Data Innovation

Our vision

We’re building a culture of innovation to ensure UNHCR can responsibly and creatively take advantage of big data analytics, AI, intelligent automation, and other exponential technologies to further our mandate.

Our approach

The industry of new information and communication technologies is rapidly advancing, but is still nascent in many areas, and not yet fully tested in society. The humanitarian sector faces a challenge of how to adopt nascent technologies while exploring how to use them to support the delivery of the UNHCR protection mandate in a way that complies with UN policies, human-rights based approaches, and humanitarian and ethical standards.

UNHCR’s Data Innovation programme is inspired and in support of creating evidence for the advancement of the UN Secretary General Digital Roadmap, the UN Secretary General Data Strategy 2020-2022 and the UNHCR Data Transformation Strategy 2020-2025.

This programme works to innovate, experiment and leverage data in new and creative ways to improve UNHCR’s work and the lives of the people it serves. Innovative solutions include ethics and human rights-based approaches, responsible data practices, evidence-based humanitarian decision making, and privacy-enhancing technologies that can shape the future of the humanitarian sector.

Data Innovation Fund

The Data Innovation Fund provides targeted financial and technical support to colleagues in UNHCR who are interested in exploring innovation methodologies in combination with data science and other non-traditional analysis techniques, or exploring emerging technologies to perform data analysis in more creative ways. 

Learn more about the Fund

The Data Innovation Roadmap

The Data Innovation Programme nurtures innovative, ethical approaches to data and emerging technology using the Data Innovation Roadmap. The Roadmap is a bespoke practical guide through the process of data innovation in humanitarian contexts, ensuring a rigorous engagement with data science, data engineering, and innovation methodologies.

Through both a visual map and a guiding document, it lays out the different stages that data innovation initiatives should go through – scoping, research and development, production, and scale – and the tools, methodologies, and deliverables required to advance from one stage to the next. You can explore the Roadmap here:

Download the Data Innovation Roadmap

Our past projects

The Innovation Service’s work on big data and artificial intelligence takes many forms, including support and services to UNHCR operations, training on bias ethics and a human-rights based approach, partnering with non-traditional actors to explore creative approaches, and holistic support to nurture pilots breaking new ground. Here’s a glimpse into some of this work:

Project Jetson

Project Jetson is a predictive analytics experiment to discover, understand, and measure the specific push and pull factors that cause, indicate or exacerbate the forced displacement.

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Division of Human Resources (DHR) “ARiN”

Project ARiN is a Human Resources-led project designed with the Innovation Service to improve the pre-screening process of applications collected in UNHCR’s Talent Pools.

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Automatic Refugee Law Classification in Ref World (Fund winner)

Refworld is a UNHCR repository that contains much of the legal documentation on humanitarian affairs and refugee law, and many use it for easier access to legal precedents and court decisions in advancing their legal research.

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Text analytics for online hate speech monitoring and protection

In 2016, the Innovation Service and UN Global Pulse used data from Twitter to monitor protection issues for the first time using artificial intelligence

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Call Detail Records (CDRs) Analysis: Turkey Case

This analysed anonymized CDRs provided by the telecom operator, Turk Telecom, to better understand refugee integration in Turkey.

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Lights at Night in Aleppo Syria

Using nighttime satellite imagery above Aleppo, this project was able to demonstrate how light can be used to monitor humanitarian crises in conflict that prevents access to an area by humanitarian actors.

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Epidemic Simulation Modelling of COVID-19 in refugee settlements

The simulation probabilistically determines what agents (refugees) do during the day.

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Qualminer: text analytics on ActivityInfo (Fund winner)

https://www.activityinfo.org/blog/posts/2019-06-18-qualminer-project-emergency-response-and-text-mining.htmlhttps://www.psu.edu/news/research/story/improving-qualitative-data-management-agencies-responding-refugee-crises/https://bedatadriven.github.io/QualMiner/index.html

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Stories 

The Innovation Service’s Data Innovation team uses narratives and stories to bring insight and learnings into its work, collaboration alongside colleagues and refugees and how the team imagines the future of data in the humanitarian sector. You can find our latest articles here.

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Research and publications

A collection of research, insights, and publications from at the crossroads of data innovation and humanitarian response to learn how UNHCR navigates challenges and is thinking about the role of data innovation in its work with refugee communities. 

White Paper: Social Media and Forced Displacement: Big Data Analytics & Machine-Learning.

This white paper summarizes the initial findings and lessons learned from a project conducted by UNHCR’s Innovation Service and UN Global Pulse to inform on the viability and value of social media analytics to complement understandings of the Europe Refugee Emergency.

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Operational response simulation tool for epidemics within refugee and IDP settlements

This paper explores the use of computer modeling to evaluate several public health interventions for COVID-19 in Cox’s Bazar refugee settlement in Bangladesh.

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Pioneering Predictive Analytics for Decision-Making in Forced Displacement Contexts

This chapter describes the work of UNHCR’s Innovation Service in data science research to improve the work of UNHCR in advocacy, emergency preparedness, and operational response.

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BD4M Practitioners' Guide on Harnessing Data Innovation for Migration Policy (IOM, book chapter) on Jetson Case Study

This paper describes important considerations and indicators that non-technical policy makers should consider prior to creating, developing and utilizing predictive analytics to inform anticipatory action on migration policy, using Project Jetson as a case study.

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Guide to Mobile Data Analytics in Refugee Scenarios, Chapter 8: Towards an Understanding of Refugee Segregation, Isolation, Homophily and Ultimately Integration in Turkey Using Call Detail Records

This chapter describes how segregation, isolation and homophily can be measured by deriving population estimates from call detail records (CDRs), and how the evolution of refugees’ communication patterns and mobility traces can provide initial insights into their social integration in Turkey.

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Explicability of Humanitarian AI: A Matter of Principles

This article opens with an overview of AI and Automated Decision-Making systems (ADMs) in the humanitarian sector, with special attention to the concept of algorithmic opacity. It explores the transformative potential of these systems on the complex power dynamics between humanitarians, principled assistance, and affected communities during acute crises.

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Technical guidance

Key technical resources to support UNHCR’s data and artificial intelligence work, from the practical “how-tos” to due diligence, technical guidance, and policy.

Data Transformation Strategy 2020-2025

This strategy lays out UNHCR’s vision of becoming a trusted leader on data and information related to refugees and other affected populations.

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Reflective practice in data innovation

The innovation methodology of reflective practice can support forward-thinking approaches to data in humanitarian contexts. The UNHCR Data Innovation Fund's first cohort came together to explore this methodology and to learn from one another in a webinar focused on three themes: co-design and stakeholder management; foresight and strategic planning; and values-based innovation.

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UNHCR Data Protection Policy (2015)

This strategy lays out the necessary requirements for UNHCR staff and partners to ensure the data protection of persons of concern.

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UNHCR Data Protection Policy, Guidelines (2018)

This guidance assists UNHCR personnel in the application and interpretation of the Policy on the Protection of Personal Data of Persons of Concern.

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USAID Managing ML Projects in International Development: A Practical Guide

The guide breaks down the process of developing a ML/AI model into four phases: evaluating feasibility of the use of ML/AI in a project context, designing and building a ML/AI model, implementing the model in practice, and post-implementation considerations.

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OCHA Predictive Analytics, Peer-Review Framework

The framework aims to support humanitarians making the best use of predictive models, highlighting the scope within which models can be applied and the main risks that their deployment entails.

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ICRC Handbook on Data Protection in Humanitarian Action

This handbook builds on existing guidelines, working procedures and practices that have been established in humanitarian action and portrays use-cases for enhancing data protection in humanitarian action.

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OHCHR Data Privacy Guidelines in the Context of Artificial Intelligence

These OHCHR Guidelines on “Data Privacy Guidelines for the development and operation of Artificial Intelligence solutions” seek to provide international guidance based on the values enshrined in the UN Charter on Human Rights and International Covenant on Civil and Political Rights.

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Policy Guidance on AI for Children

These UNICEF recommendations for building AI policies and systems that uphold children’s rights.

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Data Maturity Guidelines

This is an assessment tool for data maturity, to use prior and during the initial stages of a data-driven project.

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Additional resources

Further resources to inform UNHCR’s Data Innovation work.

ITU AI for Good Initiative - United Nations work on AI

This compendium provides further details on the experiments of UN agencies (members of the AI for Good UN Partners) to improve their response to global challenges.

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OHCHR Report on Artificial Intelligence technologies and implications for freedom of expression and the information environment

In this report, the Special Rapporteur examines the impact of AI on the information environment, and proposes a human rights framework for the design and use of AI technologies by states and private actors.

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UNESCO AI Initiative, Ethics of AI

This webpage hosts a variety of projects and ongoing initiatives within the UN system related to AI applications, as well as hosting resources,stories and ideas.

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DFID - Predictive analytics in humanitarian action: a preliminary mapping and analysis

This research maps and analyzes different predictive analytics projects and initiatives by humanitarians.

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Human Rights Impact Assessments for AI: Learning from Facebook’s Failure in Myanmar

This paper examines if Human Rights Impact Assessments, or HRIAs, are an appropriate and effective way of reducing harms resulting from AI. This paper uses the case study of the HRIA of Facebook in Myanmar, and the failures and challenges to appropriately capture and protect human rights.

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Toward a Critique of Algorithmic Violence

This paper examines how algorithmic systems feed into specific forms of violence and explores the instances and challenges that arise when studying and conceptualizing that violence.

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MIT AI Blindspots

The MIT guide on the discovery process for spotting unconscious biases and structural inequalities in AI systems in their planning, building and deployment phases.

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Narratives and Counternarratives on Data Sharing in Africa

This paper examines the narratives around data and data sharing in Africa, exploring the long-lasting impacts of colonialism, etho-centrism, slavery and Western-centered contemporary politics that result in power imbalances and policies that are ill-suited to African contexts.

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The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good

This paper examines both the positive opportunities and the potential negative consequences of social good decision-making algorithms that practitioners should be aware of and address in order to truly realize the potential of this emergent field.

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Believe in the Model: Mishandle the Emergency

This examines the ways in which computer models can lead practitioners to mishandle crises, as they put too much faith in models and do not see the link between inputs and outputs.

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Gender Bias in Artificial Intelligence: The Need for Diversity and Gender Theory in Machine Learning

This paper examines the growing concern around gender bias in AI, including how data has centuries worth of gender biases that impact training, output and outcome of applied AI.

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From Rationality to Relationality: Ubuntu as an Ethical & Human Rights Framework for Artificial Intelligence Governance

This paper examines the relational Sub-Saharan African philosophy of ubuntu, to show that the harms caused by AI, with a particular focus on automated decision making systems (ADMS), are in essence violations of ubuntu’s relational personhood and relational model of the universe.

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Continuous Delivery for Machine Learning

This article combines continuous delivery applications with the development, deployment and maintenance of projects using machine learning.

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Ethical funding for trustworthy AI: proposals to address the responsibilities of funders to ensure that projects adhere to trustworthy AI practice

This paper focuses on the funding processes for AI research grants which we have identified as a gap in the current range of ethical AI solutions, such as AI procurement guidelines, AI impact assessments and AI audit frameworks.

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FAQs

A list of some of our most frequently asked questions on the Innovation Service’s data and artificial intelligence work.

What is UNHCR Innovation Service’s Data Innovation work focused on?
Our work is focused on improving and innovating UNHCR’s capacity to collect, analyse and visualise data for strengthening its programme and protection-related work, aiming for the delivery of the UNHCR protection mandate in a way that complies with UN policies, human-rights based approaches, and humanitarian and ethical principles.
How is the Innovation Service’s work different from UNHCR’s Global Data Service (GDS) and/or the Joint World Bank-UNHCR Data Center (JDC)
Our role is to foster and mainstream data innovation within UNHCR with a responsible and human-rights based data approach and to help UNHCR achieve the data transformation strategy’s innovation-related work. The Innovation Service contributes to the UNHCR-WB Joint Data Centre in sharing research insights, particularly on predictive analytics and other big data/AI-research based projects.
Why are big data and artificial intelligence relevant to the UN Refugee Agency?
Part of UNHCR’s vision of becoming a trusted leader in data and information relating to refugees and affected populations requires understanding, co-designing, building, launching and maintaining projects that utilize either big data or AI. These technologies will be fundamental to an agile and innovative organisation that will be more prepared to anticipate and respond to the crises of tomorrow.
Does the Innovation Service collaborate with partners on big data and AI?
Yes, we have worked with many partners, such as academia, the nonprofit sector, collaborative platforms, governments, the private sector, other UN agencies and persons of concern. Our recent collaborations include:

How can we collaborate, engage or know more about this area of work?
Collaboration with the Innovation Service’s Data Innovation can take many forms, including research in data-related work, designing webinars and knowledge sharing, providing scoping for challenge identification, mainstreaming innovation methodologies in data-related work and strengthening a human-rights based approach to humanitarian innovation work.
What types of technologies have you worked with?
Everything and anything: we either build our own computer programme tools from open source repositories and packages, or we test commercial off-the-shelf tools and solutions. We are technology agnostic, and only use technology when it is appropriate and adapted to the humanitarian context and abides with data protection, data responsibility, ethics and human-rights based approaches. This entails a wide range of technologies, from radio to satellites, techniques, preliminary analysis and scenario building.
What are some options for qualitative data analysis or text analysis? What tools do you recommend?
In our projects section, the project “Text analytics for improved protection” describes some of the methodologies, techniques and other partners’ projects in relation to text analytics, including social media and other formats of text for humanitarian/displacement analysis. There are many different open source and off-the-shelf commercial tools that allow  exploration of the different research questions (what you want to obtain from the data) and methodologies and techniques (e.g. topics modelling, natural language processing, NLP) to be able to process and make sense out of it. We recommend getting familiar with the  following links for a brief introduction to text analysis, and to understand how to make sense out of your data, prior to recommending a specific tool: Link 1, Link 2, Link 3
What if I have other questions I need answered?
Please get in touch at innovation@unhcr.org with any questions or ideas.

Contact

Are you working on big data, artificial intelligence and other exponential technologies and displacement or related human-rights or ethics work, and you have interesting perspectives to share? Do you have questions or want to support our work? Get in touch at innovation@unhcr.org