Given AidData's efforts to increase aid effectiveness through better use of data, many of you might expect me to make the case that the data revolution is going to deliver a wide range of wonderful development benefits. I’m not going to do that. Instead, I want to talk about how we can parlay the data revolution into an accountability revolution.
Don’t get me wrong, I believe that open data is critically important for accountability. However, for data to make a difference, we must consider what happens - or doesn’t happen - after the data is liberated. After all, if data isn’t used, it isn’t very useful.
I will admit that it is very tempting to jump on the bandwagon and embrace this call for a data revolution. But I think we need to come to grips with the fact that this term “data revolution” belies the importance of the other ingredients needed for citizens to hold governments and donors accountable.There are many ways in which the data revolution has the potential to bring about an accountability revolution, but we shouldn’t harbor any illusions that data by itself is going to solve many problems.
If data is going to be a catalyst for accountability, a few other things must be true. First, there must be a robust community of data users who want to use the data to further their goals. Second, these users must be able to make sense of the vast stores of data. Third, there must be political commitment on the part of donors and governments to make course corrections based on analysis of the data and feedback from local stakeholders in the communities that they seek to support. If we take these ingredients — or other critical ingredients — for granted, we risk launching a data revolution that produces a lot of information with little accountability.
What should we do? To make development data more useable, I would submit to you that the data must be hyper-local. AidData is betting big on geospatial because we have seen first-hand that citizens, donors, public officials, CSOs, and journalists use hyper-local data to visualize and analyze what is going on in the areas where they work and live.
I would also submit to you that we need to think creatively about new ways of making development data meaningful for those who want to use it. When citizens and officials are inundated with information, it is hard to hold anyone accountable. We need to do a much better job of identifying and equipping infomediaries who can help others make meaning of vast stores of data and then package and deliver this information to ordinary citizens and decision-makers in an understandable way.
However, in the grand scheme of things, all of this is relatively easy compared to the task of creating mechanisms and incentives for funders and service providers to collect and act upon local citizen feedback. In the coming weeks, AidData will be rolling out functionality upgrades to aiddata.org that focus on closing the feedback loop between donors, governments, and their intended beneficiaries through user input. You will now be able to comment on projects; upload documents, videos, and photographs; and challenge the accuracy of individual data points. We want to collect the best information that the crowd has to offer. However, getting the technology right is not the hard part. The really hard part is getting the incentives right for users to supply useful and timely information about the performance of development projects in non-emergency settings. To this end, AidData has a number of experimental evaluations in the pipeline that will test when citizens, journalists, civil society groups, and members of parliament are willing to provide feedback on development projects, and what conditions must be in place for governments and donors to respond to feedback.
Is an accountability revolution possible? I certainly hope so, but it will take many people experimenting and building a body of knowledge about what works and what doesn’t to find out. We need to get ready to pilot, test, and fine-tune new crowdsourcing methods and mechanisms. We also need to keep in mind usability, accessibility, and human capability before attempting to go to scale.
I look forward to working with you all to put data to better use for the communities we serve.