How Belgium is Giving Citizens a Say on AI

Curated on Posted on by Stefaan Verhulst

Article by Graham Wetherall-Grujić: “A few weeks before the European Parliament’s final debate on the AI Act, 60 randomly selected members of the Belgian public convened in Brussels for a discussion of their own. The aim was not to debate a particular piece of legislation, but to help shape a European vision on the future of AI, drawing on the views, concerns, and ideas of the public. 

They were taking part in a citizens’ assembly on AI, held as part of Belgium’s presidency of the European Council. When Belgium assumed the presidency for six months beginning in January 2024, they announced they would be placing “special focus” on citizens’ participation. The citizen panel on AI is the largest of the scheduled participation projects. Over a total of three weekends, participants are deliberating on a range of topics including the impact of AI on work, education, and democracy. 

The assembly comes at a point in time with rising calls for more public inputs on the topic of AI. Some big tech firms have begun to respond with participation projects of their own. But this is the first time an EU institution has launched a consultation on the topic. The organisers hope it will pave the way for more to come…(More)”.

Next Generation Evidence: Strategies for More Equitable Social Impact

Curated on Posted on by Stefaan Verhulst

Book edited by Kelly Fitzsimmons and Tamar Bauer: “Evidence is remarkably powerful; it helps us understand the needs of communities, make decisions in times of change and scarcity, and build and do more of what works. However, practitioners face a number of structural and practical hurdles to building and using evidence. Traditional evaluation and research methods are often not timely, affordable, meaningful, or inclusive for helping practitioners make decisions to increase their impact for people and communities. Too often and for too long, evaluation was a thing done to practitioners and the communities they serve, relegating them to a passive role when they should be regarded as leaders of this work. Worse, their data and evidence has been used against them in disempowering thumbs-up, thumbs-down circumstances, rather than for learning and improvement that leads to impact.

Next Generation Evidence features innovative thinking from leaders across policy, philanthropy, research, and practice. Together, these leaders lay out a vision for a stronger, more equitable data and evidence ecosystem that centers on the voices of people and communities most directly impacted by the problems we seek to solve. Throughout the book, case studies featuring practitioners at various stages in their evidence-building journey highlight concrete illustrations of how continuous evidence building can benefit organizations and outcomes for communities…(More)”.

The Global State of Social Connections

Curated on Posted on by Stefaan Verhulst

Gallup: “Social needs are universal, and the degree to which they are fulfilled — or not — impacts the health, well-being and resilience of people everywhere. With increasing global interest in understanding how social connections support or hinder health, policymakers worldwide may benefit from reliable data on the current state of social connectedness. Despite the critical role of social connectedness for communities and the people who live in them, little is known about the frequency or form of social connection in many — if not most — parts of the world.

Meta and Gallup have collaborated on two research studies to help fill this gap. In 2022, the Meta-Gallup State of Social Connections report revealed important variations in people’s sense of connectedness and loneliness across the seven countries studied. This report builds on that research by presenting data on connections and loneliness among people from 142 countries…(More)”.

AI-driven public services and the privacy paradox: do citizens really care about their privacy?

Curated on Posted on by Stefaan Verhulst

Paper by Based on privacy calculus theory, we derive hypotheses on the role of perceived usefulness and privacy risks of artificial intelligence (AI) in public services. In a representative vignette experiment (n = 1,048), we asked citizens whether they would download a mobile app to interact in an AI-driven public service. Despite general concerns about privacy, we find that citizens are not susceptible to the amount of personal information they must share, nor to a more anthropomorphic interface. Our results confirm the privacy paradox, which we frame in the literature on the government’s role to safeguard ethical principles, including citizens’ privacy…(More)”.

The impact of generative artificial intelligence on socioeconomic inequalities and
policy making

Curated on Posted on by Stefaan Verhulst

Paper by Valerio Capraro et al: “Generative artificial intelligence, including chatbots like ChatGPT, has the potential to both exacerbate and ameliorate existing socioeconomic inequalities. In this article, we provide a state-of-the-art interdisciplinary overview of the probable impacts of generative AI on four critical domains: work, education, health, and information. Our goal is to warn about how generative AI could worsen existing inequalities while illuminating directions for using AI to resolve pervasive social problems. Generative AI in the workplace can boost productivity and create new jobs, but the benefits will likely be distributed unevenly. In education, it offers personalized learning but may widen the digital divide. In healthcare, it improves diagnostics and accessibility but could deepen pre-existing inequalities. For information, it democratizes content creation and access but also dramatically expands the production and proliferation of misinformation. Each section covers a specific topic, evaluates existing research, identifies critical gaps, and recommends research directions. We conclude with a section highlighting the role of policymaking to maximize generative AI’s potential to reduce inequalities while
mitigating its harmful effects. We discuss strengths and weaknesses of existing policy frameworks in the European Union, the United States, and the United Kingdom, observing that each fails to fully confront the socioeconomic challenges we have identified. We contend that these policies should promote shared prosperity through the advancement of generative AI. We suggest several concrete policies to encourage further research and debate. This article emphasizes the need for interdisciplinary collaborations to understand and address the complex challenges of generative AI…(More)”.

Co-Designing Urban Futures: Innovation and partnerships for improved service delivery in intermediary cities

Curated on Posted on by Stefaan Verhulst

Report by GSMA: “Cities across low- and middle-income countries (LMICs) are grappling with the concurrent challenges of rapid urbanisation, climate change and widening inequalities. For intermediary cities, which account for more than half of the urban population in LMICs, these challenges are more pronounced. There is growing evidence that partnerships, collaboration and innovative service delivery models can address these challenges. The GSMA, Connected Places Catapult and UN-Habitat have come together to support cities by driving collaboration between the public and private sectors and enabling the adoption of these innovative models.

This report first outlines the state of urbanisation and the challenges of urban service provision associated with the rapid pace with which cities are growing. It then delves into the unique challenges that intermediary cities face: Governance, digital development, financial capacity and climate change, making the case to accelerate innovation and partnerships in these cities…(More)”.

Social Movements and Public Opinion in the United States

Curated on Posted on by Stefaan Verhulst

Paper by Amory Gethin & Vincent Pons: “Recent social movements stand out by their spontaneous nature and lack of stable leadership, raising doubts on their ability to generate political change. This article provides systematic evidence on the effects of protests on public opinion and political attitudes. Drawing on a database covering the quasi-universe of protests held in the United States, we identify 14 social movements that took place from 2017 to 2022, covering topics related to environmental protection, gender equality, gun control, immigration, national and international politics, and racial issues. We use Twitter data, Google search volumes, and high-frequency surveys to track the evolution of online interest, policy views, and vote intentions before and after the outset of each movement. Combining national-level event studies with difference-in-differences designs exploiting variation in local protest intensity, we find that protests generate substantial internet activity but have limited effects on political attitudes. Except for the Black Lives Matter protests following the death of George Floyd, which shifted views on racial discrimination and increased votes for the Democrats, we estimate precise null effects of protests on public opinion and electoral behavior…(More)”.

Data-Driven Innovation in the Creative Industries

Curated on Posted on by Stefaan Verhulst

Open Access Book edited by Melissa Terras, Vikki Jones, Nicola Osborne, and Chris Speed: “The creative industries – the place where art, business, and technology meet in economic activity – have been hugely affected by the relatively recent digitalisation (and often monetisation) of work, home, relationships, and leisure. Such trends were accelerated by the global COVID-19 pandemic. This edited collection examines how the creative industries can be supported to make best use of opportunities in digital technology and data-driven innovation.

Since digital markets and platforms are now essential for revenue generation and audience engagement, there is a vital need for improved data and digital skills in the creative and cultural sectors. Taking a necessarily global perspective, this book explores the challenges and opportunities of data-driven approaches to creativity in different contexts across the arts, cultural, and heritage sectors. Chapters reach beyond the platforms and approaches provided by the technology sector to delve into the collaborative work that supports innovation around the interdisciplinary and cross-sectoral issues that emerge where data infrastructures and approaches meet creativity.

A novel intervention that uniquely centres the role of data in the theory and practice of creative industries’ innovation, this book is valuable reading for those researching and studying the creative economy as well for those who drive investment for the creative industries in a digitalised society…(More)”.

The tech industry can’t agree on what open-source AI means. That’s a problem.

Curated on Posted on by Stefaan Verhulst

Article by Edd Gent: “Suddenly, “open source” is the latest buzzword in AI circles. Meta has pledged to create open-source artificial general intelligence. And Elon Musk is suing OpenAI over its lack of open-source AI models.

Meanwhile, a growing number of tech leaders and companies are setting themselves up as open-source champions. 

But there’s a fundamental problem—no one can agree on what “open-source AI” means. 

On the face of it, open-source AI promises a future where anyone can take part in the technology’s development. That could accelerate innovation, boost transparency, and give users greater control over systems that could soon reshape many aspects of our lives. But what even is it? What makes an AI model open source, and what disqualifies it?

The answers could have significant ramifications for the future of the technology. Until the tech industry has settled on a definition, powerful companies can easily bend the concept to suit their own needs, and it could become a tool to entrench the dominance of today’s leading players.

Entering this fray is the Open Source Initiative (OSI), the self-appointed arbiters of what it means to be open source. Founded in 1998, the nonprofit is the custodian of the Open Source Definition, a widely accepted set of rules that determine whether a piece of software can be considered open source. 

Now, the organization has assembled a 70-strong group of researchers, lawyers, policymakers, activists, and representatives from big tech companies like Meta, Google, and Amazon to come up with a working definition of open-source AI…(More)”.

New Jersey is turning to AI to improve the job search process

Curated on Posted on by Stefaan Verhulst

Article by Beth Simone Noveck: “Americans are experiencing some conflicting feelings about AI.

While people are flocking to new roles like prompt engineer and AI ethicist, the technology is also predicted to put many jobs at risk, including computer programmers, data scientists, graphic designers, writers, lawyers.

Little wonder, then, that a national survey by the Heldrich Center for Workforce Development found an overwhelming majority of Americans (66%) believe that they “will need more technological skills to achieve their career goals.” One thing is certain: Workers will need to train for change. And in a world of misinformation-filled social media platforms, it is increasingly important for trusted public institutions to provide reliable, data-driven resources.

In New Jersey, we’ve tried doing just that by collaborating with workers, including many with disabilities, to design technology that will support better decision-making around training and career change. Investing in similar public AI-powered tools could help support better consumer choice across various domains. When a public entity designs, controls and implements AI, there is a far greater likelihood that this powerful technology will be used for good.

In New Jersey, the public can find reliable, independent, unbiased information about training and upskilling on the state’s new MyCareer website, which uses AI to make personalized recommendations about your career prospects, and the training you will need to be ready for a high-growth, in-demand job…(More)”.