Tag Archives: Ushahidi

My TEDx Talk: From Photosynth to ALLsynth

I just gave a TEDx talk and my presentation played off a recent blog post of mine entitled “Wag The Dog, or How Falsifying Crowdsourced Information can be a Pain.” I introduced some new ideas and angles to the topic so here is basically a blog post version of the presentation.

We all know that open crowdsourcing platforms are susceptible to information vandalism, i.e., false information deliberately used to mislead. For example, if an Ushahidi platform were used in Iran, the government there could start reporting events to Ushahidi that never happened; perhaps events that suggest protesters attacked first and that riot police were just acting in self defense. But, I’m going to argue that falsifying crowdsourced information can actually be a pain. And I’m going to use the analogy of “Wag the Dog” to explain why. If you haven’t watched the movie, the story is based on a White House Administration that pretends a war has broken out in Albania to divert public opinion and hopefully increase the President’s ratings prior to re-election.

Here’s a 30 second highlight on how they created a fake war:

In a way, Wag the Dog already happened for real. Except the story was called “The War of the Worlds” and it was played as a radio broadcast in 1938. “War of the Worlds” is drama about a Martian invasion of Earth. What was particularly fun about this radio broadcast was that the first 2/3 of the 1-hr long story was just a series of simulated news bulletins. And the story ran uninterrupted, ie, without commercials. So many radio listeners in the US freaked out, thinking a real invasion was taking place!

The panic this caused even made it on the front page of the New York Times! Clearly, pulling of a Wag-the-Dog in the 1930s was a piece of cake!

And that’s because the information ecosystem looked something like this in the 1930s. Largely disconnected and broadcast only, ie, one-to-many. Can anyone point out an important node that should be included in this ecosystem? That’s right, the newspaper. But the paper would not have been printed at the speed that the radio broadcast was taking place to help counter fears; unlike today, of course, thanks to online news.

Today’s information ecosystem obviously looks little different. Many-to-many, peer-to-peer, 2-way, real-time information and communication technologies. Now, we might argue that this kind of ecosystem makes it easier for repressive regimes to game since the system is closely integrated and interoperable, which means information can propagate very quickly. Secretary Clinton recently called our information ecosystem the new nervous system of the planet. But then again, these diverse sources of user-generated content could also make it easier to triangulate and filter out false information.

For example, in the case of Iran, the high volume of pictures and videos posted on Flickr and YouTube made it rather difficult for the government to claim nothing was happening. Information blockades are likely to join the Berlin Walls of history. Today, you can get pictures of the same incident from three different camera phones, in addition to tweets and text messages, etc.

This is what Ushahidi is about, aggregating crisis information across different media and mapping that information in near real time to improve transparency, accountability and coordination.

Take the Ushahidi-Haiti map, for example. Crowdsourcing crisis information on Haiti allowed us to map several thousand incidents over just a few weeks, which actually saved lives on the ground. The incidents we mapped came from a myriad of sources: thousands of text messages directly from Haiti, hundreds of Tweets, information from Facebook Groups, online media, live Skype chats with the Search and Rescue Teams in Port-au-Prince, list serves, radio, you name it. Volunteers at The Fletcher School mapped this information in near real-time for several weeks and first responders used the map to save lives.

Check out this animation of the events unfolding from just a few hours after the quake.

What you see are events “overlapping” and clustering, ie, on several occasions we get two or more text messages from different numbers reporting the same event. And then a Tweet with similar information, for example. The crowdsourcing of crisis information allows us to triangulate and validate information thanks to the reporting coming from a myriad of sources in near real-time. This would hardly have been possible in the 1930s, which is what prompted my colleague Anand at the New York Times to write an article on our work and ask,

They say that history is written by the winners, will future history be written by the crowd?

Ushahidi’s crowded map of Haiti reminded me of Photosynth. Taking hundreds crowdsourced pictures and “stitching” them together to reproduce historical monuments. In 3D no less!

Here’s a quick 20 second video demo:

So the question is, can Ushahidi become the “ALLsynth” by stitching together crowdsourced crisis information across many different types of media? Ushahidi platforms have been deployed hundreds of times across the world. Here are just four examples.

From mapping the Swine Flu outbreak to reporting on the war in Gaza, to citizen-powered election monitoring in India and disaster response in the Philippines. Would stitching together these hundreds of platforms amount to creating an ALLsynth? What would it take to game an ALLsynth?

As I mentioned in my Wag the Dog post, perhaps some of the following:

  • Dozens of pictures from as many different camera phones of an event that never happened.
  • Text messages using different wording to describe an event that never happened.
  • Tweets (not retweets!).
  • Fake blog posts, Facebook groups and Wikipedia entries.
  • Fake video footage. Heck, you’d probably want to hack the international media and plant a fake article in the New York Times home page.
  • If you really want to go all out, you’d want to get hundreds of (paid?) actors like in The Truman Show.
  • You’d likely want to cordon off an entire area of the city or city outskirts.
  • Then you’d want to choreograph a few fight scenes with these actors.
  • A few rehearsals would probably be in order too.
  • Oh and of course props, plus lots of ketchup if you want things to look like they went badly.

In other words, you’d probably want to move to Hollywood to fabricate all this… That said, there’s another way that repressive regimes could deal with an unwanted Ushahidi platform, like this one being used by Sudanese civil society groups in the Sudan to monitor the elections currently taking place. We found out yesterday from our Sudanese colleagues that the site was no longer accessible in the Sudan (see official press release here in PDF). Blocking and censoring websites is really easy for governments to do, and we expected that Sudan would be no different.

So our Sudanese colleagues have been working with their tech-savvy friends to circumvent the censorship and continue mapping election irregularities—this is my applied dissertation research in action, I just never thought that my own actions would influence the data.  They set up a mirror site under an different domain name. This may become a cyber-game-of-cat-and-mouse, there is plenty of precedents for this: civil society finds a loophole, which is then blocked by the state, which prompts the search for another loophole, etc, etc. I expect that repressive regimes may eventually give up on blocking websites given the likely futility. Instead, they may try to game the platforms by falsifying crowdsourced information.

But as I have just argued, falsifying crowdsourced information can be a pain. So if repressive regimes start pouring money into their domestic film industries, particularly in blue screen technology, you’ll know why, and this is what you can expect to happen next:

Patrick Philippe Meier

The Rise of CrisisMapping and the CrisisMappers Group

My colleague Jennifer Leaning and I co-founded the Program on Crisis Mapping and Early (CM&EW) at the Harvard Humanitarian Initiative (HHI) back in June 2007. At the time, the term “Crisis Mapping” was virtually unheard of. In January 2008, Ushahidi demonstrated how crisis mapping could be combined with crowdsourcing and SMS.

In October 2009, my colleague Jen Ziemke and I launched the International Network of CrisisMappers with a dedicated Crisis Mappers Google Group, which currently has over 700 subscribers. Jen and I also co-organized the  first International Conference on Crisis Mapping (ICCM 2009) last year and are now preparing for ICCM 2010, which will focus on Haiti and Beyond. Over 30 online videos on Crisis Mapping have also been produced and we recently launched a dedicated monthly WebCast series on CrisisMapping as well.

On January 21, 2010, I attended a speech by Secretary of State Hillary Clinton in which she noted the pivotal role of interactive maps and SMS in the disaster response to Haiti. In her own words:

“The technology community has set up interactive maps to help us identify needs and target resources. And on Monday, a seven-year-old girl and two women were pulled from the rubble of a collapsed supermarket by an American search-and-rescue team after they sent a text message calling for help. Now, these examples are manifestations of a much broader phenomenon. The spread of information networks is forming a new nervous system for our planet.”

The CrisisMappers community played an instrumental role in the disaster response to Haiti. The interactive maps that Clinton refers to  include OpenStreetMap, Sahana, Telescience and Ushahidi. I like this idea of a new nervous system and hope the CrisisMappers community can continue growing this nervous system to ensure more rapid responses to crises. The term “crisis mapping” is at least beginning to make the rounds.

A Google search of “crisis mapping” in October 2009 returned 36,500 hits. Today, 5 months later, the search returns “123,000” hits.  During this time, Crisis Mapping initiatives have been written about and featured on CNN, ABC News, MSNBC, BBC, Reuters, UK Guardian, Al-Jazeera, NPR, the New York Times, the Washington Post, the Boston Globe, Huffington Post, Newsweek, the Globe and Mail, Wired, NewScientist, PC World, DiscoveryNews, Forbes Magazine and the TED Blog.

Several members of the CrisisMappers Group are currently preparing to present their projects at this year’s Where 2.0 Conference:

  • Haiti: Crisis Mapping the Earthquake –> link
  • Crowdsourcing the Impossible: Ushahidi-Haiti –> link
  • Community-Based Grassroots Mapping –> link
  • Mobilizing Ushahidi-Haiti  –> link
  • Crisis Mapping –> link
  • MapKibera –> link

I very much look forward to ICCM 2010 as I’m very curious to discuss what the next generation of crisis mapping technologies and applications will bring.

Patrick Philippe Meier

Ushahidi & The Unprecedented Role of SMS in Disaster Response

What if we could communicate with disaster affected communities in real-time just days after a major disaster like the quake in Haiti? That is exactly what happened thanks to a partnership between the Emergency Information Service (EIS), InSTEDD, Ushahidi, Haitian Telcos and the US State Department. Just 4 days after the earthquake, Haitians could text their location and urgent needs to “4636” for free.

I will focus primarily on the way that Ushahidi used 4636. Since the majority of incoming text messages were in Creole, we needed a translation service. My colleague Brian Herbert from Ushahidi and Robert Munro of Energy for Opportunity thus built a dedicated interface for crowdsourcing this step and reached out to dozens of Haitian communities groups to aid in the translation, categorization and geo-location of every message, quickly mobilizing 100s of motivated and dedicated volunteers. So not only was Ushahidi crowdsourcing crisis information in near real-time but also crowdsourcing translation in near real-time.

Text messages are translated into English just minutes after they leave a mobile phone in Haiti. The translated messages then appear directly on the Ushahidi platform. The screenshots below (click on graphics to enlarge) illustrates how the process works. The original SMS in Creole (or French) is displayed in the header. In order to view the translation, one simply clicks on “Read More”.

Ushahidi Back End

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Incoming Text Messages

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If further information is required, then one can reply to the sender of the text message directly from the Ushahidi platform. This is an important feature for several reasons. First, this allows for two-way communication with disaster affected communities. Second, an important number of messages we received were not actionable because of insufficient location information. The reply feature allowed us to get more precise information.

The screenshots below show how the “Send Reply” feature works. We weren’t sure if Universite Wayal was the same as Royal University. So we replied and asked for more location information. Note the preset replies in both English and Creole. The presets include thanks & requests for more location information, for example. Of course, one is not limited to these presets. Any text can be typed in and sent back to the sender of the original SMS. This feature has been part of the Ushahidi for almost two years now. We send off the request for more information and receive the following reply within minutes.

Preset Replies

When we receive an urgent and actionable SMS like this one, we can immediately create a report. By actionable, we mean there is sufficient location information and the description of the need is specific enough to respond to, just like the example above.

Creating a Report

First, the GPS coordinates for the location is identified. This can be done directly from the Ushahidi platform by entering the street address or town name. Sometimes a bit of detective work is needed to pinpoint the exact coordinates. Next, a title and description for the report is included–the latter usually comprising the text of the SMS. This is what we mean by structured information. The report is then tagged based on the category framework. Pictures can be uploaded with the report, and links to videos can also be included. Finally the report is saved and then approved for publication.

This is how the Ushahidi-Haiti @ Tufts team mapped 1,500+ text messages on the Ushahidi platform. We are now working with Samasource and Crowdflower to have the translation work serve as a source of income for Haitians inside Haiti. But how does all this connect to response?

Ushahidi’s “Get Alerts” feature is one of my favorite because it allows responders themselves to customize the specific type of actionable information that is important to them; i.e., demand driven situational awareness in near real-time. Not only can responders elect to receive automated alerts via email, but they can also do so via SMS. Responders can also specify their geographic area of interest.

Subscribe to Alerts

For example, if a relief worker from the Red Cross has a field office in neighborhood of Delmas, they can subscribe to Ushahidi to receive information on all reports originating from their immediate vicinity by specifying a radius, as shown below.

Selecting Area of Interest

The above Alerts feature is now being upgraded to the one depicted below, which was designed by my colleague Caleb Bell from Ushahidi. Not only are responders able to specify their geographic area of interest, but they can also select the type of alert (e.g., collapsed building, food shortage, looting, etc.) they want to receive. They can even add key words of interest to them, such as “water”, “violence” or “UN”. The goal is to provide responders with an unprecedented degree of customization to ensure they receive exactly the kind of alerts that they can respond to.

Highly Customized Alerts

On a more “macro” level, I recently reached out to colleagues at the EC’s Joint Research Center (JRC) to leverage their automated sentiment (“mood”) analysis platform. Sentiment Analysis is a branch of natural language processing (NLP) that seeks to quantify positive vs negative perceptions; akin to “tone” analysis. I suggested that we use their platform on the incoming text messages from Haiti to get a general sense of changing mood on an hourly basis. I’ll blog about the results shortly. In the meantime, here’s a previous blog post on the use of Sentiment Analysis for early warning.

Patrick Philippe Meier

Location Based Mobile Alerts for Disaster Response in Haiti

Using demand-side and supply-side economics as an analogy for the use of communication and information technology (ICT) in disaster response may yield some interesting insights. Demand-side economics (a.k.a. Keynesian economics) argues that government policies should seek to “increase aggregate demand, thus increasing economic activity and reducing unemployment.” Supply-side economics, in contrast, argues that “overall economic well-being is maximized by lowering the barriers to producing goods and services.”

I’d like to take this analogy and apply it to the subject of text messaging in Haiti. The 4636 SMS system was set up in Haiti by the Emergency Information Service or EIS (video) with InSTEDD (video), Ushahidi (video) and the US State Department. The system allows for both demand-side and supply-side disaster response. Anyone in the country can text 4636 with their location and needs, i.e., demand-side. The system is also being used to supply some mobile phone users with important information updates, i.e., supply-side.

Both communication features are revolutionizing disaster response. Lets take the supply-side approach first. EIS together with WFP, UNICEF, IOM, the Red Cross and others are using the system to send out SMS to all ~7,500 mobile phones (the number is increasing daily) with important information updates. Here are screen shots of the latest messages sent out from the EIS system:

The supply-side approach is possible thanks to the much lower (technical and financial) barriers to disseminating this information in near real-time. Providing some beneficiaries with this information can serve to reassure them that aid is on the way and to inform them where they can access various services thus maximizing overall economic well-being.

Ushahidi takes both a demand-side and supply-side approach by using the 4636 SMS system. 4636 is used to solicit text messages from individuals in urgent need. These SMS’s are then geo-tagged in near real-time on Ushahidi’s interactive map of Haiti. In addition, Ushahidi provides a feature for users to receive alerts about specific geographic locations. As the screen shot below depicts, users can specify the location and geographical radius they want to receive information on via automated email and/or SMS alerts; i.e., supply-side.

The Ushahidi Tech Team is currently working to allow users to subscribe to specific alert categories/indicators based on the categories/indicators already being used to map the disaster and humanitarian response in Haiti. See the Ushahidi Haiti Map for the list. This will enable subscribers to receive even more targeted location based mobile alerts,  thus further improving their situational awareness, which will enable them to take more informed decisions about their disaster response activities.

Both the demand- and supply-side approaches are important. They comprise an unprecedented ability to provide location-based mobile alerts for disaster response; something not dissimilar to location based mobile advertising, i.e., targeted communication based on personal preferences and location. The next step, therefore, is to make all supply-side text messages location based when necessary. For example, the following SMS broadcast would only go to mobile phone subscribers in Port-au-Prince:

It is important that both demand- and supply-side mobile alerts be location based when needed. Otherwise, we fall prey to Seeing Like a State.

“If we imagine a state that has no reliable means of enumerating and locating its population, gauging its wealth, and mapping its land, resources, and settlements, we are imagining a state whose interventions in that society are necessarily crude.”

In “Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed,” James Scott uses the following elegant analogy to emphasize the importance of locality.

“When a large freighter or passenger liner approaches a major port, the captain typically turns the control of his vessel over to a local pilot, who brings it into the harbor and to its berth. The same procedure is followed when the ship leaves its berth until it is safely out into the sea-lanes. This sensible procedure, designed to avoid accidents, reflects the fact that navigation on the open sea (a more “abstract” space) is the more general skill. While piloting a ship through traffic in a particular port is a highly contextual skill. We might call the art of piloting a “local and situated knowledge.”

An early lesson learned in the SMS deployment in Haiti is that more communication between the demand- and supply-side organizations need to happen. We are sharing the 4636 number,  so we are dependent on each other and need to ensure that changes to the system be up for open discussion. This lack of joint outreach has been the single most important challenge in my opinion. The captains are just not talking to the local pilots.

Patrick Philippe Meier

Crisis Information and The End of Crowdsourcing

When Wired journalist Jeff Howe coined the term crowdsourcing back in 2006, he did so in contradistinction to the term outsourcing and defined crowdsourcing as tapping the talent of the crowd. The tag line of his article was: “Remember outsourcing? Sending jobs to India and China is so 2003. The new pool of cheap labor: everyday people using their spare cycles to create content, solve problems, even do corporate R & D.”

If I had a tag line for this blog post it would be: “Remember crowdsourcing? Cheap labor to create content and solve problems using the Internet is so 2006. What’s new and cool today is the tapping of official and unofficial sources using new technologies to create and validate quality content.” I would call this allsourcing.

The word “crowdsourcing” is obviously a compound word that combines “crowd” and “sourcing”. But what exactly does “crowd” mean in this respect? And how has “sourcing” changed since Jeff introduced the term crowdsourcing over three-and-a-half years ago?

Lets tackle the question of “sourcing” first. In his June 2006 article on crowdsourcing, Jeff provides case studies that all relate to a novel application of a website and perhaps the most famous example of crowdsourcing is Wikipedia, another website. But we’ve just recently seen some interesting uses of mobile phones to crowdsource information. See Ushahidi or Nathan Eagle’s talk at ETech09, for example:

So the word “sourcing” here goes beyond the website-based e-business approach that Jeff originally wrote about in 2006. The mobile technology component here is key. A “crowd” is not still. A crowd moves, especially in crisis, which is my area of interest. So the term “allsourcing” not only implies collecting information from all sources but also the use of “all” technologies to collect said information in different media.

As for the word “crowd”, I recently noted in this Ushahidi blog post that we may need some qualifiers—namely bounded and unbounded crowdsourcing. In other words, the term “crowd” can mean a large group of people (unbounded crowdsourcing) or perhaps a specific group (bounded crowdsourcing). Unbounded crowdsourcing implies that the identity of individuals reporting the information is unknown whereas bounded crowdsourcing would describe a known group of individuals supplying information.

The term “allsourcing” represents a combination of bounded and unbounded crowdsourcing coupled with new “sourcing” technologies. An allsourcing approach would combined information supplied by known/official sources and unknown/unofficial sources using the Web, e-mail, SMS, Twitter, Flickr, YouTube etc. I think the future of crowdsourcing is allsourcing because allsourcing combines the strengths of both bounded and unbounded approaches while reducing the constraints inherent to each individual approach.

Let me explain. One main important advantage of unbounded crowdsourcing is the ability to collect information from unofficial sources. I consider this an advantage over bounded crowdsourcing since more information can be collected this way. The challenge of course is how to verify the validity of said information. Verifying information is by no means a new process, but unbounded crowdsourcing has the potential to generate a lot more information than bounded crowdsourcing since the former does not censor unofficial content. This presents a challenge.

At the same time, bounded crowdsourcing has the advantage of yielding reliable information since the reports are produced by known/official sources. However, bounded crowdsourcing is constrained to a relatively small number of individuals doing the reporting. Obviously, these individuals cannot be everywhere at the same time. But if we combined bounded and unbounded crowdsourcing, we would see an increase in (1) overall reporting, and (2) in the ability to validate reports from unknown sources.

The increased ability to validate information is due to the fact that official and unofficial sources can be triangulated when using an allsourcing approach. Given that official sources are considered trusted sources, any reports from unofficial sources that match official reports can be considered more reliable along with their associated sources. And so the combined allsourcing approach in effect enables the identification of new reliable sources even if the identify of these sources remains unknown.

Ushahidi is good example of an allsourcing platform. Organizations can use Ushahidi to capture both official and unofficial sources using all kinds of new sourcing technologies. Allsourcing is definitely something new so there’s still much to learn. I have a hunch that there is huge potential. Jeff Howe titled his famous article in Wired “The Rise of Crowdsourcing.” Will a future edition of Wired include an article on “The Rise of Allsourcing”?

Patrick Philippe Meier

Three Common Misconceptions About Ushahidi

Cross posted on Ushahidi

Here are three interesting misconceptions about Ushahidi and crowdsourcing in general:

  1. Ushahidi takes the lead in deploying the Ushahidi platform
  2. Crowdsourced information is statistically representative
  3. Crowdsourced information cannot be validated

Lets start with the first. We do not take the lead in deploying Ushahidi platforms. In fact, we often learn about new deployments second-hand via Twitter. We are a non-profit tech company and our goal is to continue developing innovative crowdsourcing platforms that cater to the growing needs of our current and prospective partners. We provide technical and strategic support when asked but otherwise you’ll find us in the backseat, which is honestly where we prefer to be. Our comparative advantage is not in deployment. So the credit for Ushahidi deployments really go the numerous organizations that continue to implement the platform in new and innovative ways.

On this note, keep in mind that the first downloadable Ushahidi platform was made available just this May, and the second version just last week. So implementing organizations have been remarkable test pilots, experimenting and learning on the fly without recourse to any particular manual or documented best practices. Most election-related deployments, for example, were even launched before May, when platform stability was still an issue and the code was still being written. So our hats go off to all the organizations that have piloted Ushahidi and continue to do so. They are the true pioneers in this space.

Also keep in mind that these organizations rarely had more than a month or two of lead-time before scheduled elections, like in India. If all of us have learned anything from watching these deployments in 2009, it is this: the challenge is not one of technology but election awareness and voter education. So we’re impressed that several organizations are already customizing the Ushahidi platform for elections that are more than 6-12 months away. These deployments will definitely be a first for Ushahidi and we look forward to learning all we can from implementing organizations.

The second misconception, “crowdsourced information is statistically representative,” often crops up in conversations around election monitoring. The problem is largely one of language. The field of election monitoring is hardly new. Established organizations have been involved in election monitoring for decades and have gained a wealth of knowledge and experience in this area. For these organizations, the term “election monitoring” has specific connotations, such as random sampling and statistical analysis, verification, validation and accredited election monitors.

When partners use Ushahidi for election monitoring, I think they mean something different. What they generally mean is citizen-powered election monitoring aided by crowdsourcing. Does this imply that crowdsourced information is statistically representative of all the events taking place across a given country? Of course not: I’ve never heard anyone suggest that crowdsourcing is equivalent to random sampling.

Citizen-powered election monitoring is about empowering citizens to take ownership over their elections and to have a voice. Indeed, elections do not start and stop at the polling booth. Should we prevent civil society groups from crowdsourcing crisis information on the basis that their reports may not be statistically representative? No. This is not our decision to make and the data is not even meant for us.

Another language-related problem has to due with the term “crowdsourcing”. The word  “crowd” here can literally mean anyone (unbounded crowdsourcing) or a specific group (bounded crowdsourcing) such as designated election monitors. If these official monitors use Ushahidi and they are deliberately positioned across a country for random sampling purposes, then this becomes no different at all to standard and established approaches to election monitoring. Bounded crowdsourcing can be statistically representative.

The third misconception about Ushahidi has to do with the tradeoff between unbounded crowdsourcing and the validation of said crowdsourced information. One of the main advantages of unbounded crowdsourcing is the ability to collect a lot of information from a variety of sources and media—official and nonofficial sources—in near real time. Of course, this means that a lot more of information can be reported at once, which can make the validation of said information a challenging process.

A common reaction to this challenge is to dismiss crowdsourcing altogether because unofficial sources may be unreliable or at worse deliberately misleading. Some organizations thus find it easier to write off all unofficial content because of these concerns. Ushahidi takes a different stance. We recognize that user-generated content is not about to disappear any time soon and that a lot of good can come out of such content, not least because official information can too easily become proprietary and guarded instead of shared.

So we’re not prepared to write off user-generated content because validating information happens to be challenging. Crowdsourcing crisis information is our business and so is (obviously) the validation of crowdsourced information. This is why Ushahidi is fully committed to developing Swift River. Swift is a free and open source platform that validates crowdsourced information in near real-time. Follow the Ushahidi blog for exciting updates!

Crowdsourcing for Peace Mapping

Lynda Gratton at the London Business School gave one of the best Keynote speeches that I’ve heard all year. Her talk was a tour de force on how to catalyze innovation and one of her core recommendations really hit home for me: “If you really want to be at the cutting edge of innovation, then you better make sure that 20% of your team is under the age of 27.” Lynda upholds this principle in all her business ventures.

I find this absolutely brilliant, which explains why I prefer teaching undergraduate seminars and why I always try to keep in touch with former students. Without fail, they continue to be an invaluable source of inspiration and innovative thinking.

A former student of mine, Adam White, recently introduced me to another undergraduate student at Tufts University, Rachel Brown. Rachel is a perfect example of why I value interacting with bright young minds. She wants to return to Kenya next year to identify and connect local peace initiatives in Nairobi in preparation for the 2012 elections.

Rachel was inspired by the story of Solo 7, a Kenyan graffiti artist in Kibera who drew messages of peace throughout the slum as a way to prevent violence from escalating shortly after the elections. “Imagine,” she said, “if we could identify all the Solo 7’s of Nairobi, all the individuals and local communities engaged in promoting peace.”

I understood at once why Adam recommended I meet with Rachel: Ushahidi.

I immediately told Rachel about Ushahidi, a free and open source platform that uses crowdsourcing to map crisis information. I suggested she consider using the platform to crowdsource and map local peace initiatives across Kenya, not just Nairobi. I’ve been so focused on crisis mapping that I’ve completely ignored my previous work in the field of conflict early warning. An integral part of this field is to monitor indicators of conflict and cooperation.

There are always pockets of cooperation no matter how dire a conflict is. Even in Nazi Germany and the Rwandan genocide we find numerous stories of people risking their lives to save others. The fact is that most people, most of the time in most places choose cooperation over conflict. If that weren’t the case, we’d be living in state of total war as described by Clausewitz.

If we only monitor indicators of war and violence, then that’s all we’ll see. Our crisis maps only depict a small part of reality. It is incredibly important that we also map indicators of peace and cooperation. By identifying the positive initiatives that exist before and during a crisis, we automatically identify multiple entry points for intervention and a host of options for conflict prevention. If we only map conflict, then we may well identify where most of the conflict is taking place, but we won’t necessarily know who in the area might be best placed to intervene.

Documenting peace and cooperation also has positive psychological effects. How often do we lament the fact that the only kind of news available in the media is bad news? We turn on CNN or BBC and there’s bad news—sometimes breaking news of bad news. It’s easy to get depressed and to assume that only bad things happen. But violence is actually very rare statistically speaking. The problem is that we don’t systematically document peace, which means that our perceptions are completely skewed.

Take the following anecdote, which occurred to me several years ago when I taught my first undergraduate course on conflict early warning systems. I was trying to describe the important psychological effects of documenting peace and cooperation by using the example of the London underground (subway).

If you’ve been to London, you’ve probably experienced the frequent problems and delays with the underground system. And like most other subway systems, announcements are made to inform passengers of annoying delays and whatnot. But unlike other subway systems I’ve used, the London underground also makes announcements to let passengers know that all lines are currently running on time.

Now lets take this principle and apply it to Rachel’s project proposal combined with Ushahidi. Imagine if she were to promote the crowdsourcing of local peace initiatives all across Kenya. She could work with national and local media to get the word out. Individuals could send text messages to report what kinds of peace activities they are involved in.

This would allow Rachel and others to follow up on select text messages to learn more about each activity. In fact, she could use Ushahidi’s customizable reporting forms to ask individuals texting in information to elaborate on their initiatives. Rachel wants to commit no less than a year to this project, which should give her and colleagues plenty of time to map hundreds of local peace initiatives across Kenya.

Just imagine a map covered with hundreds of doves or peace dots representing local peace initiatives? What a powerful image. The Peace Map would be public, so that anyone with Internet access could learn about the hundreds of different peace initiatives in Kenya. Kenyan peace activists themselves could make use of this map to learn about creative approaches to conflict prevention and conflict management. They could use Ushashidi’s subscription feature to receive automatic updates when a new peace project is reported in their neighborhood, town or province.

When peace activists (and anyone else, for that matter) find peace projects they like on Ushahidi’s Peace Map, they can “befriend” that project, much like the friend feature in Facebook. That way they can receive updates from a particular project via email, SMS or even Twitter. These updates could include information on how to get involved. When two projects (or two individuals) are connected this way, Ushahidi could depict the link on the map with a line connecting the two nodes.

Imagine if this Peace Map were then shown on national television in the lead up to the elections. Not only would there be hundreds of peace dots representing individual peace efforts, but many of these would be linked, depicting a densely connected peace network.

The map could also be printed in Kenya’s national and local newspapers. I think a Peace Map of Kenya would send a powerful message that Kenyans want peace and won’t stand for a repeat of the 2007 post-election violence. When the elections do happen, this Peace Map could be used operationally to quickly respond to any signs of escalating tensions.

Rachel could use the Peace Map to crowdsource reports of any election violence that might take place. Local peace activists could use Ushahidi’s subscription feature to receive alerts of violent events taking place in their immediate vicinity. They would receive these via email and/or SMS in near real-time.

This could allow peace activists to mobilize and quickly respond to escalating signs of violence, especially if preparedness measures and contingency plans already in place. This is what I call fourth generation conflict early warning and early response (4G). See this blog post for more on 4G systems. This is where The Third Side framework for conflict resolution meets the power of new technology platforms like Ushahidi.

It is when I meet inspiring students like Rachel that I wish I were rich so I could just write checks to turn innovative ideas into reality. The next best thing I can do is to work with Rachel and her undergraduate friends to write up a strong proposal. So if you want to get involved or you know a donor, foundation or a philanthropist who might be interested in funding Rachel’s project, please do email me so I can put you directly in touch with her: Patrick@iRevolution.net.

In the meantime, if you’re about to start a project, remember Lynda’s rule of thumb: make sure 20% of your team is under 27. You won’t regret it.

Patrick Philippe Meier