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)”.

Tech Agnostic

Curated on Posted on by Stefaan Verhulst

Book by Greg Epstein: “…Today’s technology has overtaken religion as the chief influence on twenty-first century life and community. In Tech Agnostic, Harvard and MIT’s influential humanist chaplain Greg Epstein explores what it means to be a critical thinker with respect to this new faith. Encouraging readers to reassert their common humanity beyond the seductive sheen of “tech,” this book argues for tech agnosticism—not worship—as a way of life. Without suggesting we return to a mythical pre-tech past, Epstein shows why we must maintain a freethinking critical perspective toward innovation until it proves itself worthy of our faith or not.

Epstein asks probing questions that center humanity at the heart of engineering: Who profits from an uncritical faith in technology? How can we remedy technology’s problems while retaining its benefits? Showing how unbelief has always served humanity, Epstein revisits the historical apostates, skeptics, mystics, Cassandras, heretics, and whistleblowers who embody the tech reformation we desperately need. He argues that we must learn how to collectively demand that technology serve our pursuit of human lives that are deeply worth living…(More)”.

Key lesson of this year’s Nobel Prize: The importance of unlocking data responsibly to advance science and improve people’s lives

Curated on Posted on by Stefaan Verhulst

Article by Stefaan Verhulst, Anna Colom, and Marta Poblet: “This year’s Nobel Prize for Chemistry owes a lot to available, standardised, high quality data that can be reused to improve people’s lives. The winners, Prof David Baker from the University of Washington, and Demis Hassabis and John M. Jumper from Google DeepMind, were awarded respectively for the development and prediction of new proteins that can have important medical applications. These developments build on AI models that can predict protein structures in unprecedented ways. However, key to these models and their potential to unlock health discoveries is an open curated dataset with high quality and standardised data, something still rare despite the pace and scale of AI-driven development.

We live in a paradoxical time of both data abundance and data scarcity: a lot of data is being created and stored, but it tends to be inaccessible due to private interests and weak regulations. The challenge, then, is to prevent the misuse of data whilst avoiding its missed use.

The reuse of data remains limited in Europe, but a new set of regulations seeks to increase the possibilities of responsible data reuse. When the European Commission made the case for its European Data Strategy in 2020, it envisaged the European Union “a role model for a society empowered by data to make better decisions — in business and the public sector,” and acknowledged the need to improve “governance structures for handling data and to increase its pools of quality data available for use and reuse”…(More)”.

How Artificial Intelligence Can Support Peace

Curated on Posted on by Stefaan Verhulst

Essay by Adam Zable, Marine Ragnet, Roshni Singh, Hannah Chafetz, Andrew J. Zahuranec, and Stefaan G. Verhulst: “In what follows we provide a series of case studies of how AI can be used to promote peace, leveraging what we learned at the Kluz Prize for PeaceTech and NYU Prep and Becera events. These case studies and applications of AI are limited to what was included in these initiatives and are not fully comprehensive. With these examples of the role of technology before, during, and after a conflict, we hope to broaden the discussion around the potential positive uses of AI in the context of today’s global challenges.

Ai for Peace Blog GraphicThe table above summarizes the how AI may be harnessed throughout the conflict cycle and the supporting examples from the Kluz Prize for PeaceTech and NYU PREP and Becera events

(1) The Use of AI Before a Conflict

AI can support conflict prevention by predicting emerging tensions and supporting mediation efforts. In recent years, AI-driven early warning systems have been used to identify patterns that precede violence, allowing for timely interventions. 

For instance, The Violence & Impacts Early-Warning System (VIEWS), developed by a research consortium at Uppsala University in Sweden and the Peace Research Institute Oslo (PRIO) in Norway, employs AI and machine learning algorithms to analyze large datasets, including conflict history, political events, and socio-economic indicators—supporting negative peace and peacebuilding efforts. These algorithms are trained to recognize patterns that precede violent conflict, using both supervised and unsupervised learning methods to make predictions about the likelihood and severity of conflicts up to three years in advance. The system also uses predictive analytics to identify potential hotspots, where specific factors—such as spikes in political unrest or economic instability—suggest a higher risk of conflict…(More)”.

G7 Toolkit for Artificial Intelligence in the Public Sector

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OECD Toolkit: “…a comprehensive guide designed to help policymakers and public sector leaders translate principles for safe, secure, and trustworthy Artificial Intelligence (AI) into actionable policies. AI can help improve the efficiency of internal operations, the effectiveness of policymaking, the responsiveness of public services, and overall transparency and accountability. Recognising both the opportunities and risks posed by AI, this toolkit provides practical insights, shares good practices for the use of AI in and by the public sector, integrates ethical considerations, and provides an overview of G7 trends. It further showcases public sector AI use cases, detailing their benefits, as well as the implementation challenges faced by G7 members, together with the emerging policy responses to guide and coordinate the development, deployment, and use of AI in the public sector. The toolkit finally highlights key stages and factors characterising the journey of public sector AI solutions…(More)”.

The Age of AI Nationalism and Its Effects

Curated on Posted on by Stefaan Verhulst

Paper by Susan Ariel Aaronson: “Policy makers in many countries are determined to develop artificial intelligence (AI) within their borders because they view AI as essential to both national security and economic growth. Some countries have proposed adopting AI sovereignty, where the nation develops AI for its people, by its people and within its borders. In this paper, the author makes a distinction between policies designed to advance domestic AI and policies that, with or without direct intent, hamper the production or trade of foreign-produced AI (known as “AI nationalism”). AI nationalist policies in one country can make it harder for firms in another country to develop AI. If officials can limit access to key components of the AI supply chain, such as data, capital, expertise or computing power, they may be able to limit the AI prowess of competitors in country Y and/or Z. Moreover, if policy makers can shape regulations in ways that benefit local AI competitors, they may also impede the competitiveness of other nations’ AI developers. AI nationalism may seem appropriate given the import of AI, but this paper aims to illuminate how AI nationalistic policies may backfire and could divide the world into AI haves and have nots…(More)”.

Social Systems Evidence

Curated on Posted on by Stefaan Verhulst

About: “…a continuously updated repository of syntheses of research evidence about the programs, services and products available in a broad range of government sectors and program areas (e.g., climate action, community and social services, economic development and growth, education, environmental conservation, education, housing and transportation) as well as the governance, financial and delivery arrangements within which these programs, services and products are provided, and the implementation strategies that can help to ensure that these programs, services and products get to those who need them. 

The content covers the Sustainable Development Goals, with the exceptions of the health part of goal 3 (which is already well covered by existing databases).

The types of syntheses include evidence briefs for policy, overviews of evidence syntheses, evidence syntheses addressing questions about effectiveness, evidence syntheses addressing other types of questions, evidence syntheses in progress (i.e., protocols for evidence syntheses), and evidence syntheses being planned (i.e., registered titles for evidence syntheses). Social Systems Evidence also contains a continuously updated repository of economic evaluations in these same domains…(More)”

We are Developing AI at the Detriment of the Global South — How a Focus on Responsible Data Re-use Can Make a Difference

Curated on Posted on by Stefaan Verhulst

Article by Stefaan Verhulst and Peter Addo: “…At the root of this debate runs a frequent concern with how data is collected, stored, used — and responsibly reused for other purposes that initially collected for…

In this article, we propose that promoting responsible reuse of data requires addressing the power imbalances inherent in the data ecology. These imbalances disempower key stakeholders, thereby undermining trust in data management practices. As we recently argued in a report on “responsible data reuse in developing countries,” prepared for Agence Française de Development (AFD), power imbalences may be particularly pernicious when considering the use of data in the Global South. Addressing these requires broadening notions of consent, beyond current highly individualized approaches, in favor of what we instead term a social license for reuse.

In what follows, we explain what a social license means, and propose three steps to help achieve that goal. We conclude by calling for a new research agenda — one that would stretch existing disciplinary and conceptual boundaries — to reimagine what social licenses might mean, and how they could be operationalized…(More)”.

Science Diplomacy and the Rise of Technopoles

Curated on Posted on by Stefaan Verhulst

Article by Vaughan Turekian and Peter Gluckman: “…Science diplomacy has an important, even existential imperative to help the world reconsider the necessity of working together toward big global goals. Climate change may be the most obvious example of where global action is needed, but many other issues have similar characteristics—deep ocean resources, space, and other ungoverned areas, to name a few.

However, taking up this mantle requires acknowledging why past efforts have failed to meet their goals. The global commitment to Sustainable Development Goals (SDGs) is an example. Weaknesses in the UN system, compounded by varied commitments from member states, will prevent the achievement of the SDGs by 2030. This year’s UN Summit of the Future is intended to reboot the global commitment to the sustainability agenda. Regardless of what type of agreement is signed at the summit, its impact may be limited.  

Science diplomacy has an important, even existential imperative to help the world reconsider the necessity of working together toward big global goals.

The science community must play an active part in ensuring progress is in fact made, but that will require an expansion of the community’s current role. To understand what this might mean, consider that the Pact for the Future agreed in New York City in September 2024 places “science, technology, and innovation” as one of its five themes. But that becomes actionable either in the narrow sense that technology will provide “answers” to global problems or in the platitudinous sense that science provides advice that is not acted upon. This dichotomy of unacceptable approaches has long bedeviled science’s influence.

For the world to make better use of science, science must take on an expanded responsibility in solving problems at both global and local scales. And science itself must become part of a toolkit—both at the practical and the diplomatic level—to address the sorts of challenges the world will face in the future. To make this happen, more countries must make science diplomacy a core part of their agenda by embedding science advisors within foreign ministries, connecting diplomats to science communities.

As the pace of technological change generates both existential risk and economic, environmental, and social opportunities, science diplomacy has a vital task in balancing outcomes for the benefit of more people. It can also bring the science community (including the social sciences and humanities) to play a critical role alongside nation states. And, as new technological developments enable nonstate actors, and especially the private sector, science diplomacy has an important role to play in helping nation states develop policy that can identify common solutions and engage key partners…(More)”.

How The New York Times incorporates editorial judgment in algorithms to curate its home page

Curated on Posted on by Stefaan Verhulst

Article by Zhen Yang: “Whether on the web or the app, the home page of The New York Times is a crucial gateway, setting the stage for readers’ experiences and guiding them to the most important news of the day. The Times publishes over 250 stories daily, far more than the 50 to 60 stories that can be featured on the home page at a given time. Traditionally, editors have manually selected and programmed which stories appear, when and where, multiple times daily. This manual process presents challenges:

  • How can we provide readers a relevant, useful, and fresh experience each time they visit the home page?
  • How can we make our editorial curation process more efficient and scalable?
  • How do we maximize the reach of each story and expose more stories to our readers?

To address these challenges, the Times has been actively developing and testing editorially driven algorithms to assist in curating home page content. These algorithms are editorially driven in that a human editor’s judgment or input is incorporated into every aspect of the algorithm — including deciding where on the home page the stories are placed, informing the rankings, and potentially influencing and overriding algorithmic outputs when necessary. From the get-go, we’ve designed algorithmic programming to elevate human curation, not to replace it…

The Times began using algorithms for content recommendations in 2011 but only recently started applying them to home page modules. For years, we only had one algorithmically-powered module, “Smarter Living,” on the home page, and later, “Popular in The Times.” Both were positioned relatively low on the page.

Three years ago, the formation of a cross-functional team — including newsroom editors, product managers, data scientists, data analysts, and engineers — brought the momentum needed to advance our responsible use of algorithms. Today, nearly half of the home page is programmed with assistance from algorithms that help promote news, features, and sub-brand content, such as The Athletic and Wirecutter. Some of these modules, such as the features module located at the top right of the home page on the web version, are in highly visible locations. During major news moments, editors can also deploy algorithmic modules to display additional coverage to complement a main module of stories near the top of the page. (The topmost news package of Figure 1 is an example of this in action.)…(More)”

How is editorial judgment incorporated into algorithmic programming?