow-up of their inputs (or action). 

So, how can crowdsourcing designers create positive experiences for implementing crowdsourcing that truly create effective policies and increase trust between citizens and governments, especially with the new generation of citizens? Our research (Liu 2017) shows that crowdsourcing designers should anticipate users’ experiences, with users including both government officials and citizens as their communication takes place over the crowdsourcing platforms. By examining an interdisciplinary body of literature on crowdsourcing, we can highlight the implications of these design lessons that can create empathy and rewarding and positive experiences through participation in public policies and services.

First, effective crowdsourcing creates empathetic experiences for citizens. Through participation in crowdsourcing, citizens have a better chance of understanding the complexity and conflicting views of others and of public issues. The key to success is (Lesson 1) to align crowdsourcing adoption with solutions for public problems and (Lesson 2) to align crowdsourcing tasks with the capacity of the participants (Liu 2017). The key is to be specific about what you want your citizens to achieve collectively through their individual efforts and then leave some space for deliberation among the citizens. For example, the City of Melbourne set up Future Melbourne, a crowdsourcing platform with wiki technology that requires the participants to read others’ editing before they change the content. Thus, participants with different backgrounds and expertise can exchange their views and experiences on policy for the city (Liu 2016). 

Second, accomplishing crowdsourcing tasks should be coupled with rewarding experiences and rewards can take different forms. The literature points to two essential incentive designs: (Lesson 3) use prizes and rewards to increase participation; and (Lesson 4) build skills to enhance the quality of contributions. Evidence shows that monetary rewards can increase participation because participants treat crowdsourcing projects as jobs and a sufficient number of prizes and rewards can attract the public’s attention, as found in the case of the US Office of Management and Budget (2009), which used prizes to increase public participation in social innovation. However, to improve the quality of contributions, studies show that it is essential to build participants’ skills and capacities by designing a variety of manageable tasks. For instance, the National Archives Records Administration (NARA) initiated the Citizen Archivist Program, which engages participants to transcribe documents, thus making archived records publicly accessible online (Bowser and Shanley 2013). Approximately 170,000 participants indexed 132 million names from the 1940 Census Community Indexing Project within five months. Why are citizens so keen to do this? NARA did a very good job of providing transcription tips and training on their platforms through videos and a step-by-step manual. With each task a citizen performed, they could see how “their contribution” fit into the system and immediately received feedback from their peers. These citizen archivists learned on the basis of their interests, not by performing tasks.  

Third, crowdsourcing is not a technology but a community that can generate positive experiences from participation. Positive experiences could also come from socializing among participants and discovering the impacts of their meaningful contribution. It is essential to (Lesson 5) empower participants through peer review and (Lesson 6) legitimize evaluation by integrating a reputation system into the crowdsourcing process (Liu 2017). Evidence from the literature shows that combining constructive competition and supportive cooperation is essential to build a crowdsourcing community (Hutter et al 2011). For instance, studies show that a sense of community belonging and social identity play an important role in creating a meaningful contribution in communities like Look at Linz in Austria. A community-based approach could optimize data sharing and negotiation, and internalize priority setting among participants (Almirall, Lee, and Majchrzak 2014). 

Don’t “Look for” the Solutions

Looking for a solution implies that a predetermined set of criteria has been used to find it, and this might prevent a solution surfacing from the “wisdom of the crowd.” To adopt crowdsourcing in government, officials should be prepared for solutions to be completely different and unexpected. While government officials can certainly impart their views, these should be part of a larger deliberation within the crowd. It should be remembered that crowdsourcing is a learning process, and a process to generate empathy. It is the process that generates trust, not just the outcomes of the crowdsourcing. In the public sector, the issues are often complex and full of diverse views from different parties. Thus, public officials should be prepared mentally to be open to any input because there is no good or bad solution, but a perceived solution of citizens’ satisfaction. 

Don’t Stop with Generating Ideas

Governments should also institutionalize ideas generated through crowdsourcing. The paper points out that sometimes crowdsourcing projects like hackathons for software programs or apps in the public sector are unsustainable without government support to scale up or create impacts. The reality is that very few apps created from hackathons continue to be active. Therefore, state governments can standardize these data to build national tools. For example, the Bloomington Indiana Open311 project has created open-source civic reporting apps that other cities are allowed to adopt. 

Inflated Reviews and Risks

Brabham (2012) found that cheating in contest ratings and voting was a major concern in the Next Stop Design competition in Salt Lake City, Utah, USA. He found that 27.6% of all votes that were cast were from a handful of users who created several dummy accounts. Thus, a rigorous method is needed to detect fraudulent accounts. Also, studies increasingly highlight the risks of adopting crowdsourcing in the private sector. Lieberstein (2012) points out that crowdsourced projects might suffer from infringing or use of unauthorized material and it is costly to verify information and sources of content, as found in the legal cases Disney v Wiler and Larry Montz v Pilgrim Film and Television. When adopting crowdsourcing practices, legal aspects should also be considered, in particular regarding the unauthorized use of copyrighted materials. 

Future Development of Crowdsourcing in Governments

The six lessons learned from the existing literature represent the basis for a new policy approach to public engagement for innovation in government. Crowdsourcing is a new institutional arrangement that connects citizens through alignments (Lessons 1-2), incentives (Lessons 3-4), and evaluative community (Lessons 5-6) to public affairs that have a direct or indirect effect on their daily lives. This approach with the appreciated design allows governments to create positive crowdsourcing experiences for citizens when deliberating policies and serving others. 

Helen K. Liu is Associate Professor of Public Management at the Department of Political Science, National Taiwan University.

References

Almirall, Esteve, Melissa Lee, and Ann Majchrzak. 2014. “Open Innovation Requires Integrated Competition-Community Ecosystems: Lessons Learned from Civic Open Innovation.” Business Horizons no. 57 (3):391-400.

Bowser, A., and L. Shanley (2013). New Visions in Citizen Science. Case Study Ser, 3, 1-53.

Brabham, Daren C. 2012. “Motivations for Participation in a Crowdsourcing Application to Improve Public Engagement in Transit Planning.” Journal of Applied Communication Research no. 40 (3):307-328.

Lieberstein, M., and A. Tucker. “Crowdsourcing and Intellectual Property Issues.” Association of Corporate Counsel (2012).

Liu, H. 2016. “Exploring Online Engagement in Public Policy Consultation: The Crowd or the Few?” Australian Journal of Public Administration.

Liu, H. K. 2017. “Crowdsourcing Government: Lessons from Multiple Disciplines.” Public Administration Review, 77: 656-667.

Mergel, Ines, and Kevin C. Desouza. 2013. “Implementing Open Innovation in the Public Sector: The Case of Challenge.gov.” Public Administration Review no. 73 (6):882-890.

Noveck, Beth Simone. 2009. Wiki Government: How Technology Can Make Government Better, Democracy Stronger, and Citizens More Powerful: Brookings Institution Press.