Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance


Paper by Emily Aiken et al: “The COVID-19 pandemic has devastated many low- and middle-income countries (LMICs), causing widespread food insecurity and a sharp decline in living standards. In response to this crisis, governments and humanitarian organizations worldwide have mobilized targeted social assistance programs. Targeting is a central challenge in the administration of these programs: given available data, how does one rapidly identify the individuals and families with the greatest need? This challenge is particularly acute in the large number of LMICs that lack recent and comprehensive data on household income and wealth.

Here we show that non-traditional “big” data from satellites and mobile phone networks can improve the targeting of anti-poverty programs. Our approach uses traditional survey-based measures of consumption and wealth to train machine learning algorithms that recognize patterns of poverty in non-traditional data; the trained algorithms are then used to prioritize aid to the poorest regions and mobile subscribers. We evaluate this approach by studying Novissi, Togo’s flagship emergency cash transfer program, which used these algorithms to determine eligibility for a rural assistance program that disbursed millions of dollars in COVID-19 relief aid. Our analysis compares outcomes – including exclusion errors, total social welfare, and measures of fairness – under different targeting regimes. Relative to the geographic targeting options considered by the Government of Togo at the time, the machine learning approach reduces errors of exclusion by 4-21%. Relative to methods that require a comprehensive social registry (a hypothetical exercise; no such registry exists in Togo), the machine learning approach increases exclusion errors by 9-35%. These results highlight the potential for new data sources to contribute to humanitarian response efforts, particularly in crisis settings when traditional data are missing or out of date….(More)”.

Coding Democracy: How Hackers Are Disrupting Power, Surveillance, and Authoritarianism


Book by Maureen Webb: “Hackers have a bad reputation, as shady deployers of bots and destroyers of infrastructure. In Coding Democracy, Maureen Webb offers another view. Hackers, she argues, can be vital disruptors. Hacking is becoming a practice, an ethos, and a metaphor for a new wave of activism in which ordinary citizens are inventing new forms of distributed, decentralized democracy for a digital era. Confronted with concentrations of power, mass surveillance, and authoritarianism enabled by new technology, the hacking movement is trying to “build out” democracy into cyberspace.

Webb travels to Berlin, where she visits the Chaos Communication Camp, a flagship event in the hacker world; to Silicon Valley, where she reports on the Apple-FBI case, the significance of Russian troll farms, and the hacking of tractor software by desperate farmers; to Barcelona, to meet the hacker group XNet, which has helped bring nearly 100 prominent Spanish bankers and politicians to justice for their role in the 2008 financial crisis; and to Harvard and MIT, to investigate the institutionalization of hacking. Webb describes an amazing array of hacker experiments that could dramatically change the current political economy. These ambitious hacks aim to displace such tech monoliths as Facebook and Amazon; enable worker cooperatives to kill platforms like Ubergive people control over their data; automate trust; and provide citizens a real say in governance, along with capacity to reach consensus. Coding Democracy is not just another optimistic declaration of technological utopianism; instead, it provides the tools for an urgently needed upgrade of democracy in the digital era….(More)”.

Data Literacy in Government: How Are Agencies Enhancing Data Skills?


Randy Barrett at FedTech: “The federal government is vast, and the challenge of understanding its oceans of data grows daily. Rather than hiring thousands of new experts, agencies are moving to train existing employees on how to handle the new frontier.

Data literacy is now a common buzzword, spurred by the publication of the Federal Data Strategy 2020 Action Plan last year and the growing empowerment of chief data officers in the government. The document outlines a multiyear, holistic approach to government information that includes building a culture that values data, encouraging strong management and protection and promoting its efficient and appropriate use.

“While the Federal government leads globally in many instances in developing and providing data about the United States and the world, it lacks a robust, integrated approach to using data to deliver on mission, serve the public and steward resources,” the plan notes.

A key pillar of the plan is to “identify opportunities to increase staff data skills,” and it directs all federal agencies to undertake a gap analysis of skills to see where the weaknesses and needs lie….

The Department of Health and Human Services launched its Data Science CoLab in 2017 to boost basic and intermediate data skills. The collaborative program is the first try at a far reaching and cohort-based data-skills training for the agency. In addition to data analytics skills, HHS is currently training hundreds of employees on how to write Python and R.

“Demand for a seat in the Data Science CoLab has grown approximately 800 percent in the past three years, a testament to its success,” says Bishen Singh, a senior adviser in the Office of the Assistant Secretary for Health. “Beyond skill growth, it has led to incredible time and cost savings, as well as internal career growth for past participants across the department.”

The National Science Foundation was less successful with its Data Science and Data Certification Pilot, which had a class of 10 participants from various federal agencies. The workers were trained in advanced analytics techniques, with a focus on applying data tools to uncover meaning and solve Big Data challenges. However, the vendor curriculum used general data sets rather than agency-specific ones.

“As a result, participants found it more difficult to apply their learnings directly to real-world scenarios,” notes the CDO Council’s “Data Skill Training Program: Case Studies” report. The learning modules were mostly virtual and self-paced. Communication was poor with the vendor, and employees began to lag in completing their coursework. The pilot was discontinued.

Most of the training pilot programs were launched as the pandemic closed down government offices. The shift to virtual learning made progress difficult for some students. Another key lesson: Allow workers to use their new skills quickly, while they’re fresh….(More)”.

Proposal for a European Interoperability Framework for Smart Cities and Communities (EIF4SCC) published


Article by Nóirín Ní Earcáin: “In recognition of the importance of interoperability and the specific challenges it presents in a city context, The Commission (DG DIGIT and DG CONNECT) appointed Deloitte and KU Leven to prepare a Proposal for a European Interoperability Framework for Smart Cities and Communities. While an EIF for eGovernment has been in place since 2010, this is the first time the concepts and ideas developed there have been adapted to the local context.

The aim of the EIF4SCC is to provide EU local administration leaders with definitions, principles, recommendations, practical use cases drawn from cities and communities from around Europe and beyond, and a common model to facilitate delivery of services to the public across domains, cities, regions and borders.

The framework was developed by building on and finding complementarities with previous and ongoing initiatives, such as the Living-in.EU movement, the 2017 European Interoperability Framework (EIF), the Minimal Interoperability Mechanisms (MIMs Plus) and the outcomes of EU funded initiatives (e.g.Connecting Europe Facility (CEF) Digital Building BlocksSmart Cities MarketplaceIntelligent Cities ChallengeDigital Transition Partnership under the Urban Agenda) and EU funded projects (SynchronicityTriangulum, etc.).

Why do cities and communities need interoperability?

The EIF4SCC is targeted at EU local administration leaders and aims to provide a generic framework of interoperability of all types, and how it can contribute to the development of a Smart(er) City/Community. This will pave the way for services for citizens and business to be offered not only in a single city, but also across cities, regions and across borders.

European Interoperability Framework for Smart Cities and Communities

The EIF4SCC includes three concepts (interoperability, smart city or community, EIF4SCC), five principles (drawing on the Living-in.EU declaration), and seven elements (consisting of the five components of interoperability, one cross-cutting layer – Integrated Service Governance, and a foundational layer of Interoperability Governance)….The European Commission encourages local administrations at regional, city and community level to review the Proposed EIF4SCC, and the accompanying Final Study Report which details the methodology, literature review, and stakeholder engagement process undertaken. It will be discussed through the Living-in.EU community and other fora, with a view to its adoption as an official Commission document, based on users’ and stakeholders’ feedback…(More)”.

Behavioural science is unlikely to change the world without a heterogeneity revolution


Article by Christopher J. Bryan, Elizabeth Tipton & David S. Yeager: “In the past decade, behavioural science has gained influence in policymaking but suffered a crisis of confidence in the replicability of its findings. Here, we describe a nascent heterogeneity revolution that we believe these twin historical trends have triggered. This revolution will be defined by the recognition that most treatment effects are heterogeneous, so the variation in effect estimates across studies that defines the replication crisis is to be expected as long as heterogeneous effects are studied without a systematic approach to sampling and moderation. When studied systematically, heterogeneity can be leveraged to build more complete theories of causal mechanism that could inform nuanced and dependable guidance to policymakers. We recommend investment in shared research infrastructure to make it feasible to study behavioural interventions in heterogeneous and generalizable samples, and suggest low-cost steps researchers can take immediately to avoid being misled by heterogeneity and begin to learn from it instead….(More)”.

Designing Institutional Collaboration into Global Governance


Policy Brief by C. Randall Henning: “Collaboration among international institutions is essential for high-quality governance in many areas of global policy, yet it is chronically undersupplied. Numerous opportunities for institutional collaboration are being missed and there are calls for deepening collaboration in discourse on global governance — in new areas of governance, such as digital privacy, content moderation and platforms; better-established areas, such as climate change and biodiversity; as well as long-established but nonetheless evolving areas, such as international finance, development and trade. There are several obstacles to collaboration, including key countries’ using some institutions to constrain others, a strategy of “complexity for control.” This policy brief suggests that in designing international institutions, states and other principals should draw from a tool kit of strategies and techniques for promoting collaboration, including introducing or developing formal and informal mechanisms, and harnessing the Group of Seven and the Group of Twenty to foster collaboration proactively. New institutions should be designed from the outset to collaborate with others in a dense institutional environment….(More)”.

Governing smart cities: policy benchmarks for ethical and responsible smart city development


Report by the World Economic Forum: “… provides a benchmark for cities looking to establish policies for ethical and responsible governance of their smart city programmes. It explores current practices relating to five foundational policies: ICT accessibility, privacy impact assessment, cyber accountability, digital infrastructure and open data. The findings are based on surveys and interviews with policy experts and city government officials from the Alliance’s 36 “Pioneer Cities”. The data and insights presented in the report come from an assessment of detailed policy elements rather than the high-level indicators often used in maturity frameworks….(More)”.

To solve big issues like climate change, we need to reframe our problems



Essay by Thomas Wedell-Wedellsborg and Jonathan Wichmann: “Imagine you own an office building and your tenants are complaining that the elevator is way too slow. What do you do?

Faced with this problem, most people instinctively jump into solution mode. How can we make the elevator faster? Can we upgrade the motor? Tweak the algorithm? Do we need to buy a new elevator?

The speed of the elevator might be the wrong problem to focus on, however. Talk to an experienced landlord and they might offer you a more elegant solution: put up mirrors next to the elevator so people don’t notice the wait. Gazing lovingly at your own reflection tends to have that effect.

The mirror doesn’t make the elevator faster. It solves a different problem – that the wait is annoying.

Solve the right problem

The slow elevator story highlights an important truth, in that the way we frame a problem often determines which solutions we come up with. By shifting the way we see a problem, we can sometimes find better solutions.

Problem framing is of paramount importance when it comes to tackling the many hard challenges our societies face. And yet, we’re not terribly good at it. In a survey of 106 corporate leaders, 87% said their people waste significant resources solving the wrong problems. When we go to the doctor, we know very well that identifying the right problem is key. Too often, we fail to apply the same thinking to social and global problems.

Three common patterns

So, how do we get better at it? One starting point is to recognise that there are often patterns in the way we frame problems. Get better at recognising those patterns, and you can dramatically improve your ability to solve the right problems. Here are three typical patterns:

1. We prefer framings that allow us to avoid change

People tend to frame problems so they don’t have to change their own behaviour. When the lack of women leading companies first became a prominent concern decades ago, it was often framed as a pipeline problem. Many corporate leaders simply assumed that, once there were enough women in junior positions, the C-suite would follow.

That framing allowed companies to carry on as usual for about a generation until time eventually proved the pipeline theory wrong, or at best radically incomplete. The gender balance among senior executives would surely be better by now if companies had not spent a few decades ignoring other explanations for the skewed ratio….(More)”.

Have behavioral sciences delivered on their promise to influence environmental policy and conservation practice?


Paper by Maria Alejandra Velez and Lina Moros: “After four decades of refining our understanding of decision-making processes, a form of consensus has developed around the crucial role that behavioral science can play in changing non-cooperative decisions and promoting pro-environmental behaviors. However, has behavioral science delivered on its promise to influence environmental policy and conservation practice? We discuss key lessons coming from studies into the dual process theory of thinking and the presence of cognitive biases, social norms and intrinsic motivations. We then discuss the empirical findings by reviewing relevant research published over the past five years, and identify emerging lessons. Recent studies focus on providing feedback, manipulating framing, using green nudges, or activating social norms on urban contexts, mainly energy and water. Interventions are needed in the context of common pool resources in the global south. We end by discussing the great potential for scaling-up programs and interventions, but there are still challenges for research and practice….(More)”

Big data for economic statistics


Stats Brief by ESCAP: “This Stats Brief gives an overview of big data sources that can be used to produce economic statistics and presents country examples of the use of online price data, scanner data, mobile phone data, Earth Observations, financial transactions data and smart meter data to produce price indices, tourism statistics, poverty estimates, experimental economic statistics during COVID-19 and to monitor public sentiment. The Brief is part of ESCAP’s series on the use of non-traditional data sources for official statistics….(More)”.