Vote Ki Vaat Mat Lagne Do is Mumbai-speak for “Don’t Let Them Screw Around With the Vote“.

Please feel free to share the poster on blogs and social networks.

It was that crisis that started two members of the Ushahidi dev community (Chris Blow and Kaushal Jhalla) thinking about what needs to be done when you have massive amounts of information flying around. We’re at that point where the barriers for any ordinary person sharing valuable tactical and strategic information openly is at hand. How do you ferret the good data from the bad?

When the noise is overwhelming the signal, what do you do?

Thus began project “Swift River” at Ushahidi, which for 3 months now has been thought through, wireframed, re-thought and prototyped. Chris and Kaushal started asking, what can we do that most significantly effects quality of information in the first 3 hours of a crisis? And then answered, what if we created a swift river of information that gets quickly edited? Events like US Airways Flight 1549 and the inauguration gave us real-time live events that also had massive amounts of data to test things out on.

And, after all that, we’re not done, but we do have some solid ideas on what needs to be done. We think of it as using a crowd to filter, or edit, the already crowdsourced information coming through tools like Ushahidi, Twitter, Flickr and YouTube. To us, Swift River is “Crowdsourcing the Filter”.

How does it work? (non-tech version)

Since we don’t believe there will ever be one tool that everyone uses for gathering information on global crisis, we see a future where a tool like Swift River aggregates data from tools such as the aforementioned Twitter, Ushahidi, Flickr, YouTube, local mobile and web social networks. At this point what you have is a whole lot of noise and very little signal as to what the value is of the data you’re seeing.

Anyone who has access to a computer (and possibly just a mobile phone in the future), can then go and rate information as it comes in. This is classic “crowdsourcing”, where the more people you have weighing in on any specific data point raises the probability of the finding the right answer. The information with greater veracity is highlighted and bubbles to the top, weighted also by proximity, severity and category of the incident.

At this point we have successfully filtered a large amount of data. Something difficult to do with a small team of experts, which can be accomplished by a large number of non-experts and experts combined.

What Next?

So far we have some comps and David created a rough prototype of the engine driving it for the US inauguration. If this type of tool interests you, and you’d like to help, then do let us know. Here’s a glimpse at some of the idea flows that spur on our conversation at Ushahidi. This was created by Chris Blow, using the assumption that the user of this tool and protocol was a Twitter user:

The tool is really quite simple, and can be made better by clustering “like” incidents and reports, rating of the users on proximity, history and expertise and by developing a general protocol so that any other developer can expand on it as well.

Many others are talking about the citizen reporting, and it’s value and challenges. Mainstream media is concerned, as are many experts and government officials, about how empowered ordinary people are in gathering, providing and amplifying information in ways that just weren’t possible before.

There is no stopping this change in information dynamics, there is only harnessing it in ways that add more value to the good guys than the bad (when you can figure out which is which). At the very least, we need to figure out how greater information flow and transparency can be leveraged to help in emergencies, especially when there are negative forces at work who have equal accessibility to the same tools.

Aggregation vs early warning

During, or after, a conflict there are a lot of tools available and already being used, especially in technologically advanced countries like India. Technically, it’s fairly easy to aggregate Twitter, Wikipedia, Flickr and YouTube videos. That should be done, and we are creating the superstructure for this to happen easily worldwide. (note: Twitter is useful in India, the US and Canada, but what about all those areas of the world where it was turned off?)

What is more interesting to me, especially about Mumbai and Jos, is the fact that if a tool like Ushahidi was available globally beforehand, then it would have provided a place for people to send in anonymous information and tips before anything happened. After all, even if the local law enforcement isn’t aware of what is happening, someone within the community does. Of course, this begs the question, “how would they know of it?” To which I don’t have any more of a complete answer other than if it was up and live, it would gain traction over time, just as any effective web/mobile service does.

The “right” and “best” tool

The best tool in any given crisis is what ever is available. There isn’t any time to deploy something then, you have to use devices and services that people are already using. Chris Albon noted that there was a lot of information and data flying around during the crisis in Mumbai, and that Ushahidi wasn’t present. Instead, it was a mixture of Wikipedia editing and Google maps that people were using. For a major global city, these two tools makes sense. But what about places like Jos?

This reminds me of a what I wrote about on holistically dealing with disaster scenarios during the hurricanes in the US earlier this year. The value of the current Ushahidi Engine is good for information gathering and visualization, but there is a definite need of a more wiki-like functionality in these tools. Both the hurricanes and these other conflicts have been rapidly collaborated and edited into Wikipedia, so the usefulness of that type of tool is shown. I’m very interested in getting something like this figured out, if we had the resources internally, we’d be doing it already.

What about when the ‘bad’ guys use it?

The other questions were hard, but this ones even harder. As much as mainstream media and experts are up in arms over the way that the terrorists in Mumbai could use information coming in from these new digital channels to monitor their own situation, we have to remember this isn’t new. Groups like this have been able to do this with mainstream TV and radio for years. What’s disturbing is that not even the government can stop it now.

The problem is that it’s no longer one-to-many mass broadcast, it’s now mass-broadcast to mast-broadcast. How do you stop 6 million SMS messages without crippling your own infrastructure and ability to get work done?

I think one answer might be found in figuring out a way to harness information from an even greater number of people. The more data that is collected, the less chance that bad data can have an adverse effect. For instance, if 2 reports come in that widely differ from the reports by 10 other people, then we can assume that they are false. That at least helps us solve for a greater probability of good info being available and can help with the adverse use of it by the “bad guys”.

What it doesn’t do is solve for the problem of the “bad guys” having more information available at their fingertips. Nothing will solve that now. What it does do is mean those opposing them will have equal access to the same information, and possibly even more than is currently available on the “bad guys” movements and operations by tapping into the greater public.

Just more questions…

This all left me with a no final answer, just more questions.

• How does the transparency of a tool help and hinder during hot-flash conflicts?
• Beyond Ushahidi, what are the best tools to use in hot-flashes?
• How does rural, and conflicts with greater geographic distribution than one city, differ in coverage and information?
• What is Ushahidi’s role?