Tag Archives: Web 2.0

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

New Tech in Emergencies and Conflicts: Role of Information and Social Networks

I had the distinct pleasure of co-authoring this major new United Nations Foundation & Vodafone Foundation Technology Report with my distinguished colleague Diane Coyle. The report looks at innovation in the use of technology along the time line of crisis response, from emergency preparedness and alerts to recovery and rebuilding.

“It profiles organizations whose work is advancing the frontlines of innovation, offers an overview of international efforts to increase sophistication in the use of IT and social networks during emergencies, and provides recommendations for how governments, aid groups, and international organizations can leverage this innovation to improve community resilience.”

Case studies include:

  • Global Impact and Vulnerability Alert System (GIVAS)
  • European Media Monitor (EMM, aka OPTIMA)
  • Emergency Preparedness Information Center (EPIC)
  • Ushahidi Crowdsourcing Crisis Information
  • Télécoms sans Frontières (TSF)
  • Impact of Social Networks in Iran
  • Social Media, Citizen Journalism and Mumbai Terrorist Attacks
  • Global Disaster Alert and Coordination System (GDACS)
  • InSTEDD RIFF
  • UNOSAT
  • AAAS Geospatial Technologies for Human Rights
  • Info Technology for Humanitarian Assistance, Cooperation and Action (ITHACA)
  • Camp Roberts
  • OpenStreetMap and Walking Papers
  • UNDP Threat and Risk Mapping Analysis project (TRMA)
  • Geo-Spatial Info Analysis for Global Security, Stability Program (ISFEREA)
  • FrontlineSMS
  • M-PESA and M-PAISA
  • Souktel

I think this long and diverse list of case studies clearly shows that the field of humanitarian technology is coming into it’s own.  Have a look at the report to learn how all these fit in the ecosystem of humanitarian technologies. And check out the tag #Tech4Dev on Twitter or the UN Foundation’s Facebook page to discuss the report and feel free to add any comments to this blog post below. I’m happy to answer all questions. In the meantime, I salute the UN Foundation for producing a forward looking report on projects that are barely two years old, and some just two months old.

Patrick Philippe Meier

Towards a “Theory” (or analogy) of Crisis Mapping?

The etymology of the word “theory” is particularly interesting. The word originates from the ancient Greek; theoros means “spectator,” from thea “a view” + horan “to see.” In 1638, theory was used to describe “an explanation based on observation and reasoning.” How fitting that the etymologies of “theory” resonate with the purpose of crisis mapping.

But is there a formal theory of crisis mapping per se?  There are little bits and pieces here and there, sprinkled across various disciplines, peer-reviewed journals and conference presentations. But I have yet to come across a “unified theory” of crisis mapping. This may be because the theory (or theories) are implicit and self-evident. Even so, there may be value in rendering the implicit—why we do crisis mapping—more visible.

Crises occur in time and space. Yet our study of crises (and conflict in particular) has generally focused on identifying trends over time rather than over space. Why? Because unlike the field of disaster management, we do not have seismographs scattered around the planet that  precisely pint point the source of escalating social tremors. This means that the bulk of our datasets describe conflict as an event happening in countries and years, not cities and days, let alone towns and hours.

This is starting to change thanks to several factors: political scientists are now painstakingly geo-referencing conflict data (example); natural language processing algorithms are increasingly able to extract time and place data from online media and user-generated content (example);  and innovative crowdsourcing platforms are producing new geo-referenced conflict datasets (example).

In other words, we have access to more disaggregated data, which allows us to study conflict dynamics at a more appropriate scale. By the way, this stands in contrast to the “goal of the modern state [which] is to reduce the chaotic, disorderly, constantly changing social reality beneath it to something more closely resembling the administrative grid of its observations” (1). Instead of Seeing Like a State, crisis mapping corrects the myopic grid to give us The View from Below.

Crises are patterns; by this I mean that crises are not random. Military or militia tactics are not random either. There is a method to the madnes—the fog of war not withstanding. Peace is also a pattern. Crisis mapping gives us the opportunity to detect peace and conflict patterns at a finer temporal and spatial resolution than previously possible; a resolution that more closely reflects reality at the human scale.

Why do scientists increasingly build more sophisticated microscopes? So they can get more micro-level data that might explain patterns at a macro-scale. (I wonder whether this means we’ll get to a point where we cannot reconcile quantum conflict mechanics with the general theory of conflict relativity). But I digress.

Compare analog televisions with today’s high-definition digital televisions. The latter is a closer reflection of reality. Or picture a crystal clear lake on a fine Spring day. You peer over the water and see the pattern of rocks on the bottom of the lake. You also see a perfect reflection of the leaves on the trees by the lake shore. If the wind picks up, however, or if rain begins to fall, the water drops cause ripples (“noise” in the data) that prevent us from seeing the same patterns as clearly. Crisis mapping calms the waters.

Keeping with the lake analogy, the ripples form certain patterns. Conflict is also the result of ripples in the socio-political fabric. The question is how to dampen or absorb the ripples without causing unintended ripples elsewhere? What kinds of new patterns might we generate to “cancel out” conflict patterns and amplify peaceful patterns? Thinking about patterns and anti-patterns in time and space may be a useful way to describe a theory of crisis mapping.

Some patterns may be more visible or detectable at certain temporal-spatial scales or resolutions than at others. Crisis mapping allows us to vary this scale freely; to see the Nazsca Lines of conflict from another perspective and at different altitudes. In short, crisis mapping allow us to escape the linear, two-dimensional world of Euclidean political science to see patterns that otherwise remain hidden.

In theory then, adding spatial data should improve the accuracy and explanatory power of conflict models. This should provide us with better and more rapid ways detect the patterns behind conflict ripples before they become warring tsunamis. But we need more rigorous and data-driven studies that demonstrate this theory in practice.

This is one theory of crisis mapping. Problem is, I have many others! There’s more to crisis mapping than modeling. In theory, crisis mapping should also provide better decision support, for example. Also, crisis mapping should theoretically be more conducive to tactical early response, not to mention monitoring & evaluation. Why? I’ll ramble on about that some other day. In the meantime, I’d be grateful for feedback on the above.

Patrick Philippe Meier

Towards a “Theory” (or analogy) of Crisis Mapping?

The etymology of the word “theory” is particularly interesting. The word originates from the ancient Greek; theoros means “spectator,” from thea “a view” + horan “to see.” In 1638, theory was used to describe “an explanation based on observation and reasoning.” How fitting that the etymologies of “theory” resonate with the purpose of crisis mapping.

But is there a formal theory of crisis mapping per se?  There are little bits and pieces here and there, sprinkled across various disciplines, peer-reviewed journals and conference presentations. But I have yet to come across a “unified theory” of crisis mapping. This may be because the theory (or theories) are implicit and self-evident. Even so, there may be value in rendering the implicit—why we do crisis mapping—more visible.

Crises occur in time and space. Yet our study of crises (and conflict in particular) has generally focused on identifying trends over time rather than over space. Why? Because unlike the field of disaster management, we do not have seismographs scattered around the planet that  precisely pint point the source of escalating social tremors. This means that the bulk of our datasets describe conflict as an event happening in countries and years, not cities and days, let alone towns and hours.

This is starting to change thanks to several factors: political scientists are now painstakingly geo-referencing conflict data (example); natural language processing algorithms are increasingly able to extract time and place data from online media and user-generated content (example);  and innovative crowdsourcing platforms are producing new geo-referenced conflict datasets (example).

In other words, we have access to more disaggregated data, which allows us to study conflict dynamics at a more appropriate scale. By the way, this stands in contrast to the “goal of the modern state [which] is to reduce the chaotic, disorderly, constantly changing social reality beneath it to something more closely resembling the administrative grid of its observations” (1). Instead of Seeing Like a State, crisis mapping corrects the myopic grid to give us The View from Below.

Crises are patterns; by this I mean that crises are not random. Military or militia tactics are not random either. There is a method to the madnes—the fog of war not withstanding. Peace is also a pattern. Crisis mapping gives us the opportunity to detect peace and conflict patterns at a finer temporal and spatial resolution than previously possible; a resolution that more closely reflects reality at the human scale.

Why do scientists increasingly build more sophisticated microscopes? So they can get more micro-level data that might explain patterns at a macro-scale. (I wonder whether this means we’ll get to a point where we cannot reconcile quantum conflict mechanics with the general theory of conflict relativity). But I digress.

Compare analog televisions with today’s high-definition digital televisions. The latter is a closer reflection of reality. Or picture a crystal clear lake on a fine Spring day. You peer over the water and see the pattern of rocks on the bottom of the lake. You also see a perfect reflection of the leaves on the trees by the lake shore. If the wind picks up, however, or if rain begins to fall, the water drops cause ripples (“noise” in the data) that prevent us from seeing the same patterns as clearly. Crisis mapping calms the waters.

Keeping with the lake analogy, the ripples form certain patterns. Conflict is also the result of ripples in the socio-political fabric. The question is how to dampen or absorb the ripples without causing unintended ripples elsewhere? What kinds of new patterns might we generate to “cancel out” conflict patterns and amplify peaceful patterns? Thinking about patterns and anti-patterns in time and space may be a useful way to describe a theory of crisis mapping.

Some patterns may be more visible or detectable at certain temporal-spatial scales or resolutions than at others. Crisis mapping allows us to vary this scale freely; to see the Nazsca Lines of conflict from another perspective and at different altitudes. In short, crisis mapping allow us to escape the linear, two-dimensional world of Euclidean political science to see patterns that otherwise remain hidden.

In theory then, adding spatial data should improve the accuracy and explanatory power of conflict models. This should provide us with better and more rapid ways detect the patterns behind conflict ripples before they become warring tsunamis. But we need more rigorous and data-driven studies that demonstrate this theory in practice.

This is one theory of crisis mapping. Problem is, I have many others! There’s more to crisis mapping than modeling. In theory, crisis mapping should also provide better decision support, for example. Also, crisis mapping should theoretically be more conducive to tactical early response, not to mention monitoring & evaluation. Why? I’ll ramble on about that some other day. In the meantime, I’d be grateful for feedback on the above.

Patrick Philippe Meier

Folksomaps: Gold Standard for Community Mapping

There were a number of mapping-related papers, posters and demo’s at ICTD2009. One paper in particular caught my intention given the topic’s direct relevance to my ongoing consulting work with the UN’s Threat and Risk Mapping Analysis (TRMA) project in the Sudan and the upcoming ecosystem project in Liberia with Ushahidi and Humanity United.

Introduction

Entitled “Folksomaps – Towards Community Intelligent Maps for Developing Regions,” the paper outlines a community-driven approach for creating maps by drawing on “Web 2.0 principles” and “Semantic Web technologies” but without having to rely entirely on a web-based interface. Indeed, Folksomaps “makes use of web and voice applications to provide access to its services.”

I particularly value the authors’ aim to “provide map-based services that represent user’s intuitive way of finding locations and directions in developing regions.” This is an approach that definitely resonates with me. Indeed, it is our responsibility to adapt and customize our community-based mapping tools to meet the needs, habits and symbology of the end user; not the other way around.

I highly recommend this paper (or summary below) to anyone doing work in the crisis mapping field. In fact, I consider it required reading. The paper is co-authored by Arun Kumar, Dipanjan Chakraborty, Himanshu Chauhan, Sheetal Agarwal and Nitendra Rajput of IBM India Research Lab in New Delhi.

Background

Vast rural areas of developing countries do not have detailed maps or mapping tools. Rural populations are generally semi-literate, low-income and non-tech savvy. They are hardly like to have access to neogeography platforms like Google Earth. Moreover, the lack of electricity access and Internet connection also complicates the situation.

We also know that cities, towns and villages in developing countries “typically do not have well structured naming of streets, roads and houses,” which means “key landmarks become very important in specifying locations and directions.”

Drawing on these insights, the authors seek to tap the collective efforts of local communities to populate, maintain and access content for their own benefit—an approach I have described as crowdfeeding.

Surveys of Tech and Non-Tech Users

The study is centered on end-user needs, which is rather refreshing. The authors carried out a series of surveys to be better understand the profiles of end-users, e.g., tech and non-tech users.

The first survey sought to identify answers to the following questions:

  • How do people find out points of interest?
  • How do much people rely on maps versus people on the streets?
  • How do people provide local information to other people?
  • Whether people are interested in consuming and feeding information for a community-driven map system?

The results are listed in the table below:

folksotb1

Non-tech savvy users did not use maps to find information about locations and only 36% of these users required precise information. In addition, 75% of non-tech respondents preferred the choice of a phone-based interface, which really drives home the need for what I have coined “Mobile Crisis Mapping” or MCM.

Tech-users also rely primarily on others (as opposed to maps) for location related information. The authors associate this result with the lack of signboards in countries like India. “Many a times, the maps do not contain fine-grained information in the first place.”

Most tech-users responded that a phone-based location and direction finding system in addition to a web-based interface. Almost 80% expressed interest in “contributing to the service by uploading content either over the phone or though a web-based portal.”

The second survey sought to identify how tech and non-tech users express directions and local information. For example:

  • How do you give directions to people on the road or to friends?
  • How do you describe proximity of a landmark to another one?
  • How do you describe distance? Kilometers or using time-to-travel?

The results are listed in the table below:

folksotb2

The majority of non-tech savvy participants said they make use of landmarks when giving directions. “They use names of big roads […] and use ‘near to’, ‘adjacent to’, ‘opposite to’ relations with respect to visible and popular landmarks […].” Almost 40% of responders said they use time only to describe the distance between any two locations.

Tech-savvy participants almost always use both time and kilometers as a measure to represent distance. Only 10% or so of participants used kilometers only to represent distance.

The Technology

The following characteristics highlight the design choices that differentiate Folksomaps from established notions of map systems:

  • Relies on user generated content rather than data populated by professionals;
  • Strives for spatial integrity in the logical sense and does not consider spatial integrity in the physical sense as essential (which is a defining feature of social maps);
  • Does not consider visual representation as essential, which is important considering the fact that a large segment of users in developing countries do not have access to Internet (hence my own emphasis on mobile crisis mapping);
  • Is non-static and intelligent in the sense that it infers new information from what is entered by the users.
  • User input is not verified by the system and it is possible that pieces of incorrect information in the knowledgebase may be present at different points of time. Folksomaps adopts the Wiki model and allows all users to add, edit and remove content freely while keeping maps up-to-date.

Conceptual Design

Folksomaps uses “landmark” as the basic unit in the mapping knowledgebase model while “location” represents more coarse-grained geographical areas such as a village, city or country. The model then seeks to capture a few key logical characteristics of locations such as direction, distance, proximity and reachability and layer.

The latter constitutes the granularity of the geographic area that a location represents. “The notion of direction and distance from a location is interpreted with respect to the layer that the location represents. In other words, direction and distance could be viewed as binary operator over locations of the same level. For instance, ‘is towards left of ’ would be appropriate if the location pair being considered is <Libya, Egypt>,” but not if the pair is <Nairobi, India>.

The knowledgebase makes use of two modules, the Web Ontology Language (OWL) and a graph database, to represent and store the above concepts. The Semantic Web language OWL is used to model the categorical characteristics of a landmark (e.g., direction, proximity, etc), and thence infer new relationships not explicitly specified by users of the system. In other words, OWL provides an ontology of locations.

The graph database is used represent distance (numerical relationships) between landmarks. “The locations are represented by nodes and the edges between two nodes of the graph are labeled with the distance between the corresponding locations.” Given the insights gained from user surveys, precise distances and directions are not integral components of community-based maps.

The two modules are used to generate answers to queries submitted by users.

User Interaction

The authors rightly recognize that the user interface design is critical to the success of community-based mapping projects. To be sure, users of may be illiterate, or semi-illiterate and not very tech-savvy. Furthermore, users will tend to query the map system when they need it most, e.g., “when they are stuck on the road looking for directions […] and would be pressed for time.” This very much holds true for crisis mapping as well.

Users can perform three main tasks with the system: “find place”, “trace path” and “add info.” In addition, some or all users may be granted the right to edit or remove entries from the knowledgebase. The Folksomaps system can also be bootstrapped from existing databases to populate instances of location types. “Two such sources of data in the absence of a full-fledged Geographical Information System (GIS) come from the Telecom Industry and the Postal Department.”

folksofig3

How the users interface with the system to carry out these tasks will depend on how tech-savvy or literate they are and what type of access they have to information and communication technologies.

Folksomaps thus provides three types of interface: web-based, voice-based and SMS-based. Each interface allows the user to query and update the database. The web-based interface was developed using Java Server Pages (JSP) while the voice-based interface uses JSPs and VoiceXML.

folksofig41

I am particularly interested in the voice-based interface. The authors point to previous studies that suggest a voice-based interaction works well with users who are illiterate or semi-illiterate and who cannot afford to have high-end devices but can use ordinary low-end phones.

folksofig1

I will share this with the Ushahidi development team with the hopes that they will consider adding a voice-based interface for the platform later this year. To be sure, could be very interesting to integrate Freedom Fone’s work in this area.

Insights from User Studies

The authors conducted user studies to verify the benefit and acceptability of Folksomaps. Tech-savvy used the web-based interface while non-tech savvy participants used the voice-based interface. The results are shown in the two tables below.

folksotb3

Several important insights surfaced from the results of the user studies. For example, an important insight gained from the non-tech user feedback was “the sense of security that they would get with such a system. […] Even though asking for travel directions from strangers on the street is an option, it exposes the enquirer to criminal elements […].”

Another insight gain was the fact that many non-tech savvy participants were willing to pay for the call even a small premium over normal charges as they saw value to having this information available to them at all times.” That said, the majority of participants “preferred the advertisement model where an advertisement played in the beginning of the call pays for the entire call.”

Interestingly, almost all participants preferred the voice-based interface over SMS even though the former led to a number of speech recognition errors. The reason being that “many people are either not comfortable using SMS or not comfortable using a mobile phone itself.”

There were also interesting insights on the issue of accuracy from the perspective of non-tech savvy participants. Most participants asked for full accuracy and only a handful were tolerant of minor mistakes. “In fact, one of the main reasons for preferring a voice call over asking people for directions was to avoid wrong directions.”

This need for high accuracy is driven by the fact that most people use public transportation, walk or use a bicycle to reach their destination, which means the cost of incorrect information is large compared to someone who owns a car.

This is an important insight since the authors had first assumed that tolerance for incorrect information was higher. They also learned that meta information is as important to non-tech savvy users as the landmarks themselves. For instance, low-income participants were more interested in knowing the modes of available transportation, timetables and bus route numbers than the road route from a source to a destination.

folkstb4

In terms of insights from tech-savvy participants, they did not ask for fine-grained directions all the time. “They were fight with getting high level directions involving major landmarks.” In addition, the need for accuracy was not as strong as for the non-tech savvy respondents and they preferred the content from the queries sent to them via SMS so they could store it for future access, “pointing out that it is easy to forget the directions if you just hear it.”

Some tech-savvy participants also suggested that the directions provided by Folksomaps should “take into consideration the amount of knowledge the subject already has about the area, i.e., it should be personalized based upon user profile. Other participants mentioned that “frequent changes in road plans due to constructions should be captured by such a system—thus making it more usable than just getting directions.”

Conclusion

In sum, the user interface of Folksomaps needs to be “rich and adaptive to the information needs of the user […].” To be sure, given user preference towards “voice-based interface over SMS, designing an efficient user-friendly voice-based user interface […].” In addition, “dynamic and real-time information augmented with traditional services like finding directions and locations would certainly add value to Folksomaps.” Furthermore, the authors recognize that Folksomaps can “certainly benefit from user interface designs,” and “multi-model front ends.”

Finally, the user surveys suggest “the community is very receptive towards the concept of a community-driven map,” so it is important that the TRMA project in the Sudan and the ecosystem Liberia project build on the insights and lessons learned provided in this study.

Patrick Philippe Meier

ISA 2009: Digital Technologies in Kenya’s Post Election Crisis

The fourth presentation at the ISA panel that I’m chairing will feature research by Joshua Goldstein and Juliana Rotich on the role of digital networked technologies during Kenya’s post-election violence (PDF). Blog posts on the other three presentations are available here on human rights, here on political activism and here on digital resitance.

Introduction

Josh and Juliana pose the following question: do mobile phones and the Internet promote transparency and good governance or do they promote hate speech and conflict? The authors draw on the 2007-2008 Kenyan presidential elections to assess the impact of digitally networked technologies, specifically mobile phones and the Internet, on the post-election violence.

This study is an important contribution to the scholarly research on the impact of digital technology on democracy since the majority of the existing literature is largely written through the lens of established, Western democracies. The literature thus “excludes the experience of Sub-Saharan Africa, where meaningful access to digital tools is only beginning to emerge, but where the struggle between failed state and functioning democracy are profound.”

Case Study

Josh and Juliana draw on Kenya as a case study to assess the individual impact of mobile phones and the Internet on the post-election violence. The mobile phone is the most widely used digital application in Kenya and the rest of Africa. The low cost and ease of texting explains how quickly “hate SMS” began circulating after Kenya’s election day. Some examples of the messages texted:

Fellow Kenyans, the Kikuyu’s have stolen our children’s future… we must deal with them in a way they understand… violence.

No more innocent Kikuyu blood will be shed. We will slaughter them right here in the capital city. For justice, compile a list of Luo’s you know… we will give you numbers to text this information.

The authors are concerned about the troubling trend of hate SMS in East Africa citing a violent icident in neighboring Uganda that was organized via SMS to protest the government’s sale of a forest to a company. As they note, “mass SMS tools are remarkably useful for organizing this type of explicit, systematic, and publicly organized campaign of mob violence.”

However, the authors also recognize that “since SMS, unlike radio, is a multi-directional tool, there is also hope that voices of moderation can make themselves heard.” They point to the response taken by Michael Joseph, the CEO of Kenya’s largest mobile phone provider Safaricom when he was asked by government officials to consider shutting down the SMS system:

Joseph convinced the government not to shut down the SMS system, and instead to allow SMS providers to send out messages of peace and calm, which Safaricom did to all nine million of its customers.

Josh and Juliana also note that tracking and identifying individuals that promote hate speech is relatively easy for governments and companies to do. “In the aftermath of the violence, contact information for over one thousand seven hundred individuals who allegedly promoted mob violence was forwarded to the Government of Kenya.” While Kenya didn’t have a law to prosecute hate SMS, the Parliament has begun to create such a law.

The Internet in Kenya was also used for predatory and civic speech. For example, “the leading Kenyan online community, Mashahada, became overwhelmed with divisive and hostile messages,” which prompted the moderators to “shut down the site, recognizing that civil discourse was rapidly becoming impossible.”

However, David Kobia, the administrator of Mashahada, decided to launch a new site a few days later explicitly centered on constructive dialogue. The site, “I Have No Tribe,” was successful in promoting a more constructive discourse and demonstrates “that one possible response to destructive speech online is to encourage constructive speech.”

Mobile phones and the Internet were combined by Ushahidi to crowdsource human rights violation during the post-election violence. The authors contend that the Ushahidi platform is “revolutionary for human rights campaigns in the way that Wikipedia is revolutionary for encyclopedias; they are tools that allow cooperation on a massive scale.” I have already blogged extensively about Ushahidi here and here so will not expand on this point other than to emphasize that Ushahidi was not used to promote hate speech.

Josh and Juliana also draw on the role of Kenya’s citizen journalists to highlight another peaceful application of digital technologies. As they note, Kenya has one of the richest blogging traditions in sub-Saharan Africa, which explains why,

Kenyan bloggers became a critical part of the conversation [when] the web traffic from within Kenya shot through the roof. The influence ballooned further when radio broadcasters began to read influential bloggers over the airwaves, helping them reach [...] 95% of the Kenyan population.”

When the Government of Kenya declared a ban on live news coverage on December 30, 2007, Kenyan bloggers became indispensable in their role as citizen journalists. [...] Blogs challenged the government’s version of events as they unfolded.

[...] Further, Blogs became a critical source of information for Kenyans in Nairobi and the diaspora. Rumors spread via SMS were dispelled via an online dialogue that took place on blogs and in the comments section of blogs.

Conclusion

When we talk about the ‘networked public sphere,’ we are usually referring to a Western public sphere; one that facilitates public discourse, increased transparency and positive cooperation. However, as the case study above demonstrates, the narrative is more involved when we talk about an African or Kenyan ‘networked public sphere.’ Indeed, the authors conclude that digital networked technologies catalyzed both “predatory behavior such as ethnic-based mob violence and civic behavior such as journalism and human rights campaigns.”

Several questions remain to be addressed in further research. Namely, how important is a vibrant blogosphere to promote positive applications of digital technologies in times of crises? Are networked digital technologies like Ushahidi more susceptible to positive uses than predatory uses? And finally, how does the Kenya case compare to others like the Orange Revolution in the Ukraine?

Patrick Philippe Meier

ISA 2009: Digital Technologies in Kenya’s Post Election Crisis

The fourth presentation at the ISA panel that I’m chairing will feature research by Joshua Goldstein and Juliana Rotich on the role of digital networked technologies during Kenya’s post-election violence (PDF). Blog posts on the other three presentations are available here on human rights, here on political activism and here on digital resitance.

Introduction

Josh and Juliana pose the following question: do mobile phones and the Internet promote transparency and good governance or do they promote hate speech and conflict? The authors draw on the 2007-2008 Kenyan presidential elections to assess the impact of digitally networked technologies, specifically mobile phones and the Internet, on the post-election violence.

This study is an important contribution to the scholarly research on the impact of digital technology on democracy since the majority of the existing literature is largely written through the lens of established, Western democracies. The literature thus “excludes the experience of Sub-Saharan Africa, where meaningful access to digital tools is only beginning to emerge, but where the struggle between failed state and functioning democracy are profound.”

Case Study

Josh and Juliana draw on Kenya as a case study to assess the individual impact of mobile phones and the Internet on the post-election violence. The mobile phone is the most widely used digital application in Kenya and the rest of Africa. The low cost and ease of texting explains how quickly “hate SMS” began circulating after Kenya’s election day. Some examples of the messages texted:

Fellow Kenyans, the Kikuyu’s have stolen our children’s future… we must deal with them in a way they understand… violence.

No more innocent Kikuyu blood will be shed. We will slaughter them right here in the capital city. For justice, compile a list of Luo’s you know… we will give you numbers to text this information.

The authors are concerned about the troubling trend of hate SMS in East Africa citing a violent icident in neighboring Uganda that was organized via SMS to protest the government’s sale of a forest to a company. As they note, “mass SMS tools are remarkably useful for organizing this type of explicit, systematic, and publicly organized campaign of mob violence.”

However, the authors also recognize that “since SMS, unlike radio, is a multi-directional tool, there is also hope that voices of moderation can make themselves heard.” They point to the response taken by Michael Joseph, the CEO of Kenya’s largest mobile phone provider Safaricom when he was asked by government officials to consider shutting down the SMS system:

Joseph convinced the government not to shut down the SMS system, and instead to allow SMS providers to send out messages of peace and calm, which Safaricom did to all nine million of its customers.

Josh and Juliana also note that tracking and identifying individuals that promote hate speech is relatively easy for governments and companies to do. “In the aftermath of the violence, contact information for over one thousand seven hundred individuals who allegedly promoted mob violence was forwarded to the Government of Kenya.” While Kenya didn’t have a law to prosecute hate SMS, the Parliament has begun to create such a law.

The Internet in Kenya was also used for predatory and civic speech. For example, “the leading Kenyan online community, Mashahada, became overwhelmed with divisive and hostile messages,” which prompted the moderators to “shut down the site, recognizing that civil discourse was rapidly becoming impossible.”

However, David Kobia, the administrator of Mashahada, decided to launch a new site a few days later explicitly centered on constructive dialogue. The site, “I Have No Tribe,” was successful in promoting a more constructive discourse and demonstrates “that one possible response to destructive speech online is to encourage constructive speech.”

Mobile phones and the Internet were combined by Ushahidi to crowdsource human rights violation during the post-election violence. The authors contend that the Ushahidi platform is “revolutionary for human rights campaigns in the way that Wikipedia is revolutionary for encyclopedias; they are tools that allow cooperation on a massive scale.” I have already blogged extensively about Ushahidi here and here so will not expand on this point other than to emphasize that Ushahidi was not used to promote hate speech.

Josh and Juliana also draw on the role of Kenya’s citizen journalists to highlight another peaceful application of digital technologies. As they note, Kenya has one of the richest blogging traditions in sub-Saharan Africa, which explains why,

Kenyan bloggers became a critical part of the conversation [when] the web traffic from within Kenya shot through the roof. The influence ballooned further when radio broadcasters began to read influential bloggers over the airwaves, helping them reach [...] 95% of the Kenyan population.”

When the Government of Kenya declared a ban on live news coverage on December 30, 2007, Kenyan bloggers became indispensable in their role as citizen journalists. [...] Blogs challenged the government’s version of events as they unfolded.

[...] Further, Blogs became a critical source of information for Kenyans in Nairobi and the diaspora. Rumors spread via SMS were dispelled via an online dialogue that took place on blogs and in the comments section of blogs.

Conclusion

When we talk about the ‘networked public sphere,’ we are usually referring to a Western public sphere; one that facilitates public discourse, increased transparency and positive cooperation. However, as the case study above demonstrates, the narrative is more involved when we talk about an African or Kenyan ‘networked public sphere.’ Indeed, the authors conclude that digital networked technologies catalyzed both “predatory behavior such as ethnic-based mob violence and civic behavior such as journalism and human rights campaigns.”

Several questions remain to be addressed in further research. Namely, how important is a vibrant blogosphere to promote positive applications of digital technologies in times of crises? Are networked digital technologies like Ushahidi more susceptible to positive uses than predatory uses? And finally, how does the Kenya case compare to others like the Orange Revolution in the Ukraine?

Patrick Philippe Meier

New Course on Digital Democracy (Updated)

As mentioned in a previous blog entry, my colleague Joshua Goldstein and I are teaching a new full-semester undergraduate course on Digital Democracy. The course is being offered as part of Tufts University‘s interdisciplinary Media and Communication Studies Program.

The course will address the following topics:

  • Introduction to Digital Democracy
  • American Democracy
  • Global Democracy
  • Media and Democracy
  • Guest Speakers: Digital Democracy
  • Bloggers Rights
  • Digital Censorship and Democracy
  • Human Rights 2.0
  • Digital Activism
  • Digital Resistance
  • Digital Technology in Developing World
  • Class Presentations

The course wiki along with the syllabus is available here. We regularly update the syllabus so do check back. Feedback on the syllabus is also very much welcomed.

We are particularly keen for suggestions vis-a-vis recommended material (websites, online videos, links, books, papers etc.) and in-class activities.

Patrick Philippe Meier

Job: Satellite Imagery & Conflict Specialist

The European Union’s Information Support for Effective and Rapid External Action (ISFEREA) is looking for a conflict specialist post-doc researcher. I haven’t posted job openings before but this one from my colleagues at the Joint Research Center (JRC) is especially relevant to iRevolution’s focus.

Background: ISFEREA develops techniques for automatic image processing of digital images acquired via satellite platforms as well as methodologies to explore the links between conflict risk and the exploitation (and degradation) of natural resources such as minerals. In particular, very high resolution (VHR) sensors with meter and sub-meter spatial resolution are being tested for multi-spectral and multi-temporal analysis.

Applications fields are related to human security, conflict resource monitoring, post-disaster damage assessment, and analysis of human settlements, including temporary settlements and refugee camps

The candidate will conduct research on conflict risk modelling and links between natural resources and conflicts. She/he would contribute to:

  1. Collecting, organizing and analyzing all available data sources on conflicts, political tensions/crises, and some types of natural resources;
  2. Developing modelling scenarios and applying them to study the relationships between natural resources and armed conflicts as well as political instability.

The position presumes the will and the interest of the candidate to publish the results of his/her work in peer reviewed publications.

Requirements: University degree in political or social sciences; PhD degree in similar discipline or 5 years of relevant work experience, especially in conflict studies; good knowledge of at least one of the following three regions: African Great Lakes, Horn of Africa and Central Asia; good oral and written communication skills in English; team player and collaborative, proactive in research, capacity to learn and adaptability to stress.

Duration: 36 months

Applications Due: before 11 Jan, 2009 – 23:59:59 CET

Please follow this link for further information.

Patrick Philippe Meier

Conference – New Challenges for Human Rights Communications

HURIDOCS

I was just invited to participate on a panel at the Human Rights Information and Documentation Systems, International (HURIDOCS) Conference in Geneva, February 25-27, 2009.

The panel will be part of Plenary IV: Trends in Information Technology and Human Rights. The other panelists include my good friend Lars Bromley from AAAS and:

  • Florence Devouard, Chair Emeritus of the Wikimedia Foundation
  • Dan Brickley, developer of Semantic Web technologies
  • Jan Kleijsen, Director of Human Rights Standard Setting, Council of Europe

Lars will also be leading a workshop on “Satellite Imagery and Mapping” which I look forward to attending. I also plan to attend Sam Gregory’s workshop on “Video Advocacy“. Sam is the Program Director of Witness.

I plan to sit in on Plenary III entitled: Drawing Together the Common Information Needs. I’m particularly interested in uses of satellite imagery by the International Criminal Court (ICC) and have had several conversations on this with my colleague Russ Schimmer based on his remote sensing work in Darfur.

Another perk of attending this conference is that the LIFT Conference will be taking place on the same days at the same location. So I really hope to attend some of the LIFT panels if time permits.

Patrick Philippe Meier