AI adoption in the public sector

Curated on Posted on by Stefaan Verhulst

Two studies from the Joint Research Centre: “…delve into the factors that influence the adoption of Artificial Intelligence (AI) in public sector organisations.

A first report analyses a survey conducted among 574 public managers across seven EU countries, identifying what are currently the main drivers of AI adoption and providing 3 key recommendations to practitioners. 

Strong expertise and various organisational factors emerge as key contributors for AI adoptions, and a second study sheds light on the essential competences and governance practices required for the effective adoption and usage of AI in the public sector across Europe…

The study finds that AI adoption is no longer a promise for public administration, but a reality, particularly in service delivery and internal operations and to a lesser extent in policy decision-making. It also highlights the importance of organisational factors such as leadership support, innovative culture, clear AI strategy, and in-house expertise in fostering AI adoption. Anticipated citizen needs are also identified as a key external factor driving AI adoption. 

Based on these findings, the report offers three policy recommendations. First, it suggests paying attention to AI and digitalisation in leadership programmes, organisational development and strategy building. Second, it recommends broadening in-house expertise on AI, which should include not only technical expertise, but also expertise on ethics, governance, and law. Third, the report advises monitoring (for instance through focus groups and surveys) and exchanging on citizen needs and levels of readiness for digital improvements in government service delivery…(More)”.

AI Investment Potential Index: Mapping Global Opportunities for Sustainable Development

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Paper by AFD: “…examines the potential of artificial intelligence (AI) investment to drive sustainable development across diverse national contexts. By evaluating critical factors, including AI readiness, social inclusion, human capital, and macroeconomic conditions, we construct a nuanced and comprehensive analysis of the global AI landscape. Employing advanced statistical techniques and machine learning algorithms, we identify nations with significant untapped potential for AI investment.
We introduce the AI Investment Potential Index (AIIPI), a novel instrument designed to guide financial institutions, development banks, and governments in making informed, strategic AI investment decisions. The AIIPI synthesizes metrics of AI readiness with socio-economic indicators to identify and highlight opportunities for fostering inclusive and sustainable growth. The methodological novelty lies in the weight selection process, which combines statistical modeling and also an entropy-based weighting approach. Furthermore, we provide detailed policy implications to support stakeholders in making targeted investments aimed at reducing disparities and advancing equitable technological development…(More)”.

NegotiateAI 

Curated on Posted on by Stefaan Verhulst

About: “The NegotiateAI app is designed to streamline access to critical information on the UN Plastic Treaty Negotiations to develop a legally binding instrument on plastic pollution, including the marine environment. It offers a comprehensive, centralized database of documents submitted by member countries available here, along with an extensive collection of supporting resources, including reports, research papers, and policy briefs. You can find more information about the NegotiateAI project on our website…The Interactive Treaty Assistant simplifies the search and analysis of documents by INC members, enabling negotiators and other interested parties to quickly pinpoint crucial information. With an intuitive interface, The Interactive Treaty Assistant supports treaty-specific queries and provides direct links to relevant documents for deeper research…(More)”.

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)”.

Boosting: Empowering Citizens with Behavioral Science

Curated on Posted on by Stefaan Verhulst

Paper by Stefan M. Herzog and Ralph Hertwig: “Behavioral public policy came to the fore with the introduction of nudging, which aims to steer behavior while maintaining freedom of choice. Responding to critiques of nudging (e.g., that it does not promote agency and relies on benevolent choice architects), other behavioral policy approaches focus on empowering citizens. Here we review boosting, a behavioral policy approach that aims to foster people’s agency, self-control, and ability to make informed decisions. It is grounded in evidence from behavioral science showing that human decision making is not as notoriously flawed as the nudging approach assumes. We argue that addressing the challenges of our time—such as climate change, pandemics, and the threats to liberal democracies and human autonomy posed by digital technologies and choice architectures—calls for fostering capable and engaged citizens as a first line of response to complement slower, systemic approaches…(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)”.

Using generative AI for crisis foresight

Curated on Posted on by Stefaan Verhulst

Article by Antonin Kenens and Josip Ivanovic: “What if the next time you discuss a complex future and its potential crises, it could be transformed from a typical meeting into an immersive experience? That’s exactly what we did at a recent strategy meeting of UNDP’s Crisis Bureau and Bureau for Policy and Programme Support.  

In an environment where workshops and meetings can often feel monotonous, we aimed to break the mold. By using AI-generated videos, we brought our discussion to life, reflecting the realities of developing nations and immersing participants in the critical issues affecting our region.  In today’s rapidly changing world, the ability to anticipate and prepare for potential crises is more crucial than ever. Crisis foresight involves identifying and analyzing possible future crises to develop strategies that can mitigate their impact. This proactive approach, highlighted multiple times in the pact for the future, is essential for effective governance and sustainable development in Europe and Central Asia and the rest of the world.

graphical user interface
Visualization of the consequences of pollution in Joraland.

Our idea behind creating AI-generated videos was to provide a vivid, immersive experience that would engage viewers and stimulate active participation by sharing their reflections on the challenges and opportunities in developing countries. We presented fictional yet relatable scenarios to gather the participants of the meeting around a common view and create a sense of urgency and importance around UNDP’s strategic priorities and initiatives. 

This approach not only captured attention but also sparked deeper engagement and thought-provoking conversations…(More)”.

What AI Can’t Do for Democracy

Curated on Posted on by Stefaan Verhulst

Essay by Daniel Berliner: “In short, there is increasing optimism among both theorists and practitioners over the potential for technology-enabled civic engagement to rejuvenate or deepen democracy. Is this optimism justified?

The answer depends on how we think about what civic engagement can do. Political representatives are often unresponsive to the preferences of ordinary people. Their misperceptions of public needs and preferences are partly to blame, but the sources of democratic dysfunction are much deeper and more structural than information alone. Working to ensure many more “citizens’ voices are truly heard” will thus do little to improve government responsiveness in contexts where the distribution of power means that policymakers have no incentive to do what citizens say. And as some critics have argued, it can even distract from recognizing and remedying other problems, creating a veneer of legitimacy—what health policy expert Sherry Arnstein once famously derided as mere “window dressing.”

Still, there are plenty of cases where contributions from citizens can highlight new problems that need addressing, new perspectives by which issues are understood, and new ideas for solving public problems—from administrative agencies seeking public input to city governments seeking to resolve resident complaints and citizens’ assemblies deliberating on climate policy. But even in these and other contexts, there is reason to doubt AI’s usefulness across the board. The possibilities of AI for civic engagement depend crucially on what exactly it is that policymakers want to learn from the public. For some types of learning, applications of AI can make major contributions to enhance the efficiency and efficacy of information processing. For others, there is no getting around the fundamental needs for human attention and context-specific knowledge in order to adequately make sense of public voices. We need to better understand these differences to avoid wasting resources on tools that might not deliver useful information…(More)”.

The Emergent Landscape of Data Commons: A Brief Survey and Comparison of Existing Initiatives

Curated on Posted on by Stefaan Verhulst

Article by Stefaan G. Verhulst and Hannah Chafetz: With the increased attention on the need for data to advance AI, data commons initiatives around the world are redefining how data can be accessed, and re-used for societal benefit. These initiatives focus on generating access to data from various sources for a public purpose and are governed by communities themselves. While diverse in focus–from health and mobility to language and environmental data–data commons are united by a common goal: democratizing access to data to fuel innovation and tackle global challenges.

This includes innovation in the context of artificial intelligence (AI). Data commons are providing the framework to make pools of diverse data available in machine understandable formats for responsible AI development and deployment. By providing access to high quality data sources with open licensing, data commons can help increase the quantity of training data in a less exploitative fashion, minimize AI providers’ reliance on data extracted across the internet without an open license, and increase the quality of the AI output (while reducing mis-information).

Over the last few months, the Open Data Policy Lab (a collaboration between The GovLab and Microsoft) has conducted various research initiatives to explore these topics further and understand:

(1) how the concept of a data commons is changing in the context of artificial intelligence, and

(2) current efforts to advance the next generation of data commons.

In what follows we provide a summary of our findings thus far. We hope it inspires more data commons use cases for responsible AI innovation in the public’s interest…(More)”.