Tag Archives: Innovation

On Humanitarian Innovation versus Robotic Natives

I recently read an excellent piece entitled “Humanitarian Innovation and the Art of the Possible,” which appeared in the latest issue of the Humanitarian Practice Network’s (HPN) magazine. The author warns that humanitarian innovation will have limited systemic impact unless there is notable shift in the culture and underlying politics of the aid system. Turns out I had written a similar piece (although not nearly as articulate) during the first year of my PhD in 2005. I had, at the time, just re-read Alex de Waal’s Famine Crimes: Politics and the Disaster Relief Industry in Africa and Peter Uvin’s Aiding Violence.

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Kim Scriven, the author of the HPN piece and one of the leading thinkers in the humanitarian innovation space, questions whether innovation efforts are truly “free from the political and institutional blockages curtailing other initiatives” in the humanitarian space. He no doubt relates to “field-based humanitarians who have looked on incredulously as technological quick fixes are deployed from afar to combat essentially political blockages to the provision of aid.” This got me thinking about the now well-accepted notion that information is aid.

What kinds of political blockages exist vis-a-vis the provision of information (communication) during or after humanitarian crises? “For example,” writes Kim, “the adoption of new technology like SMS messaging may help close the gap between aid giver and aid recipient, but it will not be sufficient to ensure that aid givers respond to the views and wishes of affected people.” One paragraph later, Kim warns that we must also “look beyond stated benefits [of innovation] to unintended consequences, for instance around how the growing use of drones and remote communication technologies in the humanitarian sphere may be contributing to the increased use of remote management practices, increasing the separation between agencies and those they seek to assist.”

I find this all very intriguing for several reasons. First, the concern regarding the separation—taken to be the physical distance—between agencies and those they seek to assist is an age-old concern. I first came across said concern while at the Harvard Humanitarian Initiative (HHI) in 2007. At the time, ironically, it was the use of SMS in humanitarian and development projects that provoked separation anxiety amongst aid groups. By 2012, humanitarian organizations were starting to fear that social media would further increase the separation. But as we’ve said, communication is aid, and unlike food and medication, digital information doesn’t need to hitch a ride on UN planes and convoys to reach their destination. Furthermore, studies in social psychology have shown that access to timely information during crises can reduce stress, anxiety and despair. So now, in 2016, it seems to be the turn of drones; surely this emerging technology will finally create the separation anxiety that some humanitarians have long-feared (more on this in a bit).

The second reason I find Kim’s points intriguing is because of all the talk around the importance of two-way communication with disaster-affected communities. Take the dire refugee crisis in Europe. When Syrians finally escape the horrid violence in their country and make it alive to Europe, their first question is: “Where am I?” and their second: “Do you have WiFi?” In other words, they want to use their smartphones to communicate & access digital information precisely because mobile technology allows for remote communication and access.

Young humanitarian professionals understand this; they too are Digital Natives. If crisis-affected communities prefer to communicate using mobile phones, then is it not the duty of humanitarian organizations to adapt and use those digital communication channels rather than force their analog channels on others? The priority here shouldn’t be about us and our preferences. But is there a political economy—an entrenched humanitarian industrial complex—that would prefer business as usual since innovation could disrupt existing funding channels? Could these be some of the political & institutional blockages that Kim hints at?

The third reason is the reference to drones. Kim warns that the “growing use of drones and remote communication technologies in the humanitarian sphere may be contributing to the increased use of remote management practices, increasing the separation between agencies and those they seek to assist.” Ironically, the same HPN magazine issue that Kim’s piece appears in also features this article on “Automation for the People: Opportunities and Challenges of Humanitarian Robotics,” co-authored by Dr. Andrew Schroeder & myself. Incidentally, drones (also as UAVs) are aerial robots.

Kim kindly provided Andrew and I with valuable feedback on earlier drafts. So he is familiar with the Humanitarian UAV Code of Conduct and its focus on Community Engagement since we delve into this in our HPN piece. In fact, the header image featured in Kim’s article (also displayed above) is a photograph I took whilst in Nepal; showing local community members using a map created with aerial robots as part of a damage assessment exercise. Clearly, the resulting map did not create physical separation—quite on the contrary, it brought the community and robotics operators together as has happened in Haiti, Tanzania, the Philippines and elsewhere.

(As an aside, a number of UAV teams in Ecuador used the Code of Conduct in their response efforts, more here. Also, I’m co-organizing an Experts Meeting in the UK this June that will, amongst other deliverables, extend said code of conduct to include the use of aerial robotics for cargo transportation).

What’s more, Andrew and I used our article for HPN to advocate for locally managed and operated robotics solutions enabled through local innovation labs (Flying Labs) to empower local responders. In other words, and to quote Kim’s own concluding paragraph, we agree that “those who focus on innovation must do a better job of relocating innovation capacity from HQ to the field, providing tools and guidance to support those seeking to solve problems in the delivery of aid.” Hence, in part, the Flying Labs.

In fact, we’ve already started co-creating Kathmandu Flying Labs, and thanks to both the relevant training and the appropriate robotics technologies that we transferred to members of Kathmandu Flying Labs following the devastating earthquakes in 2015, one of these partners—Kathmandu University—have since carried out multiple damage assessments using aerial robotics; without needing any assistance from us or needing our permission for that matter. The Labs are also about letting go of control, and deliberately so. Which projects Kathmandu Flying Labs partners decide to pursue with their new aerial robotics platforms is entirely their decision, not ours. Trust is key. Besides, the Flying Labs are not only about providing access to appropriate robotics solutions and relevant skills, they are just as much about helping to connect & turbocharge the local capacity for innovation that already exists, and disseminating that innovation globally.

Kathmandu University’s damage assessments didn’t create a separation between themselves and the local communities. KU followed the UAV Code of Conduct and worked directly with local communities throughout. So there is nothing inherent to robotics as a technology that innately creates the separation that Kim refers to. Nor is there anything inherent to robotics that will ensure that aid givers (or robots) respond to the needs of disaster-affected communities. This is also true of SMS as Kim points out above. Technology is just a tool; how we chose to use technology is a human decision.

The fourth and final reason I find Kim’s piece intriguing is because it suggests that remote management practices and physical separations between agencies and those they seek to assist are to be avoided. But the fact of the matter is that remote management is sometimes the most efficient solution; in some cases, it is the only solution, as clearly evidenced in the protracted response to the complex humanitarian crisis in Syria. In fact, the United Nation’s Inter-Agency Standing Committee (IASC) suggests bolstering remote management in some cases. And besides, the vast majority of humanitarian interventions engage in some level of remote management.

So if we can use aerial robotics to deliver essential supplies more quickly, more reliably and at lower cost (like in Rwanda), then how exactly does using fewer motorbikes or trucks to deliver said supplies create more separation between agencies and those they seek to assist? In the case of Rwanda, aerial robotics solutions are airlifting much-needed blood supplies to remote health clinics across the country. I’d like to know how exactly this creates a separation between the doctors administering the blood transfusion and the patients receiving said transfusion. As for using aerial robotics solutions to collect data, we’ve already shown that community engagement is key and that local partners can expertly manage the operation of robotics platforms independently. The most obvious alternative to aerial imagery is satellite imagery, but orbiting satellites certainly don’t allow local partners and communities to participate in data collection.

So are there “political and institutional blockages” against the use of robotics in humanitarian efforts? Might humanitarian organizations receive less funding if aerial robotics solutions prove to be cheaper, more effective and more scalable? Is this one reason, to quote Kim, that “Emerging ideas get stuck at the pilot stage or siloed within a single organization unable to achieve scale and impact”? Are political & institutional barriers curtailing in part the entry of new and radically more efficient solutions to deliver aid? If these autonomous solutions require less international staff to manually operate, will the underlying politics of the $25 billion dollar-a-year aid industry allow such a shift? Or will it revert to fears over (money) separation anxiety?

We should realize that disaster-affected communities today are increasingly digital communities. As such, Digital Natives do not necessarily share the physical separation anxieties that aid organizations seemingly experience with every new emerging technology. Digital Natives, by definition, prefer a friction-free world. But by the time we catch on, we’ll no doubt struggle to understand the newer world of Robotic Natives. We’ll look on incredulously as the new generation of Robotic and AI Natives prefer to interact with Facebook chatbots over “analog humanitarians” during disasters. Some of us may cry foul when Robotic Natives decide to get their urgent 3D-printed food supplies delivered to them via aerial robotics while riding a driverless robotics car to their auto-matically built-in-time shelter.

In conclusion, yes, we should of course be aware and weary of the unintended consequences that new innovations in technology may have when employed in humanitarian settings. Has anyone ever suggested the contrary? At the same time, we should realize that those same unintended consequences may in some cases be welcomed or even preferred over the status quo, especially by Robotic Natives. In other words, those unintended effects may not always be a bug, but rather a feature. Whether these consequences are viewed as a bug or a feature is ultimately a political decision. And whether or not the culture and underlying politics of the aid system will shift to accommodate the new bug as-a-feature worldview, we may be deluding ourselves if we think we can change the world-view of Robotics Natives to accommodate our culture and politics. Such is the nature of innovation and systemic impact.

Think Global, Fly Local: The Future of Aerial Robotics for Disaster Response

First responders during disasters are not the United Nations or the Red Cross. The real first responders, by definition, are the local communities; always have been, always will be. So the question is: can robotics empower local communities to respond and recover both faster and better? I believe the answer is Yes.

But lets look at the alternative. As we’ve seen from recent disasters, the majority of teams that deploy with aerial robotics (UAVs) do so from the US, Europe and Australia. The mobilization costs involved in flying a professional team across the world—not to mention their robotics equipment—is not insignificant. And this doesn’t even include the hotel costs for a multi-person team over the course of a mission. When you factor in these costs on top of the consulting fees owed to professional international robotics teams, then of course the use of aerial robotics versus space robotics (satellites) becomes harder to justify.

There is also an important time factor. The time it takes for international teams to obtain the necessary export/import permits and customs clearance can be highly unpredictable. More than one international UAV team that (self) deployed to Nepal after the tragic 2015 Earthquake had their robotics platforms held up in customs for days. And of course there’s the question of getting regulatory approval for robotics flights. Lastly, international teams (especially companies and start-up’s) may have little to no prior experience working in the country they’re deploying to; they may not know the culture or speak the language. This too creates friction and can slow down a humanitarian robotics mission.

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What if you had fully trained teams on the ground already? Not an international team, but a local expert robotics team that obviously speaks the local language, understands local customs and already has a relationship with the country’s Civil Aviation Authority. A local team does not need to waste time with export/import permits or customs clearance; doesn’t need expensive international flights or weeks’ worth of hotel accommodations. They’re on site, and ready to deploy at a moment’s notice. Not only would this response be faster, it would be orders of magnitudes cheaper and more sustainable to carry through to the recovery and reconstruction phase.

In sum, we need to co-create local Flying Labs with local partners including universities, NGOs, companies and government partners. Not only would these Labs be far more agile and rapid vis-a-vis disaster response efforts, they would also be far more sustainable and their impact more scalable than deploying international robotics teams. This is one of the main reasons why my team and I at WeRobotics are looking to co-create and connect a number of Flying Labs in disaster prone countries across Asia, Africa and Latin America. With these Flying Labs in place, the cost of rapidly acquiring high quality aerial imagery will fall significantly. Think Global, Fly Local.

Handbook: How to Catalyze Humanitarian Innovation in Computing Research Institutes

This research was commissioned by the World Humanitarian Summit (WHS) Innovation Team, which I joined last year. An important goal of the Summit’s Innovation Team is to identify concrete innovation pathways that can transform the humanitarian industry into a more effective, scalable and agile sector. I have found that discussions on humanitarian innovation can sometimes tend towards conceptual, abstract and academic questions. This explains why I took a different approach vis-a-vis my contribution to the WHS Innovation Track.

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The handbook below provides practical collaboration guidelines for both humanitarian organizations & computing research institutes on how to catalyze humanitarian innovation through successful partnerships. These actionable guidelines are directly applicable now and draw on extensive interviews with leading humanitarian groups and CRI’s including the International Committee of the Red Cross (ICRC), United Nations Office for the Coordination of Humanitarian Affairs (OCHA), United Nations Children’s Fund (UNICEF), United Nations High Commissioner for Refugees (UNHCR), UN Global Pulse, Carnegie Melon University (CMU), International Business Machines (IBM), Microsoft Research, Data Science for Social Good Program at the University of Chicago and others.

This handbook, which is the first of its kind, also draws directly on years of experience and lessons learned from the Qatar Computing Research Institute’s (QCRI) active collaboration and unique partnerships with multiple international humanitarian organizations. The aim of this blog post is to actively solicit feedback on this first, complete working draft, which is available here as an open and editable Google Doc. So if you’re interested in sharing your insights, kindly insert your suggestions and questions by using the Insert/Comments feature. Please do not edit the text directly.

I need to submit the final version of this report on July 1, so very much welcome constructive feedback via the Google Doc before this deadline. Thank you!

Computing Research Institutes as an Innovation Pathway for Humanitarian Technology

The World Humanitarian Summit (WHS) is an initiative by United Nations Secretary-General Ban Ki-moon to improve humanitarian action. The Summit, which is to be held in 2016, stands to be one of the most important humanitarian conferences in a decade. One key pillar of WHS is humanitarian innovation. “Transformation through Innovation” is the WHS Working Group dedicated to transforming humanitarian action by focusing explicitly on innovation. I have the pleasure of being a member of this working group where my contribution focuses on the role of new technologies, data science and advanced computing. As such, I’m working on an applied study to explore the role of computing research institutes as an innovation pathway for humanitarian technology. The purpose of this blog post is to invite feedback on the ideas presented below.

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I first realized that the humanitarian community faced a “Big Data” challenge in 2010, just months after I had joined Ushahidi as Director of Crisis Mapping, and just months after co-founding CrisisMappers: The Humanitarian Technology Network. The devastating Haiti Earthquake resulted in a massive overflow of information generated via mainstream news, social media, text messages and satellite imagery. I launched and spearheaded the Haiti Crisis Map at the time and together with hundreds of digital volunteers from all around the world went head-to head with Big Data. As noted in my forthcoming book, we realized there and then that crowdsourcing and mapping software alone were no match for Big (Crisis) Data.

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This explains why I decided to join an advanced computing research institute, namely QCRI. It was clear to me after Haiti that humanitarian organizations had to partner directly with advanced computing experts to manage the new Big Data challenge in disaster response. So I “embedded” myself in an institute with leading experts in Big Data Analytics, Data Science and Social Computing. I believe that computing research institutes (CRI’s) can & must play an important role in fostering innovation in next generation humanitarian technology by partnering with humanitarian organizations on research & development (R&D).

There is already some evidence to support this proposition. We (QCRI) teamed up with the UN Office for the Coordination of Humanitarian Affairs (OCHA) to create the Artificial Intelligence for Disaster Response platform, AIDR as well as MicroMappers. We are now extending AIDR to analyze text messages (SMS) in partnership with UNICEF. We are also spearheading efforts around the use and analysis of aerial imagery (captured via UAVs) for disaster response (see the Humanitarian UAV Network: UAViators). On the subject of UAVs, I believe that this new technology presents us (in the WHS Innovation team) with an ideal opportunity to analyze in “real time” how a new, disruptive technology gets adopted within the humanitarian system. In addition to UAVs, we catalyzed a partnership with Planet Labs and teamed up with Zooniverse to take satellite imagery analysis to the next level with large scale crowd computing. To this end, we are working with humanitarian organizations to enable them to make sense of Big Data generated via social media, SMS, aerial imagery & satellite imagery.

The incentives for humanitarian organizations to collaborate with CRI’s are obvious, especially if the latter (like QCRI) commits to making the resulting prototypes freely accessible and open source. But why should CRI’s collaborate with humanitarian organizations in the first place? Because the latter come with real-world challenges and unique research questions that many computer scientists are very interested in for several reasons. First, carrying out scientific research on real-world problems is of interest to the vast majority of computer scientists I collaborate with, both within QCRI and beyond. These scientists want to apply their skills to make the world a better place. Second, the research questions that humanitarian organizations bring enable computer scientists to differentiate themselves in the publishing world. Third, the resulting research can help advanced the field of computer science and advanced computing.

So why are we see not seeing more collaboration between CRI’s & humanitarian organizations? Because of this cognitive surplus mismatch. It takes a Director of Social Innovation (or related full-time position) to serve as a translational leader between CRI’s and humanitarian organizations. It takes someone (ideally a team) to match the problem owners and problem solvers; to facilitate and manage the collaboration between these two very different types of expertise and organizations. In sum, CRI’s can serve as an innovation pathway if the following three ingredients are in place: 1) Translation Leader; 2) Committed CRI; and 3) Committed Humanitarian Organization. These are necessary but not sufficient conditions for success.

While research institutes have a comparative advantage in R&D, they are not the best place to scale humanitarian technology prototypes. In order to take these prototypes to the next level, make them sustainable and have them develop into enterprise level software, they need to be taken up by for-profit companies. The majority of CRI’s (QCRI included) actually do have a mandate to incubate start-up companies. As such, we plan to spin-off some of the above platforms as independent companies in order to scale the technologies in a robust manner. Note that the software will remain free to use for humanitarian applications; other uses of the platform will require a paid license. Therein lies the end-to-end innovation path that computing research institutes can offer humanitarian organization vis-a-vis next generation humanitarian technologies.

As noted above, part of my involvement with the WHS Innovation Team entails working on an applied study to document and replicate this innovation pathway. As such, I am looking for feedback on the above as well as on the research methodology described below.

I plan to interview Microsoft Research, IBM Research, Yahoo Research, QCRI and other institutes as part of this research. More specifically, the interview questions will include:

  • Have you already partnered with humanitarian organizations? Why/why not?
  • If you have partnered with humanitarian organizations, what was the outcome? What were the biggest challenges? Was the partnership successful? If so, why? If not, why not?
  • If you have not yet partnered with humanitarian organizations, why not? What factors would be conducive to such partnerships and what factors serve as hurdles?
  • What are your biggest concerns vis-a-vis working with humanitarian groups?
  • What funding models did you explore if any?

I also plan to interview humanitarian organizations to better understand the prospects for this potential innovation pathway. More specifically, I plan to interview ICRC, UNHCR, UNICEF and OCHA using the following questions:

  • Have you already partnered with computing research groups? Why/why not?
  • If you have partnered with computing research groups, what was the outcome? What were the biggest challenges? Was the partnership successful? If so, why? If not, why not?
  • If you have not yet partnered with computing research groups, why not? What factors would be conducive to such partnerships and what factors serve as hurdles?
  • What are your biggest concerns vis-a-vis working with computing research groups?
  • What funding models did you explore if any?

My plan is to carry out the above semi-structured interviews in February-March 2015 along with secondary research. My ultimate aim with this deliverable is to develop a model to facilitate greater collaboration between computing research institutes and humanitarian organizations. To this end, I welcome feedback on all of the above (feel free to email me and/or add comments below). Thank you.

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See also:

  • Research Framework for Next Generation Humanitarian Technology and Innovation [link]
  • From Gunfire at Sea to Maps of War: Implications for Humanitarian Innovation [link]

And the UAV/Drone Social Innovation Award Goes To?

The winner of the Drone Social Innovation Award has just been announced! The $10,000 prize is awarded to the most socially beneficial, documented use of a UAV platform that costs less than $3,000. The purpose of this award is to “spur innovation, investment, and attention to the positive role this technology can play in our society.” Many thanks to my colleague Timothy Reuter for including me on the panel of judges for this novel Social Innovation Award, which was kindly sponsored by NEXA Capital Partners.

Here’s a quick look at our finalists!

Disaster Relief in the Philippines

Using low-cost UAVs to take high-resolution imagery of disaster-affected areas following Typhoon Haiyan in the Philippines. The team behind these efforts is also working with NGOs from around the world to enable them to use this simple technology for situational awareness in times of crisis. The team is also developing platforms to deliver critical items to locations that are difficult to access in post-disaster scenarios.

Taking Autism to the Sky

Teaching young children with autism how to build and fly their own UAVs. The team behind this initiative to scale their work and teach autistic kids both better social skills and “concrete skills in drone technology that could get them a job one day. It’s just one of the many proposed uses of drones in schools and in science and technology education.”

Crowd Estimation with UAVs

While this entry focuses specifically on the use of UAVs and algorithms to determine the size of social movements (e.g., rallies & protests), there may be application to estimating population flows in refugee and IDP settings. I have a blog post on this topic coming up, stay tuned!

Drones for environmental conservation

Aerial photos and videos helped to direct millions in funding to acquire and preserve hundreds of acres of valuable habitat and strategic additions to public park space. “In a single glance, an aerial photo allows you understand so much more about location than a view from the ground.”

Landmine detection

Bosnia-Herzegovina has one of the highest densities of land mines in the world. So this team from Barcelona is exploring how UAVs might accelerate the process of land mine detection. See this post to learn about another UAV land mine detection effort following the massive flooding in the region this summer.

Whale Research and Conservation

Using benign research tools like UAVs to prove you can study whales without killing them. This allows conservationists to study whales’ DNA  along with their stress hormones without disturbing them or requiring the use of loud and expensive airplanes.


And the award goes to… (drum roll please)… not one but two entries (yes it really was a tie)!  Big congratulations to the teams behind the Land Mine Detection and Disaster Response projects! We really look forward to following your progress. Thank you for your important contributions to social innovation!

We are hoping to making this new “Drone Social Innovation Award” an annual competition (if the stars align again next year). So stay tuned. In the meantime, many thanks again to Timothy Reuter for spearheading this social innovation challenge, to my fellow judges, and most importantly to all participants for taking the time to share their remarkable projects!

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See Also:

  • Crowdsourcing the Analysis of Aerial Imagery for Wildlife Protection  and Disaster Response [link]
  • Humanitarians in the Sky: Using UAVs for Disaster Response [link]
  • Official UN Policy Brief on Humanitarian UAVs [link]
  • Crisis Map of UAV Videos for Disaster Response [link]
  • Humanitarian UAV Missions During Balkan Floods [link]
  • UAVs, Community Mapping & Disaster Risk Reduction in Haiti [link]

A Research Framework for Next Generation Humanitarian Technology and Innovation

Humanitarian donors and organizations are increasingly championing innovation and the use of new technologies for humanitarian response. DfID, for example, is committed to using “innovative techniques and technologies more routinely in humanitarian response” (2011). In a more recent strategy paper, DfID confirmed that it would “continue to invest in new technologies” (2012). ALNAP’s important report on “The State of the Humanitarian System” documents the shift towards greater innovation, “with new funds and mechanisms designed to study and support innovation in humanitarian programming” (2012). A forthcoming land-mark study by OCHA makes the strongest case yet for the use and early adoption of new technologies for humanitarian response (2013).

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These strategic policy documents are game-changers and pivotal to ushering in the next wave of humanitarian technology and innovation. That said, the reports are limited by the very fact that the authors are humanitarian professionals and thus not necessarily familiar with the field of advanced computing. The purpose of this post is therefore to set out a more detailed research framework for next generation humanitarian technology and innovation—one with a strong focus on information systems for crisis response and management.

In 2010, I wrote this piece on “The Humanitarian-Technology Divide and What To Do About It.” This divide became increasingly clear to me when I co-founded and co-directed the Harvard Humanitarian Initiative’s (HHI) Program on Crisis Mapping & Early Warning (2007-2009). So I co-founded the annual Inter-national CrisisMappers Conference series in 2009 and have continued to co-organize this unique, cross-disciplinary forum on humanitarian technology. The CrisisMappers Network also plays an important role in bridging the humanitarian and technology divide. My decision to join Ushahidi as Director of Crisis Mapping (2009-2012) was a strategic move to continue bridging the divide—and to do so from the technology side this time.

The same is true of my move to the Qatar Computing Research Institute (QCRI) at the Qatar Foundation. My experience at Ushahidi made me realize that serious expertise in Data Science is required to tackle the major challenges appearing on the horizon of humanitarian technology. Indeed, the key words missing from the DfID, ALNAP and OCHA innovation reports include: Data Science, Big Data Analytics, Artificial Intelligence, Machine Learning, Machine Translation and Human Computing. This current divide between the humanitarian and data science space needs to be bridged, which is precisely why I joined the Qatar Com-puting Research Institute as Director of Innovation; to develop and prototype the next generation of humanitarian technologies by working directly with experts in Data Science and Advanced Computing.

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My efforts to bridge these communities also explains why I am co-organizing this year’s Workshop on “Social Web for Disaster Management” at the 2013 World Wide Web conference (WWW13). The WWW event series is one of the most prestigious conferences in the field of Advanced Computing. I have found that experts in this field are very interested and highly motivated to work on humanitarian technology challenges and crisis computing problems. As one of them recently told me: “We simply don’t know what projects or questions to prioritize or work on. We want questions, preferably hard questions, please!”

Yet the humanitarian innovation and technology reports cited above overlook the field of advanced computing. Their policy recommendations vis-a-vis future information systems for crisis response and management are vague at best. Yet one of the major challenges that the humanitarian sector faces is the rise of Big (Crisis) Data. I have already discussed this here, here and here, for example. The humanitarian community is woefully unprepared to deal with this tidal wave of user-generated crisis information. There are already more mobile phone sub-scriptions than people in 100+ countries. And fully 50% of the world’s population in developing countries will be using the Internet within the next 20 months—the current figure is 24%. Meanwhile, close to 250 million people were affected by disasters in 2010 alone. Since then, the number of new mobile phone subscrip-tions has increased by well over one billion, which means that disaster-affected communities today are increasingly likely to be digital communities as well.

In the Philippines, a country highly prone to “natural” disasters, 92% of Filipinos who access the web use Facebook. In early 2012, Filipinos sent an average of 2 billion text messages every day. When disaster strikes, some of these messages will contain information critical for situational awareness & rapid needs assess-ment. The innovation reports by DfID, ALNAP and OCHA emphasize time and time again that listening to local communities is a humanitarian imperative. As DfID notes, “there is a strong need to systematically involve beneficiaries in the collection and use of data to inform decision making. Currently the people directly affected by crises do not routinely have a voice, which makes it difficult for their needs be effectively addressed” (2012). But how exactly should we listen to millions of voices at once, let alone manage, verify and respond to these voices with potentially life-saving information? Over 20 million tweets were posted during Hurricane Sandy. 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, i.e., 2,000 tweets per second on average.

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Of course, the volume and velocity of crisis information will vary from country to country and disaster to disaster. But the majority of humanitarian organizations do not have the technologies in place to handle smaller tidal waves either. Take the case of the recent Typhoon in the Philippines, for example. OCHA activated the Digital Humanitarian Network (DHN) to ask them to carry out a rapid damage assessment by analyzing the 20,000 tweets posted during the first 48 hours of Typhoon Pablo. In fact, one of the main reasons digital volunteer networks like the DHN and the Standby Volunteer Task Force (SBTF) exist is to provide humanitarian organizations with this kind of skilled surge capacity. But analyzing 20,000 tweets in 12 hours (mostly manually) is one thing, analyzing 20 million requires more than a few hundred dedicated volunteers. What’s more, we do not have the luxury of having months to carry out this analysis. Access to information is as important as access to food; and like food, information has a sell-by date.

We clearly need a research agenda to guide the development of next generation humanitarian technology. One such framework is proposed her. The Big (Crisis) Data challenge is composed of (at least) two major problems: (1) finding the needle in the haystack; (2) assessing the accuracy of that needle. In other words, identifying the signal in the noise and determining whether that signal is accurate. Both of these challenges are exacerbated by serious time con-straints. There are (at least) two ways too manage the Big Data challenge in real or near real-time: Human Computing and Artificial Intelligence. We know about these solutions because they have already been developed and used by other sectors and disciplines for several years now. In other words, our information problems are hardly as unique as we might think. Hence the importance of bridging the humanitarian and data science communities.

In sum, the Big Crisis Data challenge can be addressed using Human Computing (HC) and/or Artificial Intelligence (AI). Human Computing includes crowd-sourcing and microtasking. AI includes natural language processing and machine learning. A framework for next generation humanitarian technology and inno-vation must thus promote Research and Development (R&D) that apply these methodologies for humanitarian response. For example, Verily is a project that leverages HC for the verification of crowdsourced social media content generated during crises. In contrast, this here is an example of an AI approach to verification. The Standby Volunteer Task Force (SBTF) has used HC (micro-tasking) to analyze satellite imagery (Big Data) for humanitarian response. An-other novel HC approach to managing Big Data is the use of gaming, something called Playsourcing. AI for Disaster Response (AIDR) is an example of AI applied to humanitarian response. In many ways, though, AIDR combines AI with Human Computing, as does MatchApp. Such hybrid solutions should also be promoted   as part of the R&D framework on next generation humanitarian technology. 

There is of course more to humanitarian technology than information manage-ment alone. Related is the topic of Data Visualization, for example. There are also exciting innovations and developments in the use of drones or Unmanned Aerial Vehicles (UAVs), meshed mobile communication networks, hyper low-cost satellites, etc.. I am particularly interested in each of these areas will continue to blog about them. In the meantime, I very much welcome feedback on this post’s proposed research framework for humanitarian technology and innovation.

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Innovation and the State of the Humanitarian System

Published by ALNAP, the 2012 State of the Humanitarian System report is an important evaluation of the humanitarian community’s efforts over the past two years. “I commend this report to all those responsible for planning and delivering life saving aid around the world,” writes UN Under-Secretary General Valerie Amos in the Preface. “If we are going to improve international humanitarian response we all need to pay attention to the areas of action highlighted in the report.” Below are some of the highlighted areas from the 100+ page evaluation that are ripe for innovative interventions.

Accessing Those in Need

Operational access to populations in need has not improved. Access problems continue and are primarily political or security-related rather than logistical. Indeed, “UN security restrictions often place sever limits on the range of UN-led assessments,” which means that “coverage often can be compromised.” This means that “access constraints in some contexts continue to inhibit an accurate assessment of need. Up to 60% of South Sudan is inaccessible for parts of the year. As a result, critical data, including mortality and morbidity, remain unavailable. Data on nutrition, for example, exist in only 25 of 79 countries where humanitarian partners have conducted surveys.”

Could satellite and/or areal imagery be used to measure indirect proxies? This would certainly be rather imperfect but perhaps better than nothing? Could crowdseeding be used?

Information and Communication Technologies

“The use of mobile devices and networks is becoming increasingly important, both to deliver cash and for communication with aid recipients.” Some humanitarian organizations are also “experimenting with different types of communication tools, for different uses and in different contexts. Examples include: offering emergency information, collecting information for needs assessments or for monitoring and evaluation, surveying individuals, or obtaining information on remote populations from an appointed individual at the community level.”

“Across a variety of interventions, mobile phone technology is seen as having great potential to increase efficiency. For example, […] the governments of Japan and Thailand used SMS and Twitter to spread messages about the disaster response.” Naturally, in some contexts, “traditional means like radios and call centers are most appropriate.”

In any case, “thanks to new technologies and initiatives to advance commu-nications with affected populations, the voices of aid recipients began, in a small way, to be heard.” Obviously, heard and understood are not the same thing–not to mention heard, understood and responded to. Moreover, as disaster affected communities become increasingly “digital” thanks to the spread of mobile phones, the number of voices will increase significantly. The humanitarian system is largely (if not completely) unprepared to handle this increase in volume (Big Data).

Consulting Local Recipients

Humanitarian organizations have “failed to consult with recipients […] or to use their input in programming.” Indeed, disaster-affected communities are “rarely given opportunities to assess the impact of interventions and to comment on performance.” In fact, “they are rarely treated as end-users of the service.” Aid recipients also report that “the aid they received did not address their ‘most important needs at the time.'” While some field-level accountability mechanisms do exist, they were typically duplicative and very project oriented. To this end, “it might be more efficient and effective to have more coordination between agencies regarding accountability approaches.”

While the ALNAP report suggests that these shortcomings could “be addressed in the near future by technical advances in methods of needs assessment,” the challenge here is not simply a technical one. Still, there are important efforts underway to address these issues.

Improving Needs Assessments

The Inter-Agency Standing Committee’s (IASC) Needs Assessment Task Force (NAFT) and the International NGO-led Assessment Capacities Project (ACAPS) are two such exempts of progress. OCHA serves as the secretariat for the NAFT through its Assessment and Classification of Emergencies (ACE) Team. ACAPS, which is a consortium of three international NGOs (X, Y and Z) and a member of NATF, aims to “strengthen the capacity of the humanitarian sector in multi-sectoral needs assessment.” ACAPS is considered to have “brought sound technical processes and practical guidelines to common needs assessment.” Note that both ACAPS and ACE have recently reached out to the Digital Humanitarian Network (DHNetwork) to partner on needs-assessment projects in South Sudan and the DRC.

Another promising project is the Humanitarian Emergency Settings Perceived Needs Scale (HESPER). This join initiative between WHO and King’s College London is designed to rapidly assess the “perceived needs of affected populations and allow their views to be taken into consideration. The project specifically aims to fill the gap between population-based ‘objective’ indicators […] and/or qualitative data based on convenience samples such as focus groups or key informant interviews.” On this note, some NGOs argue that “overall assessment methodologies should focus far more at the community (not individual) level, including an assessment of local capacities […],” since “far too often international aid actors assume there is no local capacity.”

Early Warning and Response

An evaluation of the response in the Horn of Africa found “significant disconnects between early warning systems and response, and between technical assessments and decision-makers.” According to ALNAP, “most commentators agree that the early warning worked, but there was a failure to act on it.” This disconnect is a concern I voiced back in 2009 when UN Global Pulse was first launched. To be sure, real-time information does not turn an organization into a real-time organization. Not surprisingly, most of the aid recipients surveyed for the ALNAP report felt that “the foremost way in which humanitarian organizations could improve would be to: ‘be faster to start delivering aid.'” Interestingly, “this stands in contrast to the survey responses of international aid practitioners who gave fairly high marks to themselves for timeliness […].”

Rapid and Skilled Humanitarians

While the humanitarian system’s surge capacity for the deployment of humanitarian personnel has improved, “findings also suggest that the adequate scale-up of appropriately skilled […] staff is still perceived as problematic for both operations and coordination.” Other evaluations “consistently show that staff in NGOs, UN agencies and clusters were perceived to be ill prepared in terms of basic language and context training in a significant number of contexts.” In addition, failures in knowledge and understanding of humanitarian principles were also raised. Furthermore, evaluations of mega-disasters “predictably note influxes or relatively new staff with limited experience.” Several evaluations noted that the lack of “contextual knowledge caused a net decrease in impact.” This lend one senior manager noted:

“If you don’t understand the political, ethnic, tribal contexts it is difficult to be effective… If I had my way I’d first recruit 20 anthropologists and political scientists to help us work out what’s going on in these settings.”

Monitoring and Evaluation

ALNAP found that monitoring and evaluation continues to be a significant shortcoming in the humanitarian system. “Evaluations have made mixed progress, but affected states are still notably absent from evaluating their own response or participating in joint evaluations with counterparts.” Moreover, while there have been important efforts by CDAC and others to “improve accountability to, and communication with, aid recipients,” there is “less evidence to suggest that this new resource of ground-level information is being used strategically to improve humanitarian interventions.” To this end, “relatively few evaluations focus on the views of aid recipients […].” In one case, “although a system was in place with results-based indicators, there was neither the time nor resources to analyze or use the data.”

The most common reasons cited for failing to meet community expectations include the “inability to meet the full spectrum of need, weak understanding of local context, inability to understand the changing nature of need, inadequate information-gathering techniques or an inflexible response approach.” In addition, preconceived notions of vulnerability have “led to inappropriate interventions.” A major study carried out by Tufts University and cited in the ALNAP report concludes that “humanitarian assistance remains driven by ‘anecdote rather than evidence’ […].” One important exception to this is the Danish Refugee Council’s work in Somalia.

Leadership, Risk and Principles

ALNAP identifies an “alarming evidence of a growing tendency towards risk aversion” and a “stifling culture of compliance.” In addition, adherence to humanitarian principles were found to have weakened as “many humanitarian organizations have willingly compromised a principled approach in their own conduct through close alignment with political and military activities and actors.” Moreover, “responses in highly politicized contexts are viewed as particularly problematic for the retention of humanitarian principles.” Humanitarian professionals who were interviewed by ALNAP for this report “highlighted multiple occasions when agencies failed to maintain an impartial response when under pressure from strong states, such as Pakistan and Sri Lanka.”