United Nations Global Pulse (UN Global Pulse)

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UN Global Pulse works through a network of labs to accelerate the discovery, development, and responsible use of big data and artificial intelligence innovations and policies for sustainable development, humanitarian action, and peace.

Description of Activities on AI

Project 1: Using machine learning to tackle the spread of COVID-19

Since March last year, many works have been published/proposed which attempt to use AI to tackle the COVID-19 pandemic. Last year UN Global Pulse worked with researchers from the World Health Organization (WHO) and the MILA- Quebec AI Institute to map the landscape of such AI applications. The research focused on three specific areas: individual patent diagnosis and treatment, protein and drug discovery related research, and the socio-economic impact of the disease. This work also explains main challenges and opportunities for AI cooperation against COVID-19. We have since continued to catalogue ongoing research and elaborate on lessons learned, pitfalls and ways forward as a community to use AI to effectively and safely tackly current and future public health crises.

Project 2: Operational response simulation tool for epidemics in refugee and IDP settlements

The spread of infectious diseases presents many challenges to healthcare systems and infrastructures across the world. Given their density and available infrastructure, refugee and internally displaced person (IDP) settlements can be particularly susceptible to the dangers of disease spread.

We seek to understand how COVID-19 spreads in settlements. We initially focussed our efforts on the Cox’s Bazar settlement in Bangladesh, and have since begun modeling other settlements around the world. Our model simulates the movements and interactions of each individual in the settlement, incorporating information about family structures and demographic attributes, to understand how COVID-19 might spread under various intervention strategies.

With almost 80 million forcibly displaced people in the world, we hope that this work will inspire more modeling groups to focus on these vulnerable populations, which have been traditionally under-served by such efforts, to ensure no one is left behind.

Project 3: Using Social Media Tools to Monitor and Fight the COVID-19 Infodemic

This project consists of two core components. First, in partnership with the WHO we have been conducting ongoing social media listening exercises in the Africa region. The data is explored and analyzed with the help of a third-party platform but we have developed a custom classifier to categorize mentions as positive or negative from the perspective of the WHO. UN Global Pulse has produced over 40 reports to assist WHO AFRO in monitoring its brand and understanding the conversations associated with COVID-19 and poliovirus.

Second, in a research collaboration with the WHO and Stanford University we are planning to test interventions to reduce vaccine hesitancy among social media users. Machine learning will be used to segment users into different vaccine hesitancy types, and a contextual bandits experiment will be used to dynamically assign treatments to reduce vaccine hesitancy according to the user type.

Project 4: A computational framework for predictive modeling of refugee and IDP movements

Predicting forced displacement is an important undertaking of many humanitarian aid agencies, which must anticipate flows in advance in order to provide vulnerable refugees and Internally Displaced Persons (IDPs) with shelter, food, and medical care. While there is a growing interest in using machine learning to better anticipate future arrivals, there is little standardized knowledge on how to predict refugee and IDP flows in practice. Researchers and humanitarian officers are confronted with the need to make decisions about how to structure their datasets and how to fit their problem to predictive analytics approaches, and they must choose from a variety of modeling options. In an academic paper and an accompanying set of practitioner-focused “modeling cards”, we attempt to facilitate a more comprehensive understanding of this emerging field of research by providing a systematic model-agnostic framework, adapted to the use of big data sources, for structuring the prediction problem.

Project 5: PulseSatellite: A collaboration tool using human-AI interaction to analyse satellite imagery

Humanitarian response to natural disasters and conflicts can be assisted by satellite image analysis. In a humanitarian context, very specific satellite image analysis tasks must be done accurately and in a timely manner to provide operational support. PulseSatellite is a collaborative satellite image analysis tool which leverages neural network models that can be retrained on-the fly and adapted to specific humanitarian contexts and geographies. The tool grew out of a long standing collaboration with UNOSAT which began by building an AI model for counting structures in refugee and IDP settlements. This was then expanded to a web-based toolkit – PulseSatellite – that can be easily adapted to other remote sensing applications and which allows for the incorporation of models created by other users. Currently, we have three models loaded into the system – one that allows users to map structures in refugee settlements, a roof density detection model (e.g. for slum mapping), and a flood mapping application. PulseSatellite is now open for use by other UN agencies.

Project 6: Radio monitoring for public health social listening

Radio remains the most reliable and affordable medium of accessing and sharing information in most of the developing world. Indeed, studies have shown that radio remains more prevalent as a means of communication in many parts of the world than social media. Since 2019, UN Global Pulse has worked with the WHO to explore the use of data from radio talk shows to signal early warnings of health risks and health-related matters. We have developed a radio monitoring pipeline which can ‘listen’ to radio stations, transcribe the audio using machine learning speech-to-text models, and analyse the content using a series of NLP methods for display in a frontend dashboard. The dashboard is designed to be used by infodemic managers and decision makers to inform public health interventions and communication strategies.

Project 7: Imagining post-Covid-19 UN: foresight for organizational realignment and adaptation

Through its SG Lab Futures Initiative, UN Global Pulse fostered a strategic foresight exercise and dialogue to frame the role of the UN post-COVID-19 through scenarios and future visioning. The activity leveraged partnerships with two private sector entities to access AI tools as a backbone for foresight research, including scenario building to support the UN leadership access the futures and foresight capacity.

The purpose of the exercise is to systematically analyze the driving forces and future trends underpinned by the COVID-19 pandemic, synthesizing them into alternative futures scenarios. The scenarios provided a framework for discussing implications for the UN long-term, including country-level operations.

Project 8: Understanding population movement related to COVID-19 border closures

UN Global Pulse and UNHCR are working to calculate and anticipate the number of displaced persons a) that have already crossed the Brazil-Venezuela border and b) that can potentially cross in order to understand their need for humanitarian support and overall strengthen protection efforts, particularly once COVID-19-related border restrictions are lifted. This project consists of: (i) a queue modeling tool for simulating border crossings under different conditions, (ii) a nowcasting effort to calculate the amount of urban population and potentially identify interest in population movements to Brazil using big data sources, and (iii) predictive models for forecasting future arrivals/population movements.

Related Sustainable Development Goals (SDGs)

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