Stefaan Verhulst

Special issue of the HedgeHog Review: “Numbers may be our greatest tool, but do we use them wisely?…

At a time when distraction and mendacity degrade public discourse, the heartbreaking toll of the current pandemic should at least remind us that quantification—data, numbers, statistics—are vitally important to policy, governance, and decision-making more broadly.

Confounding as they may be to some of us, numbers are arguably humankind’s most useful technology—our greatest discovery, or possibly our greatest invention. But the current global crisis should also remind us of something equally important: Good numbers, like good science, can only do so much to inform wise decisions about our personal and collective good. They cannot, in any true sense, make those decisions for us. Let the numbers speak for themselves is the rhetoric of the naïf or the con artist, and should long ago have been consigned to the dustbin of pernicious hokum. Yet how seldom in these Big Data days, in our Big Data daze, does it go unchallenged.

Or—to consider the flip side of the current bedazzlement—how often it goes challenged in exactly the wrong way, in a way that declares all facts, all data, all science to be nothing but relative, your facts versus our facts, “alternative facts.” That is the way of sophistry, where cynicism rules and might alone makes right.

Excessive or misplaced faith in the tools that should assist us in arriving at truth—a faith that can engender dangerously unreasoning or cynical reactions—is the theme of this issue. In six essays, we explore the ways the quantitative imperative has insinuated itself into various corners of our culture and society, asserting primacy if not absolute authority in matters where it should tread modestly. In the name of numbers that measure everything from GDP to personal well-being, technocrats and other masters of the postmodern economy have engineered an increasingly soulless, instrumentalizing culture whose denizens either submit to its dictates or flail darkly and destructively against them.

The origins of this nightmare version of modernity, a version that grows increasingly real, dates from at least the first stirrings of modern science in the fifteenth and sixteenth centuries, but its distinctive institutional features emerged most clearly in the early part of the last century, when progressive thinkers and leaders in politics, business, and other walks of life sought to harness humankind’s physical and mental energies to the demands of an increasingly technocratic, consumerist society….(More)”.

Tim Hartford at the Financial Times: “Will this year be 1954 all over again? Forgive me, I have become obsessed with 1954, not because it offers another example of a pandemic (that was 1957) or an economic disaster (there was a mild US downturn in 1953), but for more parochial reasons. Nineteen fifty-four saw the appearance of two contrasting visions for the world of statistics — visions that have shaped our politics, our media and our health. This year confronts us with a similar choice.

The first of these visions was presented in How to Lie with Statistics, a book by a US journalist named Darrell Huff. Brisk, intelligent and witty, it is a little marvel of numerical communication. The book received rave reviews at the time, has been praised by many statisticians over the years and is said to be the best-selling work on the subject ever published. It is also an exercise in scorn: read it and you may be disinclined to believe a number-based claim ever again….

But they can — and back in 1954, the alternative perspective was embodied in the publication of an academic paper by the British epidemiologists Richard Doll and Austin Bradford Hill. They marshalled some of the first compelling evidence that smoking cigarettes dramatically increases the risk of lung cancer. The data they assembled persuaded both men to quit smoking and helped save tens of millions of lives by prompting others to do likewise. This was no statistical trickery, but a contribution to public health that is almost impossible to exaggerate…

As described in books such as Merchants of Doubt by Erik Conway and Naomi Oreskes, this industry perfected the tactics of spreading uncertainty: calling for more research, emphasising doubt and the need to avoid drastic steps, highlighting disagreements between experts and funding alternative lines of inquiry. The same tactics, and sometimes even the same personnel, were later deployed to cast doubt on climate science. These tactics are powerful in part because they echo the ideals of science.

It is a short step from the Royal Society’s motto, “nullius in verba” (take nobody’s word for it), to the corrosive nihilism of “nobody knows anything”.  So will 2020 be another 1954? From the point of view of statistics, we seem to be standing at another fork in the road.

The disinformation is still out there, as the public understanding of Covid-19 has been muddied by conspiracy theorists, trolls and government spin doctors.  Yet the information is out there too. The value of gathering and rigorously analysing data has rarely been more evident. Faced with a complete mystery at the start of the year, statisticians, scientists and epidemiologists have been working miracles. I hope that we choose the right fork, because the pandemic has lessons to teach us about statistics — and vice versa — if we are willing to learn…(More)”.

Paper by Shobita Parthasarathy: “COVID-19 has shown the world that public policies tend to benefit the most privileged among us, and innovation policy is no exception. While the US government’s approach to innovation—research funding and patent policies and programs that value scientists’ and private sector freedoms—has been copied around the world due to its apparent success, I argue that it has hurt poor and marginalized communities. It has limited our understanding of health disparities and how to address them, and hampered access to essential technologies due to both lack of coordination and high cost. Fair and equal treatment of vulnerable citizens requires sensitive and dedicated policies that attend explicitly to the fact that the benefits of innovation do not simply trickle down….(More)”.

Essay by Teresa Scassa: “Even prior to the COVID-19 pandemic, “trust” was a key concept for governments as they asked citizens to make a leap of faith into an increasingly digital and data-driven society. Canada’s Digital Charter was billed as a tool for “building a foundation of trust.” Australia’s Data & Digital Council issued Trust Principles. Trust was a key theme in “Strengthening Digital Government,” a statement from the Organisation for Economic Co-operation and Development. Yet, in spite of this focus on trust, a 2017 study suggested disturbingly low levels of citizen trust in government’s handling of their data in the United Kingdom, the United States and Australia.

The COVID-19 pandemic has further laid bare this lack of trust in government. In the debates around contact-tracing apps it became clear that Western governments did not enjoy public trust when it came to data and technology. When they sought to use technology to support public health contact tracing during a pandemic, governments found that a lack of trust seriously constrained their options. Privacy advocates resisted contact-tracing technologies, raising concerns about surveillance and function creep. They had only to refer to the post-9/11 surveillance legacy to remind the public that “emergency” measures can easily become the new normal.

Working with privacy advocates, Google and Apple developed a fully decentralized model for contact tracing that largely left public health authorities out of the loop. Not trusting governments to set their own parameters for apps, Google and Apple dictated the rules. The Google-Apple Exposure Notification system is limited to only one app per country (creating challenges for Canada’s complicated federalism). It relies on Bluetooth only and does not collect location data. It requires full decentralization of data storage, demands that any app built on the protocol be used voluntarily and ensures post-pandemic decommissioning. Governments that saw value in collecting some centralized data — and possibly some GPS data — to support their data analyses and modelling found themselves with apps that operated less than optimally on Android or iOS platforms or that faced interoperability challenges with other apps in the “return to normal” phase….(More)”.

Article by Laura Rawlings, Jessica Jean-Francois and Catherine MacLeod: “In response to the COVID-19 pandemic, countries across the globe have been adapting social assistance policies to support their populations. In fact, since March 2020, 139 countries and territories have planned, implemented, or adapted cash transfers to support their citizens. Cash transfers specifically make up about half of the social protection programs implemented to address the pandemic. Now more than ever, it’s crucial that such programs are designed to maximize impacts. Behavioral insights can be mobilized as a cost-effective way to help beneficiaries make the most out of the available support. The World Bank and ideas42 partnership on behavioral designs for cash transfer programs is helping countries achieve this goal.

Cash transfers are a key response instrument in the social protection toolkit—and for good reason. Cash transfers have been shown to generate a wide variety of positive benefits, from helping families invest in their children to promoting gender equality. However, we know from our previous work that in order to make the most out of cash transfers, recipients of any program (already facing challenging circumstances that compete for their attention) must undertake complex decisions and actions with their cash. These challenges are only magnified by the global pandemic. COVID-19 has wrought increased uncertainty around future employment and income, which makes calculations and planning to use cash transfer benefits all the more complex.

To help practitioners design programs that account for the complex thought processes and potential barriers recipients face, we mapped out their journey to effectively spend emergency social protection cash transfers. We also created simple, actionable guidance for program designers to put to use in maximizing their programs to help recipients use their cash transfer benefit to most effectively support families and reduce mid- to long-term financial volatility. 

For example, the first step is helping recipients understand what the transfer is for. For recipients who have not yet been impacted by financial instability, or indeed have never encountered a cash transfer before, such funds might seem like a gift or bonus, and recipients may spend it accordingly. Providing clear, simple framing or labelling the transfer may signal to recipients that they should use the cash not only for immediate needs, but also in ways that can help them protect investments in their family members’ human capital and jumpstart their livelihood after the crisis wanes….(More)”.

Paper by Ridhi Kashyap, Masoomali Fatehkia, Reham Al Tamime, and Ingmar Weber: “Background: In recognition of the empowering potential of digital technologies, gender equality in internet access and digital skills is an important target in the United Nations (UN) Sustainable Development Goals (SDGs). Gender-disaggregated data on internet use are limited, particularly in less developed countries.

Objective: We leverage anonymous, aggregate data on the online populations of Google and Facebook users available from their advertising platforms to fill existing data gaps and measure global digital gender inequality.

Methods: We generate indicators of country-level gender gaps on Google and Facebook. Using these online indicators independently and in combination with offline development indicators, we build regression models to predict gender gaps in internet use and digital skills computed using available survey data from the International Telecommunications Union (ITU).

Results: We find that women are significantly underrepresented in the online populations of Google and Facebook in South Asia and sub-Saharan Africa. These platform-specific gender gaps are a strong predictor that women lack internet access and basic digital skills in these populations. Comparing platforms, we find Facebook gender gap indicators perform better than Google indicators at predicting ITU internet use and low-level digital-skill gender gaps. Models using these online indicators outperform those using only offline development indicators. The best performing models, however, are those that combine Facebook and Google online indicators with a country’s development indicators such as the Human Development Index….(More)”.

Paper by Theodora Gazi: “Data collection is valuable before, during and after interventions in order to increase the effectiveness of humanitarian projects. Although the General Data Protection Regulation (GDPR) sets forth rules for the processing of personal data, its implementation by humanitarian aid actors is crucial and presents challenges. Failure to comply triggers severe risks for both data subjects and the reputation of the actor. This article provides insights into the implementation of the guiding principles of the GDPR, the legal bases for data processing, data subjects’ rights and data sharing during the provision of humanitarian assistance…(More)”

Paper by Bertin Martens and Nestor Duch Brown: “Data and information are fundamental pieces for effective evidence-based policy making and provision of public services. In recent years, some private firms have been collecting large amounts of data, which, were they available to governments, could greatly improve their capacity to take better policy decisions and to increase social welfare. Business-to-Government (B2G) data sharing can result in substantial benefits for society. It can save costs to governments by allowing them to benefit from the use of data collected by businesses without having to collect the same data again. Moreover, it can support the production of new and innovative outputs based on the shared data by different users. Finally, the data available to government may give only an incomplete or even biased picture, while aggregating complementary datasets shared by different parties (including businesses) may result in improved policies with strong social welfare benefits.

The examples assembled by the High Level Expert Group on B2G data sharing show that most of the current B2G data transactions remain one-off experimental pilot projects that do not seem to be sustainable over time. Overall, the volume of B2G operations still seems to be relatively small and clearly sub-optimal from a social welfare perspective. The market does not seem to scale compared to the economic potential for welfare gains in society. There are likely to be significant potential economic benefits from additional B2G data sharing operations. These could be enabled by measures that would seek to improve their governance conditions to contribute to increase the overall number of transactions. To design such measures, it is important to understand the nature of the current barriers for B2G data sharing operations. In this paper, we focus on the more important barriers from an economic perspective: (a) monopolistic data markets, (b) high transaction costs and perceived risks in data sharing and (c) a lack of incentives for private firms to contribute to the production of public benefits. The following reflections are mainly conceptual, since there is currently little quantitative empirical evidence on the different aspects of B2G transactions.

• Monopolistic data markets. Some firms -like big tech companies for instance- may be in a privileged position as the exclusive providers of the type of data that a public body seeks to access. This position enables the firms to charge a high price for the data beyond a reasonable rate of return on costs. While a monopolistic market is still a functioning market, the resulting price may lead to some governments not being able or willing to purchase the data and therefore may cause social welfare losses. Nonetheless, monopolistic pricing may still be justified from an innovation perspective: it strengthens incentives to invest in more and better data collection systems and thereby increases the supply of data in the long run. In some cases, the data seller may be in a position to price-discriminate between commercial buyers and a public body, charging a lower price to the latter since the data would not be used for commercial purposes.
• High transaction costs and perceived risks. An important barrier for data sharing comes from the ex-ante costs related to finding a suitable data sharing partner, negotiating a contractual arrangement, re-formatting and cleaning the data, among others. Potentially interested public bodies may not be aware of available datasets or may not be in a position to handle them or understand their advantages and disadvantages. There may also be ex-post risks related to uncertainties in the quality and/or usefulness of the data, the technical implementation of the data sharing deal, ensuring compliance with the agreed conditions, the risk of data leaks to unauthorized third-parties and exposure of personal and confidential data.
• Lack of incentives. Firms may be reluctant to share data with governments because it might have a negative impact on them. This could be due to suspicions that the data delivered might be used to implement market regulations and to enforce competition rules that could negatively affect firms’ profits. Moreover, if firms share data with government under preferential conditions, they may have difficulties justifying the foregone profit to shareholders, since the benefits generated by better policies or public services fuelled by the private data will occur to society as a whole and are often difficult to express in monetary terms. Finally, firms might be afraid of entering into a competitive disadvantage if they provide data to public bodies – perhaps under preferential conditions – and their competitors do not.

Several mechanisms could be designed to solve the barriers that may be holding back B2G data sharing initiatives. One would be to provide stronger incentives for the data supplier firm to engage in this type of transactions. These incentives can be direct, i.e., monetary, or indirect, i.e., reputational (e.g. as part of corporate social responsibility programmes). Another way would be to ascertain the data transfer by making the transaction mandatory, with a fair cost compensation. An intermediate way would be based on solutions that seek to facilitate voluntary B2G operations without mandating them, for example by reducing the transaction costs and perceived risks for the provider data supplier, e.g. by setting up trusted data intermediary platforms, or appropriate contractual provisions. A possible EU governance framework for B2G data sharing operations could cover these options….(More)”.

OECD Report: “This report analyses the skills and capacities governments need to strengthen evidence-informed policy-making (EIPM) and identifies a range of possible interventions that are available to foster greater uptake of evidence. Increasing governments’ capacity for evidence-informed is a critical part of good public governance. However, an effective connection between the supply and the demand for evidence in the policy-making process remains elusive. This report offers concrete tools and a set of good practices for how the public sector can support senior officials, experts and advisors working at the political/administrative interface. This support entails investing in capability, opportunity and motivation and through behavioral changes. The report identifies a core skillset for EIPM at the individual level, including the capacity for understanding, obtaining, assessing, using, engaging with stakeholders, and applying evidence, which was developed in collaboration with the European Commission Joint Research Centre. It also identifies a set of capacities at the organisational level that can be put in place across the machinery of government, throughout the role of interventions, strategies and tools to strengthen these capacities. The report concludes with a set of recommendations to assist governments in building their capacities…(More)”.

Paper by David M. J. Lazer et al: “The field of computational social science (CSS) has exploded in prominence over the past decade, with thousands of papers published using observational data, experimental designs, and large-scale simulations that were once unfeasible or unavailable to researchers. These studies have greatly improved our understanding of important phenomena, ranging from social inequality to the spread of infectious diseases. The institutions supporting CSS in the academy have also grown substantially, as evidenced by the proliferation of conferences, workshops, and summer schools across the globe, across disciplines, and across sources of data. But the field has also fallen short in important ways. Many institutional structures around the field—including research ethics, pedagogy, and data infrastructure—are still nascent. We suggest opportunities to address these issues, especially in improving the alignment between the organization of the 20th-century university and the intellectual requirements of the field….(More)”.