Open & Shut


Harsha Devulapalli: “Welcome to Open & Shut — a new blog dedicated to exploring the opportunities and challenges of working with open data in closed societies around the world. Although we’ll be exploring questions relevant to open data practitioners worldwide, we’re particularly interested in seeing how civil society groups and actors in the Global South are using open data to push for greater government transparency, and tackle daunting social and economic challenges facing their societies….Throughout this series we’ll be profiling and interviewing organisations working with open data worldwide, and providing do-it-yourself data tutorials that will be useful for beginners as well as data experts. …

What do we mean by the terms ‘open data’ and ‘closed societies’?

It’s important to be clear about what we’re dealing with, here. So let’s establish some key terms. When we talk about ‘open data’, we mean data that anyone can access, use and share freely. And when we say ‘closed societies’, we’re referring to states or regions in which the political and social environment is actively hostile to notions of openness and public scrutiny, and which hold principles of freedom of information in low esteem. In closed societies, data is either not published at all by the government, or else is only published in inaccessible formats, is missing data, is hard to find or else is just not digitised at all.

Iran is one such state that we would characterise as a ‘closed society’. At Small Media, we’ve had to confront the challenges of poor data practice, secrecy, and government opaqueness while undertaking work to support freedom of information and freedom of expression in the country. Based on these experiences, we’ve been working to build Iran Open Data — a civil society-led open data portal for Iran, in an effort to make Iranian government data more accessible and easier for researchers, journalists, and civil society actors to work with.

Iran Open Data — an open data portal for Iran, created by Small Media

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..Open & Shut will shine a light on the exciting new ways that different groups are using data to question dominant narratives, transform public opinion, and bring about tangible change in closed societies. At the same time, it’ll demonstrate the challenges faced by open data advocates in opening up this valuable data. We intend to get the community talking about the need to build cross-border alliances in order to empower the open data movement, and to exchange knowledge and best practices despite the different needs and circumstances we all face….(More)

Artificial Intelligence for Citizen Services and Government


Paper by Hila Mehr: “From online services like Netflix and Facebook, to chatbots on our phones and in our homes like Siri and Alexa, we are beginning to interact with artificial intelligence (AI) on a near daily basis. AI is the programming or training of a computer to do tasks typically reserved for human intelligence, whether it is recommending which movie to watch next or answering technical questions. Soon, AI will permeate the ways we interact with our government, too. From small cities in the US to countries like Japan, government agencies are looking to AI to improve citizen services.

While the potential future use cases of AI in government remain bounded by government resources and the limits of both human creativity and trust in government, the most obvious and immediately beneficial opportunities are those where AI can reduce administrative burdens, help resolve resource allocation problems, and take on significantly complex tasks. Many AI case studies in citizen services today fall into five categories: answering questions, filling out and searching documents, routing requests, translation, and drafting documents. These applications could make government work more efficient while freeing up time for employees to build better relationships with citizens. With citizen satisfaction with digital government offerings leaving much to be desired, AI may be one way to bridge the gap while improving citizen engagement and service delivery.

Despite the clear opportunities, AI will not solve systemic problems in government, and could potentially exacerbate issues around service delivery, privacy, and ethics if not implemented thoughtfully and strategically. Agencies interested in implementing AI can learn from previous government transformation efforts, as well as private-sector implementation of AI. Government offices should consider these six strategies for applying AI to their work: make AI a part of a goals-based, citizen-centric program; get citizen input; build upon existing resources; be data-prepared and tread carefully with privacy; mitigate ethical risks and avoid AI decision making; and, augment employees, do not replace them.

This paper explores the various types of AI applications, and current and future uses of AI in government delivery of citizen services, with a focus on citizen inquiries and information. It also offers strategies for governments as they consider implementing AI….(More)”

The Tech Revolution That’s Changing How We Measure Poverty


Alvin Etang Ndip at the Worldbank: “The world has an ambitious goal to end extreme poverty by 2030. But, without good poverty data, it is impossible to know whether we are making progress, or whether programs and policies are reaching those who are the most in need.

Countries, often in partnership with the World Bank Group and other agencies, measure poverty and wellbeing using household surveys that help give policymakers a sense of who the poor are, where they live, and what is holding back their progress. Once a paper-and-pencil exercise, technology is beginning to revolutionize the field of household data collection, and the World Bank is tapping into this potential to produce more and better poverty data….

“Technology can be harnessed in three different ways,” says Utz Pape, an economist with the World Bank. “It can help improve data quality of existing surveys, it can help to increase the frequency of data collection to complement traditional household surveys, and can also open up new avenues of data collection methods to improve our understanding of people’s behaviors.”

As technology is changing the field of data collection, researchers are continuing to find new ways to build on the power of mobile phones and tablets.

The World Bank’s Pulse of South Sudan initiative, for example, takes tablet-based data collection a step further. In addition to conducting the household survey, the enumerators also record a short, personalized testimonial with the people they are interviewing, revealing a first-person account of the situation on the ground. Such testimonials allow users to put a human face on data and statistics, giving a fuller picture of the country’s experience.

Real-time data through mobile phones

At the same time, more and more countries are generating real-time data through high-frequency surveys, capitalizing on the proliferation of mobile phones around the world. The World Bank’s Listening to Africa (L2A) initiative has piloted the use of mobile phones to regularly collect information on living conditions. The approach combines face-to-face surveys with follow-up mobile phone interviews to collect data that allows to monitor well-being.

The initiative hands out mobile phones and solar chargers to all respondents. To minimize the risk of people dropping out, the respondents are given credit top-ups to stay in the program. From monitoring health care facilities in Tanzania to collecting data on frequency of power outages in Togo, the initiative has been rolled out in six countries and has been used to collect data on a wide range of areas. …

Technology-driven data collection efforts haven’t been restricted to the Africa region alone. In fact, the approach was piloted early in Peru and Honduras with the Listening 2 LAC program. In Europe and Central Asia, the World Bank has rolled out the Listening to Tajikistan program, which was designed to monitor the impact of the Russian economic slowdown in 2014 and 2015. Initially a six-month pilot, the initiative has now been in operation for 29 months, and a partnership with UNICEF and JICA has ensured that data collection can continue for the next 12 months. Given the volume of data, the team is currently working to create a multidimensional fragility index, where one can monitor a set of well-being indicators – ranging from food security to quality jobs and public services – on a monthly basis…

There are other initiatives, such as in Mexico where the World Bank and its partners are using satellite imagery and survey data to estimate how many people live below the poverty line down to the municipal level, or guiding data collectors using satellite images to pick a representative sample for the Somali High Frequency Survey. However, despite the innovation, these initiatives are not intended to replace traditional household surveys, which still form the backbone of measuring poverty. When better integrated, they can prove to be a formidable set of tools for data collection to provide the best evidence possible to policymakers….(More)”

Data Responsibility: Social Responsibility for a Data Age


TED-X Talk by Stefaan Verhulst: “In April 2015, the Gorkha earthquake hit Nepal—the worst in more than 80 years. Hundreds of thousands of people were rendered homeless and entire villages were flattened. The earthquake also triggered massive avalanches on Mount Everest, and ultimately killed nearly 9,000 people across the country.

Yet for all the destruction, the toll could have been far greater. Without mitigating or in any way denying the horrible disaster that hit Nepal that day, the responsible use of data helped avoid a worse calamity and may offer lessons for other disasters around the world.

Following the earthquake, government and civil society organizations rushed in to address the humanitarian crisis. Notably, so did the private sector. Nepal’s largest mobile operator, Ncell, for example, decided to share its mobile data—in an aggregated, de-identified way—with the the nonprofit Swedish organization Flowminder. Flowminder then used this data to map population movements around the country; these real-time maps allowed the government and humanitarian organizations to better target aid and relief to affected communities, thus maximizing the impact of their efforts.

The initiative has been widely lauded as a model for cross-sector collaboration. But what is perhaps most striking about the initiative is the way it used data—in particular, how it repurposed data originally collected for private purposes for public ends. This use of corporate data for wider social impact reflects the emerging concept of “data responsibility.” …

 

The Three Pillars of Data Responsibility

1. Share. This is perhaps the most evident: Data holders have a duty to share private data when a clear case exists that it serves the public good. There now exists manifold evidence that data—with appropriate oversight—can help improve lives, as we saw in Nepal.

2. Protect. The consequences of failing to protect data are well documented. The most obvious problems occur when data is not properly anonymized or when de-anonymized data leaks into the public domain. But there are also more subtle cases, when ostensibly anonymized data is itself susceptible to de-anonymization, and information released for the public good ends up causing or potentially causing harm.

3. Act. For the data to really serve the public good, officials and others must create policies and interventions based on the insights they gain from it. Without action, the potential remains just that—mere potential, never translated into concrete results….(Watch TEDx Video).

See also International Data Responsibility Group and Data Collaboratives Project.

Smart or dumb? The real impact of India’s proposal to build 100 smart cities


 in The Conversation: “In 2014, the new Indian government declared its intention to achieve 100 smart cities.

In promoting this objective, it gave the example of a large development in the island city of Mumbai, Bhendi Bazaar. There, 3-5 storey housing would be replaced with towers of between 40 to 60 storeys to increase density. This has come to be known as “vertical with a vengeance”.

We have obtained details of the proposed project from the developer and the municipal authorities. Using an extended urban metabolism model, which measures the impacts of the built environment, we have assessed its overall impact. We determined how the flows of materials and energy will change as a result of the redevelopment.

Our research shows that the proposal is neither smart nor sustainable.

Measuring impacts

The Indian government clearly defined what they meant with “smart”. Over half of the 11 objectives were environmental and main components of the metabolism of a city. These include adequate water and sanitation, assured electricity, efficient transport, reduced air pollution and resource depletion, and sustainability.

We collected data from various primary and secondary sources. This included physical surveys during site visits, local government agencies, non-governmental organisations, the construction industry and research.

We then made three-dimensional models of the existing and proposed developments to establish morphological changes, including building heights, street widths, parking provision, roof areas, open space, landscaping and other aspects of built form.

Demographic changes (population density, total population) were based on census data, the developer’s calculations and an assessment of available space. Such information about the magnitude of the development and the associated population changes allowed us to analyse the additional resources required as well as the environmental impact….

Case studies such as Bhendi Bazaar provide an example of plans for increased density and urban regeneration. However, they do not offer an answer to the challenge of limited infrastructure to support the resource requirements of such developments.

The results of our research indicate significant adverse impacts on the environment. They show that the metabolism increases at a greater rate than the population grows. On this basis, this proposed development for Mumbai, or the other 99 cities, should not be called smart or sustainable.

With policies that aim to prevent urban sprawl, cities will inevitably grow vertically. But with high-rise housing comes dependence on centralised flows of energy, water supplies and waste disposal. Dependency in turn leads to vulnerability and insecurity….(More)”.

The Implementation of Open Data in Indonesia


Paper by Dani Gunawan and Amalia Amalia: “Nowadays, public demands easy access to nonconfidential government data, such as public digital information on health, industry, and culture that can be accessed on the Internet. This will lead departments within government to be efficient and more transparent. As the results, rapid development of applications will solve citizens’ problems in many sectors. One Data Initiatives is the prove that the Government of Indonesia supports data transparency. This research investigates the implementation of open data in Indonesia based on Tim BernersLee five-star rating and open stage model by Kalampokis. The result shows that mostly data in Indonesia is freely available in the Internet, but most of them are not machine-readable and do not support non-proprietary format. The drawback of Indonesia’s open data is lack of ability to link the existing data with other data sources. Therefore, Indonesia is still making initial steps with data inventories and beginning to publish key datasets of public interest…(More)”

How AI Is Crunching Big Data To Improve Healthcare Outcomes


PSFK: “The state of your health shouldn’t be a mystery, nor should patients or doctors have to wait long to find answers to pressing medical concerns. In PSFK’s Future of Health Report, we dig deep into the latest in AI, big data algorithms and IoT tools that are enabling a new, more comprehensive overview of patient data collection and analysis. Machine support, patient information from medical records and conversations with doctors are combined with the latest medical literature to help form a diagnosis without detracting from doctor-patient relations.

The impact of improved AI helps patients form a baseline for well-being and is making changes all across the healthcare industry. AI not only streamlines intake processes and reduces processing volume at clinics, it also controls input and diagnostic errors within a patient record, allowing doctors to focus on patient care and communication, rather than data entry. AI also improves pattern recognition and early diagnosis by learning from multiple patient data sets.

By utilizing deep learning algorithms and software, healthcare providers can connect various libraries of medical information and scan databases of medical records, spotting patterns that lead to more accurate detection and greater breadth of efficiency in medical diagnosis and research. IBM Watson, which has previously been used to help identify genetic markers and develop drugs, is applying its neural learning networks to help doctors correctly diagnose heart abnormalities from medical imaging tests. By scanning thousands of images and learning from correct diagnoses, Watson is able to increase diagnostic accuracy, supporting doctors’ cardiac assessments.

Outside of the doctor’s office, AI is also being used to monitor patient vitals to help create a baseline for well-being. By monitoring health on a day-to-day basis, AI systems can alert patients and medical teams to abnormalities or changes from the baseline in real time, increasing positive outcomes. Take xbird, a mobile platform that uses artificial intelligence to help diabetics understand when hypoglycemic attacks will occur. The AI combines personal and environmental data points from over 20 sensors within mobile and wearable devices to create an automated personal diary and cross references it against blood sugar levels. Patients then share this data with their doctors in order to uncover their unique hypoglycemic triggers and better manage their condition.

In China, meanwhile, web provider Baidu has debuted Melody, a chat-based medical assistant that helps individuals communicate their symptoms, learn of possible diagnoses and connect to medical experts….(More)”.

China seeks glimpse of citizens’ future with crime-predicting AI


, Yingzhi Yang and Sherry Fei Ju in the Financial Times: “China, a surveillance state where authorities have unchecked access to citizens’ histories, is seeking to look into their future with technology designed to predict and prevent crime. Companies are helping police develop artificial intelligence they say will help them identify and apprehend suspects before criminal acts are committed. “If we use our smart systems and smart facilities well, we can know beforehand . . . who might be a terrorist, who might do something bad,” Li Meng, vice-minister of science and technology, said on Friday.

Facial recognition company Cloud Walk has been trialling a system that uses data on individuals’ movements and behaviour — for instance visits to shops where weapons are sold — to assess their chances of committing a crime. Its software warns police when a citizen’s crime risk becomes dangerously high, allowing the police to intervene. “The police are using a big-data rating system to rate highly suspicious groups of people based on where they go and what they do,” a company spokesperson told the Financial Times. Risks rise if the individual “frequently visits transport hubs and goes to suspicious places like a knife store”, the spokesperson added. China’s authoritarian government has always amassed personal data to monitor and control its citizens — whether they are criminals or suspected of politically sensitive activity. But new technology, from phones and computers to fast-developing AI software, is amplifying its capabilities. These are being used to crack down on even the most minor of infractions — facial recognition cameras, for instance, are also being used to identify and shame jaywalkers, according to state media. Mr Li said crime prediction would become an important use for AI technology in the government sphere.

China’s crime-prediction technology relies on several AI techniques, including facial recognition and gait analysis, to identify people from surveillance footage. In addition, “crowd analysis” can be used to detect “suspicious” patterns of behaviour in crowds, for example to single out thieves from normal passengers at a train stations. As well as tracking people with a criminal history, Cloud Walk’s technology is being used to monitor “high-risk” places such as hardware stores…(More)”

Active Citizenship in Europe: Practices and Demands in the EU, Italy, Turkey and the UK


Book by Cristiano Bee: “…provides an overview of key issues in the debate concerning the emergence of active citizenship in Europe.

The specific focus of enquiry is the promotion of patterns of civic and political engagement and civic and political participation by the EU and the relative responses drawn by organizations of the civil society operating at the supranational level and in Italy, Turkey and the UK. More specifically, it addresses key debates on the engagement and participation of organized civil society across the permanent state of euro-crisis, considering the production of policy discourses along the continuum that characterized three subsequent and interrelated emergency situations (democratic, financial and migration crises) that have hit Europe since 2005. …(More)”.

How open data can help the Global South, from disaster relief to voter turnout


Stefaan Verhulst and Andrew Young in The Conversation Global: “The modern era is marked by growing faith in the power of data. “Big data”, “open data”, and “evidence-based decision-making” have become buzzwords, touted as solutions to the world’s most complex and persistent problems, from corruption and famine to the refugee crisis.

While perhaps most pronounced in higher income countries, this trend is now emerging globally. In Africa, Latin America, Asia and beyond, hopes are high that access to data can help developing economies by increasing transparency, fostering sustainable development, building climate resiliency and the like.

This is an exciting prospect, but can opening up data actually make a difference in people’s lives?

Getting data-driven about data

The GovLab at New York University spent the last year trying to answer that question….

Our conclusion: the enthusiasm is justified – as long as it’s tempered with a good measure of realism, too. Here are our six major takeaways:

1. We need a framework – Overall, there is still little evidence to substantiate the enthusiastic claims that open data can foment sustainable development and transform governance. That’s not surprising given the early stage of most open data initiatives.

It may be early for impact evaluation, but it’s not too soon to develop a model that will eventually allow us to assess the impact of opening up data over time.

To that end, the GovLab has created an evidence-based framework that aims to better capture the role of open data in developing countries. The Open Data Logic Framework below focuses on various points in the open data value cycle, from data supply to demand, use and impact.

Logic model of open data. The GovLab

2. Open data has real promise – Based on this framework and the underlying evidence that fed into it, we can guardedly conclude that open data does in fact spur development – but only under certain conditions and within the right supporting ecosystem.

One well-known success took place after Nepal’s 2015 earthquake when open data helped NGOs map important landmarks such as health facilities and road networks, among other uses.

And in Colombia, the International Centre for Tropical Agriculture launched Aclímate Colombia, a tool that gives smallholder farmers data-driven insight into planting strategies that makes them more resilient to climate change….

3. Open data can improve people’s lives Examining projects in a number of sectors critical to development, including health, humanitarian aid, agriculture, poverty alleviation, energy and education, we found four main ways that data can have an impact….

4. Data can be an asset in development While these impacts are apparent in both developed and developing countries, we believe that open data can have a particularly powerful role in developing economies.

Where data is scarce, as it often is in poorer countries, open data can lead to an inherently more equitable and democratic distribution of information and knowledge. This, in turn, may activate a wider range of expertise to address complex problems; it’s what we in the field call “open innovation”.

This quality can allow resource-starved developing economies to access and leverage the best minds around.

And because trust in government is quite low in many developing economies, the transparency bred of releasing data can have after-effects that go well beyond the immediate impact of the data itself…

5. The ingredients matter To better understand why some open data projects fail while others succeed, we created a “periodic table” of open data (below), which includes 27 enabling factors divided into five broad categories….

6. We can plan for impact Our report ends by identifying how development organisations can catalyse the release and use of open data to make a difference on the ground.

Recommendations include:

· Define the problem, understand the user, and be aware of local conditions;

· Focus on readiness, responsiveness and change management;

· Nurture an open data ecosystem through collaboration and partnerships;

· Have a risk mitigation strategy;

· Secure resources and focus on sustainability; and

· Build a strong evidence base and support more research.

Next steps

In short, while it may still be too early to fully capture open data’s as-of-yet muted impact on developing economies, there are certainly reasons for optimism.

Much like blockchaindrones and other much-hyped technical advances, it’s time to start substantiating the excitement over open data with real, hard evidence.

The next step is to get systematic, using the kind of analytical framework we present here to gain comparative and actionable insight into if, when and how open data works. Only by getting data-driven about open data can we help it live up to its potential….(More)