Category Archives: Digital Activism

Self-Organized Crisis Response to #BostonMarathon Attack

I’m going to keep this blog post technical because the emotions from yesterday’s events are still too difficult to deal with. Within an hour of the bombs going off, I received several emails asking me to comment on the use of social media in Boston and how it differed to the digital humanitarian response efforts I am typically engaged in. So here are just a few notes, nothing too polished, but some initial reactions.

I Stand with Boston

Once again, we saw the outpouring of operational support from the “Crowd” with over two thousand people in the Boston area volunteering to take people in if they needed help, and this within 60 minutes of the attack. This was coordinated via a Google Spreadsheet & Google Form. This is not the first time that these web-based solutions were used for disaster response. For example, Google Spreadsheets was used to coordinate grassroots response efforts during the major Philippine floods in 2012.

We’re not all affected the same way during a crisis and those of us who are less affected almost always look for ways to help. Unlike the era of television broadcasting, the crowd can now become an operational actor in disaster response. To be sure, paid disaster response professionals cannot be everywhere at the same time, but the crowd is always there. This explains I have look called for a “Match.com for disaster response” to match local needs with local resources. So while I received numerous pings on Twitter, Skype and email about launching a crisis map for Boston, I am skeptical that doing so would have added much value.

What was/is needed is real-time filtering of social media content and matching of local needs (information and material needs) with local resources. There are two complementary ways to do this: human computing (e.g., crowdsourcing, microtasking, etc) and machine computing (natural language processing, machine learning, etc), which is why my team and I at QCRI are working on developing these solutions.

Other observations from the response to yesterday’s tragedy:

  • Boston Police made active use of their Twitter account to inform and advise. They also asked other Twitter users to spread their request for everyone to leave the city center area. The police and other emergency services also actively crowdsourced photographs and video footage to begin their criminal investigations. There was such heavy multimedia social media activity in the area that one could no doubt develop a Photosynth rendering of the scene.
  • There were calls for residents to unlock their Wifi networks to enable people in the streets to get access to the Internet. This was especially important after the cellphone network was taken offline for security reasons. To be sure, access to information is equally important as access to water, food, shelter, etc, during a crisis.

I’d welcome any other observation from readers, e.g., similarities and differences between the use of technologies for domestic emergency management versus international humanitarian efforts. I would also be interested to hear thoughts about how the two could be integrated or at the very least learn from each other.

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Humanitarianism in the Network Age: Groundbreaking Study

My colleagues at the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) have just published a groundbreaking must-read study on Humanitarianism in the Network Age; an important and forward-thinking policy document on humanitarian technology and innovation. The report “imagines how a world of increasingly informed, connected and self-reliant communities will affect the delivery of humanitarian aid. Its conclusions suggest a fundamental shift in power from capital and headquarters to the people [that] aid agencies aim to assist.” The latter is an unsettling prospect for many. To be sure, Humanitarianism in the Network Age calls for “more diverse and bottom-up forms of decision-making—something that most Governments and humanitarian organizations were not designed for. Systems constructed to move information up and down hierarchies are facing a new reality where information can be generated by any-one, shared with anyone and acted by anyone.”

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The purpose of this blog post (available as a PDF) is to summarize the 120-page OCHA study. In this summary, I specifically highlight the most important insights and profound implications. I also fill what I believe are some of the report’s most important gaps. I strongly recommend reading the OCHA publication in full, but if you don’t have time to leaf through the study, reading this summary will ensure that you don’t miss a beat. Unless otherwise stated, all quotes and figures below are taken directly from the OCHA report.

All in all, this is an outstanding, accurate, radical and impressively cross-disciplinary study. In fact, what strikes me most about this report is how far we’ve come since the devastating Haiti Earthquake of 2010. Just three short years ago, speaking the word “crowdsourcing” was blasphemous, like “Voldermort” (for all you Harry Potter fans). This explains why some humanitarians called me the CrowdSorcerer at the time (thinking it was a derogatory term). CrisisMappers was only launched three months before Haiti. The Standby Volunteer Task Force (SBTF) didn’t even exist at the time and the Digital Humanitarian Network (DHN) was to be launched 2 years hence. And here we are, just three short years later, with this official, high-profile humanitarian policy document that promotes crowdsourcing, digital humanitarian response and next generation humanitarian technology. Exciting times. While great challenges remain, I dare say we’re trying our darned best to find some solutions, and this time through collaboration, CrowdSorcerers and all. The OCHA report is a testament to this collaboration.

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Summary

the Rise of big (crisis) data

Over 100 countries have more mobile phone subscriptions than they have people. One in four individuals in developing countries use the Internet. This figure will double within 20 months. About 70% of Africa’s total population are mobile subscribers. In short, “The planet has gone online, producing and sharing vast quantities of information.” Meanwhile, however, hundreds of millions of people are affected by disasters every year—more than 250 million in 2010 alone. There have been over 1 billion new mobile phone subscriptions since 2010. In other words, disaster affected communities are becoming increasingly “digital” as a result of the information revolution. These new digital technologies continue are evolving new nervous system for our planet, taking the pulse of our social, economic and political networks in real-time.

“Filipinos sent an average of 2 billion SMS messages every day in early 2012,” for example. When disaster strikes, many of these messages are likely to relay crisis information. In Japan, over half-a-million new users joined Twitter the day after the 2011 Earthquake. More than 177 million tweets about the disaster were posted that same day—that is, 2,000 tweets per second on average. Welcome to “The Rise of Big (Crisis) Data.” Meanwhile, back in the US, 80% of the American public expects emergency responders to monitor social media; and almost as many expect them to respond within three hours of posting a request on social media (1). These expectations have been shown to increase year-on year. “At the same time,” however, the OCHA report notes that “there are greater numbers of people […] who are willing and able to respond to needs.”

communities first

A few brave humanitarian organizations are embracing these changes and new realities, “reorienting their approaches around the essential objectives of helping people to help themselves.” That said, “the frontline of humanitarian action has always consisted of communities helping themselves before outside aid arrives.” What is new, however, is “affected people using technology to communicate, interact with and mobilize their social networks quicker than ever before […].” To this end, “by rethinking how aid agencies work and communicate with people in crisis, there is a chance that many more lives can be saved.” In sum, “the increased reach of communications networks and the growing network of people willing and able to help, are defining a new age—a network age—for humanitarian assistance.”

This stands in stark contrast to traditional notions of humanitarian assistance, which refer to “a small group of established international organizations, often based in and funded by high-income countries, providing help to people in a major crisis. This view is now out of date.” As my colleague Tim McNamara noted on the CrisisMappers list-serve, (cited in the OCHA report), this is “…not simply a technological shift [but] also a process of rapid decentralization of power. With extremely low barriers to entry, many new entrants are appearing in the fields of emergency and disaster response. They are ignoring the traditional hierarchies, because the new entrants perceive that there is something they can do which benefits others.” In other words, the humanitarian “world order” is shifting towards a more multipolar system. And so, while Tim was “referring to the specific case of volunteer crisis mappers […], the point holds true across all types of humanitarian work.”

Take the case of Somalia Speaks, for example. A journalist recently asked me to list the projects I am most proud of in this field. Somalia Speaks ranks very high. I originally pitched the idea to my Al-Jazeera colleagues back in September 2011; the project was launched three months later. Together with my colleagues at Souktelwe texted 5,000 Somalis across the country to ask how were personally affected by the crisis.

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As the OCHA study notes, we received over 3,000 responses, which were translated into English and geotagged by the Diaspora and subsequently added to a crisis map hosted on the Al-Jazeera website. From the OCHA report: “effective communication can also be seen as an end itself in promoting human dignity. More than 3,000 Somalis responded to the Somalia Speaks project, and they seemed to feel that speaking out was a worthwhile activity.” In sum, “The Somalia Speaks project enabled the voices of people from one of the world’s most inaccessible, conflict-ridden areas, in a language known to few outside their community, to be heard by decision makers from across the planet.” The project has since been replicated several times; see Uganda Speaks for example. The OCHA study refers to Somalia Speaks at least four times, highlighting the project as an example of networked humanitarianism.

PRIVACY, SECURITY & PROTECTION

The report also emphasizes the critical importance of data security, privacy and protection in the network age. OCHA’s honest and balanced approach to the topic is another reason why this report is so radical and forward thinking. “Concern over the protection of information and data is not a sufficient reason to avoid using new communications technologies in emergencies, but it must be taken into account. To adapt to increased ethical risks, humanitarian responders and partners need explicit guidelines and codes of conduct for managing new data sources.” This is precisely why I worked with GSMA’s Disaster Response Program to draft and publish the first ever Code of Conduct for the Use of SMS in Disaster Response. I have also provided extensive feedback to the International Committee of the Red Cross’s (ICRC) latest edition of the “Professional Standards for Protection Work,” which was just launched in Geneva this month. My colleagues Emmanuel Letouzé and Patrick Vinck also included a section on data security and ethics in our recent publication on the use of Big Data for Conflict Prevention. In addition, I have blogged about this topic quite a bit: herehere and here, for example.

crisis in decision making

“As the 2010 Haiti crisis revealed, the usefulness of new forms of information gathering is limited by the awareness of responders that new data sources exist, and their applicability to existing systems of humanitarian decision-making.” The fact of the matter is that humanitarian decision-making structures are simply not geared towards using Big Crisis Data let alone new data sources. More pointedly, however, humanitarian decision-making processes are often not based on empirical data in the first place, even when the data originate from traditional sources. As DfID notes in this 2012 strategy document, “Even when good data is available, it is not always used to inform decisions. There are a number of reasons for this, including data not being available in the right format, not widely dispersed, not easily accessible by users, not being transmitted through training and poor information management. Also, data may arrive too late to be able to influence decision-making in real time operations or may not be valued by actors who are more focused on immediate action.”

This is the classic warning-response gap, which has been discussed ad nauseum for decades in the field of famine early warning systems and conflict early warning systems. More data in no way implies action. Take the 2011 Somalia Famine, which was one of the best documented crises yet. So the famine didn’t occur because data was lacking. “Would more data have driven a better decision making process that could have averted disaster? Unfortunately, this does not appear to be the case. There had, in fact, been eleven months of escalating warnings emanating from the famine early warning systems that monitor Somalia. Somalia was, at the time, one of the most frequently surveyed countries in the world, with detailed data available on malnutrition prevalence, mortality rates, and many other indicators. The evolution of the famine was reported in almost real time, yet there was no adequate scaling up of humanitarian intervention until too late” (2).

At other times, “Information is sporadic,” which is why OCHA notes that “decisions can be made on the basis of anecdote rather than fact.” Indeed, “Media reports can significantly influence allocations, often more than directly transmitted community statements of need, because they are more widely read or better trusted.” (It is worth keeping in mind that the media makes mistakes; the New York Times alone makes over 7,000 errors every year). Furthermore, as acknowledged, by OCHA, “The evidence suggests that new information sources are no less representative or reliable than more traditional sources, which are also imperfect in crisis settings.” This is one of the most radical statements in the entire report. OCHA should be applauded for their remarkable fortitude in plunging into this rapidly shifting information landscape. Indeed, they go on to state that, “Crowdsourcing has been used to validate information, map events, translate text and integrate data useful to humanitarian decision makers.”

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The vast major of disaster datasets are not perfect, regardless of whether they are drawn from traditional or non-traditional sources. “So instead of criticizing the lack of 100% data accuracy, we need to use it as a base and ensure our Monitoring and Evaluation (M&E) and community engagement pieces are strong enough to keep our programming relevant” (Bartosiak 2013). And so, perhaps the biggest impact of new technologies and recent disasters on the humanitarian sector is the self disrobing of the Emperor’s Clothes (or Data). “Analyses of emergency response during the past five years reveal that poor information management has severely hampered effective action, costing many lives.” Disasters increasingly serve as brutal audits of traditional humanitarian organizations; and the cracks are increasingly difficult to hide in an always-on social media world. The OCHA study makes clear that  decision-makers need to figure out “how to incorporate these sources into decisions.”

Fact is, “To exploit the opportunity of the network age, humanitarians must understand how to use the new range of available data sources and have the capacity to transform this data into useful information.” Furthermore, it is imperative “to ensure new partners have a better understanding of how [these] decisions are made and what information is useful to improve humanitarian action.” These new partners include the members of the Digital Humanitarian Network (DHN), for example. Finally, decision-makers also need to “invest in building analytic capacity across the entire humanitarian network.” This analytic capacity can no longer rest on manual solutions alone. The private sector already makes use of advanced computing platforms for decision-making purposes. The humanitarian industry would be well served to recognize that their problems are hardly unique. Of course, investing in greater analytic capacity is an obvious solution but many organizations are already dealing with limited budgets and facing serious capacity constraints. I provide some creative solutions to this challenge below, which I refer to as “Data Science Philanthropy“.

Commentary

Near Perfection

OCHA’s report is brilliant, honest and forward thinking. This is by far the most important official policy document yet on humanitarian technology and digital humanitarian response—and thus on the very future of humanitarian action. The study should be required reading for everyone in the humanitarian and technology communities, which is why I plan to organize a panel on the report at CrisisMappers 2013 and will refer to the strategy document in all of my forthcoming talks and many a future blog post. In the meantime, I would like to highlight and address a some of the issues that I feel need to be discussed to take this discussion further.

Ironically, some of these gaps appear to reflect a rather limited understanding of advanced computing & next generation humanitarian technology. The following topics, for example, are missing from the OCHA report: Microtasking, Sentiment Analysis and Information Forensics. In addition, the report does not relate OCHA’s important work to disaster resilience and people-centered early warning. So I’m planning to expand on the OCHA report in the technology chapter for this year’s World Disaster Report (WDR 2013). This high-profile policy document is an ideal opportunity to amplify OCHA’s radical insights and to take these to their natural and logical conclusions vis-à-vis Big (Crisis) Data. To be clear, and I must repeat this, the OCHA report is the most important forward thinking policy document yet on the future of humanitarian response. The gaps I seek to fill in no way make the previous statement any less valid. The team at OCHA should be applauded, recognized and thanked for their tremendous work on this report. So despite some of the key shortcomings described below, this policy document is by far the most honest, enlightened and refreshing look at the state of the humanitarian response today; a grounded and well-researched study that provides hope, leadership and a clear vision for the future of humanitarianism in the network age.

BIG DATA HOW

OCHA recognizes that “there is a significant opportunity to use big data to save lives,” and they also get that, “finding ways to make big data useful to humanitarian decision makers is one of the great challenges, and opportunities, of the network age.” Moreover, they realize that “While valuable information can be generated anywhere, detecting the value of a given piece of data requires analysis and understanding.” So they warn, quite rightly, that “the search for more data can obscure the need for more analysis.” To this end, they correctly conclude that “identifying the best uses of crowdsourcing and how to blend automated and crowdsourced approaches is a critical area for study.” But the report does not take these insights to their natural and logical conclusions. Nor does the report explore how to tap these new data sources let alone analyze them in real time.

Yet these Big Data challenges are hardly unique. Our problems in the humanitarian space are not that “special” or  different. OCHA rightly notes that “Understanding which bits of information are valuable to saving lives is a challenge when faced with this ocean of data.” Yes. But such challenges have been around for over a decade in other disciplines. The field of digital disease detection, for example, is years ahead when it comes to real-time analysis of crowdsourced big data, not to mention private sector companies, research institutes and even new startups whose expertise is Big Data Analytics. I can also speak to this from my own professsional experience. About a decade ago, I worked with a company specializing in conflict forecasting and early using Reuters news data (Big Data).

In sum, the OCHA report should have highlighted the fact that solutions to many of these Big Data challenges already exist, which is precisely why I joined the Qatar Computing Research Institute (QCRI). What’s more, a number of humanitarian technology projects at QCRI are already developing prototypes based on these solutions; and OCHA is actually the main partner in one such project, so it is a shame they did not get credit for this in their own report.

sentiment analysis

While I introduced the use of sentiment analysis during the Haiti Earthquake, this has yet to be replicated in other humanitarian settings. Why is sentiment analysis key to humanitarianism in the network age? The answer is simple: “Communities know best what works for them; external actors need to listen and model their response accordingly.” Indeed, “Affected people’s needs must be the starting point.” Actively listening to millions of voices is a Big Data challenge that has already been solved by the private sector. One such solution is real-time sentiment analysis to capture brand perception. This is a rapidly growing multimillion dollar market, which is why many companies like Crimson Hexagon exist. Numerous Top 500 Fortune companies have been actively using automated sentiment analysis for years now. Why? Because these advanced listening solutions enable them to better understand customer perceptions.

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In Haiti, I applied this approach to tens of thousands of text messages sent by the disaster-affected population. It allowed us to track the general mood of this population on a daily basis. This is important because sentiment analysis as a feedback loop works particularly well with Big Data, which explains why the private sector is all over it. If just one or two individuals in a community are displeased with service delivery during a disaster, they may simply be “an outlier”  or perhaps exaggerating. But if the sentiment analysis at the community level suddenly starts to dip, then this means hundreds, perhaps thousands of affected individuals are now all feeling the same way about a situation. In other words, sentiment analysis serves as a triangulating mechanism. The fact that the OCHA report makes no mention of this existing solution is unfortunate since sentiment feedback loops enable organizations to assess the impact of their interventions by capturing their clients’ perceptions.

Information forensics

“When dealing with the vast volume and complexity of information available in the network age, understanding how to assess the accuracy and utility of any data source becomes critical.” Indeed, and the BBC’s User-Generated Content (UGC) Hub has been doing just this since 2005—when Twitter didn’t even exist. The field of digital information forensics may be new to the humanitarian sector, but that doesn’t mean it is new to every other sector on the planet. Furthermore, recent research on crisis computing has revealed that the credibility of social media reporting can be modeled and even predicted. Twitter has even been called a “Truth Machine” because of the self-correcting dynamic that has been empirically observed. Finally, one of QCRI’s humanitarian technology projects, Verily, focuses precisely on the issue of verifying crowdsourced social media information from social media. And the first organization I reached out to for feedback on this project was OCHA.

microtasking

The OCHA report overlooks microtasking as well. Yes, the study does address and promote the use of crowdsourcing repeatedly, but again, this  tends to focus on the collection of information rather than the processing of said information. Microtasking applications in the humanitarian space are not totally unheard of, however. Microtasking was used to translate and geolocate tens of thousands of text messages following the Haiti Earthquake. (As the OCHA study notes, “some experts estimated that 90 per cent [of the SMS's] were ‘repetition’, or ‘white noise’, meaning useless chatter”). There have been several other high profile uses of microtasking for humanitarian operations such as this one thanks to OCHA’s leadership in response to Typhoon Pablo. In sum, microtasking has been used extensively in other sectors to manage the big data and quality control challenge for many years now. So this important human computing solution really ought to have appeared in the OCHA report along with the immense potential of microtasking humanitarian information using massive online multiplayer games (more here).

Open Data is Open Power

OCHA argues that “while information can be used by anyone, power remains concentrated in the hands of a limited number of decision makers.” So if the latter “do not use this information to make decisions in the interests of the people they serve, its value is lost.” I don’t agree that the value is lost. One of the reports’ main themes is the high-impact agency and ingenuity of disaster-affected communities. As OCHA rightly points out, “The terrain is continually shifting, and people are finding new and brilliant ways to cope with crises every day.” Openly accessible crisis information posted on social media has already been used by affected populations for almost a decade now. In other words, communities affected by crises are (quite rightly) taking matters into their own hands in today’s networked world—just like they did in the analog era of yesteryear. As noted earlier, “affected people [are] using technology to communicate, interact with and mobilize their social networks quicker than ever before […].” This explains why “the failure to share [information] is no longer a matter of institutional recalcitrance: it can cost lives.”

creative partnerships

The OCHA study emphasizes that “Humanitarian agencies can learn from other agencies, such as fire departments or militaries, on how to effectively respond to large amounts of often confusing information during a fast-moving crisis.” This is spot on. Situational awareness is first and foremost a military term. The latest Revolution in Military Affairs (RMA) provides important insights into the future of humanitarian technology—see these recent developments, for example. Mean-while, the London Fire Brigade has announced plans to add Twitter as a communication channel, which means city residents will have the option of reporting a fire alert via Twitter. Moreover, the 911 service in the US (999 in the UK) is quite possibly the oldest and longest running crowdsourced emergency service in the world. So there much that humanitarian can learn from 911. But the fact of the matter is that most domestic emergency response agencies are completely unprepared to deal with the tidal wave of Big (Crisis) Data, which is precisely why the Fire Department of New York City (FDNY) and San Francisco City’s Emergency Response Team have recently reached out to me.

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But some fields are way ahead of the curve. The OCHA report should thus have pointed to crime mapping and digital disease detection since these fields have more effectively navigated the big data challenge. As for the American Red Cross’s Digital Operations Center, the main technology they are using, Radian6, has been used by private sector clients for years now. And while the latter can afford the very expensive licensing fees, it is unlikely that cash-strapped domestic emergency response officers and international humanitarian organizations will ever be able to afford these advanced solutions. This is why we need more than just “Data Philanthropy“.

We also need “Data Science Philanthropy“. As the OCHA report states, decision-makers need to “invest in building analytic capacity across the entire humanitarian network.” This is an obvious recommendation, but perhaps not particularly realistic given the limited budgets and capacity constraints in the humanitarian space. This means we need to create more partnerships with Data Science groups like DataKind, Kaggle and the University of Chicago’s Data Science for Social Good program. I’m in touch with these groups and others for this reason. I’ve also been (quietly) building a global academic network called “Data Science for Humanitarian Action” which will launch very soon. Open Source solutions are also imperative for building analytic capacity, which is why the humanitarian technology platforms being developed by QCRI will all be Open Source and freely available.

DISASTER RESILIENCE

This points to the following gap in the OCHA report: there is no reference whatsoever to resilience. While the study does recognize that collective self-help behavior is typical in disaster response and should be amplified, the report does not make the connection that this age-old mutual-aid dynamic is the humanitarian sector’s own lifeline during a major disaster. Resilience has to do with a community’s capacity for self-organization. Communication technologies increasingly play a pivotal role in self-organization. This explains why disaster preparedness and disaster risk reduction programs ought to place greater emphasis on building the capacity of at-risk communities to self-organize and mitigate the impact of disasters on their livelihoods. More about this here. Creating resilience through big data is also more academic curiosity, as explained here.

DECENTRALIZING RESPONSE

As more and more disaster-affected communities turn to social media in time of need, “Governments and responders will soon need answers to the questions: ‘Where were you? We Facebooked/tweeted/texted for help, why didn’t someone come?'” Again, customer support challenges are hardly unique to the humanitarian sector. Private sector companies have had to manage parallel problems by developing more advanced customer service platforms. Some have even turned to crowdsourcing to manage customer support. I blogged about this here to drive the point home that solutions to these humanitarian challenges already exist in other sectors.

Yes, that’s right, I am promoting the idea of crowdsourcing crisis response. Fact is, disaster response has always been crowdsourced. The real first responders are the disaster affected communities themselves. Thanks to new technologies, this crowdsourced response can be accelerated and made more efficient. And yes, there’s an app (in the making) for that: MatchApp. This too is a QCRI humanitarian technology project (in partnership with MIT’s Computer Science and Artificial Intelligence Lab). The purpose of MatchApp is to decentralize disaster response. After all, the many small needs that arise following a disaster rarely require the attention of paid and experienced emergency responders. Furthermore, as a colleague of mine at NYU shared based on her disaster efforts following Hurricane Sandy, “Solving little challenges can make the biggest differences” for disaster-affected communities.

As noted above, more and more individuals believe that emergency responders should monitor social media during disasters and respond accordingly. This is “likely to increase the pressure on humanitarian responders to define what they can and cannot provide. The extent of communities’ desires may exceed their immediate life-saving needs, raising expectations beyond those that humanitarian responders can meet. This can have dangerous consequences. Expectation management has always been important; it will become more so in the network age.”

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PEOPLE-CENTERED

“Community early warning systems (CEWS) can buy time for people to implement plans and reach safety during a crisis. The best CEWS link to external sources of assistance and include the pre-positioning of essential supplies.” At the same time, “communities do not need to wait for information to come from outside sources, […] they can monitor local hazards and vulnerabilities themselves and then shape the response.” This sense and shaping capacity builds resilience, which explains why “international humanitarian organizations must embrace the shift of warning systems to the community level, and help Governments and communities to prepare for, react and respond to emergencies using their own resources and networks.”

This is absolutely spot on and at least 7 years old as far as  UN policy goes. In 2006, the UN’s International Strategy for Disaster Risk Reduction (UNISDR) published this policy document advocating for a people-centered approach to early warning and response systems. They defined the purpose of such as systems as follows:

“… to empower individuals and communities threatened by hazards to act in sufficient time and in an appropriate manner so as to reduce the possibility of personal injury, loss of life, damage to property and the environment, and loss of livelihoods.”

Unfortunately, the OCHA report does not drive these insights to their logical conclusion. Disaster-affected communities are even more ill-equipped to manage the rise of Big (Crisis) Data. Storing, let alone analyzing Big Data Analytics in real-time, is a major technical challenge. As noted here vis-à-vis Big Data Analytics on Twitter, “only corporate actors and regulators—who possess both the intellectual and financial resources to succeed in this race—can afford to participate […].” Indeed, only a handful of research institutes have the technical ability and large funding base carry out the real-time analysis of Big (Crisis) Data. My team and I at QCRI, along with colleagues at UN Global Pulse and GSMA are trying to change this. In the meantime, however, the “Big Data Divide” is already here and very real.

information > Food

“Information is not water, food or shelter; on its own, it will not save lives. But in the list of priorities, it must come shortly after these.” While I understand the logic behind this assertion, I consider it a step back, not forward from the 2005 World Disaster Report (WDR 2005), which states that “People need information as much as water, food, medicine or shelter. Information can save lives, livelihoods and resources.” In fact, OCHA’s assertion contradicts an earlier statement in the report; namely that “information in itself is a life-saving need for people in crisis. It is as important as water, food and shelter.” Fact is: without information, how does one know where/when and from whom clean water and food might be available? How does one know which shelters are open, whether they can accommodate your family and whether the road to the shelter is safe to drive on?

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OCHA writes that, “Easy access to data and analysis, through technology, can help people make better life-saving decisions for themselves and mobilize the right types of external support. This can be as simple as ensuring that people know where to go and how to get help. But to do so effectively requires a clear understanding of how information flows locally and how people make decisions.” In sum, access to information is paramount, which means that local communities should have easy access to next generation humanitarian technologies that can manage and analyze Big Crisis Data. As a seasoned humanitarian colleague recently told me, “humanitarians sometimes have a misconception that all aid and relief comes through agencies.  In fact, (especially with things such a shelter) people start to recover on their own or within their communities. Thus, information is vital in assuring that they do this safely and properly.  Think of the Haiti, build-back-better campaign and the issues with cholera outbreaks.”

Them not us

The technologies of the network age should not be restricted to empowering second- and third-level responders. Unfortunately, as OCHA rightly observes, “there is still a tendency for people removed from a crisis to decide what is best for the people living through that crisis.” Moreover, these paid responders cannot be everywhere at the same time. But the crowd is always there. And as OCHA points out, there are “growing groups of people willing able to help those in need;” groups that unlike their analog counterparts of yesteryear now operate in the “network age with its increased reach of communications networks.” So information is not simply or “primarily a tool for agencies to decide how to help people, it must be understood as a product, or service, to help affected communities determine their own priorities.” Recall the above definition of people-centered early warning. This definition does not all of a sudden become obsolete in the network age. The purpose of next generation technologies is to “empower individuals and communities threatened by hazards to act in sufficient time and in an appropriate manner so as to reduce the possibility of personal injury, loss of life, damage to property and the environment, and loss of livelihoods.”

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Digital humanitarian volunteers are also highly unprepared to deal with the rise of Big Crisis Data, even though they are at the frontlines and indeed the pioneers of digital response. This explains why the Standby Volunteer Task Force (SBTF), a network of digital volunteers that OCHA refers to half-a-dozen times throughout the report, are actively looking to becoming early adopters of next generation humanitarian technologies. Burn out is a serious issue with digital volunteers. They too require access to these next generation technologies, which is precisely why the American Red Cross equips their digital volunteers with advanced computing platforms as part of their Digital Operations Center. Unfortunately, some humanitarians still think that they can just as easily throw more (virtual) volunteers at the Big Crisis Data challenge. Not only are they terribly misguided but also insensitive, which is why, As OCHA notes, “Using new forms of data may also require empowering technical experts to overrule the decisions of their less informed superiors.” As the OCHA study concludes, “Crowdsourcing is a powerful tool, but ensuring that scarce volunteer and technical resources are properly deployed will take further research and the expansion of collaborative models, such as SBTF.”

Conclusion

So will next generation humanitarian technology solve everything? Of course not, I don’t know anyone naïve enough to make this kind of claim. (But it is a common tactic used by the ignorant to attack humanitarian innovation). I have already warned about techno-centric tendencies in the past, such as here and here (see epilogue). Furthermore, one of the principal findings from this OECD report published in 2008 is that “An external, interventionist, and state-centric approach in early warning fuels disjointed and top down responses in situations that require integrated and multilevel action.” You can throw all the advanced computing technology you want at this dysfunctional structural problem but it won’t solve a thing. The OECD thus advocates for “micro-level” responses to crises because “these kinds of responses save lives.” Preparedness is obviously central to these micro-level responses and self-organization strategies. Shockingly, however, the OCHA study reveals that, “only 3% of humanitarian aid goes to disaster prevention and preparedness,” while barely “1% of all other development assistance goes towards disaster risk reduction.” This is no way to build disaster resilience. I doubt these figures will increase substantially in the near future.

This reality makes it even more pressing to ensure that “responders listen to affected people and find ways to respond to their priorities will require a mindset change.” To be sure, “If aid organizations are willing to listen, learn and encourage innovation on the front lines, they can play a critical role in building a more inclusive and more effective humanitarian system.” This need to listen and learn is why next generation humanitarian technologies are not optional. Ensuring that first, second and third-level responders have access to next generation humanitarian technologies is critical for the purposes of self-help, mutual aid and external response.

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Digital Humanitarians and The Theory of Crowd Capital

An iRevolution reader very kindly pointed me to this excellent conceptual study: “The Theory of Crowd Capital”. The authors’ observations and insights resonate with me deeply given my experience in crowdsourcing digital humanitarian response. Over two years ago, I published this blog post in which I wrote that, “The value of Crisis Mapping may at times have less to do with the actual map and more with the conversations and new collaborative networks catalyzed by launching a Crisis Mapping project. Indeed, this in part explains why the Standby Volunteer Task Force (SBTF) exists in the first place.” I was not very familiar with the concept of social capital at the time, but that’s precisely what I was describing. I’ve since written extensively about the very important role that social capital plays in disaster resilience and digital humanitarian response. But I hadn’t taken the obvious next step: “Crowd Capital.”

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John Prpić and Prashant Shukla, the authors of “The Theory of Crowd Capital,” find inspiration in F. A. Hayek, “who in 1945 wrote a seminal work titled: The Use of Knowledge in Society. In this work, Hayek describes dispersed knowledge as:

“The knowledge of the circumstances of which we must make use never exists in concentrated or integrated form but solely as the dispersed bits of incomplete and frequently contradictory knowledge which all the separate individuals possess. […] Every individual has some advantage over all others because he possesses unique information of which beneficial use might be made, but of which use can be made only if the decisions depending on it are left to him or are made with his active cooperation.”

“Crowd Capability,” according to John and Prashant, “is what enables an organization to tap this dispersed knowledge from individuals. More formally, they define Crowd Capability as an “organizational level capability that is defined by the structure, content, and process of an organizations engagement with the dispersed knowledge of individuals—the Crowd.” From their perspective, “it is this engagement of dispersed knowledge through Crowd Capability efforts that endows organizations with data, information, and knowledge previously unavailable to them; and the internal processing of this, in turn, results in the generation of Crowd Capital within the organization.”

In other words, “when an organization defines the structure, content, and processes of its engagement with the dispersed knowledge of individuals, it has created a Crowd Capability, which in turn, serves to generate Crowd Capital.” And so, the authors contend, a Crowd Capable organization “puts in place the structure, content, and processes to access Hayek’s dispersed knowledge from individuals, each of whom has some informational advantage over the other, and thus forming a Crowd for the organization.” Note that a crowd can “exist inside of an organization, exist external to the organization, or a combination of the latter and the former.”

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The “Structure” component of Crowd Capability connotes “the geographical divisions and functional units within an organization, and the technological means that they employ to engage a Crowd population for the organization.” The structure component of Crowd Capability is always an Information-Systems-mediated phenomenon. The “Content” of Crowd Capability constitutes “the knowledge, information or data goals that the organization seeks from the population,” while the “Processes” of Crowd Capability are defined as “the internal procedures that the organization will use to organize, filter, and integrate the incoming knowledge, information, and/or data.” The authors observe that in each Crowd Capital case they’ve analyzed , “an organization creates the structure, content, and/or process to engage the knowledge of dispersed individuals through Information Systems.”

Like the other forms of capital, “Crowd Capital requires investments (for example in Crowd Capability), and potentially pays literal or figurative dividends, and hence, is endowed with typical ‘capital-like’ qualities.” But the authors are meticulous when they distinguish Crowd Capital from Intellectual Capital, Human Capital, Social Capital, Political Capital, etc. The main distinguishing factor is that Crowd Capability is strictly an Information-Systems-mediated phenomenon. “This is not to say that Crowd Capability could not be leveraged to create Social Capital for an organization. It likely could, however, Crowd Capability does not require Social Capital to function.”

That said, I would opine that Crowd Capability can function better thanks to Social Capital. Indeed, Social Capital can influence the “structure”, “content” and “processes” integral to Crowd Capability. And so, while the authors argue that  “Crowd Capital can be accrued without such relationship and network concerns” that are typical to Social Capital, I would counter that the presence of Social Capital certainly does not take away Crowd Capability but quite on the contrary builds greater capability. Otherwise, Crowd Capability is little else than the cultivation of cognitive surplus in which crowd workers can never unite. The Matrix comes to mind. So this is where my experience in crowdsourcing digital humanitarian response makes me diverge from the authors’ conceptualization of “Crowd Capital.” Take the Blue Pill to stay in the disenfranchised version of Crowd Capital; or take the Red Pill if you want to build the social capital required to hack the system.

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To be sure, the authors of Crowd Capital Theory point to Google’s ReCaptcha system for book digitization to demonstrate that Crowd Capability does not require a network of relationships for the accrual of Crowd Capital.” While I understand the return on investment to society both in the form of less spam and more digitized books, this mediated information system is authoritarian. One does not have a choice but to comply, unless you’re a hacker, perhaps. This is why I share Jonathan Zittrain’s point about “The future of the Internet and How To Stop It.” Zittrain promotes the notion of a “Generative Technologies,” which he defines as having the ability “to produce unprompted, user-driven change.”

Krisztina Holly makes a related argument in her piece on crowdscaling. “Like crowdsourcing, crowdscaling taps into the energy of people around the world that want to contribute. But while crowdsourcing pulls in ideas and content from outside the organization, crowdscaling grows and scales its impact outward by empowering the success of others.” Crowdscaling is possible when Crowd Capa-bility generates Crowd Capital by the crowd, for the crowd. In contrast, said crowd cannot hack or change a ReCaptcha requirement if they wish to proceed to the page they’re looking for. In The Matrix, Crowd Capital accrues most directly to The Matrix rather than to the human cocoons being farmed for their metrics. In the same vein, Crowd Capital generated by ReCaptcha accrues most directly to Google Inc. In short, ReCaptcha doesn’t even ask the question: “Blue Pill or Red Pill?” So is it only a matter of time until the users that generate the Crowd Capital unite and revolt, as seems to be the case with the lawsuit against CrowdFlower?

I realize that the authors may have intended to take the conversation on Crowd Capital in a different direction. But they do conclude with a number of inter-esting, open-ended questions that suggest various “flavors” of Crowd Capital are possible, and not just the dark one I’ve just described. I for one will absolutely make use of the term Crowd Capital, but will flavor it based on my experience with digital humanitarias, which suggests a different formula: Social Capital + Social Media + Crowdsourcing = Crowd Capital. In short, I choose the Red Pill.

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Resilience = Anarchism = Resilience?

Resilience is often defined as the capacity for self-organization, which in essence is cooperation without hierarchy. In turn, such cooperation implies mutuality; reciprocation, mutual dependence. This is what the French politician, philo-sopher, economist and socialist “Pierre-Joseph Proudhon had in mind when he first used the term ‘anarchism,’ namely, mutuality, or cooperation without hierarchy or state rule” (1).

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As renowned Yale Professor James Scott explains in his latest bookTwo Cheers for Anarchism, “Forms of informal cooperation, coordination, and action that embody mutuality without hierarchy are the quotidian experience of most people.” To be sure, “most villages and neighborhoods function precisely be-cause of the informal, transient networks of coordination that do not require formal organization, let alone hierarchy. In other words, the experience of anar-chistic mutuality is ubiquitous. The existence, power and reach of the nation-state over the centuries may have undermined the self-organizing capacity (and hence resilience) of individuals and small communities.” Indeed, “so many functions that were once accomplished by mutuality among equals and informal coordination are now state organized or state supervised.” In other words, “the state, arguably, destroys the natural initiative and responsibility that arise from voluntary cooperation.”

This is goes to the heart what James Scott argues in his new book, and he does so  in a very compelling manner. Says Scott: “I am suggesting that two centuries of a strong state and liberal economies may have socialized us so that we have largely lost the habits of mutuality and are in danger now of becoming precisely the dangerous predators that Hobbes thought populated the state of nature. Leviathan may have given birth to its own justification.” And yet, we also see a very different picture of reality, one in which solidarity thrives and mutual-aid remains the norm: we see this reality surface over & over during major disasters—a reality facilitated by mobile technology and social media networks.

Recall Jürgen Habermas’s treatise that “those who take on the tools of open expression become a public, and the presence of a synchronized public increas-ingly constrains undemocratic rulers while expanding the right of that public.” One of the main instruments for synchronization is what the military refers to as “shared awareness.” As my colleague Clay Shirky notes in his excellent piece on The Political Power of Social Media, “shared awareness is the ability of each member of a group to not only understand the situation at hand but also under-stand that everyone else does, too. Social media increase shared awareness by propagating messages through social networks.” Moreover, while “Opinions are first transmitted by the media,” they are then “echoed by friends, family mem-bers, and colleagues. It is in this second, social step that political opinions are formed. This is the step in which the Internet in general, and social media in particular, can make a difference.”

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In 1990, James Scott published Domination and the Arts of Resistance: Hidden Transcripts, in which he distinguishes between public and hidden transcripts. The former describes the open, public interactions that take place between dominators and oppressed while hidden transcripts relate to the critique of power that “goes on offstage” and which the power elites cannot decode. This hidden transcript is comprised of the second step described above, i.e., the social conversations that ultimately change political behavior. Scott writes that when the oppressed classes publicize this “hidden transcript”, they become conscious of its common status. Borrowing from Habermas, the oppressed thereby become a public and more importantly a synchronized public. Social media is the metronome that can synchronize the collective publication of the hidden trans-cript, yielding greater shared awareness that feeds on itself, thereby threatening the balance of power between Leviathan and now-empowered and self-organized mutual-aid communities.

I have previously argued that social media and online social networks also can and do foster social capital, which increases capacity for self-organization and renders local communities more resilient & independent, thus sowing the seeds for future social movements. In other words, habits of mutuality are not all lost and the Leviathan may still face some surprisesAs Peter Kropotkin observed well over 100 years ago in his exhaustive study, Mutual Aid: A Factor of Evolution, cooperation and mutual aid are the most important factors in the evolution of species and their ability to survive. “There is an immense amount of warfare and extermination going on amidst various species; there is, at the same time, as much, or perhaps even more, of mutual support, mutual aid, and mutual defense… Sociability is as much a law of nature as mutual struggle.” 

Sociability is the tendency or property of being social, of interacting with others. Social media, meanwhile, has become the media for mass social interaction; enabling greater volumes of interactions than at any other time in human history. By definition, these mass social interactions radically increase the probability of mutuality and self-organization. And so, as James Scott puts it best, Two Cheers for Anarchism

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Video: Minority Report Meets Crisis Mapping

This short video was inspired by the pioneering work of the Standby Volunteer Task Force (SBTF). A global network of 1,000+ digital humanitarians in 80+ countries, the SBTF is responsible for some of the most important live crisis mapping operations that have supported both humanitarian and human rights organizations over the past 2+ years. Today, the SBTF is a founding and active member of the Digital Humanitarian Network (DHN) and remains committed to rapid learning and innovation thanks to an outstanding team of volunteers (“Mapsters”) and their novel use of next-generation humanitarian technologies.

The video first aired on the National Geographic Television Channel in February 2013. A big thanks to the awesome folks from National Geographic and the outstanding Evolve Digital Cinema Team for visioning the future of digital humanitarian technologies—a future that my Crisis Computing Team and I at QCRI are working to create.

An aside: I tried on several occasions to hack the script and say “We” rather than “I” since crisis mapping is very rarely a solo effort but the main sponsor insisted that the focus be on one individual. On the upside, one of the scenes in the commercial is of a Situation Room full of Mapsters coupled with the narration: “Our team can map the pulse of the planet, from anywhere, getting aid to the right places.” Our team = SBTF! Which is why the $$ received for being in this commercial will go towards supporting Mapsters.

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The World at Night Through the Eyes of the Crowd

Ushahidi has just uploaded the location of all CrowdMap reports to DevSeed’s awesome MapBox and the result looks gorgeous. Click this link to view the map below in an interactive, full-browser window. Ushahidi doesn’t disclose the actual number of reports depicted, only the number of maps that said reports have been posted to and the number of countries that CrowdMaps have been launched for. But I’m hoping they’ll reveal that figure soon as well. (Update from Ushahidi: This map shows the 246,323 unique locations used for reports from the launch of Crowdmap on Aug 9, 2010 to Jan 18, 2013).

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In any event, I’ve just emailed my colleagues at Ushahidi to congratulate them and ask when their geo-dataset will be made public since they didn’t include a link to said dataset in their recent blog post. I’ll be sure to let readers know in the comments section as soon as I get a reply. There are a plethora of fascinating research questions that this dataset could potentially help us answer. I’m really excited and can’t wait for my team and I at QCRI to start playing with the data. I’d also love to see this static map turned into a live map; one that allows users to actually click on individual reports as they get posted to a CrowdMap and to display the category (or categories) they’ve been tagged with. Now that would be just be so totally über cool—especially if/when Ushahidi opens up that data to the public, even if at a spatially & temporally aggregated level.

For more mesmerizing visualizations like this one, see my recent blog post entitled “Social Media: Pulse of the Planet?” which is also cross-posted on the National Geographic blog here. In the meantime, I’m keeping my fingers crossed that Ushahidi will embrace an Open Data policy from here on out and highly recommend the CrowdGlobe Report to readers interested in learning more about CrowdMap and Ushahidi.

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Map or Be Mapped: Otherwise You Don’t Exist

“There are hardly any street signs here. There are no official zip codes. No addresses. Just word of mouth” (1). Such is the fate of Brazil’s Mare shanty-town and that of most shantytowns around the world where the spoken word is king (and not necessarily benevolent). “The sprawling complex of slums, along with the rest of Rio de Janerio’s favelas, has hung in a sort of ‘legal invisibility’ since 1937, when a city ordinance ruled that however unsightly, favelas should be kept off maps because they were merely ‘temporary'” (2).

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The socio-economic consequences were far-reaching. For decades, this infor-mality meant that “entire neighborhoods did not receive mail. It had also blocked people from giving required information on job applications, getting a bank account or telling the police or fire department where to go in an emergency call. Favela residents had to pick up their mail from their neighborhood associations, and entire slums housing a small town’s worth of residents had to use the zip code of the closest officially recognized street” (3).

All this is starting to change thanks to a grassroots initiative that is surveying Mare’s 16 favelas, home to some 130,000 people. This community-driven project has appropriated the same survey methodology used by the Brazilian government’s Institute of Geography and Statistics. The collected data includes “not only street names but the history of the original smaller favelas that make up the community” (4). This data is then “formatted into pocket guides and distributed gratis to residents. These guides also offer background on certain streets’ namesakes, but leave some blank so that residents can fill them in as Mare [...] continues shifting out from the shadows of liminal space to a city with distinct identities” (5). And so, “residents of Rio’s famed favelas are undergoing their first real and ‘fundamental step toward citizenship'” (6).

These bottom-up, counter-mapping efforts are inherently political—call it guerrilla mapping. Traditionally, maps have represented “not just the per-spective of the cartographer herself, but of much larger institutions—of corporations, organizations, and governments” (7). The scale was fixed at one and only one scale, that of the State. Today, informal communities can take matters into their own hands and put themselves on the map; at the scale of their choosing. But companies like Google still have the power to make these communities vanish. In Brazil, Google said it “would tweak the site’s [Google Maps'] design, namely its text size and district labeling to show favela names only after users zoomed in on those areas.”

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Meanwhile, Google is making North Korea’s capital city more visible. But I had an uncomfortable feeling after reading National Geographic’s take on Google’s citizen mapping expedition to North Korea. The Director for National Geographic Maps, Juan José Valdéscautions that, “In many parts of the world such citizen mapping has proven challenging, if not downright dangerous. In many places, little can be achieved without the approval of local and or national authorities—especially in North Korea.” Yes, but in many parts of the world citizen mapping is safe and possible. More importantly, citizen mapping can be a powerful tool for digital activism. My entire doctoral dissertation focuses on exactly this issue.

Yes, Valdés is absolutely correct when he writes that “In many countries, place-names, let alone the alignment of boundaries, remain a powerful symbol of independence and national pride, and not merely indicators of location. This is where citizen cartographers need to understand the often subtle nuances and potential pitfalls of mapping.” As the New Yorker notes, “Maps are so closely associated with power that dictatorships regard information on geography as a state secret.” But map-savvy digital activists already know this better than most, and they deliberately seek to exploit this to their advantage in their struggles for democracy.

National Geographic’s mandate is of course very different. “From National Geographic’s perspective, all a map should accomplish is the actual portrayal of national sovereignty, as it currently exists. It should also reflect the names as closely as possible to those recognized by the political entities of the geographic areas being mapped. To do otherwise would give map readers an unrealistic picture of what is occurring on the ground.”

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This makes perfect sense for National Geographic. But as James Scott reminds us in his latest book, “A great deal of the symbolic work of official power is precisely to obscure the confusion, disorder, spontaneity, error, and improvisation of political power as it is in fact exercised, beneath a billiard-ball-smooth surface of order, deliberation, rationality, and control. I think of this as the ‘miniaturization of order.'” Scott adds that, “The order, rationality, abstractness and synoptic legibility of certain kinds of schemes of naming, landscape, architecture, and work processes lend themselves to hierarchical power [...] ‘landscapes of control and appropriation.'”

Citizen mapping, especially in repressive environments, often seeks to change that balance of power by redirecting the compass of political power with the  use of subversive digital maps. Take last year’s example of Syrian pro-democracy activists changing place & street names depicted on on the Google Map of Syria. They did this intentionally as an act of resistance and defiance. Again, I fully understand and respect that National Geographic’s mandate is completely different to that of pro-democracy activists fighting for freedom. I just wish that Valdés had a least added one sentence to acknowledge the importance of maps for the purposes of resistance and pro-democracy movements. After all, he is himself a refugee from Cuba’s political repression.

There is of course a flip side to all this. While empowering, visibility and legibility can also undermine a community’s autonomy. As Pierre-Joseph Proudhon famously put it, “To be governed is to be watched, inspected, spied upon, directed, law-driven, numbered, regulated, enrolled, indoctrinated, preached at, controlled, checked, estimated, valued, censured, commanded, by creatures who have neither the right nor the wisdom nor the virtue to do so.” To be digitally mapped is to be governed, but perhaps at multiple scales including the preferred scale of self-governance and self-determination.

And so, we find ourselves repeating the words of Shakespeare’s famous character Hamlet: “To be, or not to be,” to map, or not to map.

 

See also:

  • Spying with Maps [Link]
  • How to Lie With Maps [Link]
  • Folksomaps for Community Mapping [Link]
  • From Social Mapping to Crisis Mapping [Link]
  • Crisis Mapping Somalia with the Diaspora [Link]
  • Perils of Crisis Mapping: Lessons from Gun Map [Link]
  • Crisis Mapping the End of Sudan’s Dictatorship? [Link]
  • Threat and Risk Mapping Analysis in the Sudan [Link]
  • Rise of Amateur Professionals & Future of Crisis Mapping [Link]
  • Google Inc + World Bank = Empowering Citizen Cartographers? [Link]

Note: Readers interested in the topics discussed above may also be interested in a forthcoming book to be published by Oxford University Press entitled “Information and Communication Technologies in Areas of Limited State-hood.” I have contributed a chapter to this book entitled “Crisis Mapping in Areas of Limited Statehood,” which analyzes how the rise of citizen-genera-ted crisis mapping replaces governance in areas of limited statehood. The chapter distills the conditions for the success of these crisis mapping efforts in these non-permissive and resource-restricted environments.