Using Democratic Innovation to Rebuild Trust between Elected Officials and Citizens

Curated on Posted on by Stefaan Verhulst

Article by Nick Vlahos: “According to Pew Research, public trust in government is among the lowest it has been in 70 years of polling. Today, 25% of Democrats and Democratic-leaning independents say they trust the federal government just about always or most of the time, compared with 8% of Republicans and Republican leaners.

The dismal statistics we continue to see year in and year out are compounded by the fact that democracy is under threat around the world. In response, many are turning to democratic innovations. According to Oliver Escobar and Stephen Elstub, democratic innovations are “processes or institutions that are new to a policy issue, policy role, or level of governance, and developed to reimagine and deepen the role of citizens in governance processes by increasing opportunities for participation, deliberation and influence.”

Many of these innovations intend to redefine the role of citizens and carve out unique opportunities for them to engage with their peers, collectively problem-solving, and making decisions on important issues. However, there are increasing calls for re-envisioning the relationship between elected officials and citizens using deliberative and participatory processes.

One such approach is the deliberative town hall, implemented by the Institute for Democratic Engagement and Accountability at Ohio State University. The model utilizes democratic innovation in the form of a deliberative mini-public within a single constituency, in relation to an elected official. Deliberative town halls bring together a cross-section of the community using stratified sampling, or civic lottery. The process further involves informed discussion on a topic with an elected official.

This approach has been commonly used with Members of Congress, but has recently been used in other Commonwealth countries, notably in Australia. What we know from this experience is that deliberative town halls can rebuild democratic relations by making interactions between elected officials and citizens more authentic, using reciprocal reason giving and sharing, and through active listening. In addition, ensuring that people with lived experience and scientific or topical expertise are present in conversations creates conditions for members of the public to better understand the nuances of an issue. Lastly, the Australian example highlights how having some type of impact over an outcome is highly prized by the public – they want to have their input factored into a decision, if not determining a decision altogether…(More)”.

Governing the economics of the common good

Curated on Posted on by Stefaan Verhulst

Paper by Mariana Mazzucato: “To meet today’s grand challenges, economics requires an understanding of how common objectives may be collaboratively set and met. Tied to the assumption that the state can, at best, fix market failures and is always at risk of ‘capture’, economic theory has been unable to offer such a framework. To move beyond such limiting assumptions, the paper provides a renewed conception of the common good, going beyond the classic public good and commons approach, as a way of steering and shaping (rather than just fixing) the economy towards collective goals…(More)”.

Urban Artificial Intelligence: From Real-world Observations to a Paradigm-Shifting Concept

Curated on Posted on by Stefaan Verhulst

Blog by Hubert Beroche: “Cities are facing unprecedented challenges. The figures are well known: while occupying only 2% of the earth’s surface, urban settlements host more than 50% of the global population and are responsible for 70% of greenhouse emissions. While concentrating most capital and human wealth, they are also places of systemic inequalities (Nelson, 2023), exacerbating and materializing social imbalances. In the meantime, cities have fewer and fewer resources to face those tensions. Increasing environmental constraints, combined with shrinking public budgets, are putting pressure on cities’ capacities. More than ever, urban stakeholders have to do more with less.

In this context, Artificial Intelligence has usually been seen as a much-welcomed technology. This technology can be defined as machines’ ability to perform cognitive functions, mainly through learning algorithms since 2012. First embedded in heavy top-down Smart City projects, AI applications in cities have gradually proliferated under the impetus of various stakeholders. Today’s cities are home to numerous AIs, owned and used by multiple stakeholders to serve different, sometimes divergent, interests.

The diversity of urban AIs in cities is well illustrated in our project co-produced with Cornell Tech: “The Future of Urban AI”. This graph represents different urban AI trends based on The Future of UrbanTech Horizon Scan. Each colored dot represents a major urban tech/urban AI trend, with its ramifications. Some of these trends are opposed but still cohabiting (eg “Dark Plans” and “New Screen Deal”)…(More)”.

When Science Meets Power

Curated on Posted on by Stefaan Verhulst

Book by Geoff Mulgan: “Science and politics have collaborated throughout human history, and science is repeatedly invoked today in political debates, from pandemic management to climate change. But the relationship between the two is muddled and muddied.

Leading policy analyst Geoff Mulgan here calls attention to the growing frictions caused by the expanding authority of science, which sometimes helps politics but often challenges it.

He dissects the complex history of states’ use of science for conquest, glory and economic growth and shows the challenges of governing risk – from nuclear weapons to genetic modification, artificial intelligence to synthetic biology. He shows why the governance of science has become one of the biggest challenges of the twenty-first century, ever more prominent in daily politics and policy.

Whereas science is ordered around what we know and what is, politics engages what we feel and what matters. How can we reconcile the two, so that crucial decisions are both well informed and legitimate?

The book proposes new ways to organize democracy and government, both within nations and at a global scale, to better shape science and technology so that we can reap more of the benefits and fewer of the harms…(More)”.

Shaping the Future: Indigenous Voices Reshaping Artificial Intelligence in Latin America

Curated on Posted on by Stefaan Verhulst

Blog by Enzo Maria Le Fevre Cervini: “In a groundbreaking move toward inclusivity and respect for diversity, a comprehensive report “Inteligencia artificial centrada en los pueblos indígenas: perspectivas desde América Latina y el Caribe” authored by Cristina Martinez and Luz Elena Gonzalez has been released by UNESCO, outlining the pivotal role of Indigenous perspectives in shaping the trajectory of Artificial Intelligence (AI) in Latin America. The report, a collaborative effort involving Indigenous communities, researchers, and various stakeholders, emphasizes the need for a fundamental shift in the development of AI technologies, ensuring they align with the values, needs, and priorities of Indigenous peoples.

The core theme of the report revolves around the idea that for AI to be truly respectful of human rights, it must incorporate the perspectives of Indigenous communities in Latin America, the Caribbean, and beyond. Recognizing the UNESCO Recommendation on the Ethics of Artificial Intelligence, the report highlights the urgency of developing a framework of shared responsibility among different actors, urging them to leverage their influence for the collective public interest.

While acknowledging the immense potential of AI in preserving Indigenous identities, conserving cultural heritage, and revitalizing languages, the report notes a critical gap. Many initiatives are often conceived externally, prompting a call to reevaluate these projects to ensure Indigenous leadership, development, and implementation…(More)”.

A Manifesto on Enforcing Law in the Age of ‘Artificial Intelligence’

Curated on Posted on by Stefaan Verhulst

Manifesto by the Transatlantic Reflection Group on Democracy and the Rule of Law in the Age of ‘Artificial Intelligence’: “… calls for the effective and legitimate enforcement of laws concerning AI systems. In doing so, we recognise the important and complementary role of standards and compliance practices. Whereas the first manifesto focused on the relationship between democratic law-making and technology, this second manifesto shifts focus from the design of law in the age of AI to the enforcement of law. Concretely, we offer 10 recommendations for addressing the key enforcement challenges shared across transatlantic stakeholders. We call on those who support these recommendations to sign this manifesto…(More)”.

Using AI to support people with disability in the labour market

Curated on Posted on by Stefaan Verhulst

OECD Report: “People with disability face persisting difficulties in the labour market. There are concerns that AI, if managed poorly, could further exacerbate these challenges. Yet, AI also has the potential to create more inclusive and accommodating environments and might help remove some of the barriers faced by people with disability in the labour market. Building on interviews with more than 70 stakeholders, this report explores the potential of AI to foster employment for people with disability, accounting for both the transformative possibilities of AI-powered solutions and the risks attached to the increased use of AI for people with disability. It also identifies obstacles hindering the use of AI and discusses what governments could do to avoid the risks and seize the opportunities of using AI to support people with disability in the labour market…(More)”.

AI and Democracy’s Digital Identity Crisis

Curated on Posted on by Stefaan Verhulst

Paper by Shrey Jain, Connor Spelliscy, Samuel Vance-Law and Scott Moore: “AI-enabled tools have become sophisticated enough to allow a small number of individuals to run disinformation campaigns of an unprecedented scale. Privacy-preserving identity attestations can drastically reduce instances of impersonation and make disinformation easy to identify and potentially hinder. By understanding how identity attestations are positioned across the spectrum of decentralization, we can gain a better understanding of the costs and benefits of various attestations. In this paper, we discuss attestation types, including governmental, biometric, federated, and web of trust-based, and include examples such as e-Estonia, China’s social credit system, Worldcoin, OAuth, X (formerly Twitter), Gitcoin Passport, and EAS. We believe that the most resilient systems create an identity that evolves and is connected to a network of similarly evolving identities that verify one another. In this type of system, each entity contributes its respective credibility to the attestation process, creating a larger, more comprehensive set of attestations. We believe these systems could be the best approach to authenticating identity and protecting against some of the threats to democracy that AI can pose in the hands of malicious actors. However, governments will likely attempt to mitigate these risks by implementing centralized identity authentication systems; these centralized systems could themselves pose risks to the democratic processes they are built to defend. We therefore recommend that policymakers support the development of standards-setting organizations for identity, provide legal clarity for builders of decentralized tooling, and fund research critical to effective identity authentication systems…(More)”.

Remote collaboration fuses fewer breakthrough ideas

Curated on Posted on by Stefaan Verhulst

Paper by Yiling Lin, Carl Benedikt Frey & Lingfei Wu: “Theories of innovation emphasize the role of social networks and teams as facilitators of breakthrough discoveries. Around the world, scientists and inventors are more plentiful and interconnected today than ever before. However, although there are more people making discoveries, and more ideas that can be reconfigured in new ways, research suggests that new ideas are getting harder to find—contradicting recombinant growth theory. Here we shed light on this apparent puzzle. Analysing 20 million research articles and 4 million patent applications from across the globe over the past half-century, we begin by documenting the rise of remote collaboration across cities, underlining the growing interconnectedness of scientists and inventors globally. We further show that across all fields, periods and team sizes, researchers in these remote teams are consistently less likely to make breakthrough discoveries relative to their on-site counterparts. Creating a dataset that allows us to explore the division of labour in knowledge production within teams and across space, we find that among distributed team members, collaboration centres on late-stage, technical tasks involving more codified knowledge. Yet they are less likely to join forces in conceptual tasks—such as conceiving new ideas and designing research—when knowledge is tacit. We conclude that despite striking improvements in digital technology in recent years, remote teams are less likely to integrate the knowledge of their members to produce new, disruptive ideas…(More)”.

Transmission Versus Truth, Imitation Versus Innovation: What Children Can Do That Large Language and Language-and-Vision Models Cannot (Yet)

Curated on Posted on by Stefaan Verhulst

Paper by Eunice Yiu, Eliza Kosoy, and Alison Gopnik: “Much discussion about large language models and language-and-vision models has focused on whether these models are intelligent agents. We present an alternative perspective. First, we argue that these artificial intelligence (AI) models are cultural technologies that enhance cultural transmission and are efficient and powerful imitation engines. Second, we explore what AI models can tell us about imitation and innovation by testing whether they can be used to discover new tools and novel causal structures and contrasting their responses with those of human children. Our work serves as a first step in determining which particular representations and competences, as well as which kinds of knowledge or skills, can be derived from particular learning techniques and data. In particular, we explore which kinds of cognitive capacities can be enabled by statistical analysis of large-scale linguistic data. Critically, our findings suggest that machines may need more than large-scale language and image data to allow the kinds of innovation that a small child can produce…(More)”.