Stefaan Verhulst
Book by Angèle Christin: “When the news moved online, journalists suddenly learned what their audiences actually liked, through algorithmic technologies that scrutinize web traffic and activity. Has this advent of audience metrics changed journalists’ work practices and professional identities? In Metrics at Work, Angèle Christin documents the ways that journalists grapple with audience data in the form of clicks, and analyzes how new forms of clickbait journalism travel across national borders.
Drawing on four years of fieldwork in web newsrooms in the United States and France, including more than one hundred interviews with journalists, Christin reveals many similarities among the media groups examined—their editorial goals, technological tools, and even office furniture. Yet she uncovers crucial and paradoxical differences in how American and French journalists understand audience analytics and how these affect the news produced in each country. American journalists routinely disregard traffic numbers and primarily rely on the opinion of their peers to define journalistic quality. Meanwhile, French journalists fixate on internet traffic and view these numbers as a sign of their resonance in the public sphere. Christin offers cultural and historical explanations for these disparities, arguing that distinct journalistic traditions structure how journalists make sense of digital measurements in the two countries.
Contrary to the popular belief that analytics and algorithms are globally homogenizing forces, Metrics at Work shows that computational technologies can have surprisingly divergent ramifications for work and organizations worldwide….(More)”.
Matthias Daub, Tony D’Emidio, Zaana Howard, and Seckin Ungur at McKinsey: “Who knew that one could develop warm feelings for a German Federal Employment Agency chatbot? If you own a business and wish to apply for state funds to supplement your employees’ reduced salaries, then UDO will fill in the application form for you. “Let’s go!” the digital assistant declares, launching into a series of questions. The system displays reassuring expertise; the queries—about the size of your workforce, the extent of the reduction in working hours, and so on—are simple, clear, and sensitive to previous responses, and the interface offers soothing blue tones and rounded edges. UDO goes on to ask why the workers are on reduced hours: for economic reasons, such as the cancellation of a large order due to the coronavirus, or because of an unavoidable event, such as a measure to mitigate the spread of the pandemic? And by now, a powerful and comforting thought may well arise in the citizen’s mind: UDO really cares.
In this article, we argue that smart use of automation can enable governments to provide outstanding levels of customer experience, driven by innovations that are as sensitive to people as they are to technology. We begin by considering the challenges and rewards of enhancing customer experience for governments. Then we discuss the benefits to governments of using automation to improve customer experience. Finally, we turn from why to how, identifying three key practices common to successful automation initiatives in public services….(More)”.
Mozilla: “Timely and open access to novel outputs is key to scientific research. It allows scientists to reproduce, test, and build on one another’s work — and ultimately unlock progress.
The most recent example of this is the research into COVID-19. Much of the work was published in open access journals, swiftly reviewed and ultimately improving our understanding of how to slow the spread and treat the disease. Although this rapid increase in scientific publications is evident in other domains too, we might not be reaping the benefits. The tools to parse and combine this newly created knowledge have roughly remained the same for years.
Today, Mozilla Fellow Kostas Stathoulopoulos is launching Orion — an open-source tool to illuminate the science behind the science and accelerate knowledge discovery in the life sciences. Orion enables users to monitor progress in science, visually explore the scientific landscape, and search for relevant publications.
Orion collects, enriches and analyses scientific publications in the life sciences from Microsoft Academic Graph.
Users can leverage Orion’s views to interact with the data. The Exploration view shows all of the academic publications in a three-dimensional visualization. Every particle is a paper and the distance between them signifies their semantic similarity; the closer two particles are, the more semantically similar. The Metrics view visualizes indicators of scientific progress and how they have changed over time for countries and thematic topics. The Search view enables the users to search for publications by submitting either a keyword or a longer query, for example, a sentence or a paragraph of a blog they read online….(More)”.
Article by Eliza McCullough: “….Instead of a smart city model that extracts from, surveils, and displaces poor people of color, we need a democratic model that allows community members to decide how technological infrastructure operates and to ensure the equitable distribution of benefits. Doing so will allow us to create cities defined by inclusion, shared ownership, and shared prosperity.
In 2016, Barcelona, for example, launched its Digital City Plan, which aims to empower residents with control of technology used in their communities. The document incorporates over 8,000 proposals from residents and includes plans for open source software, government ownership of all ICT infrastructure, and a pilot platform to help citizens maintain control over their personal data. As a result, the city now has free applications that allow residents to easily propose city development ideas, actively participate in city council meetings, and choose how their data is shared.
In the U.S., we need a framework for tech sovereignty that incorporates a racial equity approach: In a racist society, race neutrality facilitates continued exclusion and exploitation of people of color. Digital Justice Lab in Toronto illustrates one critical element of this kind of approach: access to information. In 2018, the organization gave community groups a series of grants to hold public events that shared resources and information about digital rights. Their collaborative approach intentionally focuses on the specific needs of people of color and other marginalized groups.
The turn toward intensified surveillance infrastructure in the midst of the coronavirus outbreak makes the need to adopt such practices all the more crucial. Democratic tech models that uplift marginalized populations provide us the chance to build a city that is just and open to everyone….(More)”.
Paper by Ciara Greene and Gillian Murphy: “Previous research has argued that fake news may have grave consequences for health behaviour, but surprisingly, no empirical data have been provided to support this assumption. This issue takes on new urgency in the context of the coronavirus pandemic. In this large preregistered study (N = 3746) we investigated the effect of exposure to fabricated news stories about COVID-19 on related behavioural intentions. We observed small but measurable effects on some related behavioural intentions but not others – for example, participants who read a story about problems with a forthcoming contact-tracing app reported reduced willingness to download the app. We found no effects of providing a general warning about the dangers of online misinformation on response to the fake stories, regardless of the framing of the warning in positive or negative terms. We conclude with a call for more empirical research on the real-world consequences of fake news….(More)”
Matthew Hutson at IEEE Spectrum: “…Researchers say they’ve learned a lot of lessons modeling this pandemic, lessons that will carry over to the next.
The first set of lessons is all about data. Garbage in, garbage out, they say. Jarad Niemi, an associate professor of statistics at Iowa State University who helps run the forecast hub used by the CDC, says it’s not clear what we should be predicting. Infections, deaths, and hospitalization numbers each have problems, which affect their usefulness not only as inputs for the model but also as outputs. It’s hard to know the true number of infections when not everyone is tested. Deaths are easier to count, but they lag weeks behind infections. Hospitalization numbers have immense practical importance for planning, but not all hospitals release those figures. How useful is it to predict those numbers if you never have the true numbers for comparison? What we need, he said, is systematized random testing of the population, to provide clear statistics of both the number of people currently infected and the number of people who have antibodies against the virus, indicating recovery. Prakash, of Georgia Tech, says governments should collect and release data quickly in centralized locations. He also advocates for central repositories of policy decisions, so modelers can quickly see which areas are implementing which distancing measures.
Researchers also talked about the need for a diversity of models. At the most basic level, averaging an ensemble of forecasts improves reliability. More important, each type of model has its own uses—and pitfalls. An SEIR model is a relatively simple tool for making long-term forecasts, but the devil is in the details of its parameters: How do you set those to match real-world conditions now and into the future? Get them wrong and the model can head off into fantasyland. Data-driven models can make accurate short-term forecasts, and machine learning may be good for predicting complicated factors. But will the inscrutable computations of, for instance, a neural network remain reliable when conditions change? Agent-based models look ideal for simulating possible interventions to guide policy, but they’re a lot of work to build and tricky to calibrate.
Finally, researchers emphasize the need for agility. Niemi of Iowa State says software packages have made it easier to build models quickly, and the code-sharing site GitHub lets people share and compare their models. COVID-19 is giving modelers a chance to try out all their newest tools, says Meyers, of the University of Texas. “The pace of innovation, the pace of development, is unlike ever before,” she says. “There are new statistical methods, new kinds of data, new model structures.”…(More)”.
Poster by Geoffrey Henry Siwo: The promise of artificial intelligence (AI) in medicine is advancing rapidly driven by exponential growth in computing speed, data and new modeling techniques such as deep learning. Unfortunately, advancements in AI stand to disproportionately benefit diseases that predominantly affect the developed world because the key ingredients for AI – computational resources, big data and AI expertise – are less accessible in the developing world. Our research on automated mining of biomedical literature indicates that adoption of machine learning algorithms in global health, for example to understand malaria, lags several years behind diseases like cancer.
To shift these inequities, we have been exploring the use of crowdsourced data science challenges as a means to rapidly advance computational models in global health. Data science challenges involve seeking computational solutions for specific, well-defined questions from anyone in the world. Here we describe key lessons from our work in this area and the potential value of data science challenges in accelerating AI for global health.
In one of our first initiatives in this area – the Malaria DREAM Challenge – we invited data scientists from across the world to develop computational models that predict the in vitro and in vivo drug sensitivity of malaria parasites to artemisinin using gene expression datasets. More than 360 individuals drawn from academia, government and startups across 31 countries participated in the challenge. Approximately 100 computational solutions to the problem were generated within a period of 3 months. In addition to this sheer volume of participation, a diverse range of modeling approaches including artificial neural networks and automated machine learning were employed….(More)”.
Book by Bharat Vagadia: “Implications and opportunities for Economies, Society, Policy Makers and Business Leaders: “This book goes beyond the hype, delving into real world technologies and applications that are driving our future and examines the possible impact these changes will have on industries, economies and society at large. It details the actions governments and regulators must take in order to ensure these changes bring about positive benefits to the public without stifling innovation that may well be the future source of value creation. It examines how organisations in a world of digital ecosystems, where industry boundaries are blurring, must undertake radical digital transformation to survive and thrive in this new digital world. The reader is taken through a framework that critically examines (i) Digital Connectivity including 5G and IoT; (ii) Data Capture and Distribution which includes smart connected verticals; (iii) Data Integrity, Control and Tokenisation that includes cyber security, digital signatures, blockchain, smart contracts, digital assets and cryptocurrencies; (iv) Data Processing and Artificial Intelligence; and (v) Disruptive Applications which include platforms, virtual and augmented reality, drones, autonomous vehicles, digital twins and digital assistants…(More)”.
Book edited by Martin Paul Eve and Jonathan Gray: “The Open Access Movement proposes to remove price and permission barriers for accessing peer-reviewed research work—to use the power of the internet to duplicate material at an infinitesimal cost-per-copy. In this volume, contributors show that open access does not exist in a technological or policy vacuum; there are complex social, political, cultural, philosophical, and economic implications for opening research through digital technologies. The contributors examine open access from the perspectives of colonial legacies, knowledge frameworks, publics and politics, archives and digital preservation, infrastructures and platforms, and global communities.
he contributors consider such topics as the perpetuation of colonial-era inequalities in research production and promulgation; the historical evolution of peer review; the problematic histories and discriminatory politics that shape our choices of what materials to preserve; the idea of scholarship as data; and resistance to the commercialization of platforms. Case studies report on such initiatives as the Making and Knowing Project, which created an openly accessible critical digital edition of a sixteenth-century French manuscript, the role of formats in Bruno Latour’s An Inquiry into Modes of Existence, and the Scientific Electronic Library Online (SciELO), a network of more than 1,200 journals from sixteen countries. Taken together, the contributions represent a substantive critical engagement with the politics, practices, infrastructures, and imaginaries of open access, suggesting alternative trajectories, values, and possible futures…(More)”.
Book edited by John R. Vacca: “… the most complete guide for integrating next generation smart city technologies into the very foundation of urban areas worldwide, showing how to make urban areas more efficient, more sustainable, and safer. Smart cities are complex systems of systems that encompass all aspects of modern urban life. A key component of their success is creating an ecosystem of smart infrastructures that can work together to enable dynamic, real-time interactions between urban subsystems such as transportation, energy, healthcare, housing, food, entertainment, work, social interactions, and governance. Solving Urban Infrastructure Problems Using Smart City Technologies is a complete reference for building a holistic, system-level perspective on smart and sustainable cities, leveraging big data analytics and strategies for planning, zoning, and public policy. It offers in-depth coverage and practical solutions for how smart cities can utilize resident’s intellectual and social capital, press environmental sustainability, increase personalization, mobility, and higher quality of life….(More)”