AI-assisted diplomatic decision-making during crises—Challenges and opportunities

Curated on Posted on by Stefaan Verhulst

Article by Neeti Pokhriyal and Till Koebe: “Recent academic works have demonstrated the efficacy of employing or integrating “non-traditional” data (e.g., social media, satellite imagery, etc) for situational awareness tasks…

Despite these successes, we identify four critical challenges unique to the area of diplomacy that needs to be considered within the growing AI and diplomacy community going ahead:

1. First, decisions during crises are almost always taken using limited or incomplete information. There may be deliberate misuse and obfuscation of data/signals between different parties involved. At the start of a crisis, information is usually limited and potentially biased, especially along socioeconomic and rural-urban lines as crises are known to exacerbate the vulnerabilities already existing in the populations. This requires AI tools to quantify and visualize calibrated uncertainty in their outputs in an appropriate manner.

2. Second, in many cases, human lives and livelihoods are at stake. Therefore, any forecast, reasoning, or recommendation provided by AI assistance needs to be explainable and transparent for authorized users, but also secure against unauthorized access as diplomatic information is often highly sensitive. The question of accountability in case of misleading AI assistance needs to be addressed beforehand.

3. Third, in complex situations with high stakes but limited information, cultural differences and value-laden judgment driven by personal experiences play a central role in diplomatic decision-making. This calls for the use of learning techniques that can incorporate domain knowledge and experience.

4. Fourth, diplomatic interests during crises are often multifaceted, resulting in deep mistrust in and strategic misuse of information. Social media data, when used for consular tasks, has been shown to be susceptible to various d-/misinformation campaigns, some by the public, others by state actors for strategic manipulation…(More)”

Global Trends in Government Innovation 2023

Curated on Posted on by Stefaan Verhulst

OECD Report: “In the face of what has increasingly been referred to as an ongoing “permacrisis”, governments must cope with and respond to emerging threats while already grappling with longstanding issues such as climate change, digital disruption and low levels of trust. Despite compounding challenges, governments have been able to adapt and innovate to transform their societies and economies, and to transform themselves and how they design and deliver policies and services. Indeed, recent crises have served to catalyse innovation, and innovation has emerged as a much-needed driver of stability that can generate public value in difficult times.

In this context, understanding new approaches and spreading successful ideas has never been more important. In seeking to do our part to promote this, OPSI and the United Arab Emirates (UAE) Mohammed Bin Rashid Centre for Government Innovation (MBRCGI) have worked in partnership for nearly seven years to surface leading edge public sector innovation trends and to tell the stories of innovators around the world who are working to challenge existing norms and embed new ways of doing things.

Today, we are excited to jointly launch our report Global Trends in Government Innovation 2023, the preliminary report of which was launched at the World Government Summit (WGS), which brings together over 4 000 participants from more than 190 countries to discuss innovative ways to solve the challenges facing humanity…(More)”.

What do data portals do? Tracing the politics of online devices for making data public

Curated on Posted on by Stefaan Verhulst

Paper by Jonathan Gray: “The past decade has seen the rise of “data portals” as online devices for making data public. They have been accorded a prominent status in political speeches, policy documents, and official communications as sites of innovation, transparency, accountability, and participation. Drawing on research on data portals around the world, data portal software, and associated infrastructures, this paper explores three approaches for studying the social life of data portals as technopolitical devices: (a) interface analysis, (b) software analysis, and (c) metadata analysis. These three approaches contribute to the study of the social lives of data portals as dynamic, heterogeneous, and contested sites of public sector datafication. They are intended to contribute to critically assessing how participation around public sector datafication is invited and organized with portals, as well as to rethinking and recomposing them…(More)”.

Digital Anthropology Meets Data Science

Curated on Posted on by Stefaan Verhulst

Article by Katie Hillier: “Analyzing online ecosystems in real time, teams of anthropologists and data scientists can begin to understand rapid social changes as they happen.

Ask not what data science can do for anthropology, but what anthropology can do for data science. —Anders Kristian Munk, Why the World Needs Anthropologists Symposium 2022

In the last decade, emerging technologies, such as AI, immersive realities, and new and more addictive social networks, have permeated almost every aspect of our lives. These innovations are influencing how we form identities and belief systems. Social media influences the rise of subcultures on TikTok, the communications of extremist communities on Telegram, and the rapid spread of conspiracy theories that bounce around various online echo chambers. 

People with shared values or experiences can connect and form online cultures at unprecedented scales and speeds. But these new cultures are evolving and shifting faster than our current ability to understand them. 

To keep up with the depth and speed of online transformations, digital anthropologists are teaming up with data scientists to develop interdisciplinary methods and tools to bring the deep cultural context of anthropology to scales available only through data science—producing a surge in innovative methodologies for more effectively decoding online cultures in real time…(More)”.

Five Enablers for a New Phase of Behavioral Science

Curated on Posted on by Stefaan Verhulst

Article by Michael Hallsworth: “Over recent weeks I’ve been sharing parts of a “manifesto” that tries to give a coherent vision for the future of applied behavioral science. Stepping back, if I had to identify a theme that comes through the various proposals, it would be the need for self-reflective practice.

Behavioral science has seen a tremendous amount of growth and interest over the last decade, largely focused on expanding its uses and methods. My sense is it’s ready for a new phase of maturity. That maturity involves behavioral scientists reflecting on the various ways that their actions are shaped by structural, institutional, environmental, economic, and historical factors.

I’m definitely not exempt from this need for self-reflection. There are times when I’ve focused on a cognitive bias when I should have been spending more time exploring the context and motivations for a decision instead. Sometimes I’ve homed in on a narrow slice of a problem that we can measure, even if that means dispensing with wider systemic effects and challenges. Once I spent a long time trying to apply the language of heuristics and biases to explain why people were failing to use the urgent care alternatives to hospital emergency departments, before realizing that their behavior was completely reasonable.     

The manifesto critiques things like this, but it doesn’t have all the answers. Because it tries to both cover a lot of ground and go into detail, many of the hard knots of implementation go unpicked. The truth is that writing reports and setting goals is the easy part. Turning those goals into practice is much tougher; as behavioral scientists know, there is often a gap between intention and action.

Right now, I and others don’t always realize the ambitions set out in the manifesto. Changing that is going to take time and effort, and it will involve the discomfort of disrupting familiar practices. Some have made public commitments in this direction; my organization is working on upgrading its practices in line with proposals around making predictions prior to implementation, strengthening RCTs to cope with complexity, and enabling people to use behavioral science, among others.

The truth is that writing reports and setting goals is the easy part. Turning those goals into practice is much tougher; as behavioral scientists know, there is often a gap between intention and action.

But changes by individual actors will not be enough. The big issue is that several of the proposals require coordination. For example, one of the key ideas is the need for more multisite studies that are well coordinated and have clear goals. Another prioritizes developing international professional networks to support projects in low- and middle-income countries…(More)”.

The Rise of Virtual Communities

Curated on Posted on by Stefaan Verhulst

Book by Amber Atherton: “Uncover the fascinating history of virtual communities and how we connect to each other online. The Rise of Virtual Communities, explores the earliest online community platforms, mapping the technological evolutions, and the individuals, that have shaped the culture of the internet.

Read in-depth interviews with the visionary founders of iconic online platforms, and uncover the history of virtual communities and how the industry has developed over time. Featuring never-before told stories, this exploration introduces new ideas and predictions for the future, explaining how we got here and challenging what we think we may know about building online communities….(More)”.

International Data Governance – Pathways to Progress

Curated on Posted on by Stefaan Verhulst

Press Release: “In May 2023, the United Nations System Chief Executives Board for Coordination endorsed International Data Governance – Pathways to Progress, developed through the High-level Committee on Programmes (HLCP) which approved the paper at its 45th session in March 2023.  International Data Governance – Pathways to Progress and its addenda were developed by the HLCP Working Group on International Data Governance…(More)”. (See Annex 1: Mapping and Comparing Data Governance Frameworks).

Regulating Cross-Border Data Flows

Curated on Posted on by Stefaan Verhulst

Book by Bryan Mercurio, and Ronald Yu: “Data is now one of, if not the world’s most valuable resource. The adoption of data-driven applications across economic sectors has made data and the flow of data so pervasive that it has become integral to everything we as members of society do – from conducting our finances to operating businesses to powering the apps we use every day. For this reason, governing cross-border data flows is inherently difficult given the ubiquity and value of data, and the impact government policies can have on national competitiveness, business attractiveness and personal rights. The challenge for governments is to address in a coherent manner the broad range of data-related issues in the context of a global data-driven economy.

This book engages with the unexplored topic of why and how governments should develop a coherent and consistent strategic framework regulating cross-border data flows. The objective is to fill a very significant gap in the legal and policy setting by considering multiple perspectives in order to assist in the development of a jurisdiction’s coherent and strategic policy framework…(More)“.

3 barriers to successful data collaboratives

Curated on Posted on by Stefaan Verhulst

Article by Federico Bartolomucci: “Data collaboratives have proliferated in recent years as effective means of promoting the use of data for social good. This type of social partnership involves actors from the private, public, and not-for-profit sectors working together to leverage public or private data to enhance collective capacity to address societal and environmental challenges. The California Data Collaborative for instance, combines the data of numerous Californian water managers to enhance data-informed policy and decision making. 

But, in my years as a researcher studying more than a hundred cases of data collaboratives, I have observed widespread feelings of isolation among collaborating partners due to the absence of success-proven reference models. …Below, I provide an overview of three governance challenges faced by practitioners, as well as recommendations for addressing them. In doing so, I encourage every practitioner embarking on a data collaborative initiative to reflect on these challenges and create ad-hoc strategies to address them…

1. Overly relying on grant funding limits a collaborative’s options.

Data Collaboratives are typically conceived as not-for-profit projects, relying solely on grant funding from the founding partners. This is the case, for example, with TD1_Index, a global collaboration that seeks to gather data on Type 1 diabetes, raise awareness, and advance research on the topic. Although grant funding schemas work in some cases (like in that of T1D_Index), relying solely on grant funding makes a data collaborative heavily dependent on the willingness of one or more partners to sustain its activities and hinders its ability to achieve operational and decisional autonomy.

Operational and decisional autonomy indeed appears to be a beneficial condition for a collaborative to develop trust, involve other partners, and continuously adapt its activities and structure to external events—characteristics required for operating in a highly innovative sector.

Hybrid business models that combine grant funding with revenue-generating activities indicate a promising evolutionary path. The simplest way to do this is to monetize data analysis and data stewardship services. The ActNow Coalition, a U.S.-based not-for-profit organization, combines donations with client-funded initiatives in which the team provides data collection, analysis, and visualization services. Offering these types of services generates revenues for the collaborative and gaining access to them is among the most compelling incentives for partners to join the collaboration.

In studying data collaboratives around the world, two models emerge as most effective: (1) pay-per-use models, in which collaboration partners can access data-related services on demand (see Civity NL and their project Sniffer Bike) and (2) membership models, in which participation in the collaborative entitles partners to access certain services under predefined conditions (see the California Data Collaborative).

2. Demonstrating impact is key to a collaborative’s survival. 

As partners’ participation in data collaboratives is primarily motivated by a shared social purpose, the collaborative’s ability to demonstrate its efficacy in achieving its purpose means being able to defend its raison d’être. Demonstrating impact enables collaboratives to retain existing partners, renew commitments, and recruit new partners…(More)”.

Misunderstanding Misinformation

Curated on Posted on by Stefaan Verhulst

Article by Claire Wardle: “In the fall of 2017, Collins Dictionary named fake news word of the year. It was hard to argue with the decision. Journalists were using the phrase to raise awareness of false and misleading information online. Academics had started publishing copiously on the subject and even named conferences after it. And of course, US president Donald Trump regularly used the epithet from the podium to discredit nearly anything he disliked.

By spring of that year, I had already become exasperated by how this term was being used to attack the news media. Worse, it had never captured the problem: most content wasn’t actually fake, but genuine content used out of context—and only rarely did it look like news. I made a rallying cry to stop using fake news and instead use misinformation, disinformation, and malinformation under the umbrella term information disorder. These terms, especially the first two, have caught on, but they represent an overly simple, tidy framework I no longer find useful.

Both disinformation and misinformation describe false or misleading claims, but disinformation is distributed with the intent to cause harm, whereas misinformation is the mistaken sharing of the same content. Analyses of both generally focus on whether a post is accurate and whether it is intended to mislead. The result? We researchers become so obsessed with labeling the dots that we can’t see the larger pattern they show.

By focusing narrowly on problematic content, researchers are failing to understand the increasingly sizable number of people who create and share this content, and also overlooking the larger context of what information people actually need. Academics are not going to effectively strengthen the information ecosystem until we shift our perspective from classifying every post to understanding the social contexts of this information, how it fits into narratives and identities, and its short-term impacts and long-term harms…(More)”.