Stefaan Verhulst

Chatham House Report by Bennett Freeman, Harriet Moynihan and Thiago Alves Pinto: “Robust civic space is essential for good governance, the rule of law and for enabling citizens to shape their societies. However, civil society space around the world is under significant pressure and the COVID-19 pandemic has exacerbated this situation.

The weakening of international institutions and democratic norms worldwide has resulted in fewer constraints on autocracies. Meanwhile, the rise of nationalism, populism and illiberalism is taking its toll on civil liberties.

The private sector is in a unique position to work with civil society organizations to uphold and defend civic freedoms and support sustainable and profitable business environments. Companies have the capacity, resources and expertise to enhance the protection of civic space….(More)”.

“A Guide for Scholars, Researchers, and Wonks” by Jonathan Schwabish: “Now more than ever, content must be visual if it is to travel far. Readers everywhere are overwhelmed with a flow of data, news, and text. Visuals can cut through the noise and make it easier for readers to recognize and recall information. Yet many researchers were never taught how to present their work visually.

This book details essential strategies to create more effective data visualizations. Jonathan Schwabish walks readers through the steps of creating better graphs and how to move beyond simple line, bar, and pie charts. Through more than five hundred examples, he demonstrates the do’s and don’ts of data visualization, the principles of visual perception, and how to make subjective style decisions around a chart’s design. Schwabish surveys more than eighty visualization types, from histograms to horizon charts, ridgeline plots to choropleth maps, and explains how each has its place in the visual toolkit. It might seem intimidating, but everyone can learn how to create compelling, effective data visualizations. This book will guide you as you define your audience and goals, choose the graph that best fits for your data, and clearly communicate your message….(More)”.

Paper by César A. Hidalgo: “Economic complexity methods have become popular tools in economic geography, international development and innovation studies. Here, I review economic complexity theory and applications, with a particular focus on two streams of literature: the literature on relatedness, which focuses on the evolution of specialization patterns, and the literature on metrics of economic complexity, which uses dimensionality reduction techniques to create metrics of economic sophistication that are predictive of variations in income, economic growth, emissions and income inequality….(More)”.

Karen Hao at MIT Technology Review: “In 1964, mathematician and computer scientist Woodrow Bledsoe first attempted the task of matching suspects’ faces to mugshots. He measured out the distances between different facial features in printed photographs and fed them into a computer program. His rudimentary successes would set off decades of research into teaching machines to recognize human faces.

Now a new study shows just how much this enterprise has eroded our privacy. It hasn’t just fueled an increasingly powerful tool of surveillance. The latest generation of deep-learning-based facial recognition has completely disrupted our norms of consent.

Deborah Raji, a fellow at nonprofit Mozilla, and Genevieve Fried, who advises members of the US Congress on algorithmic accountability, examined over 130 facial-recognition data sets compiled over 43 years. They found that researchers, driven by the exploding data requirements of deep learning, gradually abandoned asking for people’s consent. This has led more and more of people’s personal photos to be incorporated into systems of surveillance without their knowledge.

It has also led to far messier data sets: they may unintentionally include photos of minors, use racist and sexist labels, or have inconsistent quality and lighting. The trend could help explain the growing number of cases in which facial-recognition systems have failed with troubling consequences, such as the false arrests of two Black men in the Detroit area last year.

People were extremely cautious about collecting, documenting, and verifying face data in the early days, says Raji. “Now we don’t care anymore. All of that has been abandoned,” she says. “You just can’t keep track of a million faces. After a certain point, you can’t even pretend that you have control.”…(More)”.

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)”.