Stefaan Verhulst

Paper by Pablo Aragon, Adriana Alvarado Garcia, Christopher A. Le Dantec, Claudia Flores-Saviaga, and Jorge Saldivar: “Over the last years, civic technology projects have emerged around the world to advance open government and community action. Although Computer-Supported Cooperative Work (CSCW) and Human-Computer Interaction (HCI) communities have shown a growing interest in researching issues around civic technologies, yet most research still focuses on projects from the Global North. The goal of this workshop is, therefore, to advance CSCW research by raising awareness for the ongoing challenges and open questions around civic technology by bridging the gap between researchers and practitioners from different regions.

The workshop will be organized around three central topics: (1) discuss how the local context and infrastructure affect the design, implementation, adoption, and maintenance of civic technology; (2) identify key elements of the configuration of trust among government, citizenry, and local organizations and how these elements change depending on the sociopolitical context where community engagement takes place; (3) discover what methods and strategies are best suited for conducting research on civic technologies in different contexts. These core topics will be covered across sessions that will initiate in-depth discussions and, thereby, stimulate collaboration between the CSCW research community and practitioners of civic technologies from both Global North and South….(More)”.

Paper by Nikolaos Yiannakoulias, Catherine E. Slavik, Shelby L. Sturrock, J. Connor Darlington: “Governments around the world have made data on COVID-19 testing, case numbers, hospitalizations and deaths openly available, and a breadth of researchers, media sources and data scientists have curated and used these data to inform the public about the state of the coronavirus pandemic. However, it is unclear if all data being released convey anything useful beyond the reputational benefits of governments wishing to appear open and transparent. In this analysis we use Ontario, Canada as a case study to assess the value of publicly available SARS-CoV-2 positive case numbers. Using a combination of real data and simulations, we find that daily publicly available test results probably contain considerable error about individual risk (measured as proportion of tests that are positive, population based incidence and prevalence of active cases) and that short term variations are very unlikely to provide useful information for any plausible decision making on the part of individual citizens. Open government data can increase the transparency and accountability of government, however it is essential that all publication, use and re-use of these data highlight their weaknesses to ensure that the public is properly informed about the uncertainty associated with SARS-CoV-2 information….(More)”

Essay by Luc de Brabandere: “The history of computer science did not begin eighty years ago with the creation of the first electronic computer. To program a computer to process information – or in other words, to simulate thought – we need to be able to understand, dismantle and disassemble thoughts. In IT-speak, in order to encrypt a thought, we must first be able to decrypt it! And this willingness to analyse thought already existed in ancient times. So the principles, laws, and concepts that underlie computer science today originated in an era when the principles of mathematics and logic each started on their own paths, around their respective iconic thinkers, such as Plato and Aristotle. Indeed, the history of computer science could be described as fulfilling the dream of bringing mathematics and logic together. This dream was highlighted for the first time during the thirteenth century by Raymond Lulle, a theologian and missionary from Majorca, but it became the dream of Gottfried Leibniz in particular. This German philosopher wondered why these two fields had evolved side by side separately since ancient times, when both seemed to strive for the same goal. Mathematicians and logicians both wish to establish undeniable truths by fighting against errors of reasoning and implementing precise laws of correct thinking. The Hungarian journalist, essayist and Nobel laureate Arthur Koestler called this shock (because it always is a shock) of an original pairing of two apparently very separate things a bisociation.

We know today that the true and the demonstrable will always remain distinct, so to that extent, logic and mathematics will always remain fundamentally irreconcilable. In this sense Leibniz’s dream will never come true. But three other bisociations, admittedly less ambitious, have proved to be very fruitful, and they structure this short history. Famous Frenchman René Descartes reconciled algebra and geometry; the British logician George Boole brought algebra and logic together; and an American engineer from MIT, Claude Shannon, bisociated binary calculation with electronic relays.

Presented as such, the history of computer science resembles an unexpected remake of Four Weddings and a Funeral! Let’s take a closer look….(More)”.

Introduction to Special Issue of California Management Review by Anita M. McGahan, Marcel L. A. M. Bogers, Henry Chesbrough, and Marcus Holgersson: “Open innovation includes external knowledge sources and paths to market as complements to internal innovation processes. Open innovation has to date been driven largely by business objectives, but the imperative of social challenges has turned attention to the broader set of goals to which open innovation is relevant. This introduction discusses how open innovation can be deployed to address societal challenges—as well as the trade-offs and tensions that arise as a result. Against this background we introduce the articles published in this Special Section, which were originally presented at the sixth Annual World Open Innovation Conference….(More)”.

About: “As of December 2020, we have built a robust, open-source architecture to discover and explore nearly a half million people records and 5 million data points. From archival fragments and spreadsheet entries, we see the lives of the enslaved in richer detail. Yet there’s much more work to do, and with the help of scholars, educators, and family historians, Enslaved.org will be rapidly expanding in 2021. We are just getting started….

In recent years, a growing number of archives, databases, and collections that organize and make sense of records of enslavement have become freely and readily accessible for scholarly and public consumption. This proliferation of projects and databases presents a number of challenges:

• Disambiguating and merging individuals across multiple datasets is nearly impossible given their current, siloed nature;
• Searching, browsing, and quantitative analysis across projects is extremely difficult;
• It is often difficult to find projects and databases;
• There are no best practices for digital data creation;
• Many projects and datasets are in danger of going offline and disappearing.

In response to these challenges, Matrix: The Center for Digital Humanities & Social Sciences at Michigan State University (MSU), in partnership with the MSU Department of History, University of Maryland, and scholars at multiple institutions, developed Enslaved: Peoples of the Historical Slave Trade. Enslaved.org’s primary focus is people—individuals who were enslaved, owned slaves, or participated in slave trading….(More)”.

Report by the Center for Data Ethics and Innovation (CDEI) (UK): “Unfair biases, whether conscious or unconscious, can be a problem in many decision-making processes. This review considers the impact that an increasing use of algorithmic tools is having on bias in decision-making, the steps that are required to manage risks, and the opportunities that better use of data offers to enhance fairness. We have focused on the use of
algorithms in significant decisions about individuals, looking across four sectors (recruitment, financial services, policing and local government), and making cross-cutting recommendations that aim to help build the right systems so that algorithms improve, rather than worsen, decision-making…(More)”.

Essay by Samanth Subramanian: “Whenever President Donald Trump is questioned about why the United States has nearly three times more coronavirus cases than the entire European Union, or why hundreds of Americans are still dying every day, he whips out one standard comment. We find so many cases, he contends, because we test so many people. The remark typifies Trump’s deep distrust of data: his wariness of what it will reveal, and his eagerness to distort it. In April, when he refused to allow coronavirus-stricken passengers off the Grand Princess cruise liner and onto American soil for medical treatment, he explained: “I like the numbers where they are. I don’t need to have the numbers double because of one ship.” Unable—or unwilling—to fix the problem, Trump’s instinct is to fix the numbers instead.

The administration has failed on so many different fronts in its handling of the coronavirus, creating the overall impression of sheer mayhem. But there is a common thread that runs through these government malfunctions. Precise, transparent data is crucial in the fight against a pandemic—yet through a combination of ineptness and active manipulation, the government has depleted and corrupted the key statistics that public health officials rely on to protect us.

In mid-July, just when the U.S. was breaking and rebreaking its own records for daily counts of new coronavirus cases, the Centers for Disease Control and Prevention found itself abruptly relieved of its customary duty of collating national numbers on COVID-19 patients. Instead, the Department of Health and Human Services instructed hospitals to funnel their information to the government via TeleTracking, a small Tennessee firm started by a real estate entrepreneur who has frequently donated to the Republican Party. For a while, past data disappeared from the CDC’s website entirely, and although it reappeared after an outcry, it was never updated thereafter. The TeleTracking system was riddled with errors, and the newest statistics sometimes appeared after delays. This has severely limited the ability of public health officials to determine where new clusters of COVID-19 are blooming, to notice demographic patterns in the spread of the disease, or to allocate ICU beds to those who need them most.

To make matters more confusing still, Jared Kushner moved to start a separate coronavirus surveillance system run out of the White House and built by health technology giants—burdening already-overwhelmed officials and health care experts with a needless stream of queries. Kushner’s assessments often contradicted those of agencies working on the ground. When Andrew Cuomo, New York’s governor, asked for 30,000 ventilators, Kushner claimed the state didn’t need them: “I’m doing my own projections, and I’ve gotten a lot smarter about this.”…(More)”.

OECD: “…we released the third and latest edition of the OECD Digital Economy Outlook, our comprehensive analysis of emerging trends, opportunities and challenges in the digital economy….

Below are four key findings from this year’s Outlook. Find out more in our full publication and watch our virtual launch event here.

• Widespread connectivity has allowed many to adapt to the crisis

Our report finds that connectivity has continued to improve over time. Mobile broadband subscriptions nearly tripled between 2009 and June 2019, rising from 32 to nearly 113 subscriptions per 100 inhabitants, while average mobile data usage quadrupled over the course of four years, reaching 4.6 GB in 2018. Although fibre connections have increased at a slower rate, by June 2019 they accounted for 27% of all fixed broadband connections in the OECD and no less than 50% in nine OECD countries.

• But there are still significant divides in access, use and skills…

• Governments are increasingly putting the digital transformation front and centre

By mid-2020, 34 OECD countries had put in place a national digital strategy co-ordinated at the highest levels of government, and they are devoting more attention to emerging digital technologies such as AI, blockchain and 5G infrastructure. By mid-2020, 60 countries had established a national AI strategy, and several OECD countries – Australia, Austria, Colombia, France, Germany, Korea, Spain, the United Kingdom and the United States – have issued national 5G strategies. Several countries – Australia, People’s Republic of China, Germany, India and Switzerland – have issued a blockchain strategy, while others (France and Italy) are currently developing one.

• But more needs to be done to ensure an inclusive digital transformation…(More)”.

Tool developed by GODAN: “Codes of conduct, voluntary guidelines and sets of principles around how to transparently govern farm data are a recent thing. While laws and regulations that govern personal data are becoming more and more common, legislation still does not cover data flows in many industries where different actors in the value chain need to share data while protecting all involved from the risks of data sharing. Data in these value chains is currently governed through private data contracts and licensing agreements, which are normally very complex and over which data producers have very little negotiating power.

Codes of conduct have started to emerge to fill the legislative void, setting common standards for data sharing contracts. Codes provide principles that the signatories agree to apply in their contracts. Farm data is an example of such sensitive data flows. Farm data flows go from the farm through many other actors (extensionists/ advisory service providers/ ag tech companies, farmers’ associations, financial service providers, government…), before returning – aggregated and combined and in the form of services – back to the farm. Such flows potentially open up sensitive data that should only be shared with specific actors under specific conditions, or should be anonymised in order to avoid harming the farmer’s interests and privacy. This is especially true in the case of smallholder farmers, whose farm data often coincides with household data and personal data, and who are in the weakest position to negotiate their data rights.

This online tool, therefore, also has another important practical purpose: providing the conceptual basis for general, scalable guidelines for everyone dealing with the production, ownership, sharing and use of data in agriculture….(More)”.

Book by Hélène Landemore: “To the ancient Greeks, democracy meant gathering in public and debating laws set by a randomly selected assembly of several hundred citizens. To the Icelandic Vikings, democracy meant meeting every summer in a field to discuss issues until consensus was reached. Our contemporary representative democracies are very different. Modern parliaments are gated and guarded, and it seems as if only certain people—with the right suit, accent, wealth, and connections—are welcome. Diagnosing what is wrong with representative government and aiming to recover some of the lost openness of ancient democracies, Open Democracy presents a new paradigm of democracy in which power is genuinely accessible to ordinary citizens.

Hélène Landemore favors the ideal of “representing and being represented in turn” over direct-democracy approaches. Supporting a fresh nonelectoral understanding of democratic representation, Landemore recommends centering political institutions around the “open mini-public”—a large, jury-like body of randomly selected citizens gathered to define laws and policies for the polity, in connection with the larger public. She also defends five institutional principles as the foundations of an open democracy: participatory rights, deliberation, the majoritarian principle, democratic representation, and transparency.

Open Democracy demonstrates that placing ordinary citizens, rather than elites, at the heart of democratic power is not only the true meaning of a government of, by, and for the people, but also feasible and, today more than ever, urgently needed….(More)”.