Report by Rwitwika Bhattacharya and Mohitkumar Daga: “The importance of data in informing the policy-making process is being increasingly realized across the world. With India facing significant developmental challenges, use of data offers an important opportunity to improve the quality of public services. However, lack of formal structures to internalize a data-informed decision-making process impedes the path to robust policy formation. This paper seeks to highlight these challenges through a case study of data dashboard implementation in the state of Andhra Pradesh. The study suggests the importance of capacity building, improvement of data collection and engagement of non-governmental players as measures to address issues….(More)”
The Internet for farmers without Internet
Project Breakthrough: “Mobile Internet is rapidly becoming a primary source of knowledge for rural populations in developing countries. But not every one of the world’s 500 million smallholder farmers is connected to the Internet – which means they can struggle to solve daily agricultural challenges. With no way to access to information on things like planting, growing and selling, farmers in Asia, Latin America and Africa simply cannot grow. Many live on less than a dollar a day and don’t have smartphones to ask Google what to do.
London-based startup WeFarm is the world’s first free peer-to-peer network that spreads crowdsourced knowledge via SMS messages, which only need simple mobile phones. Since launching in November 2015, its aim has been to give remote, offline farmers access to the vital innovative insight, such as crop diversification, tackling soil erosion or changing climatic conditions. Billing itself as ‘The internet for people without the internet’, WeFarm strongly believes in the power of grassroots information. That’s why it costs nothing.
“With WeFarm we want all farmers in the world to be able to search for and access the information they need to improve their livelihoods,” Kenny Ewan, CEO tells us. The seeds for his idea were planted after many years working with indigenous communities in Latin America, based in Peru. “To me it makes perfect sense to allow farmers to connect with other farmers in order to find solutions to their problems. These farmers are experts in agriculture, and they come up with low-cost, innovative solutions, that are easy to implement.”
Farmers send questions by SMS to a local WeFarm number. Then they are connected to a huge crowdsourcing platform. The network’s back-end uses machine-learning algorithms to match them to farmers with answers. This data creates a sort of Google for agriculture…(More)”
Putting the brakes on traffic violations in China
Springwise: “When it comes to public awareness and behavior change campaigns, it’s always interesting to see how organizations effect change. Last year, we covered a Russian nonprofit which uses hologram projections of disabled drivers to ward off those tempted to take disabled parking spaces. Road deaths in China have long been a cause for concern with the WHO estimating that 250,000 people were killed on China’s roads, amongst them over 10,000 children. This figure is disputed by Chinese authorities, who put the figure around 60,000, but it is clearly a serious problem. The latest rising death toll comes from non-motorized vehicles, in particular e-bikes. Some estimates put the number of e-bikes in use in China at over 200 million. ….
In response to this alarming figure, Chinese traffic police have been trialling two interesting strategies to improve road safety, focussing in on non-motorized vehicles. The more traditional of the strategies was an online radio broadcast earlier on this month which detailed the various aspects of their law enforcement process. 210,000 people tuned in for the one hour broadcast.
The second, earlier this year, was a novel approach that – to some extent – gamified traffic regulation. Officials handed out 15,000, ’50 percent discount coupons’ to people breaking traffic rules incurring a fine. The coupons had the highway code printed on the reverse. Rule-breakers were asked ‘on the spot’ questions about the highway code which, if answered correctly, resulted in the fine being lifted altogether. ‘Contestants’ were even allowed to phone a friend. Not quite a “get out jail free card” but a good incentive for learning the highway code….(More)”
Artificial intelligence is hard to see
Kate Crawford and Meredith Whittaker on “Why we urgently need to measure AI’s societal impacts“: “How will artificial intelligence systems change the way we live? This is a tough question: on one hand, AI tools are producing compelling advances in complex tasks, with dramatic improvements in energy consumption, audio processing, and leukemia detection. There is extraordinary potential to do much more in the future. On the other hand, AI systems are already making problematic judgements that are producing significant social, cultural, and economic impacts in people’s everyday lives.
AI and decision-support systems are embedded in a wide array of social institutions, from influencing who is released from jail to shaping the news we see. For example, Facebook’s automated content editing system recently censored the Pulitzer-prize winning image of a nine-year old girl fleeing napalm bombs during the Vietnam War. The girl is naked; to an image processing algorithm, this might appear as a simple violation of the policy against child nudity. But to human eyes, Nick Ut’s photograph, “The Terror of War”, means much more: it is an iconic portrait of the indiscriminate horror of conflict, and it has an assured place in the history of photography and international politics. The removal of the image caused an international outcry before Facebook backed down and restored the image. “What they do by removing such images, no matter what good intentions, is to redact our shared history,” said the Prime Minister of Norway, Erna Solberg.
It’s easy to forget that these high-profile instances are actually the easy cases. As Tarleton Gillespie has observed, hundreds of content reviews are occurring with Facebook images thousand of times per day, and rarely is there a Pulitzer prize to help determine lasting significance. Some of these reviews include human teams, and some do not. In this case, there is alsoconsiderable ambiguity about where the automated process ended and the human review began: which is part of the problem. And Facebook is just one player in complex ecology of algorithmically-supplemented determinations with little external monitoring to see how decisions are made or what the effects might be.
The ‘Terror of War’ case, then, is the tip of the iceberg: a rare visible instance that points to a much larger mass of unseen automated and semi-automated decisions. The concern is that most of these ‘weak AI’ systems are making decisions that don’t garner such attention. They are embedded at the back-end of systems, working at the seams of multiple data sets, with no consumer-facing interface. Their operations are mainly unknown, unseen, and with impacts that take enormous effort to detect.
Sometimes AI techniques get it right, and sometimes they get it wrong. Only rarely will those errors be seen by the public: like the Vietnam war photograph, or when a AI ‘beauty contest’ held this month was called out for being racist for selecting white women as the winners. We can dismiss this latter case as a problem of training data — they simply need a more diverse selection of faces to train their algorithm with, and now that 600,000 people have sent in their selfies, they certainly have better means to do so. But while a beauty contest might seem like a bad joke, or just a really good trick to get people to give up their photos to build a large training data set, it points to a much bigger set of problems. AI and decision-support systems are reaching into everyday life: determining who will be on a predictive policing‘heat list’, who will be hired or promoted, which students will be recruited to universities, or seeking to predict at birth who will become a criminal by the age of 18. So the stakes are high…(More)”
‘Homo sapiens is an obsolete algorithm’
Extract from Homo Deus: A Brief History of Tomorrow by Yuval Noah Harari: “There’s an emerging market called Dataism, which venerates neither gods nor man – it worships data. From a Dataist perspective, we may interpret the entire human species as a single data-processing system, with individual humans serving as its chips. If so, we can also understand the whole of history as a process of improving the efficiency of this system, through four basic methods:
1. Increasing the number of processors. A city of 100,000 people has more computing power than a village of 1,000 people.
2. Increasing the variety of processors. Different processors may use diverse ways to calculate and analyse data. Using several kinds of processors in a single system may therefore increase its dynamism and creativity. A conversation between a peasant, a priest and a physician may produce novel ideas that would never emerge from a conversation between three hunter-gatherers.
3. Increasing the number of connections between processors. There is little point in increasing the mere number and variety of processors if they are poorly connected. A trade network linking ten cities is likely to result in many more economic, technological and social innovations than ten isolated cities.
4. Increasing the freedom of movement along existing connections. Connecting processors is hardly useful if data cannot flow freely. Just building roads between ten cities won’t be very useful if they are plagued by robbers, or if some autocratic despot doesn’t allow merchants and travellers to move as they wish.
These four methods often contradict one another. The greater the number and variety of processors, the harder it is to freely connect them. The construction of the sapiens data-processing system accordingly passed through four main stages, each of which was characterised by an emphasis on different methods.
The first stage began with the cognitive revolution, which made it possible to connect unlimited sapiens into a single data-processing network. This gave sapiens an advantage over all other human and animal species. Although there is a limit to the number of Neanderthals, chimpanzees or elephants you can connect to the same net, there is no limit to the number of sapiens.
Sapiens used their advantage in data processing to overrun the entire world. However, as they spread into different lands and climates they lost touch with one another, and underwent diverse cultural transformations. The result was an immense variety of human cultures, each with its own lifestyle, behaviour patterns and world view. Hence the first phase of history involved an increase in the number and variety of human processors, at the expense of connectivity: 20,000 years ago there were many more sapiens than 70,000 years ago, and sapiens in Europe processed information differently from sapiens in China. However, there were no connections between people in Europe and China, and it would have seemed utterly impossible that all sapiens may one day be part of a single data-processing web.
The second stage began with agriculture and continued until the invention of writing and money. Agriculture accelerated demographic growth, so the number of human processors rose sharply, while simultaneously enabling many more people to live together in the same place, thereby generating dense local networks that contained an unprecedented number of processors. In addition, agriculture created new incentives and opportunities for different networks to trade and communicate.
Nevertheless, during the second phase, centrifugal forces remained predominant. In the absence of writing and money, humans could not establish cities, kingdoms or empires. Humankind was still divided into innumerable little tribes, each with its own lifestyle and world view. Uniting the whole of humankind was not even a fantasy.
The third stage kicked off with the appearance of writing and money about 5,000 years ago, and lasted until the beginning of the scientific revolution. Thanks to writing and money, the gravitational field of human co-operation finally overpowered the centrifugal forces. Human groups bonded and merged to form cities and kingdoms. Political and commercial links between different cities and kingdoms also tightened. At least since the first millennium BC – when coinage, empires, and universal religions appeared – humans began to consciously dream about forging a single network that would encompass the entire globe.
This dream became a reality during the fourth and last stage of history, which began around 1492. Early modern explorers, conquerors and traders wove the first thin threads that encompassed the whole world. In the late modern period, these threads were made stronger and denser, so that the spider’s web of Columbus’s days became the steel and asphalt grid of the 21st century. Even more importantly, information was allowed to flow increasingly freely along this global grid. When Columbus first hooked up the Eurasian net to the American net, only a few bits of data could cross the ocean each year, running the gauntlet of cultural prejudices, strict censorship and political repression.
But as the years went by, the free market, the scientific community, the rule of law and the spread of democracy all helped to lift the barriers. We often imagine that democracy and the free market won because they were “good”. In truth, they won because they improved the global data-processing system.
So over the last 70,000 years humankind first spread out, then separated into distinct groups and finally merged again. Yet the process of unification did not take us back to the beginning. When the different human groups fused into the global village of today, each brought along its unique legacy of thoughts, tools and behaviours, which it collected and developed along the way. Our modern larders are now stuffed with Middle Eastern wheat, Andean potatoes, New Guinean sugar and Ethiopian coffee. Similarly, our language, religion, music and politics are replete with heirlooms from across the planet.
If humankind is indeed a single data-processing system, what is its output? Dataists would say that its output will be the creation of a new and even more efficient data-processing system, called the Internet-of-All-Things. Once this mission is accomplished, Homo sapiens will vanish….(More)“
Questioning Big Data: Crowdsourcing crisis data towards an inclusive humanitarian response
, , , , and The aim of this paper is to critically explore whether crowdsourced Big Data enables an inclusive humanitarian response at times of crisis. We argue that all data, including Big Data, are socially constructed artefacts that reflect the contexts and processes of their creation. To support our argument, we qualitatively analysed the process of ‘Big Data making’ that occurred by way of crowdsourcing through open data platforms, in the context of two specific humanitarian crises, namely the 2010 earthquake in Haiti and the 2015 earthquake in Nepal. We show that the process of creating Big Data from local and global sources of knowledge entails the transformation of information as it moves from one distinct group of contributors to the next. The implication of this transformation is that locally based, affected people and often the original ‘crowd’ are excluded from the information flow, and from the interpretation process of crowdsourced crisis knowledge, as used by formal responding organizations, and are marginalized in their ability to benefit from Big Data in support of their own means. Our paper contributes a critical perspective to the debate on participatory Big Data, by explaining the process of in and exclusion during data making, towards more responsive humanitarian relief….(More)”.
Smart Economy in Smart Cities
Book edited by Vinod Kumar, T. M.: “The present book highlights studies that show how smart cities promote urban economic development. The book surveys the state of the art of Smart City Economic Development through a literature survey. The book uses 13 in depth city research case studies in 10 countries such as the North America, Europe, Africa and Asia to explain how a smart economy changes the urban spatial system and vice versa. This book focuses on exploratory city studies in different countries, which investigate how urban spatial systems adapt to the specific needs of smart urban economy. The theory of smart city economic development is not yet entirely understood and applied in metropolitan regional plans. Smart urban economies are largely the result of the influence of ICT applications on all aspects of urban economy, which in turn changes the land-use system. It points out that the dynamics of smart city GDP creation takes ‘different paths,’ which need further empirical study, hypothesis testing and mathematical modelling. Although there are hypotheses on how smart cities generate wealth and social benefits for nations, there are no significant empirical studies available on how they generate urban economic development through urban spatial adaptation. This book with 13 cities research studies is one attempt to fill in the gap in knowledge base….(More)”
5 Crowdsourced News Platforms Shaping The Future of Journalism and Reporting
Maria Krisette Capati at Crowdsourcing Week: “We are exposed to a myriad of news and updates worldwide. As the crowd becomes moreinvolved in providing information, adopting that ‘upload mindset’ coined by Will Merritt ofZooppa, access to all kinds of data is a few taps and clicks away….
Google News Lab – Better reporting and insightful storytelling
Last week, Google announced its own crowdsourced news platform dubbed News Lab as part of their efforts “to empower innovation at the intersection of technology and media.”
Scouting for real-time stories, updates, and breaking news is much easier and systematize for journalists worldwide. They can use Google’s tools for better reporting, data for insightful storytelling and programs to focus on the future of media, tackling this initiative in three ways.
“There’s a revolution in data journalism happening in newsrooms today, as more data sets and more tools for analysis are allowing journalists to create insights that were never before possible,” Google said.
Grasswire – first-hand information in real-time
The design looks bleak and simple, but the site itself is rich with content—first-hand information crowdsourced from Twitter users in real-time and verified. Austen Allred, co-founder of Grasswire was inspired to develop the platform after his “minor slipup” as the American Journalism Review (AJR) puts it, when he missed his train out of Shanghai that actually saved his life.
“The bullet train Allred was supposed to be on collided with another train in the Wenzhou area ofChina’s Zhejiang province,” AJR wrote. “Of the 1,630 passengers, 40 died, and another 210 were injured.” The accident happened in 2011. Unfortunately, the Chinese government made some cover upon the incident, which frustrated Allred in finding first-hand information.
After almost four years, Grasswire was launched, a website that collects real-time information from users for breaking news infused with crowdsourcing model afterward. “It’s since grown into a more complex interface, allowing users to curate selected news tweets by voting and verifying information with a fact-checking system,” AJR wrote, which made the verification of data open and systematized.
Rappler – Project Agos: a technology for disaster risk reduction
The Philippines is a favorite hub for typhoons. The aftermath of typhoon Haiyan was exceedingly disastrous. But the crowds were steadfast in uploading and sharing information and crowdsourcing became mainstream during the relief operations. Maria Ressa said that they had to educate netizens to use the appropriate hashtags for years (#nameoftyphoonPH, e.g. #YolandaPH) for typhoons to collect data on social media channels easily.
Education and preparation can mitigate the risks and save lives if we utilize the right technology and act accordingly. In her blog, After Haiyan: Crisis management and beyond, Maria wrote, “We need to educate not just the first responders and local government officials, but more importantly, the people in the path of the storms.” …
China’s CCDI app – Crowdsourcing political reports to crack down corruption practices
In China, if you want to mitigate or possible, eradicate corrupt practices, then there’s an app for that.China launched its own anti-corruption app called, Central Commission for Discipline InspectionWebsite App, allowing the public to upload text messages, photos and videos of Chinese officials’ any corrupt practices.
The platform was released by the government agency, Central Committee for Discipline Inspection.Nervous in case you’ll be tracked as a whistleblower? Interestingly, anyone can report anonymously.China Daily said, “the anti-corruption authorities received more than 1,000 public reports, and nearly70 percent were communicated via snapshots, text messages or videos uploaded,” since its released.Kenya has its own version, too, called Ushahidi using crowdmapping, and India’s I Paid a Bribe.
Newzulu – share news, publish and get paid
While journalists can get fresh insights from Google News Labs, the crowd can get real-time verified news from Grasswire, and CCDI is open for public, Newzulu crowdsourced news platforms doesn’t just invite the crowd to share news, they can also publish and get paid.
It’s “a community of over 150,000 professional and citizen journalists who share and break news to the world as it happens,” originally based in Sydney. Anyone can submit stories, photos, videos, and even stream live….(More)”
Through the looking glass: Harnessing big data to respond to violent extremism
Michele Piercey, Carolyn Forbes, and Hasan Davulcu at Devex:”People think and say all sorts of things that they would never actually do. One of the biggest challenges in countering violent extremism is not only figuring out which people hold radical views, but who is most likely to join and act on behalf of violent extremist organizations. Determining who is likely to become violent is key to designing and evaluating more targeted interventions, but it has proven to be extremely difficult.
There are few recognized tools for assessing perceptions and beliefs, such as whether community sentiment about violent extremist organizations is more or less favorable, or which narratives and counternarratives resonate with vulnerable populations.
Program designers and monitoring and evaluation staff often rely on perception surveying to assess attitudinal changes that CVE programs try to achieve, but there are limitations to this method. Security and logistical challenges to collecting perception data in a conflict-affected community can make it difficult to get a representative sample, while ensuring the safety of enumerators and respondents. And given the sensitivity of the subject matter, respondents may be reluctant to express their actual beliefs to an outsider (that is, social desirability bias can affect data reliability).
The rise of smartphone technology and social media uptake among the burgeoning youth populations of many conflict-affected countries presents a new opportunity to understand what people believe from a safer distance, lessening the associated risks and data defects. Seeing an opportunity in the growing mass of online public data, the marketing industry has pioneered tools to “scrape” and aggregate the data to help companies paint a clearer picture of consumer behavior and perceptions of brands and products.
These developments present a critical question for CVE programs: Could similar tools be developed that would analyze online public data to identify who is being influenced by which extremist narratives and influences, learn which messages go viral, and distinguish groups and individuals who simply hold radical views from those who support or carry out violence?
Using data to track radicalization
Seeking to answer this question, researchers at Arizona State University’s Center for the Study of Religion and Conflict, Cornell University’s Social Dynamics Laboratory, and Carnegie Mellon’s Center for Computational Analysis of Social and Organizational systems have been innovating a wide variety of data analytics tools. ASU’s LookingGlass tool, for example, maps networks of perception, belief, and influence online. ASU and Chemonics International are now piloting the tool on a CVE program in Libya.
Drawn from the humanities and social and computational sciences, LookingGlass retrieves, categorizes, and analyzes vast amounts of data from across the internet to map the spread of extremist and counter-extremist influence online. The tool displays what people think about their political situation, governments and extremist groups, and tracks changes in these perceptions over time and in response to events. It also lets users visualize how groups emerge, interact, coalesce, and fragment in relation to emerging issues and events and evaluates “information cascades” to assess what causes extremist messages to go viral on social media and what causes them to die out.
For CVE planners, LookingGlass can map social movements in relation to specific countries and regions. Indonesia, for example, has been the site of numerous violent movements and events. A relatively young democracy, the country’s complex political environment encompasses numerous groups seeking radical change across a wide spectrum of social and political issues….(More)”
Open Data for Developing Economies
Scan of the literature by Andrew Young, Stefaan Verhulst, and Juliet McMurren: This edition of the GovLab Selected Readings was developed as part of the Open Data for Developing Economies research project (in collaboration with WebFoundation, USAID and fhi360). Special thanks to Maurice McNaughton, Francois van Schalkwyk, Fernando Perini, Michael Canares and David Opoku for their input on an early draft. Please contact Stefaan Verhulst (stefaan@thegovlab.org) for any additional input or suggestions.
Open data is increasingly seen as a tool for economic and social development. Across sectors and regions, policymakers, NGOs, researchers and practitioners are exploring the potential of open data to improve government effectiveness, create new economic opportunity, empower citizens and solve public problems in developing economies. Open data for development does not exist in a vacuum – rather it is a phenomenon that is relevant to and studied from different vantage points including Data4Development (D4D), Open Government, the United Nations’ Sustainable Development Goals (SDGs), and Open Development. The below-selected readings provide a view of the current research and practice on the use of open data for development and its relationship to related interventions.
Selected Reading List (in alphabetical order)
- Open Data and Open Government for Development
- Solomon Benjamin, R. Bhuvaneswari, P. Rajan, Manjunatha – Bhoomi: ‘E-Governance’, or, An Anti-Politics Machine Necessary to Globalize Bangalore? – a paper offering a critical take on digitization and transparency efforts, particularly in Bangalore.
- Rosie McGee and Duncan Edwards – Introduction: Opening Governance – Change, Continuity and Conceptual Ambiguity – an introduction to a special issue of IDS bulletin on open government for development.
- Open Data and Data 4 Development
- 3rd International Open Data Conference (IODC) – Enabling the Data Revolution: An International Open Data Roadmap – a summary report of the third International Open Data Conference offering a roadmap for leveraging open data for sustainable development.
- Martin Hilbert – Big Data for Development: A Review of Promises and Challenges – an article offering a conceptual framework on the opportunities and threats of leveraging data for international development.
- International Development Research Centre, World Wide Web Foundation, and Berkman Center at Harvard University – Fostering a Critical Development Perspective on Open Government Data – a paper assessing how the real-world impact of open data, particularly in the Global South, are or are not meeting expectations.
- Open Data for Development – Open Data for Development: Building an Inclusive Data Revolution – a report providing an overview of the Open Data for Development (OD4D) program and its early findings.
- Elizabeth Stuart, Emma Samman, William Avis, Tom Berliner – The Data Revolution: Finding the Missing Millions – a report outlining the challenge of using data for development when many people are not represented in official databases.
- United Nations Independent Expert Advisory Group on a Data Revolution for Sustainable Development – A World That Counts, Mobilizing the Data Revolution – a report examining the opportunities and risks for using data for sustainable development.
- The World Bank – Digital Dividends: World Development Report 2016 – a report on the use of digital technologies, including big and open data, to improve development efforts.
- Open Data and Open Development…
- Open Data and Development Goals
- Evangelia Berdou – Mediating Voices and Communicating Realities: Using Information Crowdsourcing Tools, Open Data Initiatives and Digital Media to Support and Protect the Vulnerable and Marginalised – a report exploring how crowdsourcing, mapping and open data can generate and publicly share information that could benefit vulnerable and marginalized communities.
- Michael Canares, Satyarupa Shekhar – Open Data and Sub-national Governments: Lessons from Developing Countries – a synthesis paper providing lessons learned regarding sub-national open data from the Open Data in Developing Countries research project.
- Tim Davies – Open Data in Developing Countries – Emerging Insights from Phase I – a report offering 15 central insights from 13 countries studied in the Exploring the Emerging Impacts of Open Data in Developing Countries research network.
- Tim Davies, Duncan Edwards – Emerging Implications of Open and Linked Data for Knowledge Sharing Development – a study and collection of case studies examining how open and linked data can benefit development.
- Tim Davies, Fernando Perini, and Jose Alonso – Researching the Emerging Impacts of Open Data – a paper providing a conceptual framework and comparative theory of change for open data, with a particular focus on developing countries.
- Elise Montano and Diogo Silva – Exploring the Emerging Impacts of Open Data in Developing Countries (ODDC): ODDC1 Follow-up Outcome Evaluation Report – a report summarizing the findings of a project on open data’s impact on governance in developing countries.
- Fiona Smith, William Gerry, Emma Truswell – Supporting Sustainable Development with Open Data – a report describing the the benefits and challenges of using open data to achieve the SDGs.
- Open Data and Developing Countries (National Case Studies)….(More)”