Stefaan Verhulst
Paper by Rony Medaglia, Ben Eaton, Jonas Hedman, and Edgar A. Whitley: “Establishing IT governance arrangements is a deeply political process, where relationships of power play a crucial role. While the importance of power relationships is widely acknowledged in IS literature, specific mechanisms whereby the consequences of power relationships affect IT governance arrangements are still under‐researched. This study investigates the way power relationships are inscribed in the governance of digital identity systems in Denmark and the United Kingdom, where public and private actors are involved. Drawing on the theoretical lens of circuits of power, we contribute to research on the role of power in IT governance by identifying two distinct mechanisms of power inscription into IT governance: power cultivation and power limitation….(More)“.
Book by Vlad P. Glăveanu: “This book explores an eminently human phenomenon: our capacity to engage with the possible, to go beyond what is present, visible, or given in our existence. Possibility studies is an emerging field of research including topics as diverse as creativity, imagination, innovation, anticipation, counterfactual thinking, wondering, the future, social change, hope, agency, and utopia. The Possible: A Sociocultural Theory contributes to this wide field by developing a sociocultural account of the possible grounded in the notions of difference, position, perspective, dialogue, action, and culture. This theory aims to offer conceptual, methodological, and practical tools for all those interested in studying human possibility and cultivating it in education, at the workplace, in everyday life, and in society….(More)“.
“The Governance Lab (The GovLab), NYU Tandon School of Engineering, Global AI Ethics Consortium (GAIEC), Center for Responsible AI @ NYU (R/AI), and Technical University of Munich (TUM) Institute for Ethics in Artificial Intelligence (IEAI) jointly launched a free, online course, AI Ethics: Global Perspectives, on February 1, 2021. Designed for a global audience, it conveys the breadth and depth of the ongoing interdisciplinary conversation on AI ethics and seeks to bring together diverse perspectives from the field of ethical AI, to raise awareness and help institutions work towards more responsible use.
“The use of data and AI is steadily growing around the world – there should be simultaneous efforts to increase literacy, awareness, and education around the ethical implications of these technologies,” said Stefaan Verhulst, Co-Founder and Chief Research and Development Officer of The GovLab. “The course will allow experts to jointly develop a global understanding of AI.”
“AI is a global challenge, and so is AI ethics,” said Christoph Lütge, the director of IEAI. “Τhe ethical challenges related to the various uses of AI require multidisciplinary and multi-stakeholder engagement, as well as collaboration across cultures, organizations, academic institutions, etc. This online course is GAIEC’s attempt to approach and apply AI ethics effectively in practice.”
The course modules comprise pre-recorded lectures on either AI Applications, Data and AI, and Governance Frameworks, along with supplemental readings. New course lectures will be released the first week of every month.
“The goal of this course is to create a nuanced understanding of the role of technology in society so that we, the people, have tools to make AI work for the benefit of society,” said Julia Stoyanvoich, a Tandon Assistant Professor of Computer Science and Engineering, Director of the Center for Responsible AI at NYU Tandon, and an Assistant Professor at the NYU Center for Data Science. “It is up to us — current and future data scientists, business leaders, policy makers, and members of the public — to make AI what we want it to be.”
The collaboration will release four new modules in February. These include lectures from:
- Idoia Salazar, President and Co-Founder of OdiselA, who presents “Alexa vs Alice: Cultural Perspectives on the Impact of AI.” Salazar explores why it is important to take into account the cultural, geographical, and temporal aspects of AI, as well as their precise identification, in order to achieve the correct development and implementation of AI systems;
- Jerry John Kponyo, Associate Professor of Telecommunication Engineering at KNUST, who sheds light on the fundamentals of Artificial Intelligence in Transportation System (AITS) and safety, and looks at the technologies at play in its implementation;
- Danya Glabau, Director of Science and Technology studies at the NYU Tandon School of Engineering, asks and answers the question, “Who is artificial intelligence for?” and presents evidence that AI systems do not always help their intended users and constituencies;
- Mark Findlay, Director of the Centre for AI and Data Governance at SMU, reviews the ethical challenges — discrimination, lack of transparency, neglect of individual rights, and more — which have arisen from COVID-19 technologies and their resultant mass data accumulation.
To learn more and sign up to receive updates as new modules are added, visit the course website at aiethicscourse.org “
Book edited by Artemis Skarlatidou and Muki Haklay: “Little did Isaac Newton, Charles Darwin and other ‘gentlemen scientists’ know, when they were making their scientific discoveries, that some centuries later they would inspire a new field of scientific practice and innovation, called citizen science. The current growth and availability of citizen science projects and relevant applications to support citizen involvement is massive; every citizen has an opportunity to become a scientist and contribute to a scientific discipline, without having any professional qualifications. With geographic interfaces being the common approach to support collection, analysis and dissemination of data contributed by participants, ‘geographic citizen science’ is being approached from different angles.
Geographic Citizen Science Design takes an anthropological and Human-Computer Interaction (HCI) stance to provide the theoretical and methodological foundations to support the design, development and evaluation of citizen science projects and their user-friendly applications. Through a careful selection of case studies in the urban and non-urban contexts of the Global North and South, the chapters provide insights into the design and interaction barriers, as well as on the lessons learned from the engagement of a diverse set of participants; for example, literate and non-literate people with a range of technical skills, and with different cultural backgrounds.
Looking at the field through the lenses of specific case studies, the book captures the current state of the art in research and development of geographic citizen science and provides critical insight to inform technological innovation and future research in this area….(More)”.
“Today the Governance Lab (The GovLab) at the NYU Tandon School of Engineering launched a free, online course on Solving Public Problems. The 12-part program, presented by Beth Simone Noveck, and over two-dozen global changemakers, trains participants in the skills needed to move from demanding change to making it.
Taking a practical approach to addressing entrenched problems, from systemic racism to climate change, the course combines the teaching of quantitative and qualitative methods with participatory and equitable techniques for tapping the collective wisdom of communities to design and deliver powerful solutions to contemporary problems.
“We cannot expect to tackle tomorrow’s problems with yesterday’s toolkit,” said Noveck, a former advisor on open government to President Barack Obama. “In the 21st century, we must equip ourselves with the skills to solve public problems. But those skills are not innate, and this program is designed to help people learn how to implement workable solutions to our hardest but most important challenges.”
Based on Professor Noveck’s new book, Solving Public Problems: A Practical Guide to Fix Government and Change the World (Yale University Press 2021), this online program is intended to democratize access to public problem-solving education, providing citizens with innovative tools to tap the collective wisdom of communities to take effective, organized action for change. …(More)”.
Essay by Robert Seamans: There is understandable excitement about the impact that new technologies like artificial intelligence (AI) and robotics will have on our economy. In our everyday lives, we already see the benefits of these technologies: when we use our smartphones to navigate from one location to another using the fastest available route or when a predictive typing algorithm helps us finish a sentence in our email. At the same time, there are concerns about possible negative effects of these new technologies on labor. The Council of Economic Advisers of the past two Administrations have addressed these issues in the annual Economic Report of the President (ERP). For example, the 2016 ERP included a chapter on technology and innovation that linked robotics to productivity and growth, and the 2019 ERP included a chapter on artificial intelligence that discussed the uneven effects of technological change. Both these chapters used data at highly aggregated levels, in part because that is the data that is available. As I’ve noted elsewhere, AI and robots are everywhere, except, as it turns out, in the data.
To date, there have been no large scale, systematic studies in the U.S. on how robots and AI affect productivity and labor in individual firms or establishments (a firm could own one or more establishments, which for example could be a plant in a manufacturing setting or a storefront in a retail setting). This is because the data are scarce. Academic researchers interested in the effects of AI and robotics on economic outcomes have mostly used aggregate country and industry-level data. Very recently, some have studied these issues at the firm level using data on robot imports to France, Spain, and other countries. I review a few of these academic papers in both categories below, which provide early findings on the nuanced role these new technologies have on labor. Thanks to some excellent work being done by the U.S. Census Bureau, however, we may soon have more data to work with. This includes new questions on robot purchases in the Annual Survey of Manufacturers and Annual Capital Expenditures Survey and new questions on other technologies including cloud computing and machine learning in the Annual Business Survey….(More)”.
Paper by David Van Dijcke and Austin L. Wright: “We develop a novel approach for estimating spatially dispersed community-level participation in mass protest. This methodology is used to investigate factors associated with participation in the ‘March to Save America’ event in Washington, D.C. on January 6, 2021. This study combines granular location data from more than 40 million mobile devices with novel measures of community-level voting patterns, the location of organized hate groups, and the entire georeferenced digital archive of the social media platform Parler. We find evidence that partisanship, socio-political isolation, proximity to chapters of the Proud Boys organization, and the local activity on Parler are robustly associated with protest participation. Our research fills a prominent gap in the study of collective action: identifying and studying communities involved in mass-scale events that escalate into violent insurrection….(More)”.
Paper by John Flood and Monique Lewis: “The COVID pandemic has overwhelmed many countries in their attempts at tracking and tracing people infected with the disease. Our paper examines how tracking and tracing is done looking at manual and technological means. It raises the issues around efficiency and privacy, etc. The paper investigates more closely the approaches taken by two countries, namely Taiwan and the UK. It shows how tracking and tracing can be handled sensitively and openly compared to the bungled attempts of the UK that have led to the greatest number of dead in Europe. The key messages are that all communications around tracking and tracing need to open, clear, without confusion and delivered by those closest to the communities receiving the messages.This occurred in Taiwan but in the UK the central government chose to close out local government and other local resources. The highly centralised dirigiste approach of the government alienated much of the population who came to distrust government. As local government was later brought into the COVID fold the messaging improved. Taiwan always remained open in its communications, even allowing citizens to participate in improving the technology around COVID. Taiwan learnt from its earlier experiences with SARS, whereas the UK ignored its pandemic planning exercises from earlier years and even experimented with crude ideas of herd immunity by letting the disease rip through the population–an idea soon abandoned.
We also derive a new type of citizen from the pandemic, namely the R citizen. This unfortunate archetype is both a blessing and a curse. If the citizen scores over 1 the disease accelerates and the R citizen is chastised, whereas if the citizen declines to zero it disappears but receives no plaudits for their behaviour. The R citizen can neither exist or die, rather like Schrödinger’s cat. R citizens are of course datafied individuals who are assemblages of data and are treated as distinct from humans. We argue they cannot be so distinguished without rendering them inhuman. This is as much a moral category as it is a scientific one….(More)”.
Paper by Jens Prufer and Inge Graef: “To prevent market tipping, which inhibits innovation, there is an urgent need to mandate sharing of user information in data-driven markets. Existing legal mechanisms to impose data sharing under EU competition law and data portability under the GDPR are not sufficient to tackle this problem. Mandated data sharing requires the design of a governance structure that combines elements of economically efficient centralization with legally necessary decentralization. We identify three feasible options. One is to centralize investigations and enforcement in a European Data Sharing Agency (EDSA), while decision-making power lies with National Competition Authorities in a Board of Supervisors. The second option is to set up a Data Sharing Cooperation Network coordinated through a European Data Sharing Board, with the National Competition Authority best placed to run the investigation adjudicating and enforcing the mandatory data-sharing decision across the EU. A third option is to mix both governance structures and to task national authorities to investigate and adjudicate and the EU-level EDSA with enforcement of data sharing….(More)”
Paper by Anna Petherick et al: “As the COVID-19 pandemic lingers, signs of “pandemic-policy fatigue” have raised worldwide concerns. But the phenomenon itself is yet to be thoroughly defined, documented, and delved into. Based on self-reported behaviours from samples of 238,797 respondents, representative of the populations of 14 countries, as well as global mobility and policy data, we systematically examine the prevalence and shape of people’s alleged gradual reduction in adherence to governments’ protective-behaviour policies against COVID-19. Our results show that from March through December 2020, pandemic-policy fatigue was empirically meaningful and geographically widespread. It emerged for high-cost and sensitising behaviours (physical distancing) but not for low-cost and habituating ones (mask wearing), and was less intense among retired people, people with chronic diseases, and in countries with high interpersonal trust. Particularly due to fatigue reversal patterns in high- and upper-middle-income countries, we observe an arch rather than a monotonic decline in global pandemic-policy fatigue….(More)”.