Gabriel Pestre, Emmanuel Letouzé & Emilio Zagheni
CDRs (Call Detail Records) represent an important and largely untapped source of data for the developing world. However, they are not representative of the underlying population. We combine CDRs and census data for Senegal in 2013 to evaluate biases related to estimates of population density. We show that: (i) there are systematic relationships between cell-phone use and socio-economic and geographic characteristics that can be leveraged to improve estimates of population density; (ii) when no ‘ground truth’ data is available, a difference-in-difference approach can be used to reduce bias and infer relative changes over time in population size; (iii) indicators of development can be monitored by integrating census data and CDRs.
How data are shared and used will determine, to a large extent, the future of democracy and human progress. In this context, the authors of the paper “Sharing is Caring” describe four key requirements that must inform European efforts to ensure that private data are shared and used for the public good in a safe, ethical, and sustainable manner. This paper is part of the “Digitising Europe” initiative and part of a series of discussion papers that are focussed on the challenges of European digital policy.
Members of Data-Pop contributed to this report including Emma Samman, Emanuel Letouzé and Nuria Oliver
This report presents findings from an in-depth study of women’s engagement in the gig economy in Kenya and South Africa, two middle-income countries at the forefront of developments in digitally mediated work in sub-Saharan Africa. It aims to understand the impact of this engagement on workers’ lives, considering the quality of work on offer and its implications for workers’ management of paid work and unpaid care and domestic work.
Documento 3: Emmanuel Letouzé, Alex Pentland, Isabella Loaiza, Julie Ricard, Andrés Clavijo, Nicolas de Ligny, Daniel Rodríguez, Orlando Saavedra, Luisa García y Mónica Moreno
Documento 4: Emmanuel Letouzé, Alex Pentland, Isabella Loaiza, Julie Ricard, Andrés Clavijo, Diego Silva
Vanessa Higgins, Valentina Casabuenas, Julie Ricard and Jackie Carter. This scoping phase is funded by the University of Manchester through GCRF (Global Challenges Research Funding)
EmpoderaData builds upon the success of the Q-Step paid internship programme from the University of Manchester. The project aims to promote a virtuous cycle of social transformation by fostering data literacy. The purpose of this report is threefold: (1) understand the unmet needs in terms of data literacy skills, (2) recognize to what extent might a data literacy capacity building model can be helpful to develop these skills and last to dig up (3) in the current state regarding data availability for monitoring and evaluation of the SDGs in the three countries.
"Big Data para o bem comum"
Julie Ricard, Silvia Rodrigues Follador
Desde o início do século XX, a maioria de nossas ações e interações tem sido mediada e capturada por dispositivos eletrônicos. Os rastros de dados deixados pelo caminho resultam no que foi batizado de big data. Embora a exploração do big data tenha sido desenvolvida por gigantes da internet, que transformaram a mineração dessas migalhas digitais em uma de suas principais fontes de lucro, o interesse em entender como novas fontes de dados e tecnologias podem ser empregadas na formulação de políticas públicas e no desenvolvimento sustentável tem aumentado de maneira significativa.
"Harnessing Innovative Data and Technology to Measure Development Effectiveness"
Emmanuel Letouzé, Micol Stock, Francesca De Chiara, Alberto Lizzi and Carlos Mazariegos
In this study, the authors discuss and show how new kinds of digital data and analytics methods and tools falling under the umbrella term of Big Data, including Artificial Intelligence (AI) systems, can help measure development effectiveness. Selected case studies provide examples of assessments of the effectiveness of ODA-funded policies and programmes.
"Evaluación de nuevas herramientas y técnicas del big data para proyectos del Banco Interamericano de Desarrollo"
Emmanuel Letouzé & Nicolás de Ligny Tandefelt
Emmanuel Letouzé and Alex ‘Sandy’ Pentland, published by ITU Journal
This paper discusses the possibility of applying the key principles and tools of current artificial intelligence (AI) to design future human systems in ways that could make them more efficient, fair, responsive, and inclusive.
Yves-Alexandre de Montjoye, Sébastien Gambs , Vincent Blondel, Geoffrey Canright, Nicolas de Cordes, Sébastien Deletaille, Kenth Engø-Monsen, Manuel Garcia-Herranz, Jake Kendall, Cameron Kerry, Gautier Krings, Emmanuel Letouzé, Miguel Luengo-Oroz, Nuria Oliver, Luc Rocher, Alex Rutherford, Zbigniew Smoreda, Jessica Steele, Erik Wetter, Alex ‘Sandy’ Pentland & Linus Bengtsson
The breadcrumbs we leave behind when using our mobile phones—who somebody calls, for how long, and from where—contain unprecedented insights about us and our societies. Researchers have compared the recent availability of large-scale behavioral datasets, such as the ones generated by mobile phones, to the invention of the microscope, giving rise to the new field of computational social science.
Big Data & SDGs note for Global Sustainable Development Report
This paper focuses on the intersection of Big Data and Sustainable Development Goals (SDGs) and the spectrum of ways and channels through which Big Data as an entirely new ecosystem could impact—contribute to or hamper—human progress as called for and measured by the SDGs. Applications of Big Data to SDGs have the potential to advocate for causes, shape incentives and inform policies This paper argues that BIg Data contributions to the SDGs should expand beyond monitoring–Big Data must contribute directly to SDGs, which will require a data-educated citizenry.
AFD Paper - "CDRs & Poverty and Population Analysis – Côte d’Ivoire and Senegal"
This paper considers Big Data’s potential to partly fill some key data gaps and complement or even replace official statistics. Data-Pop Alliance offers the specific case of Côte d’Ivoire, using Call Records (CDRs) from Orange in conjunction with two other datasets, the WorldPop dataset, which provides population data derived from satellite imagery, and the recently released 2013 Demographic and Health Survey (DHS). The paper intends to predict multidimensional poverty at the sous-prefecture and sub-national levels; and to predict the population of the 11 sub-national regions of Côte d’Ivoire and its 255 sous-prefectures (sub-districts).
“Big Data and Mobility: Migration and Transportation”
This paper (in progress) discusses the linkages between Big Data and mobility—specifically migration and transportation. Its main objective is to give its readers—World Bank staff, policymakers, researchers, development project managers and other professionals—an overview of the main features and parameters of this nexus, as well as provide examples and discuss key considerations—technical, ethical, institutional, etc.—for developing projects, programs and other activities in the field.