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)”

The challenges and limits of big data algorithms in technocratic governance


Paper by Marijn Janssen and George Kuk in Government Information Quarterly: “Big data is driving the use of algorithm in governing mundane but mission-critical tasks. Algorithms seldom operate on their own and their (dis)utilities are dependent on the everyday aspects of data capture, processing and utilization. However, as algorithms become increasingly autonomous and invisible, they become harder for the public to detect and scrutinize their impartiality status. Algorithms can systematically introduce inadvertent bias, reinforce historical discrimination, favor a political orientation or reinforce undesired practices. Yet it is difficult to hold algorithms accountable as they continuously evolve with technologies, systems, data and people, the ebb and flow of policy priorities, and the clashes between new and old institutional logics. Greater openness and transparency do not necessarily improve understanding. In this editorial we argue that through unraveling the imperceptibility, materiality and governmentality of how algorithms work, we can better tackle the inherent challenges in the curatorial practice of data and algorithm. Fruitful avenues for further research on using algorithm to harness the merits and utilities of a computational form of technocratic governance are presented….(More)

 

Data Ethics: Investing Wisely in Data at Scale


Report by David Robinson & Miranda Bogen prepared for the MacArthur and Ford Foundations: ““Data at scale” — digital information collected, stored and used in ways that are newly feasible — opens new avenues for philanthropic investment. At the same time, projects that leverage data at scale create new risks that are not addressed by existing regulatory, legal and best practice frameworks. Data-oriented projects funded by major foundations are a natural proving ground for the ethical principles and controls that should guide the ethical treatment of data in the social sector and beyond.

This project is an initial effort to map the ways that data at scale may pose risks to philanthropic priorities and beneficiaries, for grantmakers at major foundations, and draws from desk research and unstructured interviews with key individuals involved in the grantmaking enterprise at major U.S. foundations. The resulting report was prepared at the joint request of the MacArthur and Ford Foundations.

Grantmakers are exploring data at scale, but currently have poor visibility into its benefits and risks. Rapid technological change, the scarcity of data science expertise, limited training and resources, and a lack of clear guideposts around emergent risks all contribute to this problem.

Funders have important opportunities to invest in, learn from, and innovate around data-intensive projects, in concert with their grantees. Grantmakers should not treat the new ethical risks of data at scale as a barrier to investment, but these risks also must not become a blind spot that threatens the success and effectiveness of philanthropic projects. Those working with data at scale in the philanthropic context have much to learn: throughout our conversations with stakeholders, we heard consistently that grantmakers and grantees lack baseline knowledge on using data at scale, and many said that they are unsure how to make better informed decisions, both about data’s benefits and about its risks. Existing frameworks address many risks introduced by data-intensive grantmaking, but leave some major gaps. In particular, we found that:

  • Some new data-intensive research projects involve meaningful risk to vulnerable populations, but are not covered by existing human subjects regimes, and lack a structured way to consider these risks. In the philanthropic and public sector, human subject review is not always required and program officers, researchers, and implementers do not yet have a shared standard by which to evaluate ethical implications of using public or existing data, which is often exempt from human subjects review.
  • Social sector projects often depend on data that reflects patterns of bias or discrimination against vulnerable groups, and face a challenge of how to avoid reinforcing existing disparities. Automated decisions can absorb and sanitize bias from input data, and responsibly funding or evaluating statistical models in data-intensive projects increasingly demands advanced mathematical literacy which foundations lack.
  • Both data and the capacity to analyze it are being concentrated in the private sector, which could marginalize academic and civil society actors.Some individuals and organizations have begun to call attention to these issues and create their own trainings, guidelines, and policies — but ad hoc solutions can only accomplish so much.

To address these and other challenges, we’ve identified eight key questions that program staff and grantees need to consider in data-intensive work:

  1. For a given project, what data should be collected, and who should have access to it?
  2. How can projects decide when more data will help — and when it won’t?
  3. How can grantmakers best manage the reputational risk of data-oriented projects that may be at a frontier of social acceptability?
  4. When concerns are recognized with respect to a data-intensive grant, how will those concerns get aired and addressed?
  5. How can funders and grantees gain the insight they need in order to critique other institutions’ use of data at scale?
  6. How can the social sector respond to the unique leverage and power that large technology companies are developing through their accumulation of data and data-related expertise?
  7. How should foundations and nonprofits handle their own data?
  8. How can foundations begin to make the needed long term investments in training and capacity?

Newly emergent ethical issues inherent in using data at scale point to the need for both a broader understanding of the possibilities and challenges of using data in the philanthropic context as well as conscientious treatment of data ethics issues. Major foundations can play a meaningful role in building a broader understanding of these possibilities and challenges, and they can set a positive example in creating space for open and candid reflection on these issues. To those ends, we recommend that funders:…(More)”

Living labs: Implementing open innovation in the public sector


Paper by Mila Gascó in Government Information Quarterly: “Public sector innovation is an important issue in the agenda of policymakers and academics but there is a need for a change of perspective, one that promotes a more open model of innovating, which takes advantage of the possibilities offered by collaboration between citizens, entrepreneurs and civil society as well as of new emerging technologies. Living labs are environments that can support public open innovation processes.

This article makes a practical contribution to understand the role of living labs as intermediaries of public open innovation. The analysis focuses on the dynamics of these innovation intermediaries, their outcomes, and their main challenges. In particular, it adopts a qualitative approach (fourteen semi-structured interviews and one focus group were conducted) in order to analyze two living labs: Citilab in the city of Cornellà and the network of fab athenaeums (public fab labs) in the city of Barcelona, both in Spain. After a thorough analysis of the attributes of these living labs, the article concludes that 1) living labs provide the opportunity for public agencies to meet with private sector organizations and thus function as innovation intermediaries, 2) implementing an open innovation perspective is considered more important than obtaining specific innovation results, and 3) scalability and sustainability are the main problems living labs encounter as open innovation intermediaries….(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)”

Collective intelligence and international development


Gina Lucarelli, Tom Saunders and Eddie Copeland at Nesta: “The mountain kingdom of Lesotho, a small landlocked country in Sub-Saharan Africa, is an unlikely place to look for healthcare innovation. Yet in 2016, it became the first country in Africa to deploy the test and treat strategy for treating people with HIV. Rather than waiting for white blood cell counts to drop, patients begin treatment as soon as they are diagnosed. This strategy is backed by the WHO as it has the potential to increase the number of people who are able to access treatment, consequently reducing transmisssion and keeping people with HIV healthy and alive for longer.

While lots of good work is underway in Lesotho, and billions have been spent on HIV programmes in the country, the percentage of the population infected with HIV has remained steady and is now almost 23%. Challenges of this scale need new ideas and better ways to adopt them.

On a recent trip to Lesotho as part of a project with the United Nations Development Group, we met various UN agencies, the World Bank, government leaders, civil society actors and local businesses, to learn about the key development issues in Lesotho and to discuss the role that ‘collective intelligence’ might play in creating better country development plans. The key question Nesta and the UN are working on is: how can we increase the impact of the UN’s work by tapping into the ideas, information and possible solutions which are distributed among many partners, the private sector, and the 2 million people of Lesotho?

…our framework of collective intelligence, a set of iterative stages which can help organisations like the UN tap into the ideas, information and possible solutions of groups and individuals which are not normally involved included in the problem solving process. For each stage, we also presented a number of examples of how this works in practice.

Collective intelligence framework – stages and examples

  1. Better understanding the facts, data and experiences: New tools, from smartphones to online communities enable researchers, practitioners and policymakers to collect much larger amounts of data much more quickly. Organisations can use this data to target their resources at the most critical issues as well as feed into the development of products and services that more accurately meet the needs of citizens. Examples include mPower, a clinical study which used an app to collect data about people with Parkinsons disease via surveys and smartphone sensors.

  2. Better development of options and ideas: Beyond data collection, organisations can use digital tools to tap into the collective brainpower of citizens to come up with better ideas and options for action. Examples include participatory budgeting platforms like “Madame Mayor, I have an idea” and challenge prizes, such as USAID’s Ebola grand challenge.

  3. Better, more inclusive decision making: Decision making and problem solving are usually left to experts, yet citizens are often best placed to make the decisions that will affect them. New digital tools make it easier than ever for governments to involve citizens in policymaking, planning and budgeting. Our D-CENT tools enable citizen involvement in decision making in a number of fields. Another example is the Open Medicine Project, which designs digital tools for healthcare in consultation with both practitioners and patients.

  4. Better oversight and improvement of what is done: From monitoring corruption to scrutinising budgets, a number of tools allow broad involvement in the oversight of public sector activity, potentially increasing accountability and transparency. The Family and Friends Test is a tool that allows NHS users in the UK to submit feedback on services they have experienced. So far, 25 million pieces of feedback have been submitted. This feedback can be used to stimulate local improvement and empower staff to carry out changes… (More)”

Behavioral Economics and Fed Policymaking


Essay by Mark A. Calabria in Cato Journal: “Behavioral economics has continued to gain momentum in challenging the standard rational actor model in economics. With a few exceptions, the emphasis has been on the cognitive failure of individuals outside of government. Niclas Berggren (2013: 200) estimates that 95.5 percent of behavioral economics articles in the leading economics journals do not contain an analysis of the cognitive ability of policymakers. In this article, I offer a preliminary analysis of potential cognitive failures in the Federal Reserve’s conduct of monetary policy. Proposals to “debias” monetary policymaking are offered, along with a discussion of how the Fed’s existing institutional structure ameliorates or exasperates potential biases…(More)”

Living in the World of Both/And


Essay by Adene Sacks & Heather McLeod Grant  in SSIR: “In 2011, New York Times data scientist Jake Porway wrote a blog post lamenting the fact that most data scientists spend their days creating apps to help users find restaurants, TV shows, or parking spots, rather than addressing complicated social issues like helping identify which teens are at risk of suicide or creating a poverty index of Africa using satellite data.

That post hit a nerve. Data scientists around the world began clamoring for opportunities to “do good with data.” Porway—at the center of this storm—began to convene these scientists and connect them to nonprofits via hackathon-style events called DataDives, designed to solve big social and environmental problems. There was so much interest, he eventually quit his day job at the Times and created the organization DataKind to steward this growing global network of data science do-gooders.

At the same time, in the same city, another movement was taking shape—#GivingTuesday, an annual global giving event fueled by social media. In just five years, #GivingTuesday has reshaped how nonprofits think about fundraising and how donors give. And yet, many don’t know that 92nd Street Y (92Y)—a 140-year-old Jewish community and cultural center in Manhattan, better known for its star-studded speaker series, summer camps, and water aerobics classes—launched it.

What do these two examples have in common? One started as a loose global network that engaged data scientists in solving problems, and then became an organization to help support the larger movement. The other started with a legacy organization, based at a single site, and catalyzed a global movement that has reshaped how we think about philanthropy. In both cases, the founding groups have incorporated the best of both organizations and networks.

Much has been written about the virtues of thinking and acting collectively to solve seemingly intractable challenges. Nonprofit leaders are being implored to put mission above brand, build networks not just programs, and prioritize collaboration over individual interests. And yet, these strategies are often in direct contradiction to the conventional wisdom of organization-building: differentiating your brand, developing unique expertise, and growing a loyal donor base.

A similar tension is emerging among network and movement leaders. These leaders spend their days steering the messy process required to connect, align, and channel the collective efforts of diverse stakeholders. It’s not always easy: Those searching to sustain movements often cite the lost momentum of the Occupy movement as a cautionary note. Increasingly, network leaders are looking at how to adapt the process, structure, and operational expertise more traditionally associated with organizations to their needs—but without co-opting or diminishing the energy and momentum of their self-organizing networks…

Welcome to the World of “Both/And”

Today’s social change leaders—be they from business, government, or nonprofits—must learn to straddle the leadership mindsets and practices of both networks and organizations, and know when to use which approach. Leaders like Porway, and Henry Timms and Asha Curran of 92Y can help show us the way.

How do these leaders work with the “both/and” mindset?

First, they understand and leverage the strengths of both organizations and networks—and anticipate their limitations. As Timms describes it, leaders need to be “bilingual” and embrace what he has called “new power.” Networks can be powerful generators of new talent or innovation around complex multi-sector challenges. It’s useful to take a network approach when innovating new ideas, mobilizing and engaging others in the work, or wanting to expand reach and scale quickly. However, networks can dissipate easily without specific “handrails,” or some structure to guide and support their work. This is where they need some help from the organizational mindset and approach.

On the flip side, organizations are good at creating centralized structures to deliver products or services, manage risk, oversee quality control, and coordinate concrete functions like communications or fundraising. However, often that efficiency and effectiveness can calcify over time, becoming a barrier to new ideas and growth opportunities. When organizational boundaries are too rigid, it is difficult to engage the outside world in ideating or mobilizing on an issue. This is when organizations need an infusion of the “network mindset.”

 

…(More)

How to advance open data research: Towards an understanding of demand, users, and key data


Danny Lämmerhirt and Stefaan Verhulst at IODC blog: “…Lord Kelvin’s famous quote “If you can not measure it, you can not improve it” equally applies to open data. Without more evidence of how open data contributes to meeting users’ needs and addressing societal challenges, efforts and policies toward releasing and using more data may be misinformed and based upon untested assumptions.

When done well, assessments, metrics, and audits can guide both (local) data providers and users to understand, reflect upon, and change how open data is designed. What we measure and how we measure is therefore decisive to advance open data.

Back in 2014, the Web Foundation and the GovLab at NYU brought together open data assessment experts from Open Knowledge, Organisation for Economic Co-operation and Development, United Nations, Canada’s International Development Research Centre, and elsewhere to explore the development of common methods and frameworks for the study of open data. It resulted in a draft template or framework for measuring open data. Despite the increased awareness for more evidence-based open data approaches, since 2014 open data assessment methods have only advanced slowly. At the same time, governments publish more of their data openly, and more civil society groups, civil servants, and entrepreneurs employ open data to manifold ends: the broader public may detect environmental issues and advocate for policy changes, neighbourhood projects employ data to enable marginalized communities to participate in urban planning, public institutions may enhance their information exchange, and entrepreneurs embed open data in new business models.

In 2015, the International Open Data Conference roadmap made the following recommendations on how to improve the way we assess and measure open data.

  1. Reviewing and refining the Common Assessment Methods for Open Data framework. This framework lays out four areas of inquiry: context of open data, the data published, use practices and users, as well as the impact of opening data.
  2. Developing a catalogue of assessment methods to monitor progress against the International Open Data Charter (based on the Common Assessment Methods for Open Data).
  3. Networking researchers to exchange common methods and metrics. This helps to build methodologies that are reproducible and increase credibility and impact of research.
  4. Developing sectoral assessments.

In short, the IODC called for refining our assessment criteria and metrics by connecting researchers, and applying the assessments to specific areas. It is hard to tell how much progress has been made in answering these recommendations, but there is a sense among researchers and practitioners that the first two goals are yet to be fully addressed.

Instead we have seen various disparate, yet well meaning, efforts to enhance the understanding of the release and impact of open data. A working group was created to measure progress on the International Open Data Charter, which provides governments with principles for implementing open data policies. While this working group compiled a list of studies and their methodologies, it did not (yet) deepen the common framework of definitions and criteria to assess and measure the implementation of the Charter.

In addition, there is an increase of sector- and case-specific studies that are often more descriptive and context specific in nature, yet do contribute to the need for examples that illustrate the value proposition for open data.

As such, there seems to be a disconnect between top-level frameworks and on-the-ground research, preventing the sharing of common methods and distilling replicable experiences about what works and what does not….(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)”