Improving Governance by Asking Questions that Matter

Curated on Posted on by Stefaan Verhulst

Fiona Cece, Nicola Nixon and Stefaan Verhulst at the Open Government Partnership:

“You can tell whether a man is clever by his answers. You can tell whether a man is wise by his questions” – Naguib Mahfouz

Data is at the heart of every dimension of the COVID-19 challenge. It’s been vital in the monitoring of daily rates, track and trace technologies, doctors appointments, and the vaccine roll-out. Yet our daily diet of brightly-coloured graphed global trends masks the maelstrom of inaccuracies, gaps and guesswork that underlies the ramshackle numbers on which they are so often based. Governments are unable to address their citizens’ needs in an informed way when the data itself is partial, incomplete or simply biased. And citizens’ in turn are unable to contribute to collective decision-making that impacts their lives when the channels for doing so in meaningful ways are largely non-existent. 

There is an irony here. We live in an era in which there are an unprecedented number of methods for collecting data. Even in the poorest countries with weak or largely non-existent government systems, anyone with a mobile phone or who accesses the internet is using and producing data. Yet a chasm exists between the potential of data to contribute to better governance and what it is actually collected and used for.

Even where data accuracy can be relied upon, the practice of effective, efficient and equitable data governance requires much more than its collection and dissemination.

And although governments will play a vital role, combatting the pandemic and its associated socio-economic challenges will require the combined efforts of non-government organizations (NGOs), civil society organizations (CSOs), citizens’ associations, healthcare companies and providers, universities, think tanks and so many others. Collaboration is key.

There is a need to collectively move beyond solution-driven thinking. One initiative working toward this end is The 100 Questions Initiative by The Governance Lab (The GovLab) at the NYU Tandon School of Engineering. In partnership with the The Asia Foundation, the Centre for Strategic and International Studies in Indonesia, and the BRAC Institute of Governance and Development, the Initiative is launching a Governance domain. Collectively we will draw on the expertise of over 100 “bilinguals”– experts in both data science and governance — to identify the 10 most-pressing questions on a variety of issues that can be addressed using data and data science. The cohort for this domain is multi-sectoral and geographically varied, and will provide diverse input on these governance challenges. 

Once the questions have been identified and prioritized, and we have engaged with a broader public through a voting campaign, the ultimate goal is to establish one or more data collaboratives that can generate answers to the questions at hand. Data collaboratives are an emerging structure that allow pooling of data and expertise across sectors, often resulting in new insights and public sector innovations.  Data collaboratives are fundamentally about sharing and cross-sectoral engagement. They have been deployed across countries and sectoral contexts, and their relative success shows that in the twenty-first century no single actor can solve vexing public problems. The route to success lies through broad-based collaboration. 

Multi-sectoral and geographically diverse insight is needed to address the governance challenges we are living through, especially during the time of COVIDd-19. The pandemic has exposed weak governance practices globally, and collectively we need to craft a better response. As an open governance and data-for-development community, we have not yet leveraged the best insight available to inform an effective, evidence-based response to the pandemic. It is time we leverage more data and technology to enable citizen-centrism in our service delivery and decision-making processes, to contribute to overcoming the pandemic and to building our governance systems, institutions and structures back better. Together with over 130 ‘Bilinguals’ – experts in both governance and data – we have set about identifying the priority questions that data can answer to improve governance. Join us on this journey. Stay tuned for our public voting campaign in a couple of months’ time when we will crowdsource your views on which of the questions they pose really matter….(More)”.

The Landscape of Big Data and Gender

Curated on Posted on by Stefaan Verhulst

Report by Data2X: “This report draws out six observations about trends in big data and gender:

– The current environment COVID-19 and the global economic recession is stimulating groundbreaking gender research.

– Where we’re progressing, where we’re lagging Some gendered topics—especially mobility, health, and social norms—are increasingly well-studied through the combination of big data and traditional data. However, worrying gaps remain, especially around the subjects of economic opportunity, human security, and public participation.

– Capturing gender-representative samples using big data continues to be a challenge, but progress is being made.

– Large technology firms generate an immense volume of gender data critical for policymaking, and researchers are finding ways to reuse this data safely.

– Data collaboratives that bring private sector data-holders, researchers, and public policymakers together in a formal, enduring relationship can help big data make a practical difference in the lives of women and girls….(More)”

COVID vaccination studies: plan now to pool data, or be bogged down in confusion

Curated on Posted on by Stefaan Verhulst

Natalie Dean at Nature: “More and more COVID-19 vaccines are rolling out safely around the world; just last month, the United States authorized one produced by Johnson & Johnson. But there is still much to be learnt. How long does protection last? How much does it vary by age? How well do vaccines work against various circulating variants, and how well will they work against future ones? Do vaccinated people transmit less of the virus?

Answers to these questions will help regulators to set the best policies. Now is the time to make sure that those answers are as reliable as possible, and I worry that we are not laying the essential groundwork. Our current trajectory has us on course for confusion: we must plan ahead to pool data.

Many questions remain after vaccines are approved. Randomized trials generate the best evidence to answer targeted questions, such as how effective booster doses are. But for others, randomized trials will become too difficult as more and more people are vaccinated. To fill in our knowledge gaps, observational studies of the millions of vaccinated people worldwide will be essential….

Perhaps most importantly, we must coordinate now on plans to combine data. We must take measures to counter the long-standing siloed approach to research. Investigators should be discouraged from setting up single-site studies and encouraged to contribute to a larger effort. Funding agencies should favour studies with plans for collaborating or for sharing de-identified individual-level data.

Even when studies do not officially pool data, they should make their designs compatible with others. That means up-front discussions about standardization and data-quality thresholds. Ideally, this will lead to a minimum common set of variables to be collected, which the WHO has already hammered out for COVID-19 clinical outcomes. Categories include clinical severity (such as all infections, symptomatic disease or critical/fatal disease) and patient characteristics, such as comorbidities. This will help researchers to conduct meta-analyses of even narrow subgroups. Efforts are under way to develop reporting guidelines for test-negative studies, but these will be most successful when there is broad engagement.

There are many important questions that will be addressed only by observational studies, and data that can be combined are much more powerful than lone results. We need to plan these studies with as much care and intentionality as we would for randomized trials….(More)”.

Do conversations end when people want them to?

Curated on Posted on by Stefaan Verhulst

Paper by Adam M. Mastroianni et al: “Do conversations end when people want them to? Surprisingly, behavioral science provides no answer to this fundamental question about the most ubiquitous of all human social activities. In two studies of 932 conversations, we asked conversants to report when they had wanted a conversation to end and to estimate when their partner (who was an intimate in Study 1 and a stranger in Study 2) had wanted it to end. Results showed that conversations almost never ended when both conversants wanted them to and rarely ended when even one conversant wanted them to and that the average discrepancy between desired and actual durations was roughly half the duration of the conversation. Conversants had little idea when their partners wanted to end and underestimated how discrepant their partners’ desires were from their own. These studies suggest that ending conversations is a classic “coordination problem” that humans are unable to solve because doing so requires information that they normally keep from each other. As a result, most conversations appear to end when no one wants them to….(More)”.

Theories of Choice: The Social Science and the Law of Decision Making

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Book by Stefan Grundmann and Philipp Hacker: “Choice is a key concept of our time. It is a foundational mechanism for every legal order in societies that are, politically, constituted as democracies and, economically, built on the market mechanism. Thus, choice can be understood as an atomic structure that grounds core societal processes. In recent years, however, the debate over the right way to theorise choice—for example, as a rational or a behavioural type of decision making—has intensified. This collection therefore provides an in-depth discussion of the promises and perils of specific types of theories of choice. It shows how the selection of a specific theory of choice can make a difference for concrete legal questions, in particularly in the regulation of the digital economy or in choosing between market, firm, or network.

In its first part, the volume provides an accessible overview of the current debates about rational versus behavioural approaches to theories of choice. The remainder of the book structures the vast landscape of theories of choice along three main types: individual, collective, and organisational decision making. As theories of choice proliferate and become ever more sophisticated, however, the process of choosing an adequate theory of choice becomes increasingly intricate, too. This volume addresses this selection problem for the various legal arenas in which individual, organisational, and collective decisions matter. By drawing on economic, technological, political, and legal points of view, the volume shows which theories of choice are at the disposal of the legally relevant decision maker, and how they can be implemented for the solution of concrete legal problems….(More)“

Artificial Intelligence as an Anti-Corruption Tool (AI-ACT)

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Paper by Nils Köbis, Christopher Starke, and Iyad Rahwan: “Corruption continues to be one of the biggest societal challenges of our time. New hope is placed in Artificial Intelligence (AI) to serve as an unbiased anti-corruption agent. Ever more available (open) government data paired with unprecedented performance of such algorithms render AI the next frontier in anti-corruption. Summarizing existing efforts to use AI-based anti-corruption tools (AI-ACT), we introduce a conceptual framework to advance research and policy. It outlines why AI presents a unique tool for top-down and bottom-up anti-corruption approaches. For both approaches, we outline in detail how AI-ACT present different potentials and pitfalls for (a) input data, (b) algorithmic design, and (c) institutional implementation. Finally, we venture a look into the future and flesh out key questions that need to be addressed to develop AI-ACT while considering citizens’ views, hence putting “society in the loop”….(More)”.

Covid-19 Data Cards: Building a Data Taxonomy for Pandemic Preparedness

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Open Data Charter: “…We want to initiate the repair of the public’s trust through the building of a Pandemic Data Taxonomy with you — a network of data users and practitioners.

Building on feedback we got from our call to identify high value Open COVID-19 Data, we have structured a set of data cards, including key data types related to health issues, legal and socioeconomic impacts and fiscal transparency, within which are well-defined data models and dictionaries. Our target audience for this data taxonomy are governments. We are hoping this framework is a starting point towards building greater consistency around pandemic data release, and flag areas for better cooperation and standardisation within and between our governments and communities around the world.

We hope that together, with the input and feedback from a diverse group of data users and practitioners, we can have at the end of this public consultation and open-call, a document by a global collective, one that we can present to governments and public servants for their buy-in to reform our data infrastructures to be better prepared for future outbreaks.

In order to analyze the variables necessary to manage and investigate the different aspects of a pandemic, as exemplified by COVID-19, and based on a review of the type of data being released by 25 countries — we categorised the data in 4 major categories:

  • General — Contains the general concepts that all the files have in common and are defined, such as the METADATA, global sections of RISKS and their MITIGATION and the general STANDARDS required for the use, management and publication of the data. Then, a link to a spreadsheet, where more details of the precision, update frequency, publication methods and specific standards of each data set are defined.
  • Health Data — Describes how to manage and potentially publish the follow-up information on COVID-19 cases, considering data with temporal, geographical and demographic distribution along with the details for the study of the evolution of the disease.
  • Legal and Socioeconomic Impact Data — Contains the regulations, actions, measures, restrictions, protocols, documents and all the information regarding quarantine and the socio-economic impact as well as medical, labor or economic regulations for each data publisher.
  • Fiscal Data — Contains all budget allocations in accordance with the overall approved Pandemic budget, as well as the implemented adjustments. It also identifies specific allocations for facing prevention, detection, control, treatment and containment of the virus, as well as possible budget reallocations from other sectors or items derived from the actions mentioned above or by the derived economic constraints. It’s based on the recommendations made by GIFT and Open Contracting….(More)”

Resilience in the Digital Age

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Book edited by Fred S. Roberts and Igor A. Sheremet: “The growth of a global digital economy has enabled rapid communication, instantaneous movement of funds, and availability of vast amounts of information. With this come challenges such as the vulnerability of digitalized sociotechnological systems (STSs) to destructive events (earthquakes, disease events, terrorist attacks). Similar issues arise for disruptions to complex linked natural and social systems (from changing climates, evolving urban environments, etc.). This book explores new approaches to the resilience of sociotechnological and natural-social systems in a digital world of big data, extraordinary computing capacity, and rapidly developing methods of Artificial Intelligence….

The world-wide COVID-19 pandemic illustrates the vulnerability of our healthcare systems, supply chains, and social infrastructure, and confronts our notions of what makes a system resilient. We have found that use of AI tools can lead to problems when unexpected events occur. On the other hand, the vast amounts of data available from sensors, satellite images, social media, etc. can also be used to make modern systems more resilient.

Papers in the book explore disruptions of complex networks and algorithms that minimize departure from a previous state after a disruption; introduce a multigrammatical framework for the technological and resource bases of today’s large-scale industrial systems and the transformations resulting from disruptive events; and explain how robotics can enhance pre-emptive measures or post-disaster responses to increase resiliency. Other papers explore current directions in data processing and handling and principles of FAIRness in data; how the availability of large amounts of data can aid in the development of resilient STSs and challenges to overcome in doing so. The book also addresses interactions between humans and built environments, focusing on how AI can inform today’s smart and connected buildings and make them resilient, and how AI tools can increase resilience to misinformation and its dissemination….(More)”.

E-mail Is Making Us Miserable

Curated on Posted on by Stefaan Verhulst

Cal Newport at The New Yorker: “In early 2017, a French labor law went into effect that attempted to preserve the so-called right to disconnect. Companies with fifty or more employees were required to negotiate specific policies about the use of e-mail after work hours, with the goal of reducing the time that workers spent in their in-boxes during the evening or over the weekend. Myriam El Khomri, the minister of labor at the time, justified the new law, in part, as a necessary step to reduce burnout. The law is unwieldy, but it points toward a universal problem, one that’s become harder to avoid during the recent shift toward a more frenetic and improvisational approach to work: e-mail is making us miserable.

To study the effects of e-mail, a team led by researchers from the University of California, Irvine, hooked up forty office workers to wireless heart-rate monitors for around twelve days. They recorded the subjects’ heart-rate variability, a common technique for measuring mental stress. They also monitored the employees’ computer use, which allowed them to correlate e-mail checks with stress levels. What they found would not surprise the French. “The longer one spends on email in [a given] hour the higher is one’s stress for that hour,” the authors noted. In another study, researchers placed thermal cameras below each subject’s computer monitor, allowing them to measure the tell-tale “heat blooms” on a person’s face that indicate psychological distress. They discovered that batching in-box checks—a commonly suggested “solution” to improving one’s experience with e-mail—is not necessarily a panacea. For those people who scored highly in the trait of neuroticism, batching e-mails actually made them more stressed, perhaps because of worry about all of the urgent messages they were ignoring. The researchers also found that people answered e-mails more quickly when under stress but with less care—a text-analysis program called Linguistic Inquiry and Word Count revealed that these anxious e-mails were more likely to contain words that expressed anger. “While email use certainly saves people time effort in communicating, it also comes at a cost, the authors of the two studies concluded. Their recommendation? To “suggest that organizations make a concerted effort to cut down on email traffic.”

Other researchers have found similar connections between e-mail and unhappiness. A study, published in 2019, looked at long-term trends in the health of a group of nearly five thousand Swedish workers. They found that repeated exposure to “high information and communication technology demands” (translation: a need to be constantly connected) were associated with “suboptimal” health outcomes. This trend persisted even after they adjusted the statistics for potential complicating factors such as age, sex, socioeconomic status, health behavior, body-mass index, job strain, and social support. Of course, we don’t really need data to capture something that so many of us feel intuitively. I recently surveyed the readers of my blog about e-mail. “It’s slow and very frustrating. . . . I often feel like email is impersonal and a waste of time,” one respondent said. “I’m frazzled—just keeping up,” another admitted. Some went further. “I feel an almost uncontrollable need to stop what I’m doing to check email,” one person reported. “It makes me very depressed, anxious and frustrated.”…(More)”

Lessons from a year of Covid

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Essay by Yuval Noah Harari in the Financial Times: “…The Covid year has exposed an even more important limitation of our scientific and technological power. Science cannot replace politics. When we come to decide on policy, we have to take into account many interests and values, and since there is no scientific way to determine which interests and values are more important, there is no scientific way to decide what we should do.

For example, when deciding whether to impose a lockdown, it is not sufficient to ask: “How many people will fall sick with Covid-19 if we don’t impose the lockdown?”. We should also ask: “How many people will experience depression if we do impose a lockdown? How many people will suffer from bad nutrition? How many will miss school or lose their job? How many will be battered or murdered by their spouses?”

Even if all our data is accurate and reliable, we should always ask: “What do we count? Who decides what to count? How do we evaluate the numbers against each other?” This is a political rather than scientific task. It is politicians who should balance the medical, economic and social considerations and come up with a comprehensive policy.

Similarly, engineers are creating new digital platforms that help us function in lockdown, and new surveillance tools that help us break the chains of infection. But digitalisation and surveillance jeopardise our privacy and open the way for the emergence of unprecedented totalitarian regimes. In 2020, mass surveillance has become both more legitimate and more common. Fighting the epidemic is important, but is it worth destroying our freedom in the process? It is the job of politicians rather than engineers to find the right balance between useful surveillance and dystopian nightmares.

Three basic rules can go a long way in protecting us from digital dictatorships, even in a time of plague. First, whenever you collect data on people — especially on what is happening inside their own bodies — this data should be used to help these people rather than to manipulate, control or harm them. My personal physician knows many extremely private things about me. I am OK with it, because I trust my physician to use this data for my benefit. My physician shouldn’t sell this data to any corporation or political party. It should be the same with any kind of “pandemic surveillance authority” we might establish….(More)”.