Americas

The era of development mutants

Curated on April 17, 2016May 29, 2019 by Stefaan Verhulst

Guilo Quaggiotto at Nesta: “If you were looking for the cutting edge of the development sector, where would you go these days? You would probably look at startups like Premise who have predicted food trends 25 days faster than national statistics in Brazil, or GiveDirectly who are pushing the boundaries on evidence – from RCTs to new ways of mapping poverty – to fast track the adoption of cash transfers.

Or perhaps you might draw your attention to PetaJakarta who are experimenting with new responses to crises by harnessing human sensor networks. You might be tempted to consider Airbnb’s Disaster Response programme as an indicator of an emerging alternative infrastructure for disaster response (and perhaps raising questions about the political economy of this all).

And could Bitnation’s Refugee Emergency programme in response to the European refugee crisis be the possible precursor of future solutions for transnational issues – among the development sector’s hardest challenges? Are the business models of One Acre Fund, which provides services for smallholder farmers, or Floodtags, which analyses citizen data during floods for water and disaster managers, an indicator of future pathways to scale – that elusive development unicorn?

If you want to look at the future of procuring solutions for the development sector, should you be looking at initiatives like Citymart, which works with municipalities across the world to rethink traditional procurement and unleash the expertise and innovation capabilities of their citizens? By the same token, projects like Pathogen Box, Poverty Stoplight or Patient Innovation point to a brave new world where lead-user innovation and harnessing ‘sticky’ local knowledge becomes the norm, rather than the exception. You would also be forgiven for thinking that social movements across the world are the place to look for signs of future mechanisms for harnessing collective intelligence – Kawal Pamilu’s “citizen experts” self-organising around the Indonesian elections in 2014 is a textbook case study in this department.

The list could go on and on: welcome to the era of development mutants. While established players in the development sector are engrossed in soul-searching and their fitness for purpose is being scrutinised from all quarters, a whole new set of players is emerging, unfettered by legacy and borrowing from a variety of different disciplines. They point to a potentially different future – indeed, many potentially different futures – for the sector…..

But what if we wanted to invert this paradigm? How could we move from denial to fruitful collaboration with the ‘edgeryders’ of the development sector and accelerate its transformation?

Adopting new programming principles

Based on our experience working with development organisations, we believe that partnering with the mutants involves two types of shifts for traditional players: at the programmatic and the operational level. At the programmatic level, our work on the ground led us to articulate the following emerging principles:

Mapping what people have, not what they need: even though approaches like jugaad and positive deviance have been around for a long time, unfortunately the default starting point for many development projects is still mapping needs, not assets. Inverting this paradigm allows for potentially disruptive project design and partnerships to emerge. (Signs of the future: Patient Innovation, Edgeryders, Community Mirror, Premise)
Getting ready for multiple futures: When distributed across an organisation and not limited to a centralised function, the discipline of scanning the horizon for emergent solutions that contradict the dominant paradigm can help move beyond the denial phase and develop new interfaces to collaborate with the mutants. Here the link between analysis (to understand not only what is probable, but also what is possible) and action is critical – otherwise this remains purely an academic exercise. (Signs of the future: OpenCare, Improstuctures, Seeds of Good Anthropocene, Museum of the Future)
Running multiple parallel experiments: According to Dave Snowden, in order to intervene in a complex system “you need multiple parallel experiments and they should be based on different and competing theories/hypotheses”. Unfortunately, many development projects are still based on linear narratives and assumptions such as “if only we run an awareness raising campaign citizens will change their behaviour”. Turning linear narratives into hypotheses to be tested (without becoming religious on a specific approach) opens up the possibility to explore the solution landscape and collaborate with non-obvious partners that bring new approaches to the table. (Signs of the future: Chukua Hakua, GiveDirectly, Finnish PM’s Office of Experiments, Ideas42, Cognitive Edge)
Embracing obliquity: A deep, granular understanding of local assets and dynamics along with system mapping (see point 5 below) and pairing behavioural experts with development practitioners can help identify entry points for exploring new types of intervention based on obliquity principles. Mutants are often faster in adopting this approach and partnering with them is a way to bypass organisational inertia and explore nonlinear interventions. (Signs of the future: Sardex, social prescriptions, forensic architecture)
From projects to systems: development organisations genuinely interested in developing new partnerships need to make the shift from the project logic to system investments. This involves, among other things, shifting the focus from providing solutions to helping every actor in the system to develop a higher level of consciousness about the issues they are facing and to take better decisions over time. It also entails partnering with mutants to explore entirely new financial mechanisms. (Signs of the future: Lankelly Chase, Indonesia waste banks, Dark Matter Labs)

Adopting new interfaces for working with the mutants

Harvard Business School professor Carliss Baldwin argued that most bureaucracies these days have a ‘non-contractible’ problem: they don’t know where smart people are, or how to evaluate how good they are. Most importantly, most smart people don’t want to work for them because they find them either too callous, unrewarding or slow (or a combination of all of these)….(More)”

Data collection is the ultimate public good

Curated on April 7, 2016August 3, 2018 by Stefaan Verhulst

Lawrence H. Summers in the Washington Post: “I spoke at a World Bank conference on price statistics. … I am convinced that data is the ultimate public good and that we will soon have much more data than we do today. I made four primary observations.

First, scientific progress is driven more by new tools and new observations than by hypothesis construction and testing. I cited a number of examples: the observation that Jupiter was orbited by several moons clinched the case against the Ptolemaic system, the belief that all celestial objects circle around the Earth. We learned of cells by seeing them when the microscope was constructed. Accelerators made the basic structure of atoms obvious.

Second, if mathematics is the queen of the hard sciences then statistics is the queen of the social sciences. I gave examples of the power of very simple data analysis. We first learned that exercise is good for health from the observation that, in the 1940s, London bus conductors had much lower death rates than bus drivers. Similarly, data demonstrated that smoking was a major killer decades before the biological processes were understood. At a more trivial level, “Moneyball” shows how data-based statistics can revolutionize a major sport.

Third, I urged that what “you count counts” and argued that we needed much more timely and complete data. I noted the centrality of timely statistics to meaningful progress toward Sustainable Development Goals. In comparison to the nearly six-year lag in poverty statistics, it took the United States only about 3½ years to win World War II.

Fourth, I envisioned what might be possible in a world where there will soon be as many smartphones as adults. With the ubiquitous ability to collect data and nearly unlimited ability to process it will come more capacity to discover previously unknown relationships. We will improve our ability to predict disasters like famines, storms and revolutions. Communication technologies will allow us to better hold policymakers to account with reliable and rapid performance measures. And if history is any guide, we will gain capacities on dimensions we cannot now imagine but will come to regard as indispensable.

This is the work of both governments and the private sector. It is fantasy to suppose data, as the ultimate public good, will come into being without government effort. Equally, we will sell ourselves short if we stick with traditional collection methods and ignore innovative providers and methods such as the use of smartphones, drones, satellites and supercomputers. That is why something like the Billion Prices Project at MIT, which can provide daily price information, is so important. That is why I am excited to be a director and involved with Premise — a data company that analyzes information people collect on their smartphones about everyday life, like the price of local foods — in its capacity to mobilize these technologies as widely as possible. That is why Planet Labs, with its capacity to scan and monitor environmental conditions, represents such a profound innovation….(More)

What Should We Do About Big Data Leaks?

Curated on April 6, 2016October 10, 2018 by Stefaan Verhulst

Paul Ford at the New Republic: “I have a great fondness for government data, and the government has a great fondness for making more of it. Federal elections financial data, for example, with every contribution identified, connected to a name and address. Or the results of the census. I don’t know if you’ve ever had the experience of downloading census data but it’s pretty exciting. You can hold America on your hard drive! Meditate on the miracles of zip codes, the way the country is held together and addressable by arbitrary sets of digits.

You can download whole books, in PDF format, about the foreign policy of the Reagan Administration as it related to Russia. Negotiations over which door the Soviet ambassador would use to enter a building. Gigabytes and gigabytes of pure joy for the ephemeralist. The government is the greatest creator of ephemera ever.

Consider the Financial Crisis Inquiry Commission, or FCIC, created in 2009 to figure out exactly how the global economic pooch was screwed. The FCIC has made so much data, and has done an admirable job (caveats noted below) of arranging it. So much stuff. There are reams of treasure on a single FCIC web site, hosted at Stanford Law School: Hundreds of MP3 files, for example, with interviews with Jamie Dimonof JPMorgan Chase and Lloyd Blankfein of Goldman Sachs. I am desperate to find time to write some code that automatically extracts random audio snippets from each and puts them on top of a slow ambient drone with plenty of reverb, so that I can relax to the dulcet tones of the financial industry explaining away its failings. (There’s a Paul Krugman interview that I assume is more critical.)

The recordings are just the beginning. They’ve released so many documents, and with the documents, a finding aid that you can download in handy PDF format, which will tell you where to, well, find things, pointing to thousands of documents. That aid alone is 1,439 pages.

Look, it is excellent that this exists, in public, on the web. But it also presents a very contemporary problem: What is transparency in the age of massive database drops? The data is available, but locked in MP3s and PDFs and other documents; it’s not searchable in the way a web page is searchable, not easy to comment on or share.

Consider the WikiLeaks release of State Department cables. They were exhausting, there were so many of them, they were in all caps. Or the trove of data Edward Snowden gathered on aUSB drive, or Chelsea Manning on CD. And the Ashley Madison leak, spread across database files and logs of credit card receipts. The massive and sprawling Sony leak, complete with whole email inboxes. And with the just-released Panama Papers, we see two exciting new developments: First, the consortium of media organizations that managed the leak actually came together and collectively, well, branded the papers, down to a hashtag (#panamapapers), informational website, etc. Second, the size of the leak itself—2.5 terabytes!—become a talking point, even though that exact description of what was contained within those terabytes was harder to understand. This, said the consortia of journalists that notably did not include The New York Times, The Washington Post, etc., is the big one. Stay tuned. And we are. But the fact remains: These artifacts are not accessible to any but the most assiduous amateur conspiracist; they’re the domain of professionals with the time and money to deal with them. Who else could be bothered?

If you watched the movie Spotlight, you saw journalists at work, pawing through reams of documents, going through, essentially, phone books. I am an inveterate downloader of such things. I love what they represent. And I’m also comfortable with many-gigabyte corpora spread across web sites. I know how to fetch data, how to consolidate it, and how to search it. I share this skill set with many data journalists, and these capacities have, in some ways, become the sole province of the media. Organs of journalism are among the only remaining cultural institutions that can fund investigations of this size and tease the data apart, identifying linkages and thus constructing informational webs that can, with great effort, be turned into narratives, yielding something like what we call “a story” or “the truth.”

Spotlight was set around 2001, and it features a lot of people looking at things on paper. The problem has changed greatly since then: The data is everywhere. The media has been forced into a new cultural role, that of the arbiter of the giant and semi-legal database. ProPublica, a nonprofit that does a great deal of data gathering and data journalism and then shares its findings with other media outlets, is one example; it funded a project called DocumentCloud with other media organizations that simplifies the process of searching through giant piles of PDFs (e.g., court records, or the results of Freedom of Information Act requests).

At some level the sheer boredom and drudgery of managing these large data leaks make them immune to casual interest; even the Ashley Madison leak, which I downloaded, was basically an opaque pile of data and really quite boring unless you had some motive to poke around.

If this is the age of the citizen journalist, or at least the citizen opinion columnist, it’s also the age of the data journalist, with the news media acting as product managers of data leaks, making the information usable, browsable, attractive. There is an uneasy partnership between leakers and the media, just as there is an uneasy partnership between the press and the government, which would like some credit for its efforts, thank you very much, and wouldn’t mind if you gave it some points for transparency while you’re at it.

Pause for a second. There’s a glut of data, but most of it comes to us in ugly formats. What would happen if the things released in the interest of transparency were released in actual transparent formats?…(More)”

Drones Marshaled to Drop Lifesaving Supplies Over Rwandan Terrain

Curated on April 6, 2016August 3, 2018 by Stefaan Verhulst

John Markoff at the New York Times: “From a bluff overlooking the Pacific Ocean, aloud pop signals the catapult launch of a small fixed-wing drone that is designed to carry medical supplies to remote locations almost 40 miles away.

The drones are the brainchild of a small group of engineers at a SiliconValley start-up called Zipline, which plans to begin operating a service with them for the government of Rwanda in July. The fleet of robot planes will initially cover more than half the tiny African nation, creating a highly automated network to shuttle blood and pharmaceuticals to remote locations in hours rather than weeks or months.

Rwanda, one of the world’s poorest nations, was ranked 170th by gross domestic product in 2014 by the International Monetary Fund. And so it is striking that the country will be the first, company executives said, to establish a commercial drone delivery network — putting it ahead of places like the United States, where there have been heavily ballyhooed futuristicdrone delivery systems promising urban and suburban package delivery from tech giants such as Amazon and Google….

That Rwanda is set to become the first country with a drone delivery network illustrates the often uneven nature of the adoption of new technology. In the United States, drones have run into a wall of regulation and conflicting rules. But in Rwanda, the country’s master development plan has placed a priority on the use of the machines, first for medicine and then more broadly for economic development….

The new drone system will initially be capable of making 50 to 150 daily deliveries of blood and emergency medicine to Rwanda’s 21 transfusing facilities, mostly in hospitals and clinics in the western half of the nation.

The drone system is based on a fleet of 15 small aircraft, each with twin electric motors, a 3.5-pound payload and an almost eight-foot wingspan.The system’s speed makes it possible to maintain a “cold chain” —essentially a temperature-controlled supply chain needed to provide blood and vaccines — which is often not practical to establish in developing countries.

The Zipline drones will use GPS receivers to navigate and communicate via the Rwandan cellular network. They will be able to fly in rough weather conditions, enduring winds up to 30 miles per hour….(More)”

Website Seeks to Make Government Data Easier to Sift Through

Curated on April 5, 2016August 3, 2018 by Stefaan Verhulst

Steve Lohr at the New York Times: “For years, the federal government, states and some cities have enthusiastically made vast troves of data open to the public. Acres of paper records on demographics, public health, traffic patterns, energy consumption, family incomes and many other topics have been digitized and posted on the web.

This abundance of data can be a gold mine for discovery and insights, but finding the nuggets can be arduous, requiring special skills.

A project coming out of the M.I.T. Media Lab on Monday seeks to ease that challenge and to make the value of government data available to a wider audience. The project, called Data U S A, bills itself as “the most comprehensive visualization of U.S. public data.” It is free, and its software code is open source, meaning that developers can build custom applications by adding other data.

Cesar A. Hidalgo, an assistant professor of media arts and sciences at the M.I.T. Media Lab who led the development of Data USA, said the website was devised to “transform data into stories.” Those stories are typically presented as graphics, charts and written summaries….Type “New York” into the Data USA search box, and a drop-down menu presents choices — the city, the metropolitan area, the state and other options. Select the city, and the page displays an aerial shot of Manhattan with three basic statistics: population (8.49 million), median household income ($52,996) and median age (35.8).

Lower on the page are six icons for related subject categories, including economy, demographics and education. If you click on demographics, one of the so-called data stories appears, based largely on data from the American Community Survey of the United States Census Bureau.

Using colorful graphics and short sentences, it shows the median age of foreign-born residents of New York (44.7) and of residents born in the United States (28.6); the most common countries of origin for immigrants (the Dominican Republic, China and Mexico); and the percentage of residents who are American citizens (82.8 percent, compared with a national average of 93 percent).

Data USA features a selection of data results on its home page. They include the g ender w age g ap in Connecticut; the r acial b reakdown of po verty in Flint, Mich.; the wages of p hysicians and s urgeons across the United States; and the institutions that award the most c omputer s cience degrees….(More)

Data to the Rescue: Smart Ways of Doing Good

Curated on April 5, 2016May 29, 2019 by Stefaan Verhulst

Nicole Wallace in the Chronicle of Philanthropy: “For a long time, data served one purpose in the nonprofit world: measuring program results. But a growing number of charities are rejecting the idea that data equals evaluation and only evaluation.

Of course, many nonprofits struggle even to build the simplest data system. They have too little money, too few analysts, and convoluted data pipelines. Yet some cutting-edge organizations are putting data to work in new and exciting ways that drive their missions. A prime example: The Polaris Project is identifying criminal networks in the human-trafficking underworld and devising strategies to fight back by analyzing its data storehouse along with public information.

Other charities dive deep into their data to improve services, make smarter decisions, and identify measures that predict success. Some have such an abundance of information that they’re even pruning their collection efforts to allow for more sophisticated analysis.

The groups highlighted here are among the best nationally. In their work, we get a sneak peek at how the data revolution might one day achieve its promise.

House Calls: Living Goods…

Living Goods launched in eastern Africa in 2007 with an innovative plan to tackle health issues in poor families and reduce deaths among children. The charity provides loans, training, and inventory to locals in Uganda and Kenya — mostly women — to start businesses selling vitamins, medicine, and other health products to friends and neighbors.

Founder Chuck Slaughter copied the Avon model and its army of housewives-turned-sales agents. But in recent years, Living Goods has embraced a 21st-century data system that makes its entrepreneurs better health practitioners. Armed with smartphones, they confidently diagnose and treat major illnesses. At the same time, they collect information that helps the charity track health across communities and plot strategy….

Unraveling Webs of Wickedness: Polaris Project…

Calls and texts to the Polaris Project’s national human-trafficking hotline are often heartbreaking, terrifying, or both.

Relatives fear that something terrible has happened to a missing loved one. Trafficking survivors suffering from their ordeal need support. The most harrowing calls are from victims in danger and pleading for help.

Last year more than 5,500 potential cases of exploitation for labor or commercial sex were reported to the hotline. Since it got its start in 2007, the total is more than 24,000.

As it helps victims and survivors get the assistance they need, the Polaris Project, a Washington nonprofit, is turning those phone calls and texts into an enormous storehouse of information about the shadowy world of trafficking. By analyzing this data and connecting it with public sources, the nonprofit is drawing detailed pictures of how trafficking networks operate. That knowledge, in turn, shapes the group’s prevention efforts, its policy work, and even law-enforcement investigations….

Too Much Information: Year Up…

Year Up has a problem that many nonprofits can’t begin to imagine: It collects too much data about its program. “Predictive analytics really start to stink it up when you put too much in,” says Garrett Yursza Warfield, the group’s director of evaluation.

What Mr. Warfield describes as the “everything and the kitchen sink” problem started soon after Year Up began gathering data. The group, which fights poverty by helping low-income young adults land entry-level professional jobs, first got serious about measuring its work nearly a decade ago. Though challenged at first to round up even basic information, the group over time began tracking virtually everything it could: the percentage of young people who finish the program, their satisfaction, their paths after graduation through college or work, and much more.

Now the nonprofit is diving deeper into its data to figure out which measures can predict whether a young person is likely to succeed in the program. And halfway through this review, it’s already identified and eliminated measures that it’s found matter little. A small example: Surveys of participants early in the program asked them to rate their proficiency at various office skills. Those self-evaluations, Mr. Warfield’s team concluded, were meaningless: How can novice professionals accurately judge their Excel spreadsheet skills until they’re out in the working world?…

On the Wild Side: Wildnerness Society…Without room to roam, wild animals and plants breed among themselves and risk losing genetic diversity. They also fall prey to disease. And that’s in the best of times. As wildlife adapt to climate change, the chance to migrate becomes vital even to survival.

National parks and other large protected areas are part of the answer, but they’re not enough if wildlife can’t move between them, says Travis Belote, lead ecologist at the Wilderness Society.

“Nature needs to be able to shuffle around,” he says.

Enter the organization’s Wildness Index. It’s a national map that shows the parts of the country most touched by human activity as well as wilderness areas best suited for wildlife. Mr. Belote and his colleagues created the index by combining data on land use, population density, road location and size, water flows, and many other factors. It’s an important tool to help the nonprofit prioritize the locations it fights to protect.

In Idaho, for example, the nonprofit compares the index with information about known wildlife corridors and federal lands that are unprotected but meet the criteria for conservation designation. The project’s goal: determine which areas in the High Divide — a wild stretch that connects Greater Yellowstone with other protected areas — the charity should advocate to legally protect….(More)”

Selected Readings on Data and Humanitarian Response

Curated on April 3, 2016May 29, 2019 by Stefaan Verhulst

By Prianka Srinivasan and Stefaan G. Verhulst *

The Living Library’s Selected Readings series seeks to build a knowledge base on innovative approaches for improving the effectiveness and legitimacy of governance. This curated and annotated collection of recommended works on the topic of data and humanitarian response was originally published in 2016.

Data, when used well in a trusted manner, allows humanitarian organizations to innovate how to respond to emergency events, including better coordination of post-disaster relief efforts, the ability to harness local knowledge to create more targeted relief strategies, and tools to predict and monitor disasters in real time. Consequently, in recent years both multinational groups and community-based advocates have begun to integrate data collection and evaluation strategies into their humanitarian operations, to better and more quickly respond to emergencies. However, this movement poses a number of challenges. Compared to the private sector, humanitarian organizations are often less equipped to successfully analyze and manage big data, which pose a number of risks related to the security of victims’ data. Furthermore, complex power dynamics which exist within humanitarian spaces may be further exacerbated through the introduction of new technologies and big data collection mechanisms. In the below we share:

Selected Reading List (summaries and hyperlinks)
Annotated Selected Reading List
Additional Readings

Selected Reading List (summaries in alphabetical order)

Data and Humanitarian Response

John Karlsrud – Peacekeeping 4.0: Harnessing the Potential of Big Data, Social Media, and Cyber Technologies – Recommends that UN peacekeeping initiatives should better integrate big data and new technologies into their operations, adopting a “Peacekeeping 4.0” for the modern world.
Fancesco Mancini, International Peace Institute – New Technology and the prevention of Violence and Conflict – Explores the ways in which new tools available in communications technology can assist humanitarian workers in preventing violence and conflict.
Patrick Meier – Digital Humanitarians- How Big Data is changing the face of humanitarian response – Profiles the emergence of ‘Digital Humanitarians’—humanitarian workers who are using big data, crowdsourcing and new technologies to transform the way societies respond to humanitarian disasters.
Andrew Robertson and Steve Olson (USIP) – Using Data Sharing to Improve Coordination in Peacebuilding – Summarises the findings of a United States Institute of Peace workshop which investigated the use of data-sharing systems between government and non-government actors in conflict zones. It identifies some of the challenges and benefits of data-sharing in peacebuilding efforts.
United Nations Independent Expert Advisory Group on a Data Revolution for Sustainable Development – A World That Counts, Mobilizing the Data Revolution – Compiled by a group of 20 international experts, this report proposes ways to improve data management and monitoring, whilst mitigating some of the risks data poses.
Katie Whipkey and Andrej Verity – Guidance for Incorporating Big Data into Humanitarian Operations – Created as part of the Digital Humanitarian Network with the support of UN-OCHA, this is a manual for humanitarian organizations looking to strategically incorporate Big Data into their work.

Risks of Using Big Data in Humanitarian Context

Kate Crawford and Megan Finn – The limits of crisis data: analytical and ethical challenges of using social and mobile data to understand disasters – Analyzes the use of big data techniques following a crisis event, arguing that a reliance of social and mobile data can lead to significant oversights and ethical concerns in the wake of humanitarian disasters.
Katja Lindskov Jacobsen – Making design safe for citizens: A hidden history of humanitarian experimentation – Argues that the UNHCR’s use of iris recognition technology in 2002 and 2007 during the repatriation of Afghan refugees from Pakistan constitutes a case of “humanitarian experimentation.” It questions this sort of experimentation which compromises the security of refugees in the pursuit of safer technologies for the rest of the world.
Responsible Data Forum – Responsible Data Reflection Stories: an Overview – compiles various stories sourced by the Responsible Data Forum blog relating to data challenges faced by advocacy organizations, and draws recommendations based on these cases.
Kristin Bergtora Sandvik – The humanitarian cyberspace: shrinking space or an expanding frontier? – Provides a detailed account of the development of a “humanitarian cyberspace” and how information and communication technologies have been further integrated into humanitarian operations since the mid-1990s.

Annotated Selected Reading List (in alphabetical order)

Karlsrud, John. “Peacekeeping 4.0: Harnessing the Potential of Big Data, Social Media, and Cyber Technologies.” Cyberspace and International Relations, 2013. http://bit.ly/235Qb3e

This chapter from the book “Cyberspace and International Relations” suggests that advances in big data give humanitarian organizations unprecedented opportunities to prevent and mitigate natural disasters and humanitarian crises. However, the sheer amount of unstructured data necessitates effective “data mining” strategies for multinational organizations to make the most use of this data.
By profiling some civil-society organizations who use big data in their peacekeeping efforts, Karlsrud suggests that these community-focused initiatives are leading the movement toward analyzing and using big data in countries vulnerable to crisis.
The chapter concludes by offering ten recommendations to UN peacekeeping forces to best realize the potential of big data and new technology in supporting their operations.

Mancini, Fancesco. “New Technology and the prevention of Violence and Conflict.” International Peace Institute, 2013. http://bit.ly/1ltLfNV

This report from the International Peace Institute looks at five case studies to assess how information and communications technologies (ICTs) can help prevent humanitarian conflicts and violence. Their findings suggest that context has a significant impact on the ability for these ICTs for conflict prevention, and any strategies must take into account the specific contingencies of the region to be successful.
The report suggests seven lessons gleaned from the five case studies:
- New technologies are just one in a variety of tools to combat violence. Consequently, organizations must investigate a variety of complementary strategies to prevent conflicts, and not simply rely on ICTs.
- Not every community or social group will have the same relationship to technology, and their ability to adopt new technologies are similarly influenced by their context. Therefore, a detailed needs assessment must take place before any new technologies are implemented.
- New technologies may be co-opted by violent groups seeking to maintain conflict in the region. Consequently, humanitarian groups must be sensitive to existing political actors and be aware of possible negative consequences these new technologies may spark.
- Local input is integral to support conflict prevention measures, and there exists need for collaboration and awareness-raising with communities to ensure new technologies are sustainable and effective.
- Information shared between civil-society has more potential to develop early-warning systems. This horizontal distribution of information can also allow communities to maintain the accountability of local leaders.

Meier, Patrick. “Digital humanitarians: how big data is changing the face of humanitarian response.” Crc Press, 2015. http://amzn.to/1RQ4ozc

This book traces the emergence of “Digital Humanitarians”—people who harness new digital tools and technologies to support humanitarian action. Meier suggests that this has created a “nervous system” to connect people from disparate parts of the world, revolutionizing the way we respond to humanitarian crises.
Meier argues that such technology is reconfiguring the structure of the humanitarian space, where victims are not simply passive recipients of aid but can contribute with other global citizens. This in turn makes us more humane and engaged people.

Robertson, Andrew and Olson, Steve. “Using Data Sharing to Improve Coordination in Peacebuilding.” United States Institute for Peace, 2012. http://bit.ly/235QuLm

This report functions as an overview of a roundtable workshop on Technology, Science and Peace Building held at the United States Institute of Peace. The workshop aimed to investigate how data-sharing techniques can be developed for use in peace building or conflict management.
Four main themes emerged from discussions during the workshop:
- “Data sharing requires working across a technology-culture divide”—Data sharing needs the foundation of a strong relationship, which can depend on sociocultural, rather than technological, factors.
- “Information sharing requires building and maintaining trust”—These relationships are often built on trust, which can include both technological and social perspectives.
- “Information sharing requires linking civilian-military policy discussions to technology”—Even when sophisticated data-sharing technologies exist, continuous engagement between different stakeholders is necessary. Therefore, procedures used to maintain civil-military engagement should be broadened to include technology.
- “Collaboration software needs to be aligned with user needs”—technology providers need to keep in mind the needs of its users, in this case peacebuilders, in order to ensure sustainability.

United Nations Independent Expert Advisory Group on a Data Revolution for Sustainable Development. “A World That Counts, Mobilizing the Data Revolution.” 2014. https://bit.ly/2Cb3lXq

This report focuses on the potential benefits and risks data holds for sustainable development. Included in this is a strategic framework for using and managing data for humanitarian purposes. It describes a need for a multinational consensus to be developed to ensure data is shared effectively and efficiently.
It suggests that “people who are counted”—i.e., those who are included in data collection processes—have better development outcomes and a better chance for humanitarian response in emergency or conflict situations.

Katie Whipkey and Andrej Verity. “Guidance for Incorporating Big Data into Humanitarian Operations.” Digital Humanitarian Network, 2015. http://bit.ly/1Y2BMkQ

This report produced by the Digital Humanitarian Network provides an overview of big data, and how humanitarian organizations can integrate this technology into their humanitarian response. It primarily functions as a guide for organizations, and provides concise, brief outlines of what big data is, and how it can benefit humanitarian groups.
The report puts forward four main benefits acquired through the use of big data by humanitarian organizations: 1) the ability to leverage real-time information; 2) the ability to make more informed decisions; 3) the ability to learn new insights; 4) the ability for organizations to be more prepared.
It goes on to assess seven challenges big data poses for humanitarian organizations: 1) geography, and the unequal access to technology across regions; 2) the potential for user error when processing data; 3) limited technology; 4) questionable validity of data; 5) underdeveloped policies and ethics relating to data management; 6) limitations relating to staff knowledge.

Risks of Using Big Data in Humanitarian Context
Crawford, Kate, and Megan Finn. “The limits of crisis data: analytical and ethical challenges of using social and mobile data to understand disasters.” GeoJournal 80.4, 2015. http://bit.ly/1X0F7AI

Crawford & Finn present a critical analysis of the use of big data in disaster management, taking a more skeptical tone to the data revolution facing humanitarian response.
They argue that though social and mobile data analysis can yield important insights and tools in crisis events, it also presents a number of limitations which can lead to oversights being made by researchers or humanitarian response teams.
Crawford & Finn explore the ethical concerns the use of big data in disaster events introduces, including issues of power, privacy, and consent.
The paper concludes by recommending that critical data studies, such as those presented in the paper, be integrated into crisis event research in order to analyze some of the assumptions which underlie mobile and social data.

Jacobsen, Katja Lindskov (2010) Making design safe for citizens: A hidden history of humanitarian experimentation. Citizenship Studies 14.1: 89-103. http://bit.ly/1YaRTwG

This paper explores the phenomenon of “humanitarian experimentation,” where victims of disaster or conflict are the subjects of experiments to test the application of technologies before they are administered in greater civilian populations.
By analyzing the particular use of iris recognition technology during the repatriation of Afghan refugees to Pakistan in 2002 to 2007, Jacobsen suggests that this “humanitarian experimentation” compromises the security of already vulnerable refugees in order to better deliver biometric product to the rest of the world.

Responsible Data Forum. “Responsible Data Reflection Stories: An Overview.” http://bit.ly/1Rszrz1

This piece from the Responsible Data forum is primarily a compilation of “war stories” which follow some of the challenges in using big data for social good. By drawing on these crowdsourced cases, the Forum also presents an overview which makes key recommendations to overcome some of the challenges associated with big data in humanitarian organizations.
It finds that most of these challenges occur when organizations are ill-equipped to manage data and new technologies, or are unaware about how different groups interact in digital spaces in different ways.

Sandvik, Kristin Bergtora. “The humanitarian cyberspace: shrinking space or an expanding frontier?” Third World Quarterly 37:1, 17-32, 2016. http://bit.ly/1PIiACK

This paper analyzes the shift toward more technology-driven humanitarian work, where humanitarian work increasingly takes place online in cyberspace, reshaping the definition and application of aid. This has occurred along with what many suggest is a shrinking of the humanitarian space.
Sandvik provides three interpretations of this phenomena:
- First, traditional threats remain in the humanitarian space, which are both modified and reinforced by technology.
- Second, new threats are introduced by the increasing use of technology in humanitarianism, and consequently the humanitarian space may be broadening, not shrinking.
- Finally, if the shrinking humanitarian space theory holds, cyberspace offers one example of this, where the increasing use of digital technology to manage disasters leads to a contraction of space through the proliferation of remote services.

Additional Readings on Data and Humanitarian Response

Kristin Bergtora Sandvik, et al. – Humanitarian technology: a critical research agenda. – Takes a critical look at the field of humanitarian technology, analyzing what challenges this poses to post-disaster and conflict environment.
Kristin Bergtora Sandvik – “The Risks of Technological Innovation.” – Suggests that despite the evident benefits such technology presents, it can also undermine humanitarian action and lead to “catastrophic events” themselves needing a new type of humanitarian response.
Ryan Burns – Rethinking big data in digital humanitarianism: practices, epistemologies, and social relations – Takes a critical look at the use of big data in humanitarian spaces, arguing that the advent of digital humanitarianism has profound political and social implications, and can in fact limit information available following a humanitarian crisis.
Kate Crawford – Is Data a Danger to the Developing World? – Argues that it is not simply risks to privacy that data poses to developing countries, but suggests that “data discrimination” can affect even the basic human rights of individuals, and introduce problematic power hierarchies between those who can access data and those who cannot.
Paul Currion – Eyes Wide Shut: The challenge of humanitarian biometrics – Examines the use of biometrics by humanitarian organizations and national governments, and suggests stronger accountability is needed to ensure data from marginalized groups remain protected.
Yves-Alexandre de Montjoye, Jake Kendall and Cameron F. Kerry – Enabling Humanitarian Use of Mobile Phone Data – Analyzes how data from mobile communication can provide insights into the spread of infectious disease, and how such data can also compromise individual privacy.
Michael F. Goodchild and Alan Glennon – Crowdsourcing geographic information for disaster response: a research frontier – Explores how though volunteered geographic data may be messy and unreliable, it can provide many benefits in emergency situations.
Raphael Horler – Crowdsourcing in the Humanitarian Network – An Analysis of the Literature – A Bachelor thesis which explores the increasing use of crowdsourced data by organizations involved in disaster response, investigating some of the challenges such use of crowdsourcing poses.
Gus Hosein and Carly Nyst – Aiding Surveillance – Suggests that the unregulated use of technologies and surveillance systems by humanitarian organizations create systems which pose serious threats to individuals’ rights, particularly their right to privacy.
L. Jacobsen – The Politics of Humanitarian Technology: Good Intentions, Unintended Consequences and Insecurity – Raises concerns about the rise of data collection and digital technology in humanitarian aid organizations, arguing that its unquestioned prominence creates new structures of power and control, which remain hidden under the rubric of liberal humanitarianism.
Mirca Madianou – Digital Inequality and Second-Order Disasters: Social Media in the Typhoon Haiyan Recovery – Taking the effects of Typhoon Haiyan as a key case study, this paper investigates how digital inequalities and an unequal access to data can exacerbate existing social inequalities in a post-disaster environment.
Sean Martin McDonald – Ebola: A Big Data Disaster. Privacy, Property, and the Law of Disaster Experimentation – Analyzes the challenges and privacy risks of using unregulated data in public health coordination by taking the use of Call Detail Record (CDR) data during the Ebola crisis as a key case study.
National Academy of Engineering – Sensing and Shaping Emerging Conflicts: Report of a Joint Workshop of the National Academy of Engineering and the United States Institute of Peace: Roundtable on Technology, Science, and Peacebuilding – Building on the overview report of the United States Institute of Peace workshop examines what opportunities new technologies and data sharing provides for humanitarian groups.
Mary K.Pratt – Big Data’s role in humanitarian aid – A Computer World article which provides an overview of Big Data, and how it is improving the efficiency and efficacy of humanitarian response, especially in conflict zones.
Bertrand Taithe Róisínand and Roger Mac Ginty – Data hubris? Humanitarian information systems and the mirage of technology – Specifically looks at visual technology and crisis mapping, and big data, and suggests that there exists an over-enthusiasm in these claims made on behalf of technologically advanced humanitarian information systems.
Linnet Taylor – No place to hide? The ethics and analytics of tracking mobility using mobile phone data – Examines the ethical problems associated with the tracking of mobile phone data, especially in low or middle-income countries.
UN Office for the Coordination of Humanitarian Affairs (UN-OCHA) – Big data and humanitarianism: 5 things you need to know – Briefly outlines five issues that face humanitarian organizations as they integrate big data into their operations.
United Nations Global Pulse – Mapping the Risk-Utility Landscape of Mobile Data for Sustainable Development and Humanitarian Action – Reports on a Global Pulse project (done in partnership with Massachusetts Institute of Technology) which aimed to find how aggregated mobile data can be maximized to protect privacy and provide effective support to crisis response.
The Wilson Center – Connecting Grassroots to Government for Disaster Management: Workshop Summary – Summarizes the key points drawn from a two day Wilson Center workshop, which investigated how new technologies could engage whole communities in disaster management.

* Thanks to: Kristen B. Sandvik; Zara Rahman; Jennifer Schulte; Sean McDonald; Paul Currion; Dinorah Cantú-Pedraza and the Responsible Data Listserve for valuable input.

Elements of a New Ethical Framework for Big Data Research

Curated on April 2, 2016August 3, 2018 by Stefaan Verhulst

“The Berkman Center is pleased to announce the publication of a new paper from the Privacy Tools for Sharing Research Data project team. In this paper, Effy Vayena, Urs Gasser, Alexandra Wood, and David O’Brien from the Berkman Center, with Micah Altman from MIT Libraries, outline elements of a new ethical framework for big data research.

Emerging large-scale data sources hold tremendous potential for new scientific research into human biology, behaviors, and relationships. At the same time, big data research presents privacy and ethical challenges that the current regulatory framework is ill-suited to address. In light of the immense value of large-scale research data, the central question moving forward is not whether such data should be made available for research, but rather how the benefits can be captured in a way that respects fundamental principles of ethics and privacy.

The authors argue that a framework with the following elements would support big data utilization and help harness the value of big data in a sustainable and trust-building manner:

Oversight should aim to provide universal coverage of human subjects research, regardless of funding source, across all stages of the information lifecycle.
New definitions and standards should be developed based on a modern understanding of privacy science and the expectations of research subjects.
Researchers and review boards should be encouraged to incorporate systematic risk-benefit assessments and new procedural and technological solutions from the wide range of interventions that are available.
Oversight mechanisms and the safeguards implemented should be tailored to the intended uses, benefits, threats, harms, and vulnerabilities associated with a specific research activity.

Development of a new ethical framework with these elements should be the product of a dynamic multistakeholder process that is designed to capture the latest scientific understanding of privacy, analytical methods, available safeguards, community and social norms, and best practices for research ethics as they evolve over time.

The full paper is available for download through the Washington and Lee Law Review Online as part of a collection of papers featured at the Future of Privacy Forum workshop Beyond IRBs: Designing Ethical Review Processes for Big Data Research held on December 10, 2015, in Washington, DC….(More)”

How to stop being so easily manipulated by misleading statistics

Curated on March 30, 2016August 15, 2018 by Stefaan Verhulst

Q&A by Akshat Rathi in Quartz: “There are three kinds of lies: Lies, damned lies, and statistics.” Few people know the struggle of correcting such lies better than David Spiegelhalter. Since 2007, he has been the Winton professor for the public understanding of risk (though he prefers “statistics” to “risk”) at the University of Cambridge.In a sunlit hotel room in Washington DC, Quartz caught up with Spiegelhalter recently to talk about his unique job. The conversation sprawled from the wisdom of eating bacon (would you swallow any other known carcinogen?), to the serious crime of manipulating charts, to the right way to talk about rare but scary diseases.

In a sunlit hotel room in Washington DC, Quartz caught up with Spiegelhalter recently to talk about his unique job. The conversation sprawled from the wisdom of eating bacon (would you swallow any other known carcinogen?), to the serious crime of manipulating charts, to the right way to talk about rare but scary diseases.

When he isn’t fixing people’s misunderstandings of numbers, he works to communicate numbers better so that misunderstandings can be avoided from the beginning. The interview is edited and condensed for clarity….

What’s a recent example of misrepresentation of statistics that drove you bonkers?
I got very grumpy at an official graph of British teenage pregnancy rates that apparently showed they had declined to nearly zero. Until I realized that the bottom part of the axis had been cut off, which made it impossible to visualize the (very impressive) 50% reduction since 2000.You once said graphical representation of data does not always communicate what we think it communicates. What do you mean by that?
Graphs can be as manipulative as words. Using tricks such as cutting axes, rescaling things, changing data from positive to negative, etc. Sometimes putting zero on the y-axis is wrong. So to be sure that you are communicating the right things, you need to evaluate the message that people are taking away. There are no absolute rules. It all depends on what you want to communicate….

Poorly communicated risk can have a severe effect. For instance, the news story about the risk that pregnant women are exposing their unborn child to when they drink alcohol caused stress to one of our news editors who had consumed wine moderately through her pregnancy.

I think it’s irresponsible to say there is a risk when they actually don’t know if there is one. There is scientific uncertainty about that.

“‘Absence of evidence is not evidence of absence.’ I hate that phrase…It’s always used in a manipulative way.” In such situations of unknown risk, there is a phrase that is often used: “Absence of evidence is not evidence of absence.” I hate that phrase. I get so angry when people use that phrase. It’s always used in a manipulative way. I say to them that it’s not evidence of absence, but if you’ve looked hard enough you’ll see that most of the time the evidence shows a very small effect, if at all.

So on the risks of drinking alcohol while being pregnant, the UK’s health authority said that as a precautionary step it’s better not to drink. That’s fair enough. This honesty is important. To say that we don’t definitely know if drinking is harmful, but to be safe we say you shouldn’t. That’s treating people as adults and allowing them to use their own judgement.

Science is a bigger and bigger part of our lives. What is the limitation in science journalism right now and how can we improve it?...(More)

Your Data Footprint Is Affecting Your Life In Ways You Can’t Even Imagine

Curated on March 27, 2016November 14, 2018 by Stefaan Verhulst

Jessica Leber at Fast Co-Exist: “Cities have long seen the potential in big data to improve the government and the lives of citizens, and this is now being put into action in ways where governments touch citizens’ lives in very sensitive areas. New York City’s Department of Homelessness Services is mining apartment eviction filings, to see if they can understand who is at risk of becoming homeless and intervene early. And police departments all over the country have adopted predictive policing software that guides where officers should deploy, and at what time, leading to reduced crime in some cities.

In one study in Los Angeles, police officers deployed to certain neighborhoods by predictive policing software prevented 4.3 crimes per week, compared to 2 crimes per week when assigned to patrol a specific area by human crime analysts. Surely, a reduction in crime is a good thing. But community activists in places such as Bellingham, Washington, have grave doubts. They worry that outsiders can’t examine how the algorithms work, since the software is usually proprietary, and so citizens have no way of knowing what data the government is using to target them. They also worry that predictive policing is just exacerbating existing patterns of racial profiling. If the underlying crime data being used is the result of years of over-policing minority communities for minor offenses, then the predictions based on this biased data could create a feedback loop and lead to yet more over-policing.

At a smaller and more limited scale is the even more sensitive area of child protection services. Though the data isn’t really as “big” as in other examples, a few agencies are carefully exploring using statistical models to make decisions in several areas, such as which children in the system are most in danger of violence, which children are most in need of a trauma screening, and which are at risk of entering the criminal justice system.

In Hillsborough County, Florida, where a series of child homicides occurred, a private provider selected to manage the county’s child welfare system in 2012 came in and analyzed the data. Cases with the highest probability of serious injury or death had a few factors in common, they found: a child under the age of three, a “paramour” in the home, a substance abuse or domestic violence history, and a parent previously in the foster care system. They identified nine practices to use in these cases and hired a software provider to create a dashboard that allowed real-time feedback and dashboards. Their success has led to the program being implemented statewide….

“I think the opportunity is a rich one. At the same time, the ethical considerations need to be guiding us,” says Jesse Russell, chief program officer at the National Council on Crime and Delinquency, who has followed the use of predictive analytics in child protective services. Officials, he says, are treading carefully before using data to make decisions about individuals, especially when the consequences of being wrong—such as taking a child out of his or her home unnecessarily—are huge. And while caseworker decision-making can be flawed or biased, so can the programs that humans design. When you rely too much on data—if the data is flawed or incomplete, as could be the case in predictive policing—you risk further validating bad decisions or existing biases….

On the other hand, big data does have the potential to vastly expand our understanding of who we are and why we do what we do. A decade ago, serious scientists would have laughed someone out of the room who proposed a study of “the human condition.” It is a topic so broad and lacking in measurability. But perhaps the most important manifestation of big data in people’s lives could come from the ability for scientists to study huge, unwieldy questions they couldn’t before.

A massive scientific undertaking to study the human condition is set to launch in January of 2017. The Kavli Human Project, funded by the Kavli Foundation, plans to recruit 10,000 New Yorkers from all walks of life to be measured for 10 years. And by measured, they mean everything: all financial transactions, tax returns, GPS coordinates, genomes, chemical exposure, IQ, bluetooth sensors around the house, who subjects text and call—and that’s just the beginning. In all, the large team of academics expect to collect about a billion data points per person per year at an unprecedented low cost for each data point compared to other large research surveys.

The hope is with so much continuous data, researchers can for the first time start to disentangle the complex, seemingly unanswerable questions that have plagued our society, from what is causing the obesity epidemic to how to disrupt the poverty to prison cycle….(More)