Stefaan Verhulst
Report by Greg Feldberg: “The COVID-19 market disruption again highlighted the flaws in the data that the public and the authorities use to assess risks in the financial system. We don’t have the right data, we can’t analyze the data we do have, and there are all sorts of holes. Amidst extreme uncertainty in times like this, market participants need better data to manage their risks, just as policymakers need better data to calibrate their crisis interventions. This paper argues that the new administration should make it a priority to fix financial regulatory data, starting during the transition.
The incoming administration should, first, emphasize data when vetting candidates for top financial regulatory positions. Every agency head should recognize the problem and the roles they must play in the solution. They should recognize how the Evidence Act of 2018 and other recent legislation help define those roles. And every agency head should recognize the role of the Office of Financial Research (OFR) within the regulatory community. Only the OFR has the mandate and experience to provide the necessary leadership to address these problems.
The incoming administration should empower the OFR to do its job and coordinate a systemwide financial data strategy, working with the regulators. That strategy should set a path for identifying key data gaps that impede risk analysis; setting data standards; sharing data securely, among authorities and with the public; and embracing new technologies that make it possible to manage data far more efficiently and securely than ever before. These are ambitious goals, but the administration may be able to accomplish them with vision and leadership…(More)”.
Barry Bozeman in Issues in Science and Technology: “Why should the United States government support science? That question was apparently settled 75 years ago by Vannevar Bush in Science, the Endless Frontier: “Since health, well-being, and security are proper concerns of Government, scientific progress is, and must be, of vital interest to Government. Without scientific progress the national health would deteriorate; without scientific progress we could not hope for improvement in our standard of living or for an increased number of jobs for our citizens; and without scientific progress we could not have maintained our liberties against tyranny.”
Having dispensed with the question of why, all that remained was for policy-makers to decide, how much? Even at the dawn of modern science policy, costs and funding needs were at the center of deliberations. Though rarely discussed anymore, Endless Frontier did give specific attention to the question of how much. The proposed amounts seem, by today’s standards, modest: “It is estimated that an adequate program for Federal support of basic research in the colleges, universities, and research institutes and for financing important applied research in the public interest, will cost about 10 million dollars at the outset and may rise to about 50 million dollars annually when fully underway at the end of perhaps 5 years.”
In today’s dollars, $50 million translates to about $535 million, or less than 2% of what the federal government actually spent for basic research in 2018. One way to look at the legacy of Endless Frontier is that by answering the why question so convincingly, it logically followed that the how much question could always be answered simply by “more.”
In practice, however, the why question continues to seem so self-evident because it fails to consider a third question, who? As in, who benefits from this massive federal investment in research, and who does not? The question of who was also seemingly answered by Endless Frontier, which not only offered full employment as a major goal for expanded research but also embraced “the sound democratic principle that there should be no favored classes or special privilege.”
But I argue that this principle has now been soundly falsified. In an economic environment characterized by growth but also by extreme inequality, science and technology not only reinforce inequality but also, in some instances, help widen the gap. Science and technology can be a regressivefactor in the economy. Thus, it is time to rethink the economic equation justifying government support for science not just in terms of why and how much, but also in terms of who.
What logic supports my claim that under conditions of conspicuous inequality, science and technology research is often a regressive force? Simple: except in the case of the most basic of basic research (such as exploration of other galaxies), effects are never randomly distributed. Both the direct and indirect effects of science and technology tend to differentially affect citizens according to their socioeconomic power and purchasing power….(More)”.
Report by the Open Data Watch: “The 2020/21 Open Data Inventory (ODIN) is the fifth edition of the index compiled by Open Data Watch. ODIN 2020/21 provides an assessment of the coverage and openness of official statistics in 187 countries, an increase of 9 countries compared to ODIN 2018/19. The year 2020 was a challenging year for the world as countries grappled with the COVID-19 pandemic. Nonetheless, and despite the pandemic’s negative impact on the capacity of statistics producers, 2020 saw great progress in open data.
However, the news on data this year isn’t all good. Countries in every region still struggle to publish gender data and many of the same countries are unable to provide sex-disaggregated data on the COVID-19 pandemic. In addition, low-income countries continue to need more support with capacity building and financial resources to overcome the barriers to publishing open data.
ODIN is an evaluation of the coverage and openness of data provided on the websites maintained by national statistical offices (NSOs) and any official government website that is accessible from the NSO site. The overall ODIN score is an indicator of how complete and open an NSO’s data offerings are. It is comprised of both a coverage and openness subscore. Openness is measured against standards set by the Open Definition and Open Data Charter. ODIN 2020/21 includes 22 data categories, grouped under social, economic and financial, and environmental statistics. ODIN scores are represented on a range between 0 and 100, with 100 representing the best performance on open data… The full report will be released in February 2021….(More)”.
Essay by Crawford Hollingworth and Liz Barker: “…Both of these stories are illustrations of what many mums and gym–goers may have experienced across the United Kingdom and United States as they tried to cope with the pandemic. We, along with other behavioral scientists, would label both as sludge—when users face high levels of friction obstructing their efforts to achieve something that is in their best interest, or are misled or encouraged to take action that is not in their best interest.
We can think of what the English mum goes through as unintentional sludge—friction due to factors like rushed design, poor infrastructure, and inadequate oversight. The mother is trying to access a benefit that will help her and which she has a right to claim, and which the government genuinely wants her to access. Yet multiple barriers prevented her from accessing the voucher that would help feed her children. Millions of parents found themselves in this situation as schools closed in England earlier this year. All over the country schools ended up paying for food parcels and gift vouchers out of their own budgets to help families who were going hungry.
What the New York gym-goer faces is different. It is intentional sludge—friction put in place knowingly to benefit an organization at the expense of the user. The gym doesn’t want him to cancel the membership, which would mean lost revenue. Even absent the pandemic, the policy would be considered unnecessarily difficult to cancel. The gym’s hope is that people forget, give up, or don’t bother canceling in person or over the phone, or that it takes them longer to do so. This translates into revenue for them, without any of the costs of providing a service. Stories like this have resulted in class-action lawsuits against companies that make it overly difficult or impossible to cancel gym memberships. One lawsuit alleged that one large gym company was stealing over $30 million per month from customers….(More)”.
Paper by Elizabeth Nelson and Frances Burns: “The Administrative Data Research Centre Northern Ireland (ADRC NI) is a research partnership between Queen’s University Belfast and Ulster University to facilitate access to linked administrative data for research purposes for public benefit and for evidence-based policy development. This requires a social licence extended by publics which is maintained by a robust approach to engagement and involvement.
Public engagement is central to the ADRC NI’s approach to research. Research impact is pursued and secured through robust engagement and co-production of research with publics and key stakeholders. This is done by focusing on data subjects (the cohort of people whose lives make up the datasets, placing value on experts by experience outside of academic knowledge, and working with public(s) as key data advocates, through project steering committees and targeted events with stakeholders. The work is led by a dedicated Public Engagement, Communications and Impact Manager.
While there are strengths and weaknesses to the ADRC NI approach, examples of successful partnerships and clear pathways to impact demonstrate its utility and ability to amplify the positive impact of administrative data research. Working with publics as data use becomes more ubiquitous in a post-COVID-19 world will become more critical. ADRC NI’s model is a potential way forward….(More)”.
See also Special Issue on Public Involvement and Engagement by the International Journal of Population Data Science.
Report for the Royal Society: “The UK is well behind other countries in making use of data to have a real time understanding of the spread and economic impact of the pandemic according to Data Evaluation and Learning for Viral Epidemics (DELVE), a multi-disciplinary group convened by the Royal Society.
The report, Data Readiness: Lessons from an Emergency, highlights how data such as aggregated and anonymised mobility and payment transaction data, already gathered by companies, could be used to give a more accurate picture of the pandemic at national and local levels. That could in turn lead to improvements in evaluation and better targeting of interventions.
Maximising the value of big data at a time of crisis requires careful cooperation across the private sector, that is already gathering these data, the public sector, which can provide a base for aggregating and overseeing the correct use of the data and researchers who have the skills to analyse it for the public good. This work needs to be developed in accordance with data protection legislation and respect people’s concerns about data security and privacy.
The report calls on the Government to extend the powers of the Office for National Statistics to enable them to support trustworthy access to ‘happenstance’ data – data that are already gathered but not for a specific public health purpose – and for the Government to fund pathfinder projects that focus on specific policy questions such as how we nowcast economic metrics and how we better understand population movements.
Neil Lawrence, DeepMind Professor of Machine Learning at the University of Cambridge, Senior AI Fellow at The Alan Turing Institute and an author of the report, said: “The UK has talked about making better use of data for the public good, but we have had statements of good intent, rather than action. We need to plan better for national emergencies. We need to look at the National Risk Register through the lens of what data would help us to respond more effectively. We have to learn our lessons from experiences in this pandemic and be better prepared for future crises. That means doing the work now to ensure that companies, the public sector and researchers have pathfinder projects up and running to share and analyse data and help the government to make better informed decisions.”
During the pandemic, counts of the daily flow of people from one place to another between more than 3000 districts in Spain have been available at the click of a button, allowing policy makers to more effectively understand how the movement of people contributes to the spread of the virus. This was based on a collaboration between the country’s three main mobile phone operators. In France, measuring the impact of the pandemic on consumer spending on a daily and weekly scale was possible as a result of coordinated cooperation between the country’s national interbank network.
Professor Lawrence added: “Mobile phone companies might provide a huge amount of anonymised and aggregated data that would allow us a much greater understanding of how people move around, potentially spreading the virus as they go. And there is a wealth of other data, such as from transport systems. The more we understand about this pandemic, the better we can tackle it. We should be able to work together, the private and the public sectors, to harness big data for massive positive social good and do that safely and responsibly.”…(More)”
About: “We exist to make meaningful climate action faster and easier by mobilizing the global tech community—harnessing satellites, artificial intelligence, and collective expertise—to track human-caused emissions to specific sources in real time—independently and publicly.
Climate TRACE aims to drive stronger decision-making on environmental policy, investment, corporate sustainability strategy, and more.
WHAT WE DO
01 Monitor human-caused GHG emissions using cutting-edge technologies such as artificial intelligence, machine learning, and satellite image processing.
02 Collaborate with data scientists and emission experts from an array of industries to bring unprecedented transparency to global pollution monitoring.
03 Partner with leaders from the private and public sectors to share valuable insights in order to drive stronger climate policy and strategy.
04 Provide the necessary tools for anyone anywhere to make better decisions to mitigate and adapt to the impacts from climate change… (More)”
Book by Petros Iosifidis and Nicholas Nicoli: “Digital Democracy, Social Media and Disinformation discusses some of the political, regulatory and technological issues which arise from the increased power of internet intermediaries (such as Facebook, Twitter and YouTube) and the impact of the spread of digital disinformation, especially in the midst of a health pandemic.
The volume provides a detailed account of the main areas surrounding digital democracy, disinformation and fake news, freedom of expression and post-truth politics. It addresses the major theoretical and regulatory concepts of digital democracy and the ‘network society’ before offering potential socio-political and technological solutions to the fight against disinformation and fake news. These solutions include self-regulation, rebuttals and myth-busting, news literacy, policy recommendations, awareness and communication strategies and the potential of recent technologies such as the blockchain and public interest algorithms to counter disinformation.
After addressing what has currently been done to combat disinformation and fake news, the volume argues that digital disinformation needs to be identified as a multifaceted problem, one that requires multiple approaches to resolve. Governments, regulators, think tanks, the academy and technology providers need to take more steps to better shape the next internet with as little digital disinformation as possible by means of a regional analysis. In this context, two cases concerning Russia and Ukraine are presented regarding disinformation and the ways it was handled….(More)”
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)”