Category Archives: Digital Activism

#NoShare: A Personal Twist on Data Privacy

Countless computers worldwide automatically fingerprint our use of social media around the clock without our knowledge or consent. So we’re left with the following choice: stay digital and face the Eye of Sauron, or excommunicate ourselves from social media and face digital isolation from society. I’d chose the latter were it not for the life-saving role that social media can play during disasters. So what if there were a third way? An alternative that enabled us to use social media without being fed to the machines. Imagine if the choice were ours. My PopRock Fellows (PopTech & Rockefeller Foundation) and I are pondering this question within the context of ethical community-driven resilience in the era Big Data.

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One result of this pondering is the notion of #noshare or #ns hashtag. We propose using this hashtag on anything that we don’t want sensed and turned into fodder for the machines. This could include Facebook updates, tweets, emails, SMS, post cards, cars, buildings and even our physical selves. Buildings, for example, are increasingly captured by cameras on orbiting satellites and also by high-resolution cameras fixed to cars used for Google Streetview.

The #noshare hashtag is a humble attempt at regaining some agency over the machines—and yes the corporations and governments using said machines. To this end, #noshare is a social hack that seeks to make a public statement and establish a new norm: the right to be social without being sensed or exploited without our knowledge or consent. While traditional privacy may be dead, most of us know the difference between right and wrong. This may foster positive social pressure to respect the use of #noshare.

Think of #ns hashtag as drawing a line in the sand. When you post a public tweet and want that tweet to serve the single purpose of read-only by humans, then add #noshare. This tag simply signals the public sphere that your tweet is for human consumption only, and not to be used by machines; not for download, retweet, copying, analysis, sensing, modeling or prediction. Your use of #noshare regardless of the medium represents your public vote for trust & privacy; a vote for tuning this hashtag into a widespread social norm.

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Of course, this #noshare norm is not enforceable in a traditional sense. This means that one could search for, collect and analyze all tweets with the #noshare or #ns hashtag. We’re well aware of this “Barbara Streisand effect” and there’s nothing we can do about it just yet. But the point is to draw a normative line in the sand, to create a public and social norm that provokes strong public disapproval when people violate the #ns principle. What if this could become a social norm? What if positive social pressure could make it unacceptable to violate this norm? Could this create a deterrence effect?

Either way, the line between right and wrong would be rendered publicly explicit. There would thus be no excuse: any analysis, sensing, copying, etc., of #ns tweets would be the result of a human decision to willingly violate the public norm. This social hack would make it very easy for corporations and governments to command their data mining algorithms to ignore all our digital fingerprints that use the #ns hashtag. Crossing the #noshare line would thus provide basis for social action against the owners of the machines in question. Social pressure is favorable to norm creation. Could #ns eventually become part of a Creative Commons type license?

Obviously, #ns tagged content does not mean that content should not be made public. Contented tagged with #ns is meant to be public, but only for the human public and not for computers to store and analyze. The point is simple: we want the option of being our public digital selves without being mined, sensed and analyzed by machines without our knowledge and consent. In sum, #noshare is an awareness raising initiative that seeks to educate the public about our increasingly sensed environment. Indeed, Big Data = Big Sensing.

We suggest that #ns may return a sense of moral control to individuals, a sense of trust and local agency. These are important elements for social capital and resilience, for ethical, community-driven resilience. If this norm gains traction, we may be able to code this norm into social media platforms. In sum, sensing is not bad; sensing of social media during disasters can save lives. But the decision of whether or not to be sensed should be the decision of the individual.

My PopRock Fellows and I are looking for feedback on this proposal. We’re aware of some of the pitfalls, but are we missing anything? Are there ways to strengthen this campaign? Please let us know in the comments section below. Thank you!

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Acknowledgements: Many thanks to PopRock Fellows Gustavo, Amy, Kate, Claudia and Jer for their valuable feedback on earlier versions of this post. 

Yes, But Resilience for Whom?

I sense a little bit of history repeating, and not the good kind. About ten years ago, I was deeply involved in the field of conflict early warning and response. Eventually, I realized that the systems we were designing and implementing excluded at-risk communities even though the rhetoric had me believe they were instrumented to protect them. The truth is that these information systems were purely extractive and ultimately did little else than fill the pockets of academics who were hired as consultants to develop these early warning systems.

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The prevailing belief amongst these academics was (and still is) that large datasets and advanced quantitative methodologies can predict the escalation of political tensions and thus impede violence. To be sure, “these systems have been developed in advanced environments where the intention is to gather data so as to predict events in distant places. This leads to a division of labor between those who ‘predict’ and those ‘predicted’ upon” (Cited Meier 2008, PDF).

Those who predict assume their sophisticated remote sensing systems will enable them to forecast and thus prevent impending conflict. Those predicted upon don’t even know these systems exist. The sum result? Conflict early warning systems have failed miserably at forecasting anything, let alone catalyzing preventive action or empowering local communities to get out of harm’s way. Conflict prevention is inherently political, and “political will is not an icon on your computer screen” (Cited in Meier 2013).

In Toward a Rational Society (1970), the German philosopher Jürgen Habermas describes “the colonization of the public sphere through the use of instrumental technical rationality. In this sphere, complex social problems are reduced to technical questions, effectively removing the plurality of contending perspectives” (Cited in Meier 2006, PDF). This instrumentalization of society depoliticized complex social problems like conflict and resilience into terms that are susceptible to technical solutions formulated by external experts. The participation of local communities thus becomes totally unnecessary to produce and deliver these technical solutions. To be sure, the colonization of the public sphere crowds out both local knowledge and participation.

We run this risk of repeating these mistakes with respect the discourse on community resilience. While we speak of community resilience, we gravitate towards the instrumentalization of communities using Big Data, which is largely conceived as a technical challenge of real-time data sensing and optimization. This external, top-down approach bars local participation. The depoliticization of resilience also hides the fact that “every act of measurement is an act marked by the play of powerful relations” (Cited Meier 2013b). To make matters worse, these measurements are almost always taken without the subjects knowing, let alone their consent. And so we create the division between those who sense and those sensed upon, thereby fully excluding the latter, all in the name of building community resilience.

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Acknowledgements: I raised the question “Resilience for whom?” during the PopTech and Rockefeller Foundation workshop on “Big Data & Community Resilience.” I am thus grateful to the organizers and fellows for informing my thinking and the motivation for this post.

Why Digital Social Capital Matters for Disaster Resilience and Response

Recent empirical studies have clearly demonstrated the importance of offline social capital for disaster resilience and response. I’ve blogged about some of this analysis here and here. Social capital is typically described as those “features of social organizations, such as networks, norms, and trust, that facilitate action and cooperation for mutual benefit.” In other words, social capital increases a group’s capacity for collective action and thus self-organization, which is a key driver of disaster resilience. What if those social organizations were virtual and the networks digital? Would these online communities “generate digital social capital”? And would this digital social capital have any impact on offline social capital, collective action and resilience?

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A data-driven study published recently, “Social Capital and Pro-Social Behavior Online and Offline” (PDF), presents some fascinating insights. The study, carried out by Constantin M. Bosancianu, Steve Powell and Esad Bratovi, draws on their survey of 1,912 Internet users in Bosnia & Herzegovina, Croatia and Serbia. The authors specifically consider two types of social capital: bonding social capital and bridging social capital. “

“Bridging social capital is described as inclusive, fostered in networks where membership is not restricted to a particular group defined by strict racial, class, linguistic or ethnic criteria.  Regular interactions inside these networks would gradually build norms of generalized trust and reciprocity at the individual level. These relationships [...] are able to offer the individual access to new information but are not very adept in providing emotional support in times of need.”

“Bonding social capital, on the other hand, is exclusive, fostered in tight-knit networks of family members and close friends. Although the degree of information redundancy in these networks is likely high (as most members occupy the same social space), they provide [...] the “sociological superglue” which gets members through tough emotional stages in their lives.”

The study’s findings reveal that online and offline social capital were correlated with each other. More specifically, online bridging social capital was closely correlated with offline bridging social capital, while online binding social capital was closely correlated with offline binding social capital. Perhaps of most interest with respect to disaster resilience, the authors discovered that “offline bridging social capital can benefit from online interactions.”

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Big Data: Sensing and Shaping Emerging Conflicts

The National Academy of Engineering (NAE) and US Institute of Peace (USIP) co-organized a fascinating workshop on “Sensing & Shaping Emerging Conflicts” in November 2012. I had the pleasure of speaking at this workshop, the objective of which was to “identify major opportunities and impediments to providing better real-time information to actors directly involved in situations that could lead to deadly violence.” We explored “several scenarios of potential violence drawn from recent country cases,” and “considered a set of technologies, applications and strategies that have been particularly useful—or could be, if better adapted for conflict prevention.” 

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The workshop report was finally published this week. If you don’t have time to leaf through the 40+page study, then the following highlights may be of interest. One of the main themes to emerge was the promise of machine learning (ML), a branch of Artificial Intelligence (AI). These approaches “continue to develop and be applied in un-anticipated ways, [...] the pressure from the peacebuilding community directed at technology developers to apply these new technologies to the cause of peace could have tremendous benefits.” On a personal note, this is one of the main reasons I joined the Qatar Computing Research Institute (QCRI); namely to apply the Institute’s expertise in ML and AI to the cause of peace, development and disaster relief.

“As an example of the capabilities of new technologies, Rafal Rohozinski, principal with the SecDev Group, described a sensing exercise focused on Syria. Using social media analytics, his group has been able to identify the locations of ceasefire violations or regime deployments within 5 to 15 minutes of their occurrence. This information could then be passed to UN monitors and enable their swift response. In this way, rapid deductive cycles made possible through technology can contribute to rapid inductive cycles in which short-term predictions have meaningful results for actors on the ground. Further analyses of these events and other data also made it possible to capture patterns not seen through social media analytics. For example, any time regime forces moved to a particular area, infrastructure such as communications, electricity, or water would degrade, partly because the forces turned off utilities, a normal practice, and partly because the movement of heavy equipment through urban areas caused electricity systems go down. The electrical grid is connected to the Internet, so monitoring of Internet connections provided immediate warnings of force movements.”

This kind of analysis may not be possible in many other contexts. To be sure, the challenge of the “Digital Divide” is particularly pronounced vis-a-vis the potential use of Big Data for sensing and shaping emerging conflicts. That said, my colleague Duncan Watts “clarified that inequality in communications technology is substantially smaller than other forms of inequality, such as access to health care, clean water, transportation, or education, and may even help reduce some of these other forms of inequality. Innovation will almost always accrue first to the wealthier parts of the world, he said, but inequality is less striking in communications than in other areas.” By 2015, for example, Sub-Saharan Africa will have more people with mobile network access than with electricity at home.

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My colleague Chris Spence from NDI also presented at the workshop. He noted the importance of sensing the positive and not just the negative during an election. “In elections you want to focus as much on the positive as you do on the negative and tell a story that really does convey to the public what’s actually going on and not just a … biased sample of negative reports.” Chris also highlighted that “one problem with election monitoring is that analysts still typically work with the software tools they used in the days of manual reporting rather than the Web-based tools now available. There’s an opportunity that we’ve been trying to solve, and we welcome help.” Building on our expertise in Machine Learning and Artificial Intelligence, my QCRI colleagues and I want to develop classifiers that automatically categorize large volumes of crowdsourced election reports. So I’m exploring this further with Chris & NDI. Check out the Artificial Intelligence for Monitoring Elections (AIME) project for more information.

One of the most refreshing aspects of the day-long workshop was the very clear distinction made between warning and response. As colleague Sanjana Hattotuwa cautioned: “It’s an open question whether some things are better left unsaid and buried literally and metaphorically.”  Duncan added that, “The most important question is what to do with information once it has been gathered.” Indeed, “Simply giving people more information doesn’t necessarily lead to a better outcome, although some-times it does.” My colleague Dennis King summed it up very nicely, “Political will is not an icon on your computer screen… Generating political will is the missing factor in peacebuilding and conflict resolution.”

In other words, “the peacebuilding community often lacks actionable strategies to convert sensing into shaping,” as colleague Fred Tipson rightly noted. Libbie Prescott, who served as strategic advisor to the US Secretary of State and participated in the workshop, added: “Policymakers have preexisting agendas, and just presenting them with data does not guarantee a response.” As my colleague Peter Walker wrote in a book chapter published way back in 1992, “There is little point in investing in warning systems if one then ignores the warnings!” To be clear, “early warning should not be an end in itself; it is only a tool for preparedness, prevention and mitigation with regard to disasters, emergencies and conflict situations, whether short or long term ones. [...] The real issue is not detecting the developing situation, but reacting to it.”

Now Fast froward to 2013: OCHA just published this groundbreaking report confirming that “early warning signals for the Horn of Africa famine in 2011 did not produce sufficient action in time, leading to thousands of avoidable deaths. Similarly, related research has shown that the 2010 Pakistan floods were predictable.” 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” (DfID)So how do we reconcile all this with Fred’s critical point: “The focus needs to be on how to assist the people involved to avoid the worst consequences of potential deadly violence.”

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The fact of the matter is that this warning-response gap in the field of conflict prevention is over 20 years old. I have written extensively about the warning-response problem here (PDF) and here (PDF), for example. So this challenge is hardly a new one, which explains why a number of innovative and promising solutions have been put forward of the years, e..g, the decentralization of conflict early warning and response. As my colleague David Nyheim wrote five years ago:

A state-centric focus in conflict management does not reflect an understanding of the role played by civil society organisations in situations where the state has failed. An external, interventionist, and state-centric approach in early warning fuels disjointed and top down responses in situations that require integrated and multilevel action.” He added: “Micro-level responses to violent conflict by ‘third generation early warning systems’ are an exciting development in the field that should be encouraged further. These kinds of responses save lives.”

This explains why Sanjana is right when he emphasizes that “Technology needs to be democratized [...], made available at the lowest possible grassroots level and not used just by elites. Both sensing and shaping need to include all people, not just those who are inherently in a position to use technology.” Furthermore, Fred is spot on when he says that “Technology can serve civil disobedience and civil mobilization [...] as a component of broader strategies for political change. It can help people organize and mobilize around particular goals. It can spread a vision of society that contests the visions of authoritarian.”

In sum, As Barnett Rubin wrote in his excellent book (2002) Blood on the Doorstep: The Politics of Preventive Action, “prevent[ing] violent conflict requires not merely identifying causes and testing policy instruments but building a political movement.” Hence this 2008 paper (PDF) in which I explain in detail how to promote and facilitate technology-enabled civil resistance as a form of conflict early response and violence prevention.

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See Also:

  • Big Data for Conflict Prevention [Link]

Using Crowdring for Disaster Response?

35 million missed calls.

That’s the number of calls that 75-year old social justice leader Anna Hazare received from people across India who supported his efforts to fight corruption. Two weeks earlier, he had invited India to join his movement by making “missed calls” to a local number. Missed calls, known as beeping or flashing, are calls that are intentionally dropped after ringing. The advantage of making missed call is that neither the caller or recipient is charged. This tactic is particularly common in emerging economies to avoid paying for air time or SMS. To build on this pioneering work, Anna and his team are developing a mobile petition tool called Crowdring, which turns a free “missed call” into a signature on a petition.

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Communicating with disaster-affected communities is key for effective disaster response. Crowdring could be used to poll disaster affected communities. The service could also be used in combination with local community radio stations. The latter would broadcast a series of yes or no questions; ringing once would signify yes, twice would mean no. Some questions that come to mind:

  1. Do you have enough drinking water? 
  2. Are humanitarian organizations doing a good job?
  3. Is someone in your household displaying symptoms of cholera?

By receiving these calls, humanitarians would automatically be able to create a database of phone numbers with associated poll results. This means they could text them right back for more information or to arrange an in person meeting. You can learn more about Crowdring in this short video below.

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How Crowdsourced Disaster Response in China Threatens the Government

In 2010, Russian volunteers used social media and a live crisis map to crowdsource their own disaster relief efforts as massive forest fires ravaged the country. These efforts were seen by many as both more effective and visible than the government’s response. In 2011, Egyptian volunteers used social media to crowdsource their own humanitarian convoy to provide relief to Libyans affected by the fighting. In 2012, Iranians used social media to crowdsource and coordinate grassroots disaster relief operations following a series of earthquakes in the north of the country. Just weeks earlier, volunteers in Beijing crowd-sourced a crisis map of the massive flooding in the city. That map was immediately available and far more useful than the government’s crisis map. In early 2013, a magnitude 7  earthquake struck Southwest China, killing close to 200 and injuring more than 13,000. The response, which was also crowdsourced by volunteers using social media and mobile phones, actually posed a threat to the Chinese Government.

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“Wang Xiaochang sprang into action minutes after a deadly earthquake jolted this lush region of Sichuan Province [...]. Logging on to China’s most popular social media sites, he posted requests for people to join him in aiding the survivors. By that evening, he had fielded 480 calls” (1). While the government had declared the narrow mountain roads to the disaster-affected area blocked to unauthorized rescue vehicles, Wang and hitchhiked his way through with more than a dozen other volunteers. “Their ability to coordinate — and, in some instances, outsmart a government intent on keeping them away — were enhanced by Sina Weibo, the Twitter-like microblog that did not exist in 2008 but now has more than 500 million users” (2). And so, “While the military cleared roads and repaired electrical lines, the volunteers carried food, water and tents to ruined villages and comforted survivors of the temblor [...]” (3). Said Wang: “The government is in charge of the big picture stuff, but we’re doing the work they can’t do” (4).

In response to this same earthquake, another volunteer, Li Chengpeng, “turned to his seven million Weibo followers and quickly organized a team of volunteers. They traveled to the disaster zone on motorcycles, by pedicab and on foot so as not to clog roads, soliciting donations via microblog along the way. What he found was a government-directed relief effort sometimes hampered by bureaucracy and geographic isolation. Two days after the quake, Mr. Li’s team delivered 498 tents, 1,250 blankets and 100 tarps — all donated — to Wuxing, where government supplies had yet to arrive. The next day, they hiked to four other villages, handing out water, cooking oil and tents. Although he acknowledges the government’s importance during such disasters, Mr. Li contends that grass-roots activism is just as vital. ‘You can’t ask an NGO to blow up half a mountain to clear roads and you can’t ask an army platoon to ask a middle-aged woman whether she needs sanitary napkins, he wrote in a recent post” (5).

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As I’ve blogged in the past (here and here, for example), using social media to crowdsourced grassroots disaster response efforts serves to create social capital and strengthen collective action. This explains why the Chinese government (and others) faced a “groundswell of social activism” that it feared could “turn into government opposition” following the earthquake (6). So the Communist Party tried to turn the disaster into a “rallying cry for political solidarity. ‘The more difficult the circumstance, the more we should unite under the banner of the party,’ the state-run newspaper People’s Daily declared [...], praising the leadership’s response to the earthquake” (7).

This did not quell the rise in online activism, however, which has “forced the government to adapt. Recently, People’s Daily announced that three volunteers had been picked to supervise the Red Cross spending in the earthquake zone and to publish their findings on Weibo. Yet on the ground, the government is hewing to the old playbook. According to local residents, red propaganda banners began appearing on highway overpasses and on town fences even before water and food arrived. ‘Disasters have no heart, but people do,’ some read. Others proclaimed: ‘Learn from the heroes who came here to help the ones struck by disaster’ (8). Meanwhile, the Central Propaganda Department issued a directive to Chinese newspapers and websites “forbidding them to carry negative news, analysis or commentary about the earthquake” (9). Nevertheless, “Analysts say the legions of volunteers and aid workers that descended on Sichuan threatened the government’s carefully constructed narrative about the earthquake. Indeed, some Chinese suspect such fears were at least partly behind official efforts to discourage altruistic citizens from coming to the region” (10).

Aided by social media and mobile phones, grassroots disaster response efforts present a new and more poignant “Dictator’s Dilemma” for repressive regimes. The original Dictator’s Dilemma refers to an authoritarian government’s competing interest in using information communication technology by expanding access to said technology while seeking to control the democratizing influences of this technology. In contrast, the “Dictator’s Disaster Lemma” refers to a repressive regime confronted with effectively networked humanitarian response at the grassroots level, which improves collective action and activism in political contexts as well. But said regime cannot prevent people from helping each other during natural disasters as this could backfire against the regime.

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See also:

 •  How Civil Disobedience Improves Crowdsourced Disaster Response [Link]

Jointly: Peer-to-Peer Disaster Recovery App

My colleague Samia Kallidis is launching a brilliant self-help app to facilitate community-based disaster recovery efforts. Samia is an MFA Candidate at the School of Visual Arts in New York. While her work on this peer-to-peer app began as part of her thesis, she has since been accepted to the NEA Studio Incubator Program to make her app a reality. NEA provides venture capital to help innovative entrepreneurs build transformational initiatives around the world. So huge congrats to Samia on this outstanding accomplishment. I was already hooked back in February when she presented her project at NYU and am even more excited now. Indeed, there are exciting synergies with the MatchApp project I’m working on with QCRI and MIT-CSAIL , which is why we’re happily exploring ways to collaborate & complement our respective initiatives.

Samia’s app is aptly called Jointly and carries the tag line: “More Recovery, Less Red Tape.” In her February presentation, Samia made many very compelling arguments for a self-help approach to disaster response based on her field research and interviews she conducted following Hurricane Sandy. She rightly noted that many needs that arise during the days, weeks and months following a disaster do not require the attention of expert disaster response professionals—in fact these responders may not have the necessary skills to match the needs that frequently arise after a disaster (assuming said responders even stay the course). Samia also remarked that solving little challenges and addressing the little needs that surface post-disaster can make the biggest differences. Hence Jointly. In her own words:

“Jointly is a decentralized mobile application that helps communities self-organize disaster relief without relying on bureaucratic organizations. By directly connecting disaster victims with volunteers, Jointly allows individuals to request help through services and donations, and to find skilled volunteers who are available to fulfill those needs. This minimizes waste of resources, reduces duplication of services, and significantly shortens recovery time for individuals and communities.”

Samia kindly shared the above video and screenshots of Jointly below.

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I’m thrilled to see Jointly move forward and am excited to be collaborating with Samia on the Jointly and MatchApp connection. We certainly share the same goal: to help people help themselves. Indeed, increasing this capacity for self-organization builds resilience. These connection technologies and apps provide for more rapid and efficient self-help actions in times of need. This doesn’t mean that professional disaster response organizations are obsolete—quite on the contrary, in fact. Organizations like the American Red Cross can feed relevant service delivery data to the apps so that affected communities also know where, when and how to access these. In Jointly, official resources will be geo-tagged and updated live in the “Resources” part of the app.

You can contact Samia directly at: hello@jointly.us should you be interested in learning more or collaborating with her.

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