Even if the relationships between campaign contributions, lobbying, and votes are not as simple as some think they are, there are tangible ways money influences policy. There is a need for open government applications to investigate these influences. But I think there is a right way and a wrong way to go about it.
The surest way to bring about detrimental unintended consequences is by using regulations, fear, and shame as a tool to incite change — especially without a deep understanding of the system you are trying to change. I have been very careful leading up to this chapter to avoid examples of open government data applications that rely on negativity. I much prefer to empower the public than to shame our government. And so I put all of the bleak examples of transparency into one chapter that I hope you will just as soon forget.
So many of the examples in this book were based on the idea of empowerment. Many applications give consumers information to make better choices, from GPS signals and weather reports to the ability to find clinical trials that could improve one’s health. Other applications help consumers save time or money, such as applications around airline flight statistics and websites that display the law. Other uses of government data empower communities to make better decisions, such as where to locate new charter schools.
Recall from section 3.3 the difference in motivation between crime mapping applications that tap into fear, on the one hand, and Fruehwald’s graph of murder rates in Philadelphia which taps into humility, on the other. Or, in section 3.1, the difference between Sunlight Foundation’s charge of improper policymaking on the Amtrak privatization bill versus their Capitol Greetings project that brought congressional debate to life using art and humor. The best open government applications seek to empower consumers, to help small businesses, or to create value in some other positive, constructive way. Open government data is only a way-point on the road to improving education, improving government, and building tools to solve other real world problems.
Many of the applications discussed throughout this book were unintended consequences themselves, but of a good kind. In Chapter 1 I described the development of Federal Register 2.0, the real-time visualization of wind using weather data, and the development of the civic hacking movement, all of which no one could have predicted just a few years ago. And in Chapter 3 I surveyed how open government data is being used to improve government and policy. Campaign directors would never have thought that their fund-raising invitations would be used to educate the public about how politicians raise money from wealthy individuals and political action committees, as on Sunlight Foundation’s Party Time website. It would have been hard to predict that volunteers would help the U.S. patent office sort patent applications, but as Peer to Patent found out volunteering was a new way to impress potential employers.
Looking toward the future, I have no doubt that open government data will continue to grow and that interesting apps will be built on it. Hopefully this book has provided a useful road map of where we’ve come so far and what you could build tomorrow.