AI and Statistics for the SDGs

Data Literacy, Official Statistics, and Big Data for Measurements that Matter

Why AI and Statistics for the SDGs

Though inundated by oceans of data and surrounded by innovative, powerful technologies that hold great promise to help us accomplish and measure the Sustainable Development Goals, the access to and mastery of these resources are highly constrained and unequalboth across and within countries in ways that reflect and reinforce the weakening of global democratic principles and processes. DPA believes that equitable access to these resources is imperative to ensuring the best future. Under this Program, we equip individuals and organizations with data skills, systems, and standards to navigate the ‘age of data’ and develop measurement methodologies for policy and the SDGs.

“90% of business leaders cite data literacy as key to company success, but only 25% of workers feel confident in their data skills. Not only that, but some estimates suggest that nearly 9 in 10 data science professionals are White, and just 18% are women.” (HBR, 2021).

Methods

DPA leverages the following methods to implement projects under this program: In-person and online courses, advanced data modeling, and AI-based analysis for measuring the unmeasured

Products

Product 1

Tailored Data Trainings

Product 2

SDGs Assessments and Measurement

Product 3

OPAL for Public Data and Good

Product 4

Human AI Research

OPAL

OPAL

Tailored Data Trainings

Professional Training Program “Leveraging Big Data for Sustainable Development”

Carried on in partnership with United Nations System Staff College (UNSSC), this series of courses aimed to help practitioners and policy-makers to develop and implement Big Data innovation projects, policies, and partnerships in support of sustainable development objectives. The content was structured into three main modules: contexts and concepts; methods and tools; and strategy and conception / ethics and engagement. The workshops were delivered in Cambridge at MIT (June 2016), Bogotá (December 2016), Nairobi (June 2017), Dakar (March 2018), Bangkok (March 2018), and the MIT Media Lab (October 2018). The same workshop was also conducted in Tunisia (April 2019) with support from UN Tunisie.

Professional Training Program “Big Data for Measuring the Digital Economy”

In partnership with the United Nations Economic Commission for Latin America and the Caribbean (ECLAC), DPA offered a series of workshops particularly focused on Big Data and the Digital Economy in the Latin American and the Caribbean region designed for development practitioners, policymakers, and researchers. Five editions were delivered in: Santiago de Chile (March 2016), São Paulo (September 2017) —in partnership with Cetic.br—, Mexico City (October 2017) —in collaboration with the National Digital Strategy (EDN) program and the MIT Sloan School of Management—, Santo Domingo (April 2019), and Bogotá (May 2019) —in partnership with DANE.

Workshop “Big Data for Sustainable Development and Climate Change”

This series of workshops organized by Data-Pop Alliance, in coordination with GIZ and GIZ Colombia, addressed key terms, necessary tools and challenges in the Big Data and sustainable development landscape, focusing on the applicability of these information sources in projects related to climate change adaptation and mitigation. This in-person workshop provided an introduction to the “3 C’s of Big Data” as a basis for the development of a Project Lab, so that participants could introduce new sources of information in the development of climate change projects.

Workshop on Survey Methodology with CETIC & NIC

Data-Pop Alliance offered training in São Paulo with the Regional Center for Studies on the Development of the Information Society (CETIC) and the Brazilian Network Information Center (NIC) annually from 2016 through 2019. The 2019 edition included a session by DPA Director and Co-Founder Emmanuel Letouzé titled “Data for Public Statistics: Data Science, Big Data & Artificial Intelligence”, click below to explore it.

Workshop “Using Machine Learning with Satellite Imagery for the Measurement of a Sustainable Development Goal Indicator”

This two-day online workshop with government officials from the National Institute of Statistics and Informatics (INEI) in Peru and other public agencies sought to strengthen institutional capacities for the improvement of the national statistical system, particularly by leveraging non-traditional sources of data in administrative reports to measure different indicators of the Sustainable Development Goals (SDGs) towards the achievement of the 2030 Agenda.

EmpoderaData

EmpoderaData builds upon the success of the “Quantitative Step” (Q-Step) program, which was developed as a strategic response to the shortage of quantitatively-skilled social science graduates in the United Kingdom. Together, University of Manchester and Data-Pop Alliance expanded upon the program’s excellent results, exploring this model in the Global South as the “EmpoderaData Project”. The project aimed to promote a virtuous cycle of social transformation by fostering data literacy skills applied to addressing our society’s most pressing issues in the framework of the Sustainable Development Goals (SDGs).

Workshop “Web Data Collection and Analysis”

In November 2019, Data-Pop Alliance, in partnership with ECLAC and IBGE, conducted its first technical workshop in Rio de Janeiro, tailored specifically to the needs of the staff at the Brazilian National Statistical Office (IBGE). The goal was to help them to build and strengthen internal capacities to leverage web data collection and analysis in their projects. ​The workshop emerged as part of the broader training program carried out with ECLAC in the Latin America and Caribbean region: “Big Data for Measuring the Digital Economy”.

Capacity-Building Workshop on the Analysis and Application of Quantitative and Qualitative Data

DPA developed a four week training on qualitative and quantitative analysis and tools for the members of non-profit organization EQUIS Justicia para las Mujeres. It included various sessions, with online and in-person guided tutorials conducted by DPA facilitators, during which examples were provided through use cases based on real projects, in addition to demonstrating different techniques and tools for data analysis. The content of this training was divided into two workshops: the first focused on practical techniques and tutorials on data collection, storage and processing; the second centered on how to incorporate basic notions of statistics, database reading and use of visualizations.

Strengthening of Technical Capacities and a Regional Exploratory Study of Big Data for Sustainable Development in Latin America and the Caribbean (LAC)

This project, developed with the support of the Spanish Agency for International Development Cooperation (AECID), aims to strengthen the technical capacities of government officials in LAC to leverage Big Data for sustainable development and official statistics. During the project’s first phase, the project sought to explain the panorama of Big Data and sustainable development in LAC, focusing on the applicability of sources to obtain statistical information related to issues such as poverty reduction, migration, and climate change. The training phase, based on the report stemming from the first phase, consists of 4 workshops (Big Data for Sustainable Development, Big Data and Poverty, Big Data and Health, Big Data and Security) to be held throughout 2022 and early 2023. These will focus on the applicability of non-traditional and traditional data sources and the applications of different data analysis tools such as satellite imagery, movement range maps and surveys to analyze and create projects to achieve the SDGs.

SDGs Assessments and Measurement

Support to the Design of Tunisia’s National Strategy for Development of Statistics (NSDS)

DPA, in collaboration with the UN System in Tunisia, the National Statistical Council (NSC), the National Institute of Statistics (NIS), and under the implementation leadership of UNDP, assisted the NSC and the NIS in the development of the National Strategy for the Development of Statistics in the country. The general objectives of this consultancy focused primarily on (i) Identifying the strengths, weaknesses and needs of the Tunisian National Statistical System (NSS) through a comprehensive strategic review of the NSS; (ii) Developing a National Strategy for the Development of Statistics that facilitated the timely production of reliable statistics to contribute to informed public policy making aligned with the SDGs; and (iii) Developing a three-year action plan and a financing plan to effectively implement the NSDS.

Development of Equatorial Guinea’s First Voluntary National Review (VNR)

DPA, in collaboration with the UNDP Country Office in Equatorial Guinea, and the UN System, is assisting the Government of Equatorial Guinea in the development of the country’s first Voluntary National Review (VNR), which involves the assessment and presentation of the progress made towards the achievement of the SDGs, including the pledge to “Leave no one behind”. The purpose of the Review is to determine where Equatorial Guinea stands with regards to the implementation of the 2030 Agenda and how to accelerate its progress.

Assessing the Strategies to Achieve the Millennium Development Goals (MDGs) and the Sustainable Development Goals (SDGs) in Haiti

DPA, in support of Haiti’s Integrated National Financing Framework (CINF), and in close collaboration with the UNDP Haiti and the Ministry of Planning and External Cooperation (MPCE), has conducted a consultation with the objective of establishing a performance assessment of the achievement of the MDGs, deviations from targets, their justifications, and lessons learned. Additionally, the study measured the progress towards the achievement of the SDGs and proposed priority provisions and mechanisms for Haiti’s advancement towards them.

Harnessing Innovative Data and Technology to Measure Development Effectiveness

In partnership with Southern Voice, this research project aimed to develop a methodological framework for assessing development effectiveness and rebuild this discourse from the ground up, informed by Southern perspectives. The key objective of the study was to develop a methodological guide that makes use of new sources of data and techniques in assessing development effectiveness. The study provided an overview of possible sources of new and innovative data (primarily open access and public data) with reference to some case studies in the context of assessing development effectiveness; undertook a comparative review of scope for innovative data and techniques (including geospatial and Big Data) for assessing development effectiveness in developing countries; highlighted the advantages and disadvantages (limitations) of the available techniques and data and associated challenges and debates (including the issue of privacy); proposed a methodology (or a set of alternative methodologies) which may be applied at the country-level for measuring development effectiveness using innovative data and techniques; related the proposed methodology with inputs (instruments), processes and outputs (outcomes).

Measuring the Unmeasured: Innovative Approaches to Measuring SDG Tier III Indicators

In partnership with the United Nations Development Programme (UNDP), DPA provided support to the Europe and Central Asia Regional Hub in Istanbul in the project “Measuring the Unmeasured” to contribute to SDG measurement and achievement. The effective use of data for public policy is of critical importance to the UN in its efforts to strengthen evidence-based programming and policy development; in particular, generating, analyzing, presenting, and using data is vital to global and regional efforts to monitor and promote the Sustainable Development Goals (SDGs). Our project aims were: scoping, developing, and testing different methods for measuring Tier III indicators of high SDGs priorities for 11 countries in Arab States, Europe & Central Asia, and Asia Pacific; with the main goal of utilizing this information into policy responses.

OPAL for Public Data and Good

Open Algorithms (OPAL) for Public Data and Good

“Open Algorithm (OPAL) for Public Data and Good” seeks to merge different “privacy enhancing techniques” (PETs), such as federated learning, differential privacy, and negative databases, to allow trusted third parties such as researchers or official institutions to analyze censuses or national surveys’ microdata produced by national statistical offices (NSOs), as well as other administrative records, to derive indicators using these data, while avoiding privacy risks. A pilot is expected to be conducted in Mexico, and DPA plans to expand to additional NSOs and other public data holders in the future.

Human AI Research

Policy Paper “Sharing is Caring: Four Key Requirements for Sustainable Private Data Sharing and Use for Public Good”

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, co-published with the Vodafone Institute for Society and Communications, 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.

Position Paper “How to Use Big Data? Leading Experts’ Roadmap to Data-Driven Innovation Projects. Key Results from the Digitasing Europe Initiative”

This paper, developed in cooperation with the Vodafone Institute for Society and Communications, highlights overall takeaways and recommendations in the areas of privacy protection, responsible data governance, transparency and accountability for unleashing big data-driven innovation, including: (1) putting ‘privacy by design’ into action: privacy-preserving technical procedures and standards for data sharing and use; (2) focusing on responsibility in data use: establishing internal responsible data governance standards and (3) keeping transparency, trust, and user control at the center: engaging all data stakeholders.

Event Paper: “Big Data and Privacy: Understanding the Possibilities and Pitfalls of the Data Revolution in Germany”

How can we make full use of data analytics in a responsible and human-centered manner? Which forms of data use should be excluded, and who should set the rules? As the first event paper in the “Digitising Europe” series (published with the Vodafone Institute for Society and Communications), this publication captures the major key themes emerging from the initiative’s events in Berlin in November 2015, which explored the possibilities and pitfalls around the data revolution and served to identify key insights and practical solutions for facilitating the use of data while protecting the privacy of citizens.

White Paper “The Law, Politics and Ethics of Cell Phone Data Analytics”

This white paper, developed in partnership and with funding from The World Bank, examines Call Detail Records (CDRs) and their expanding role in providing insight into human behavior, movements, and social interaction. After providing additional contextual elements (Part 1), the paper summarizes current legal frameworks (Part 2), before exploring structural socio-political parameters and incentives structuring the sharing of CDRs (Part 3), proposing guiding ethical principles (Part 4) and discussing operational options and requirements (Part 5).

OPAL