Crowd-based reporting tools have garnered tremendous attention for their role in anticorruption efforts all around the world. Deservedly so: these platforms harness rapidly increasing internet and mobile access in the developed world to tackle the age-old problem of corruption. Perhaps the best known of this new wave of crowdsourced reporting tools, iPaidABribe (which started in India and has been successfully recreated in other parts of the world), allows any citizen with a smartphone or other access to the internet to report bribery incidents nearly-instantaneously. Citizens can report the amount of a bribe, the recipient of the bribe, the institution that took or demanded the bribe, and so on — all anonymously. Visitors can read the reports as well as view a sort of “heat map” that aggregates the reports to demonstrate where bribery is most prevalent. The very act of broadcasting one’s own experiences with corrupt officials, and the commensurate naming-and-shaming effect this has when many such reports are aggregated, is proving to be extremely powerful.
To be sure, not all attempts to use modern internet and mobile technology to crowdsource anticorruption reporting have been as successful. Some (perhaps most) platforms never really get off the ground. Observers on this blog and elsewhere have pointed out that this may be due to a mismatch between local social conditions and the platform itself. These challenges are real, but I want to focus for now on platforms that have managed to gather and report significant data on corruption. Even in these cases, some commentators have pointed out, the full potential of crowd-based corruption reporting platforms has yet to be realized. The data they are gathering is still relatively “raw” and unprocessed by entities that could really use it — such as government anticorruption agencies. Thus it is important to highlight how these platforms can improve, and how they can avoid having their efforts thwarted by unwanted side-effects. As platform developers move past their early obstacles and start achieving real success in their primary goal — getting people to use their reporting system — the need now is to direct the platforms and their potential partners in such a way as to enhance their effectiveness and to avoid the possibility that their data will be misused.
First, how to increase their effectiveness? Dieter Zinnbauer of Transparency International has a new paper on crowd-based reporting mechanisms that contains several interesting suggestions, a few of which I have selected here because they all seem to indicate that the data these platforms are already gathering could be better used right now by existing anticorruption actors:
- Drawing from the experience of other crowdsourced governance models, platforms should ideally allow for a two-way communication between citizens and officials. For instance, the popular apps FixMyStreet in the UK and SeeClickFix in the US allow users to report needed roadworks — and for the relevant city officials to report when and how they have addressed the issue. IPaidABribe is close to this with its promise to follow up on initial reports with government agencies.
- Information gathered on these platforms could be useable in future legal actions. Mr. Zinnbauer uses an analogy from New York before the internet existed: enterprising lawyers used to pay people to map and report potholes because one needed to prove that the city knew about a problem before the city could be sued over it. Although crowd platforms don’t need to pay their contributors, their reports could be used to prove in a lawsuit that officials were aware of a problem, where necessary. As an example, the platform Not In My Country, which focuses on corruption in Kenyan and Ugandan universities, is forming partnerships with private lawyers to bring lawsuits with particularly information-rich reports.
- Local antocorruption NGOs or legal aid services as well as investigative journalists could also do more to use this data. Connecting the crowd-gathered corruption data to non-government outlets that have a proven capacity to file complaints, launch investigations, and publicize scandals could at least amplify the naming and shaming effect. TI Macedonia’s partnership with Ushahadi is a good example of this partnership potential.
These are obviously just a few of the connections that are possible between crowd-based platforms and existing government, private, and NGO or media-led anticorruption efforts. Implementing such connections is crucial, not only to realize the full potential of crowdsourced anticorruption reporting technologies, but also because publishing the corruption data gathered by these platforms can actually have a harmful impact on the anticorruption effort if the data are not used properly. Mr. Zinnbauer’s paper is again helpful in highlighting some of the most serious potential side effects:
- Broadcasting the prevalence of bribery may allow participants to determine the market price for their bribes. As economists know, price transparency contributes to lower transaction costs and thus more deals being made successfully.
- Seeing how prevalent bribery is may create a “keeping up with the Joneses” atmosphere — individuals may feel that, if everyone else is paying a bribe, then in order to remain competitive he or she must pay bribes as well. The pressures on a parent to bribe school officials to favorably grade their children, for instance, may actually increase with the knowledge that such activity is pervasive.
- Relatedly, the knowledge that bribery is pervasive can have the affect of normalizing it; much like with the Broken Windows Theory of crime prevention, if the public becomes (even more) aware of bribery then future transgressions become more acceptable.
These negative side effects are admittedly speculative, but they are plausible. More important, they are avoidable. The corruption data gathered and published by crowd-based reporting platforms is extremely powerful on its own merits, and given the tireless efforts of these platforms’ developers I have no doubt the data will continue to amass. What I think Mr. Zinnbauer is too polite to say is that the onus is now squarely on institutional anticorruption groups — governments, NGOs, private lawyers, investigative journalists, and the like — to use these new tools. But that’s for future posts.