Evaluating World Bank Support to Budget Analysis and Transparency


Report by Linnea Mills and Clay G. Wescott: “BOOST is a new resource launched in 2010 to facilitate improved quality, classification, and access to budget data and promote effective use for improved government decision making, transparency and accountability. Using the Government’s own data from public expenditure accounts held in the Government’s Financial Management Information System, and benefiting from a consistent methodology, the BOOST data platform makes highly granular fiscal data accessible and ready-for-use. National authorities can significantly enhance fiscal transparency by publishing summary data and analysis or by providing open access to the underlying dataset. This paper addresses four research questions: Did BOOST help improve the quality of expenditure analysis available to government decision makers? Did it help to develop capacity in central finance and selected spending agencies to sustain expenditure analysis? Did it help to improve public access to expenditure analysis anddata? Did it help to increase awareness of the opportunities for BOOST and expenditure analysis in Sub-Saharan Africa as well as countries outside this region where BOOST has been used (Georgia, Haiti and Tunisia).

Evidence has been drawn from various sources. Survey questionnaires were sent to all World Bank task team leaders for Gates Trust Fund supported countries. Completed questionnaires were received from 18 predominantly African countries (Annex 4). These 18 countries constitute the majority but not all of the countries implementing BOOST with financial support from the Trust Fund. Information has also been gathered through a BOOST stakeholder questionnaire targeting government officials, civil society representatives and representatives from parliaments at country level, field visits to Kenya, Mozambique and Uganda, interviews with stakeholders at the Bank and at country level, participation at regional conferences on BOOST in South Africa and Senegal, and document review. Interviews covered participants from some countries that did not complete questionnaires, such as Haiti.

The research will help to inform the Bill and Melinda Gates Foundation, and the World Bank, the administrator of the trust fund on the achievements of the program, and the value of continuing support. It will inform client country Governments, and non-Government actors interested in improved dissemination and analysis of quality public financial data. The research should also be useful for vendors of similar products like OpenGov; and to international scholars and experts working to better understand public expenditure management in developing countries….(More)”

Privacy Laws Around the World


Bloomberg Law: “Development of international privacy laws and regulations with critical impact on the global economy been extremely active over the last several years.

Download Privacy Laws Around the World to access common and disparate elements of the privacy laws from 61 countries. Crafted by Cynthia Rich of Morrison & Foerster LLP, the report includes expert analysis on privacy laws in Europe and Eurasia (non-EEA); East, Central and South Asia and the Pacific; the Western Hemisphere (Latin America, Caribbean and Canada); as well as Africa and the Near East.

Privacy Laws Around the World…access:

Side-by-side charts comparing four key compliance areas including registration requirements, cross-border data transfer limitations, data breach notification requirements and data protection officer requirements

A country-by-country review of the special characteristics of framework privacy laws

An overview of privacy legislation in development around the world…(More) (Requires Registration)”

Citizen engagement in rulemaking — evidence on regulatory practices in 185 countries


Paper by Johns,Melissa Marie and Saltane,Valentina for the World Bank: “… presents a new database of indicators measuring the extent to which rulemaking processes are transparent and participatory across 185 countries. The data look at how citizen engagement happens in practice, including when and how governments open the policy-making process to public input. The data also capture the use of ex ante assessments to determine the possible cost of compliance with a proposed new regulation, the likely administrative burden of enforcing the regulation, and its potential environmental and social impacts. The data show that citizens have more opportunities to participate directly in the rulemaking process in developed economies than in developing ones. Differences are also apparent among regions: rulemaking processes are significantly less transparent and inclusive in Sub-Saharan Africa, the Middle East and North Africa, and South Asia on average than in Organisation for Economic Co-operation and Development high-income countries, Europe and Central Asia, and East Asia and the Pacific. In addition, ex ante impact assessments are much more common among higher-income economies than among lower-income ones. And greater citizen engagement in rulemaking is associated with higher-quality regulation, stronger democratic regimes, and less corrupt institutions….(More)”

Europe Should Promote Data for Social Good


Daniel Castro at Center for Data Innovation: “Changing demographics in Europe are creating enormous challenges for the European Union (EU) and its member states. The population is getting older, putting strain on the healthcare and welfare systems. Many young people are struggling to find work as economies recover from the 2008 financial crisis. Europe is facing a swell in immigration, increasingly from war-torn Syria, and governments are finding it difficult to integrate refugees and other migrants into society.These pressures have already propelled permanent changes to the EU. This summer, a slim majority of British voters chose to leave the Union, and many of those in favor of Brexit cited immigration as a motive for their vote.

Europe needs to find solutions to these challenges. Fortunately, advances in data-driven innovation that have helped businesses boost performance can also create significant social benefits. They can support EU policy priorities for social protection and inclusion by better informing policy and program design, improving service delivery, and spurring social innovations. While some governments, nonprofit organizations, universities, and companies are using data-driven insights and technologies to support disadvantaged populations, including unemployed workers, young people, older adults, and migrants, progress has been uneven across the EU due to resource constraints, digital inequality, and restrictive data regulations. renewed European commitment to using data for social good is needed to address these challenges.

This report examines how the EU, member-states, and the private sector are using data to support social inclusion and protection. Examples include programs for employment and labor-market inclusion, youth employment and education, care for older adults, and social services for migrants and refugees. It also identifies the barriers that prevent European countries from fully capitalizing on opportunities to use data for social good. Finally, it proposes a number of actions policymakers in the EU should take to enable the public and private sectors to more effectively tackle the social challenges of a changing Europe through data-driven innovation. Policymakers should:

  • Support the collection and use of relevant, timely data on the populations they seek to better serve;
  • Participate in and fund cross-sector collaboration with data experts to make better use of data collected by governments and non-profit organizations working on social issues;
  • Focus government research funding on data analysis of social inequalities and require grant applicants to submit plans for data use and sharing;
  • Establish appropriate consent and sharing exemptions in data protection regulations for social science research; and
  • Revise EU regulations to accommodate social-service organizations and their institutional partners in exploring innovative uses of data….(More)”

The Wealth of Humans: Work, Power, and Status in the Twenty-first Century


Book by Ryan Avent: “None of us has ever lived through a genuine industrial revolution. Until now.

Digital technology is transforming every corner of the economy, fundamentally altering the way things are done, who does them, and what they earn for their efforts. In The Wealth of Humans, Economist editor Ryan Avent brings up-to-the-minute research and reporting to bear on the major economic question of our time: can the modern world manage technological changes every bit as disruptive as those that shook the socioeconomic landscape of the 19th century?

Traveling from Shenzhen, to Gothenburg, to Mumbai, to Silicon Valley, Avent investigates the meaning of work in the twenty-first century: how technology is upending time-tested business models and thrusting workers of all kinds into a world wholly unlike that of a generation ago. It’s a world in which the relationships between capital and labor and between rich and poor have been overturned.

Past revolutions required rewriting the social contract: this one is unlikely to demand anything less. Avent looks to the history of the Industrial Revolution and the work of numerous experts for lessons in reordering society. The future needn’t be bleak, but as The Wealth of Humans explains, we can’t expect to restructure the world without a wrenching rethinking of what an economy should be….(More)”

Informed Choice? Motivations and methods of data usage among public officials in India


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)