Building a Responsible Humanitarian Approach: The ICRC’s policy on Artificial Intelligence

Curated on Posted on by Stefaan Verhulst

Policy by the ICRC: “…is anchored in a purely humanitarian approach driven by our mandate and Fundamental Principles. It is meant to help ICRC staff learn about AI and safely explore its humanitarian potential.

This policy is the result of a collaborative and multidisciplinary approach that leveraged the ICRC’s humanitarian and operational expertise, existing international AI standards, and the guidance and feedback of external experts.

Given the constantly evolving nature of AI, this document cannot possibly address all the questions and challenges that will arise in the future, but we hope that it provides a solid basis and framework to ensure we take a responsible and human-centred approach when using AI in support of our mission, in line with our 2024–2027 Institutional Strategy…(More)”.

Building a Policy Compass: Navigating Future Migration with Anticipatory Methods

Curated on Posted on by Stefaan Verhulst

Report by Sara Marcucci and Stefaan Verhulst: “Migration is a complex, dynamic issue, shaped by interconnected drivers like climate change, political shifts, and economic instability. Traditional migration policies often fall short, reacting to events after they unfold. In a rapidly changing world, anticipating migration trends is essential for developing responsive, proactive, and informed policies that address emerging challenges before they escalate. “Building a Policy Compass: Navigating Future Migration with Anticipatory Methods” introduces a suite of methods that aim to shift migration policy toward evidence-based, forward-looking decisions. This report, published for the Big Data for Migration Alliance, provides an overview of the challenges and criteria to consider when selecting and using anticipatory methods for migration policy.

To guide policymakers, the report organizes these methods into a taxonomy based on three categories:

  • Experience-Based Methods: These capture lived experiences through approaches like narrative interviews and participatory action research. They ground migration policy in the perspectives of those directly affected by it.
  • Expertise-Based Methods: Using specialized knowledge from migration experts, methods such as expert panels or Delphi processes can inform nuanced policy decisions.
  • Exploration-Based Methods: These methods, including scenario planning and wildcards analysis, encourage creative, out-of-the-box thinking for addressing unexpected migration challenges.

The report emphasizes that not every method is suited to all migration contexts and offers eight criteria to guide method selection…(More)”.

Privacy guarantees for personal mobility data in humanitarian response

Curated on Posted on by Stefaan Verhulst

Paper by Nitin Kohli, Emily Aiken & Joshua E. Blumenstock: “Personal mobility data from mobile phones and other sensors are increasingly used to inform policymaking during pandemics, natural disasters, and other humanitarian crises. However, even aggregated mobility traces can reveal private information about individual movements to potentially malicious actors. This paper develops and tests an approach for releasing private mobility data, which provides formal guarantees over the privacy of the underlying subjects. Specifically, we (1) introduce an algorithm for constructing differentially private mobility matrices and derive privacy and accuracy bounds on this algorithm; (2) use real-world data from mobile phone operators in Afghanistan and Rwanda to show how this algorithm can enable the use of private mobility data in two high-stakes policy decisions: pandemic response and the distribution of humanitarian aid; and (3) discuss practical decisions that need to be made when implementing this approach, such as how to optimally balance privacy and accuracy. Taken together, these results can help enable the responsible use of private mobility data in humanitarian response…(More)”.

Access, Signal, Action: Data Stewardship Lessons from Valencia’s Floods

Curated on Posted on by Stefaan Verhulst

Article by Marta Poblet, Stefaan Verhulst, and Anna Colom: “Valencia has a rich history in water management, a legacy shaped by both triumphs and tragedies. This connection to water is embedded in the city’s identity, yet modern floods test its resilience in new ways.

During the recent floods, Valencians experienced a troubling paradox. In today’s connected world, digital information flows through traditional and social media, weather apps, and government alert systems designed to warn us of danger and guide rapid responses. Despite this abundance of data, a tragedy unfolded last month in Valencia. This raises a crucial question: how can we ensure access to the right data, filter it for critical signals, and transform those signals into timely, effective action?

Data stewardship becomes essential in this process.

In particular, the devastating floods in Valencia underscore the importance of:

  • having access to data to strengthen the signal (first mile challenges)
  • separating signal from noise
  • translating signal into action (last mile challenges)…(More)”.

Proactive Mapping to Manage Disaster

Curated on Posted on by Stefaan Verhulst

Article by Andrew Mambondiyani: “..In March 2019, Cyclone Idai ravaged Zimbabwe, killing hundreds of people and leaving a trail of destruction. The Global INFORM Risk Index data shows that Zimbabwe is highly vulnerable to extreme climate-related events like floods, cyclones, and droughts, which in turn destroy infrastructure, displace people, and result in loss of lives and livelihoods.

Severe weather events like Idai have exposed the shortcomings of Zimbabwe’s traditional disaster-management system, which was devised to respond to environmental disasters by providing relief and rehabilitation of infrastructure and communities. After Idai, a team of climate-change researchers from three Zimbabwean universities and the local NGO DanChurchAid (DCA) concluded that the nation must adopt a more proactive approach by establishing an early-warning system to better prepare for and thereby prevent significant damage and death from such disasters.

In response to these findings, the Open Mapping Hub—Eastern and Southern Africa (ESA Hub)—launched a program in 2022 to develop an anticipatory-response approach in Zimbabwe. The ESA Hub is a regional NGO based in Kenya created by the Humanitarian OpenStreetMap Team (HOT), an international nonprofit that uses open-mapping technology to reduce environmental disaster risk. One of HOT’s four global hubs and its first in Africa, the ESA Hub was created in 2021 to facilitate the aggregation, utilization, and dissemination of high-quality open-mapping data across 23 countries in Eastern and Southern Africa. Open-source expert Monica Nthiga leads the hub’s team of 13 experts in mapping, open data, and digital content. The team collaborates with community-based organizations, humanitarian organizations, governments, and UN agencies to meet their specific mapping needs to best anticipate future climate-related disasters.

“The ESA Hub’s [anticipatory-response] project demonstrates how preemptive mapping can enhance disaster preparedness and resilience planning,” says Wilson Munyaradzi, disaster-services manager at the ESA Hub.

Open-mapping tools and workflows enable the hub to collect geospatial data to be stored, edited, and reviewed for quality assurance prior to being shared with its partners. “Geospatial data has the potential to identify key features of the landscape that can help plan and prepare before disasters occur so that mitigation methods are put in place to protect lives and livelihoods,” Munyaradzi says…(More)”.

Emerging technologies in the humanitarian sector

Curated on Posted on by Stefaan Verhulst

Report and project by Rand: “Emerging technologies have often been explored in the humanitarian sector through small scale pilot projects, testing their application in a specific context with limited opportunities to replicate the testing across various contexts. The level of familiarity and knowledge of technological development varies across the specific types of humanitarian activities undertaken and technology areas considered.

The study team identified five promising technology areas for the humanitarian sector that could be further explored out to 2030:

  • Advanced manufacturing systems are likely to offer humanitarians opportunities to produce resources and tools in an operating environment characterised by scarcity, the rise of simultaneous crises, and exposure to more intense and severe climate events.
  • Early Warning Systems are likely to support preparedness and response efforts across the humanitarian sector while multifactorial crises are likely to arise.
  • Camp monitoring systems are likely to support efforts not only to address security risks, but also support planning and management activities of sites or the health and wellbeing of displaced populations.
  • Coordination platforms are likely to enhance data collection and information-sharing across various humanitarian stakeholders for the development of timely and bespoke crisis response.
  • Privacy-enhancing technologies (PETs) can support ongoing efforts to comply with increased data privacy and data protection requirements in a humanitarian operating environment in which data collection will remain necessary.

Beyond these five technology areas, the study team also considered three innovation journey opportunities:

  • The establishment of a technology horizon scanning coalition
  • Visioning for emerging technologies in crisis recovery
  • An emerging technology narrative initiative.

To accompany the deployment of specific technologies in the humanitarian sector, the study team also developed a four-step approach aimed to identify specific guidance needs for end-users and humanitarian practitioners…(More)”.

The Power of Volunteers: Remote Mapping Gaza and Strategies in Conflict Areas

Curated on Posted on by Stefaan Verhulst

Blog by Jessica Pechmann: “…In Gaza, increased conflict since October 2023 has caused a prolonged humanitarian crisis. Understanding the impact of the conflict on buildings has been challenging, since pre-existing datasets from artificial intelligence and machine learning (AI/ML) models and OSM were not accurate enough to create a full building footprint baseline. The area’s buildings were too dense, and information on the ground was impossible to collect safely. In these hard-to-reach areas, HOT’s remote and crowdsourced mapping methodology was a good fit for collecting detailed information visible on aerial imagery.

In February 2024, after consultation with humanitarian and UN actors working in Gaza, HOT decided to create a pre-conflict dataset of all building footprints in the area in OSM. HOT’s community of OpenStreetMap volunteers did all the data work, coordinating through HOT’s Tasking Manager. The volunteers made meticulous edits to add missing data and to improve existing data. Due to protection and data quality concerns, only expert volunteer teams were assigned to map and validate the area. As in other areas that are hard to reach due to conflict, HOT balanced the data needs with responsible data practices based on the context.

Comparing AI/ML with human-verified OSM building datasets in conflict zones

AI/ML is becoming an increasingly common and quick way to obtain building footprints across large areas. Sources for automated building footprints range from worldwide datasets by Microsoft or Google to smaller-scale open community-managed tools such as HOT’s new application, fAIr.

Now that HOT volunteers have completely updated and validated all OSM buildings in visible imagery pre-conflict, OSM has 18% more individual buildings in the Gaza strip than Microsoft’s ML buildings dataset (estimated 330,079 buildings vs 280,112 buildings). However, in contexts where there has not been a coordinated update effort in OSM, the numbers may differ. For example, in Sudan where there has not been a large organized editing campaign, there are just under 1,500,000 in OSM, compared to over 5,820,000 buildings in Microsoft’s ML data. It is important to note that the ML datasets have not been human-verified and their accuracy is not known. Google Open Buildings has over 26 million building features in Sudan, but on visual inspection, many of these features are noise in the data that the model incorrectly identified as buildings in the uninhabited desert…(More)”.

Collaborating with Journalists and AI: Leveraging Social Media Images for Enhanced Disaster Resilience and Recovery

Curated on Posted on by Stefaan Verhulst

Paper by Murthy Dhiraj et al: “Methods to meaningfully integrate journalists into crisis informatics remain lacking. We explored the feasibility of generating a real-time, priority-driven map of infrastructure damage during a natural disaster by strategically selecting journalist networks to identify sources of image-based infrastructure-damage data. Using the REST Twitter API, 1,000,522 tweets were collected from September 13-18, 2018, during and after Hurricane Florence made landfall in the United States. Tweets were classified by source (e.g., news organizations or citizen journalists), and 11,638 images were extracted. We utilized Google’s AutoML Vision software to successfully develop a machine learning image classification model to interpret this sample of images. As a result, 80% of our labeled data was used for training, 10% for validation, and 10% for testing. The model achieved an average precision of 90.6%, an average recall of 77.2%, and an F1 score of .834. In the future, establishing strategic networks of journalists ahead of disasters will reduce the time needed to identify disaster-response targets, thereby focusing relief and recovery efforts in real-time. This approach ultimately aims to save lives and mitigate harm…(More)”.

This free app is the experts’ choice for wildfire information

Curated on Posted on by Stefaan Verhulst

Article by Shira Ovide: “One of the most trusted sources of information about wildfires is an app that’s mostly run by volunteers and on a shoestring budget.

It’s called Watch Duty, and it started in 2021 as a passion project of a Silicon Valley start-up founder, John Mills. He moved to a wildfire-prone area in Northern California and felt terrified by how difficult it was to find reliable information about fire dangers.

One expert after another said Watch Duty is their go-to resource for information, including maps of wildfires, the activities of firefighting crews, air-quality alerts and official evacuation orders…

More than a decade ago, Mills started a software company that helped chain restaurants with tasks such as food safety checklists. In 2019, Mills bought property north of San Francisco that he expected to be a future home. He stayed there when the pandemic hit in 2020.

During wildfires that year, Mills said he didn’t have enough information about what was happening and what to do. He found himself glued to social media posts from hobbyists who compiled wildfire information from public safety communications that are streamed online.

Mills said the idea for Watch Duty came from his experiences, his discussions with community groups and local officials — and watching an emergency services center struggle with clunky software for dispatching help.

He put in $1 million of his money to start Watch Duty and persuaded people he knew in Silicon Valley to help him write the app’s computer code. Mills also recruited some of the people who had built social media followings for their wildfire posts.

In the first week that Watch Duty was available in three California counties, Mills said, the app had tens of thousands of users. In the past month, he said, Watch Duty has hadroughly 1.1 million users.

Watch Duty is a nonprofit. Members who pay $25 a year have access to extra features such as flight tracking for firefighting aircraft.

Mills wants to expand Watch Duty to cover other types of natural disasters. “I can’t think of anything better I can do with my life than this,” he said…(More)”.