In Online Democracy, Fun Is Imperative

Curated on Posted on by Stefaan Verhulst

Essay by Joe Mathews: “Governments around the world, especially those at the subnational and local levels, find themselves stuck in a vise. Planetary problems like climate change, disease, and technological disruption are not being addressed adequately by national governments. Everyday people, whose lives have been disrupted by those planetary problems, press the governments closer to them to step up and protect them. But those governments lack the technical capacity and popular trust to act effectively against bigger problems.

To build trust and capacity, many governments are moving governance into the digital world and asking their residents to do more of the work of government themselves. Some cities, provinces, and political institutions have tried to build digital platforms and robust digital environments where residents can improve service delivery and make government policy themselves.

However, most of these experiments have been failures. The trouble is that most of these platforms cannot keep the attention of the people who are supposed to use them. Too few of the platforms are designed to make online engagement compelling. So, figuring out how to make online engagement in government fun is actually a serious question for governments seeking to work more closely with their people.

What does fun look like in this sphere? I first witnessed a truly fun and engaging digital tool for citizen governance in Rome in 2018. While running a democracy conference with Mayor Virginia Raggi and her team, they were always on their phones, and not just to answer emails or texts. They were constantly on a digital environment called Rousseau.

Rousseau was named after Jean-Jacques Rousseau, the eighteenth-century philosopher and author of The Social Contract. In that 1762 book, Rousseau argued that city-states (like his hometown of Geneva) were more naturally suited to democracy than nation-states (especially big nations like France). He also wrote that the people themselves, not elected representatives, were the best rulers through what we today call direct democracy…(More)”.

How Innovation Ecosystems Foster Citizen Participation Using Emerging Technologies in Portugal, Spain and the Netherlands

Curated on Posted on by Stefaan Verhulst

OECD Report: “This report examines how actors in Portugal, Spain and the Netherlands interact and work together to contribute to the development of emerging technologies for citizen participation. Through in-depth research and analysis of actors’ motivations, experiences, challenges, and enablers in this nascent but promising field, this paper presents a unique cross-national perspective on innovation ecosystems for citizen participation using emerging technology. It includes lessons and concrete proposals for policymakers, innovators, and researchers seeking to develop technology-based citizen participation initiatives…(More)”.

Data Sovereignty and Open Sharing: Reconceiving Benefit-Sharing and Governance of Digital Sequence Information

Curated on Posted on by Stefaan Verhulst

Paper by Masanori Arita: “There are ethical, legal, and governance challenges surrounding data, particularly in the context of digital sequence information (DSI) on genetic resources. I focus on the shift in the international framework, as exemplified by the CBD-COP15 decision on benefit-sharing from DSI and discuss the growing significance of data sovereignty in the age of AI and synthetic biology. Using the example of the COVID-19 pandemic, the tension between open science principles and data control rights is explained. This opinion also highlights the importance of inclusive and equitable data sharing frameworks that respect both privacy and sovereign data rights, stressing the need for international cooperation and equitable access to data to reduce global inequalities in scientific and technological advancement…(More)”.

Organisations in the Age of Algorithms

Curated on Posted on by Stefaan Verhulst

Article by Phanish Puranam: “When Google’s CEO Sundar Pichai recently revealed that 25 percent of the company’s software is now machine-generated, it underscored how quickly artificial intelligence is reshaping the workplace. 

What does this mean for how we organise and manage? Will there still be room for humans in tomorrow’s organisations? And what might their work conditions look like? I tackle these questions in my new book “Re-Humanize: How to Build Human-Centric Organizations in the Age of Algorithms”. 

The answers are not a given. They will depend on what we choose to do – what kinds of organisations we design. I make the case that successful organisation designs will have to pursue both goal-centricity (i.e. achieving objectives) and human-centricity (i.e. creating social environments that people find attractive). A myopic focus on only one or the other will not bode well for us.

The dual purpose of organisations

Why focus on organisations at a time when technology seems to be making such exciting strides? This was the very first question that INSEAD alumna Joanna Gordon asked me in a recent digital@INSEAD webinar. 

My answer: Homo sapiens’s most impressive accomplishments, from building the pyramids to developing Covid-19 vaccines, are not individual achievements. They were possible only because many people worked together effectively. “How to organise groups to attain goals” is our oldest general-purpose technology (GPT!). 

But there is more. To humans, organisations don’t just help accomplish goals. We are a species that has evolved to survive and thrive in groups, and organisations (i.e. groups with goals) are the natural habitat of Homo sapiens. They provide us with a sense of community and, as research has shown, help us strike a balance between our needs for social connection, individual autonomy and feeling capable and effective…(More)”.

Reimagining the Policy Cycle in the Age of Artificial Intelligence

Curated on Posted on by Stefaan Verhulst

Paper by Sara Marcucci and Stefaan Verhulst: “The increasing complexity of global challenges, such as climate change, public health crises, and socioeconomic inequalities, underscores the need for a more sophisticated and adaptive policymaking approach. Evidence-Informed Decision-Making (EIDM) has emerged as a critical framework, leveraging data and research to guide policy design, implementation, and impact assessment. However, traditional evidence-based approaches, such as reliance on Randomized Controlled Trials (RCTs) and systematic reviews, face limitations, including resource intensity, contextual constraints, and difficulty in addressing real-time challenges. Artificial Intelligence offers transformative potential to enhance EIDM by enabling large-scale data analysis, pattern recognition, predictive modeling, and stakeholder engagement across the policy cycle. While generative AI has attracted significant attention, this paper emphasizes the broader spectrum of AI applications (beyond Generative AI) —such as natural language processing (NLP), decision trees, and basic machine learning algorithms—that continue to play a critical role in evidence-informed policymaking. These models, often more transparent and resource-efficient, remain highly relevant in supporting data analysis, policy simulations, and decision-support.

This paper explores AI’s role in three key phases of the policy cycle: (1) problem identification, where AI can support issue framing, trend detection, and scenario creation; (2) policy design, where AI-driven simulations and decision-support tools can improve solution alignment with real-world contexts; and (3) policy implementation and impact assessment, where AI can enhance monitoring, evaluation, and adaptive decision-making. Despite its promise, AI adoption in policymaking remains limited due to challenges such as algorithmic bias, lack of explainability, resource demands, and ethical concerns related to data privacy and environmental impact. To ensure responsible and effective AI integration, this paper highlights key recommendations: prioritizing augmentation over automation, embedding human oversight throughout AI-driven processes, facilitating policy iteration, and combining AI with participatory governance models…(More)”.

Gather, Share, Build

Curated on Posted on by Stefaan Verhulst

Article by Nithya Ramanathan & Jim Fruchterman: “Recent milestones in generative AI have sent nonprofits, social enterprises, and funders alike scrambling to understand how these innovations can be harnessed for global good. Along with this enthusiasm, there is also warranted concern that AI will greatly increase the digital divide and fail to improve the lives of 90 percent of the people on our planet. The current focus on funding AI intelligently and strategically in the social sector is critical, and it will help ensure that money has the largest impact.

So how can the social sector meet the current moment?

AI is already good at a lot of things. Plenty of social impact organizations are using AI right now, with positive results. Great resources exist for developing a useful understanding of the current landscape and how existing AI tech can serve your mission, including this report from Stanford HAI and Project Evident and this AI Treasure Map for Nonprofits from Tech Matters.

While some tech-for-good companies are creating AI and thriving—Digital Green, Khan Academy, and Jacaranda Health, among many—most social sector companies are not ready to build AI solutions. But even organizations that don’t have AI on their radar need to be thinking about how to address one of the biggest challenges to harnessing AI to solve social sector problems: insufficient data…(More)”.

Advanced Flood Hub features for aid organizations and govern

Curated on Posted on by Stefaan Verhulst

Announcement by Alex Diaz: “Floods continue to devastate communities worldwide, and many are pursuing advancements in AI-driven flood forecasting, enabling faster, more efficient detection and response. Over the past few years, Google Research has focused on harnessing AI modeling and satellite imagery to dramatically accelerate the reliability of flood forecasting — while working with partners to expand coverage for people in vulnerable communities around the world.

Today, we’re rolling out new advanced features in Flood Hub designed to allow experts to understand flood risk in a given region via inundation history maps, and to understand how a given flood forecast on Flood Hub might propagate throughout a river basin. With the inundation history maps, Flood Hub expert users can view flood risk areas in high resolution over the map regardless of a current flood event. This is useful for cases where our flood forecasting does not include real time inundation maps or for pre-planning of humanitarian work. You can find more explanations about the inundation history maps and more in the Flood Hub Help Center…(More)”.

Why these scientists devote time to editing and updating Wikipedia

Curated on Posted on by Stefaan Verhulst

Article by Christine Ro: “…A 2018 survey of more than 4,000 Wikipedians (as the site’s editors are called) found that 12% had a doctorate. Scientists made up one-third of the Wikimedia Foundation’s 16 trustees, according to Doronina.

Although Wikipedia is the best-known project under the Wikimedia umbrella, there are other ways for scientists to contribute besides editing Wikipedia pages. For example, an entomologist could upload photos of little-known insect species to Wikimedia Commons, a collection of images and other media. A computer scientist could add a self-published book to the digital textbook site Wikibooks. Or a linguist could explain etymology on the collaborative dictionary Wiktionary. All of these are open access, a key part of Wikimedia’s mission.

Although Wikipedia’s structure might seem daunting for new editors, there are parallels with academic documents.

For instance, Jess Wade, a physicist at Imperial College London, who focuses on creating and improving biographies of female scientists and scientists from low- and middle-income countries, says that the talk page, which is the behind-the-scenes portion of a Wikipedia page on which editors discuss how to improve it, is almost like the peer-review file of an academic paper…However, scientists have their own biases about aspects such as how to classify certain topics. This matters, Harrison says, because “Wikipedia is intended to be a general-purpose encyclopaedia instead of a scientific encyclopaedia.”

One example is a long-standing battle over Wikipedia pages on cryptids and folklore creatures such as Bigfoot. Labels such as ‘pseudoscience’ have angered cryptid enthusiasts and raised questions about different types of knowledge. One suggestion is for the pages to feature a disclaimer that says that a topic is not accepted by mainstream science.

Wade raises a point about resourcing, saying it’s especially difficult for the platform to retain academics who might be enthusiastic about editing Wikipedia initially, but then drop off. One reason is time. For full-time researchers, Wikipedia editing could be an activity best left to evenings, weekends and holidays…(More)”.

Regulatory Markets: The Future of AI Governance

Curated on Posted on by Stefaan Verhulst

Paper by Gillian K. Hadfield, and Jack Clark: “Appropriately regulating artificial intelligence is an increasingly urgent policy challenge. Legislatures and regulators lack the specialized knowledge required to best translate public demands into legal requirements. Overreliance on industry self-regulation fails to hold producers and users of AI systems accountable to democratic demands. Regulatory markets, in which governments require the targets of regulation to purchase regulatory services from a private regulator, are proposed. This approach to AI regulation could overcome the limitations of both command-and-control regulation and self-regulation. Regulatory market could enable governments to establish policy priorities for the regulation of AI, whilst relying on market forces and industry R&D efforts to pioneer the methods of regulation that best achieve policymakers’ stated objectives…(More)”.

Tab the lab: A typology of public sector innovation labs

Curated on Posted on by Stefaan Verhulst

Paper by Aline Stoll and Kevin C Andermatt: “Many public sector organizations set up innovation laboratories in response to the pressure to tackle societal problems and the high expectations placed on them to innovate public services. Our understanding of the public sector innovation laboratories’ role in enhancing the innovation capacity of administrations is still limited. It is challenging to assess or compare the impact of innovation laboratories because of how they operate and what they do. This paper closes this research gap by offering a typology that organizes the diverse nature of innovation labs and makes it possible to compare various lab settings. The proposed typology gives possible relevant factors to increase the innovation capacity of public organizations. The findings are based on a literature review of primarily explorative papers and case studies, which made it possible to identify the relevant criteria. The proposed typology covers three dimensions: (1) value (intended innovation impact of the labs); (2) governance (role of government and financing model); and (3) network (stakeholders in the collaborative arrangements). Comparing European countries and regions with regards to the repartition of labs shows that Nordic and British countries tend to have broader scope than continental European countries…(More)”.