Paper by Peter Stone et al: “In September 2016, Stanford’s “One Hundred Year Study on Artificial Intelligence” project (AI100) issued the first report of its planned long-term periodic assessment of artificial intelligence (AI) and its impact on society. It was written by a panel of 17 study authors, each of whom is deeply rooted in AI research, chaired by Peter Stone of the University of Texas at Austin. The report, entitled “Artificial Intelligence and Life in 2030,” examines eight domains of typical urban settings on which AI is likely to have impact over the coming years: transportation, home and service robots, healthcare, education, public safety and security, low-resource communities, employment and workplace, and entertainment. It aims to provide the general public with a scientifically and technologically accurate portrayal of the current state of AI and its potential and to help guide decisions in industry and governments, as well as to inform research and development in the field. The charge for this report was given to the panel by the AI100 Standing Committee, chaired by Barbara Grosz of Harvard University….(More)”.
The political imaginary of National AI Strategies
Paper by Guy Paltieli: “In the past few years, several democratic governments have published their National AI Strategies (NASs). These documents outline how AI technology should be implemented in the public sector and explain the policies that will ensure the ethical use of personal data. In this article, I examine these documents as political texts and reconstruct the political imaginary that underlies them. I argue that these documents intervene in contemporary democratic politics by suggesting that AI can help democracies overcome some of the challenges they are facing. To achieve this, NASs use different kinds of imaginaries—democratic, sociotechnical and data—that help citizens envision how a future AI democracy might look like. As part of this collective effort, a new kind of relationship between citizens and governments is formed. Citizens are seen as autonomous data subjects, but at the same time, they are expected to share their personal data for the common good. As a result, I argue, a new kind of political imaginary is developed in these documents. One that maintains a human-centric approach while championing a vision of collective sovereignty over data. This kind of political imaginary can become useful in understanding the roles of citizens and governments in this technological age….(More)”.
Scrape, Request, Collect, Repeat: How Data Journalists Around the World Transcend Obstacles to Public Data
Paper by Jason A. Martin, Lindita Camaj & Gerry Lanosga: “This study applies a typology of public data transparency infrastructure and the contextualism framework for analysing journalism practice to examine patterns in data journalism production. The goal was to identify differences in approaches to acquiring and reporting on data around the world based on comparisons of public data transparency infrastructure. Data journalists from 34 countries were interviewed to understand challenges in data access, strategies used to overcome obstacles, innovation in collaboration, and attitudes about open-data advocacy. Analysis reveals themes of different approaches to journalistic interventionism by overcoming structural obstacles and inventive techniques journalists use to acquire and build their own data sets even in the most restrictive government contexts. Data journalists are increasingly connected with colleagues, third parties, and the public in using data, eschewing notions of competition for collaboration, and using crowdsourcing to address gaps in data. Patterns of direct and indirect activism are highlighted. Results contribute to a better understanding of global data journalism practice by revealing the influence of public data transparency infrastructure as a major factor that constrains or creates opportunities for data journalism practice as a subfield. Findings also broaden the cross-national base of empirical evidence on the developing practices and attitudes of data journalists….(More)”.
Tragedy of the Digital Commons
Paper by Chinmayi Sharma: “Google, iPhones, the national power grid, surgical operating rooms, baby monitors, surveillance technology, and wastewater management systems all run on open-source software. Open-source software, or software that is free and publicly available, powers our day-to-day lives. As a resource, it defies economic logic; it is built by developers, many of whom are volunteers, who build projects with the altruistic intention of donating them to the digital commons. Developers use it because it saves time and money and promotes innovation. Its benefits have led to its ubiquity and indispensability. Today, over 97% of all software uses open source. Without it, our critical infrastructure would crumble. The risk of that happening is more real than ever.
In December 2021, the Log4Shell vulnerability demonstrated that the issue of open-source security can no longer be ignored. One vulnerability found in a game of Minecraft threatened to take down systems worldwide—from the Belgian government to Google. The scope of the damage is unmatched; with open source, a vulnerability in one product can be used against every other entity that uses the same code. Open source’s benefits are also its burden. No one wants to pay for a resource they can get an unlimited supply of for free. Open source is not, however, truly unlimited. The open-source community is buckling under the weight of supporting over three-fourths of the world’s code. Rather than share the load, its primary beneficiaries, companies that build software, add to it. By failing to take basic precautionary measures in using open-source code, they make its exploitation nearly inevitable—when it happens, they free-ride on the already overwhelmed community to fix it. This doom cycle leaves everyone worse off because it leaves our critical infrastructure dangerously vulnerable.
Since it began, open source has worked behind the scenes to make society better. Today, its struggles are going unnoticed and unaddressed. The private sector isn’t willing to help—the few who are cannot carry the burden alone. So far, government interventions have been lacking. Secure open source requires much more. To start, it is time we treated open source as the critical infrastructure it is…(More)”.
Urban governance and civic capital: analysis of an evolving concept
Paper by Jen Nelles & David A. Wolfe: “This article argues that the concept of civic capital affords considerable insight into systems of urban economic development, usefully bridging gaps in both institution-centric and social capital approaches. While the concept has been applied in the literature on urban governance and economic development, its use has been fragmentary and has not seen broad engagement. This review of the state of the literature situates the concept of civic capital relative to existing literature in the field, highlights its relationship to other concepts, and reviews several qualitative approaches that apply the concept to case studies. It provides an overview of the concept and a description of the way it has developed alongside the rich literature on governance and social capital in urban development to illustrate its potential for further analytical study….(More)”.
Meaningful public engagement in the context of open science: reflections from early and mid-career academics
Paper by Wouter Boon et al: “How is public engagement perceived to contribute to open science? This commentary highlights common reflections on this question from interviews with 12 public engagement fellows in Utrecht University’s Open Science Programme in the Netherlands. We identify four reasons why public engagement is an essential enabler of open science. Interaction between academics and society can: (1) better align science with the needs of society; (2) secure a relationship of trust between science and society; (3) increase the quality and impact of science; and (4) support the impact of open access and FAIR data practices (data which meet principles of findability, accessibility, interoperability and reusability). To be successful and sustainable, such public engagement requires support in skills training and a form of institutionalisation in a university-wide system, but, most of all, the fellows express the importance of a formal and informal recognition and rewards system. Our findings suggest that in order to make public engagement an integral part of open science, universities should invest in institutional support, create awareness, and stimulate dialogue among staff members on how to ‘do’ good public engagement….(More)”.
A systematic review of worldwide causal and correlational evidence on digital media and democracy
Paper by Philipp Lorenz-Spreen, Lisa Oswald, Stephan Lewandowsky & Ralph Hertwig: “One of today’s most controversial and consequential issues is whether the global uptake of digital media is causally related to a decline in democracy. We conducted a systematic review of causal and correlational evidence (N = 496 articles) on the link between digital media use and different political variables. Some associations, such as increasing political participation and information consumption, are likely to be beneficial for democracy and were often observed in autocracies and emerging democracies. Other associations, such as declining political trust, increasing populism and growing polarization, are likely to be detrimental to democracy and were more pronounced in established democracies. While the impact of digital media on political systems depends on the specific variable and system in question, several variables show clear directions of associations. The evidence calls for research efforts and vigilance by governments and civil societies to better understand, design and regulate the interplay of digital media and democracy….(More)”
The Use of Data Science in a National Statistical Office
Paper by Sevgui Erman, Eric Rancourt, Yanick Beaucage, and Andre Loranger: “Objective statistical information is vital to an open and democratic society. It provides a solid foundation so that informed decisions can be made by our elected representatives, businesses, unions, and non-profit organizations, as well as individual citizens. There is a great shift towards a more virtual and digital economy and society. The traditional official statistical systems are centered on surveys, and must be adapted to this new digital reality. National statistical offices have been increasingly embracing non-survey data sources along with data science methods to better serve society.
This paper provides a blueprint for the application of data science in a government organization. It describes how data science enables innovation and the delivery of new high-value, high-quality, relevant, and trusted products that reflect the ever-evolving needs of our society and economy. We discuss practical operational considerations and impactful data science applications that supported the work of Statistics Canada’s analysts and front-line health agencies during the pandemic. We also discuss the innovative use of scanner data in lieu of survey data for large business respondents in the retail industry. We will describe computer vision methodologies, including machine learning models used to detect the start of buildings construction from satellite imagery, greenhouse area and greenhouse production, as well as crop types detection. Data science and machine learning methods have tremendous potential, and their ethical use is of primary importance. We conclude the paper with a forward-facing view of responsible data science use in statistical production.
Democracy by Design: Perspectives for Digitally Assisted, Participatory Upgrades of Society
Paper by Dirk Helbing et al: “The technological revolution, particularly the availability of more data and more powerful computational tools, has led to the emergence of a new scientific area called Computational Diplomacy. Our work focuses on a popular subarea of it. In recent years, there has been a surge of interest in using digital technologies to promote more participatory forms of democracy. While there are numerous potential benefits to using digital tools to enhance democracy, significant challenges must be addressed. It is essential to ensure that digital technologies are used in an accessible, equitable, and fair manner rather than reinforcing existing power imbalances. This paper investigates how digital tools can be used to help design more democratic societies by investigating three key research areas: (1) the role of digital technologies in facilitating civic engagement in collective decision-making; (2) the use of digital tools to improve transparency and accountability in gover-nance; and (3) the potential for digital technologies to enable the formation of more inclusive and representative democracies. We argue that more research on how digital technologies can be used to support democracy upgrade is needed, and we make some recommendations for future research in this direction…(More)”.
Artificial intelligence in government: Concepts, standards, and a unified framework
Paper by Vincent J. Straub, Deborah Morgan, Jonathan Bright, Helen Margetts: “Recent advances in artificial intelligence (AI) and machine learning (ML) hold the promise of improving government. Given the advanced capabilities of AI applications, it is critical that these are embedded using standard operational procedures, clear epistemic criteria, and behave in alignment with the normative expectations of society. Scholars in multiple domains have subsequently begun to conceptualize the different forms that AI systems may take, highlighting both their potential benefits and pitfalls. However, the literature remains fragmented, with researchers in social science disciplines like public administration and political science, and the fast-moving fields of AI, ML, and robotics, all developing concepts in relative isolation. Although there are calls to formalize the emerging study of AI in government, a balanced account that captures the full breadth of theoretical perspectives needed to understand the consequences of embedding AI into a public sector context is lacking. Here, we unify efforts across social and technical disciplines by using concept mapping to identify 107 different terms used in the multidisciplinary study of AI. We inductively sort these into three distinct semantic groups, which we label the (a) operational, (b) epistemic, and (c) normative domains. We then build on the results of this mapping exercise by proposing three new multifaceted concepts to study AI-based systems for government (AI-GOV) in an integrated, forward-looking way, which we call (1) operational fitness, (2) epistemic completeness, and (3) normative salience. Finally, we put these concepts to work by using them as dimensions in a conceptual typology of AI-GOV and connecting each with emerging AI technical measurement standards to encourage operationalization, foster cross-disciplinary dialogue, and stimulate debate among those aiming to reshape public administration with AI…(More)”.