Monthly Archives: February 2010

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


Incoming Text Messages


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

Using Mechanical Turk to Crowdsource Humanitarian Response

I’m increasingly intrigued by the idea of applying Mechanical Turk services to humanitarian response. Mechanical Turk was first developed by Amazon to crowdsource and pay for simple tasks.

An excellent example of a Mechanical Turk service in the field of ICT for Development (ICT4D) is txteagle, a platform that enables mobile phone subscribers in developing countries to earn money and accumulate savings by completing simple SMS-based micro-tasks for large corporate clients. txteagle has been used to translate pieces of text by splitting them into individual words and sending these out by SMS. Subscribers can then reply with the translation and earn some money in the process. This automatic compensation system uses statistical machinery to automatically evaluate the value of submitted work.

In Haiti, Samasource and Crowdflower have partnered with Ushahidi and FrontlineSMS to set up a Mechanical Turk service called “Mission 4636“. The system that Ushahidi and partners originally set up uses the generosity of Haitian volunteers in the US to translate urgent SMS’s from the disaster affected population in near real-time. Mission 4636 will relocate the translation work to Haiti and become an automatic compensation system for Haitian’s in-country.

At Ushahidi, we aggregate and  categorize urgent, actionable information from multiple sources including SMS and geo-tag this information on the Ushahidi’s interactive mapping platform. In the case of Haiti, this work is carried out by volunteers in Boston, Geneva, London and Portland coordinated by the Ushahidi-Haiti Situation Room at Tufts University. Volunteer retention is often a challenge, however. I wonder whether we an automated compensation system could be used to sustain future crisis mapping efforts.

Another challenge of crowdsourcing crisis information is tracking response. We know for a fact that a number of key responders are following our near real-time mapping efforts but knowing which reports they respond to is less than automatic. We have been able to document a number of success stories and continue to receive positive feedback from responders themselves but this information is hard to come by.

In a way, by crisis mapping actionable information in near real-time and in the public domain, we are in effect trying to crowdsource response. This, by nature, is a distributed and decentralized process, hence difficult to track. The tracking challenge is further magnified when the actors in question are relief and aid organizations responding to a large disaster. As anyone who has worked in disaster response knows, communicating who is doing what, where and when is not easy. Responders don’t have the bandwidth to document which reports they’ve responded to on Ushahidi.

This is problematic for several reasons including coordination. Organizations don’t necessarily know who is responding to what and whether this response is efficient. I wonder whether a Mechanical Turk system could be set up to crowdsource discrete response tasks based on individual organizations’ mandates. Sounds a little far out and may not be feasible, but the idea nevertheless intrigues me.

The automatic compensation system could be a public way to compensate response. Incoming SMS’s could be clustered along the UN Cluster system. The Shelter Cluster, for example, would have a dedicated website to which all shelter-related SMS’s would be pushed to. Organizations working in this space would each have access to this password protected website and tag the alerts they can and want to respond to.

In order to “cash in” following a response, a picture (or text based evidence) has to be submitted as proof, by the organization in question e.g., of new shelters being built. The number of completed responses could also be made public and individuals compelled to help, could send donations via SMS to each organization to reward and further fund the responses.

The task of evaluating the evidence of responses can also be crowdsource à la Mechanical Turk and serve as a source of revenue for beneficiaries.

For example, local Haitian subscribers to the system would receive an SMS notifying them that new shelters have been set up near Jacmel. Only subscribers in the Jacmel area would receive the SMS. They would then have a look for themselves to see whether the new shelters were in fact there and text back accordingly. Dozens of individuals could send in SMS’s to describe their observations which would further help triangulate the veracity of the evaluation à la Swift River. Note that the Diaspora could also get involved in this. And like txteagle, statistical machinery could also  be used to automatically evaluate the response and dispense the micro-compensations.

I have no doubt there are a number of other important kinks to be ironed out but I wanted to throw this out there now to get some preliminary feedback. This may ultimately not be feasible or worthwhile. But I do think that a partnership between Ushahidi and Crowdflower makes sense, not only in Haiti but for future deployments as well.

See also:

  • Digital Humanitarian Response: Moving from Crowdsourcing to Microtasking [Link]

How To Royally Mess Up Disaster Response in Haiti

I have to find an outlet other than this one to vent my frustrations at this time, which is why I deleted the 5 paragraphs that followed about 3 times. Not to worry, I saved them in a Word document. Good, now that I’ve got the venting part over with, lets play a crowdsourcing game.

I’d love to get your thoughts on the Top 10 ways to mess up disaster response in Haiti using information and communication technology. Suggestions can be completely made up, they can be jokes, serious commentary, witty remarks, predictions, actual observations, and so on, you get the idea. Feel free to post your comments below (anonymously if you wish), but no insults or accusations please, or else I’ll have to delete them.

I’ll keep this game open for 7 days and will post the best results on a new blog post. The person with the best comment will get a free invitation to the:

2nd International Conference on Crisis Mapping (ICCM 2010):
Haiti and Beyond

Patrick Philippe Meier