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Rewards and risks in humanitarian AI: an example

New technologies, such as artificial intelligence and machine learning, can make humanitarian work better, faster and more effective, but there are dangers too, which is why the ICRC is proceeding with caution. Various departments across the ICRC – among them Digital Transformation & Data, Protection, Information and Communication Technology, Law and Policy – are grappling with these innovations and their implications in different ways. In this article, ICRC looks at one example.

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Data for Development: An Evaluation of World Bank Support for Data and Statistical Capacity (IEG, 2018)

This evaluation asks, “How effectively has the World Bank supported the production, sharing, and use of development data?” It reviews World Bank support for developing countries’ capacity and data systems, data for the national and global public good, engagements in international
partnerships, and technological innovations, particularly relating to big data. The World Bank supports data production, sharing, and use through lending, technical assistance, and trust fund grants. This evaluation covers all three forms of support, though not in equal depth. (Appendix A
describes IEG’s methodology for this evaluation.) The reference period is from 2004 (since the launch of the Marrakech Action Plan for Statistics) through the end of 2016, a period in which the World Bank’s approach to data support underwent change (World Bank 2011).

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Choosing and engaging with citizen-generated data: A guide (Global Partnership for Sustainable Development Data, 2018)

This guide is designed for governments, international organizations, and others interested in developing, engaging with and supporting CGD initiatives. It presents a list of distinction criteria between CGD methods, highlights the benefits and pitfalls of CGD, and provides a basis for strategic engagement with CGD. The guide draws from an analytical framework presented in the report Advancing sustainability together? Citizen-generated data and the Sustainable Development Goals. The analytical framework revolves around three aspects: workflows to generate data; participation; and data’s fitness for purpose. The report illustrates these nuances through several case studies and a discussion of how CGD can support implementation and monitoring of the SDGs.

Each section of the guide is accompanied by CGD examples. The guide summarizes experiences from extensive research, and draws inspiration from existing toolkits to recommend civic technologies, as well as the many existing toolkits for participatory mapping, citizen sensing, citizen science and other data-related activities. You can find a list of the tools that inspired us at the end.

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Big Data for Social Good Toolkit (GSMA, 2018)

Backed by 20 operators accounting for over two billion connections in over 100 countries, the GSMA’s Big Data for Social Good initiative is developing a consistent approach and processes mobile operators can use to share insights with public agencies and NGOs, while building an ecosystem to support timely planning and response.

The Big Data for Social Good online toolkit, is a comprehensive guide to the key components needed to implement mobile data-driven solutions. It has been designed so that it may read from start to finish or with direct access to the subjects of particular interest. There are a number of ways to navigate the toolkit, based upon interest area within the Big Data for Social Good topic.

Click here to access the full toolkit.

Information and Communications for Development 2018 : Data-Driven Development (World Bank report, 2018)

The Information and Communications for Development report takes an in-depth look at how information and communication technologies (ICT) are impacting economic growth in developing countries. This new report, the fourth in the series, examines the topic of data-driven development, or how better information makes for better policies. The objective is to assist developing country firms and governments to unlock the value of the data they hold for better service delivery and decision making, and to empower individuals to take more control of their personal data. The chapters of the report explore different themes associated with the supply of data, the technology underlying it, and the demand for it. The concluding chapter considers government policies for data, including data protection and privacy.

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