The Sisyphean Cycle of Technology Panics


Paper by Amy Orben: “Widespread concerns about new technologies – whether they be novels, radios or smartphones – are repeatedly found throughout history. While past panics are often met with amusement today, current concerns routinely engender large research investments and policy debate. What we learn from studying past technological panics, however, is that these investments are often inefficient and ineffective. What causes technological panics to repeatedly reincarnate? And why does research routinely fail to address them?

To answer such questions, this article examines the network of political, population and academic factors driving the Sisyphean Cycle of Technology Panics. In this cycle, psychologists are encouraged to spend time investigating new technologies, and how they affect children and young people, to calm a worried population. Their endeavour is however rendered ineffective due to a lacking theoretical baseline; researchers cannot build on what has been learnt researching past technologies of concern. Thus academic study seemingly restarts for each new technology of interest, slowing down the policy interventions necessary to ensure technologies are benefitting society. This article highlights how the Sisyphean Cycle of Technology Panics stymies psychology’s positive role in steering technological change, and highlights the pervasive need for improved research and policy approaches to new technologies….(More)”.

Improving Governance with Policy Evaluation


OECD Report: “Policy evaluation is a critical element of good governance, as it promotes public accountability and contributes to citizens’ trust in government. Evaluation helps ensure that decisions are rooted in trustworthy evidence and deliver desired outcomes. Drawing on the first significant cross-country survey of policy evaluation practices covering 42 countries, this report offers a systemic analysis of the institutionalisation, quality and use of evaluation across countries and looks at how these three dimensions interrelate.

The report also covers cross-cutting aspects related to regulatory assessment and performance budgeting. The analysis illustrates the role and functions of key institutions within the executive, such as centres of government and ministries of finance. It also underlines the role of supreme audit institutions….(More)”.

The Ages of Globalization: Geography, Technology, and Institutions


Book by Jeffrey D. Sachs: “Today’s most urgent problems are fundamentally global. They require nothing less than concerted, planetwide action if we are to secure a long-term future. But humanity’s story has always been on a global scale. In this book, Jeffrey D. Sachs, renowned economist and expert on sustainable development, turns to world history to shed light on how we can meet the challenges and opportunities of the twenty-first century.

Sachs takes readers through a series of seven distinct waves of technological and institutional change, starting with the original settling of the planet by early modern humans through long-distance migration and ending with reflections on today’s globalization. Along the way, he considers how the interplay of geography, technology, and institutions influenced the Neolithic revolution; the role of the horse in the emergence of empires; the spread of large land-based empires in the classical age; the rise of global empires after the opening of sea routes from Europe to Asia and the Americas; and the industrial age. The dynamics of these past waves, Sachs demonstrates, offer fresh perspective on the ongoing processes taking place in our own time—a globalization based on digital technologies. Sachs emphasizes the need for new methods of international governance and cooperation to prevent conflicts and to achieve economic, social, and environmental objectives aligned with sustainable development. The Ages of Globalization is a vital book for all readers aiming to make sense of our rapidly changing world….(More)”.

Data4Covid19


The GovLab: “Three months ago, COVID-19 brought much of the world to a halt. Faced with the unprecedented challenges brought by the virus, The GovLab put forth a Call for Action to develop the responsible data infrastructure needed to address the pandemic and other dynamic threats. With our partners, we initiated several projects to achieve the goals outlined in the call.

Today we are launching a new hub for The GovLab’s #Data4COVID19 efforts at data4covid19.org. This site brings together our efforts to implement the Call for Action including developing a governance frameworkbuilding capacity, establishing data stewardship and a network of data stewards, and engaging people.

You can also use the site to share your updates and efforts with The GovLab team or subscribe to our newsletter to stay informed….(More)’.

Are Citizens’ Assemblies the Answer to the Climate Crisis?


Judy Dempsey’s Strategic Europe: “Mathilde Bouyé associate at the Climate Program Of The World Resources Institute: “…the impact of citizens’ deliberation depends on the link to decisionmaking, which varies with each country’s democratic culture. The UK climate assembly informed powerful parliamentary committees, while the French government created a precedent by committing to send the Citizens’ Convention on Climate’s proposals for adoption “without any filter….”

Jan Eichhorn,  Research Director Of D|Part and Senior Lecturer in Social Policy at The University Of Edinburgh: “The climate crisis is so complex that no single action can be the answer to it. However, because of the complexity, formats that can connect otherwise distant actors meaningfully can play a very helpful role. Citizens’ assemblies fit that bill.

If well designed, such assemblies connect expertise with life realities, broaden the horizon of policymakers on what publics may be willing or even excited to consider, and enable publics to learn about options they did not know about. Rather than stoking divisions between people and businesses or between activists and state officials, they can foster common ground and create shared purpose, which is needed to combat comprehensive challenges like the climate crisis….”

Tim Hughes, Director of Involve: “…they are only one way in which people can be—and need to be—involved in decisionmaking. Underpinning citizens’ assemblies are the principles of participation—people being involved in the decisions that affect their lives—and deliberation—people sharing and testing ideas through inclusive and respectful conversations.

It is these principles that we need to build into decisionmaking at all levels of society in order to develop the ideas, energy, and ownership to answer the crisis.”

Mariann Őry,  Head Of The Foreign Desk And Senior Editor At Magyar Hírlap: “Citizens’ initiatives have proven to be effective in reaching a number of goals, but the pressure they can put on stakeholders is not always enough.

It’s not even the most reliable political force: remember that the enthusiasm and momentum of the climate protests has basically vanished since the start of the coronavirus crisis, as if people simply lost interest—though this is surely not the case. A difference can be made on the level of political leaders and, very importantly, on the level of the biggest actors of industry….(More)”.

The Shape of Epidemics


Essay by David S. Jones and Stefan Helmreich: “…Is the most recent rise in new cases—the sharp increase in case counts and hospitalizations reported this week in several states—a second wave, or rather a second peak of a first wave? Will the world see a devastating second wave in the fall?

Such imagery of waves has pervaded talk about the propagation of the infection from the beginning. On January 29, just under a month after the first instances of COVID-19 were reported in Wuhan, Chinese health officials published a clinical report about their first 425 cases, describing them as “the first wave of the epidemic.” On March 4 the French epidemiologist Antoine Flahault asked, “Has China just experienced a herald wave, to use terminology borrowed from those who study tsunamis, and is the big wave still to come?” The Asia Times warned shortly thereafter that “a second deadly wave of COVID-19 could crash over China like a tsunami.” A tsunami, however, struck elsewhere, with the epidemic surging in Iran, Italy, France, and then the United States. By the end of April, with the United States having passed one million cases, the wave forecasts had become bleaker. Prominent epidemiologists predicted three possible future “wave scenarios”—described by one Boston reporter as “seascapes,” characterized either by oscillating outbreaks, the arrival of a “monster wave,” or a persistent and rolling crisis.


From Kristine Moore et al., “The Future of the COVID-19 Pandemic” (April 30, 2020). Used with permission from the Center for Infectious Disease Research and Policy, University of Minnesota.

While this language may be new to much of the public, the figure of the wave has long been employed to describe, analyze, and predict the behavior of epidemics. Understanding this history can help us better appreciate the conceptual inheritances of a scientific discipline suddenly at the center of public discussion. It can also help us judge the utility as well as limitations of those representations of epidemiological waves now in play in thinking about the science and policy of COVID-19. As the statistician Edward Tufte writes in his classic work The Visual Display of Quantitative Information (1983), “At their best, graphics are instruments for reasoning about quantitative information.” The wave, operating as a hybrid of the diagrammatic, mathematical, and pictorial, certainly does help to visualize and think about COVID-19 data, but it also does much more. The wave image has become an instrument for public health management and prediction—even prophecy—offering a synoptic, schematic view of the dynamics it describes.

This essay sketches this backstory of epidemic waves, which falls roughly into three eras: waves emerge first as a device of data visualization, then evolve into an object of mathematical modeling and causal investigation and finally morph into a tool of persuasion, intervention, and governance. Accounts of the wave-like rise and fall of rates of illness and death in populations first appeared in the mid-nineteenth century, with England a key player in developments that saw government officials collect data permitting the graphical tabulation of disease trends over time. During this period the wave image was primarily metaphorical, a heuristic way of talking about patterns in data. Using curving numerical plots, epidemiologists offered analogies between the spread of infection and the travel of waves, sometimes transposing the temporal tracing of epidemic data onto maps of geographical space. Exactly what mix of forces—natural or social—generated these “epidemic waves” remained a source of speculation….(More)”.

Five ways to ensure that models serve society: a manifesto


Andrea Saltelli et al at Nature: “The COVID-19 pandemic illustrates perfectly how the operation of science changes when questions of urgency, stakes, values and uncertainty collide — in the ‘post-normal’ regime.

Well before the coronavirus pandemic, statisticians were debating how to prevent malpractice such as p-hacking, particularly when it could influence policy1. Now, computer modelling is in the limelight, with politicians presenting their policies as dictated by ‘science’2. Yet there is no substantial aspect of this pandemic for which any researcher can currently provide precise, reliable numbers. Known unknowns include the prevalence and fatality and reproduction rates of the virus in populations. There are few estimates of the number of asymptomatic infections, and they are highly variable. We know even less about the seasonality of infections and how immunity works, not to mention the impact of social-distancing interventions in diverse, complex societies.

Mathematical models produce highly uncertain numbers that predict future infections, hospitalizations and deaths under various scenarios. Rather than using models to inform their understanding, political rivals often brandish them to support predetermined agendas. To make sure predictions do not become adjuncts to a political cause, modellers, decision makers and citizens need to establish new social norms. Modellers must not be permitted to project more certainty than their models deserve; and politicians must not be allowed to offload accountability to models of their choosing2,3.

This is important because, when used appropriately, models serve society extremely well: perhaps the best known are those used in weather forecasting. These models have been honed by testing millions of forecasts against reality. So, too, have ways to communicate results to diverse users, from the Digital Marine Weather Dissemination System for ocean-going vessels to the hourly forecasts accumulated by weather.com. Picnickers, airline executives and fishers alike understand both that the modelling outputs are fundamentally uncertain, and how to factor the predictions into decisions.

Here we present a manifesto for best practices for responsible mathematical modelling. Many groups before us have described the best ways to apply modelling insights to policies, including for diseases4 (see also Supplementary information). We distil five simple principles to help society demand the quality it needs from modelling….(More)”.

UN Data Strategy


United Nations: “As structural UN reforms consolidate, we are focused on building the data, digital, technology and innovation capabilities that the UN needs to succeed in the 21st century. The Secretary General’s “Data Strategy for Action by Everyone, Everywhere” is our agenda for the data-driven transformation.

Data permeates all aspects of our work, and its power—harnessed responsibly—is critical to the global agendas we serve. The UN family’s footprint, expertise and connectedness create unique opportunities to advance global “data action” with insight, impact and integrity. To help unlock more potential, 50 UN entities jointly designed this Strategy as a comprehensive playbook for data-driven change based on global best practice…

Our strategy pursues a simple idea: we focus not on process, but on learning, iteratively, to deliver data use cases that add value for stakeholders based on our vision, outcomes and principles. Use cases – purposes for which data is used – already permeate our organization. We will systematically identify and deliver them through dedicated data action portfolios. While new capabilities will in part emerge through “learning by doing”, we will also strengthen organizational enablers to deliver on our vision, including shifts in people and culture, partnerships, data governance and technology….(More)”.

United Nations Data Strategy

Politicians ignore far-out risks: they need to up their game


The Economist: “In 1993 this newspaper told the world to watch the skies. At the time, humanity’s knowledge of asteroids that might hit the Earth was woefully inadequate. Like nuclear wars and large volcanic eruptions, the impacts of large asteroids can knock seven bells out of the climate; if one thereby devastated a few years’ worth of harvests around the globe it would kill an appreciable fraction of the population. Such an eventuality was admittedly highly unlikely. But given the consequences, it made actuarial sense to see if any impact was on the cards, and at the time no one was troubling themselves to look.

Asteroid strikes were an extreme example of the world’s wilful ignorance, perhaps—but not an atypical one. Low-probability, high-impact events are a fact of life. Individual humans look for protection from them to governments and, if they can afford it, insurers. Humanity, at least as represented by the world’s governments, reveals instead a preference to ignore them until forced to react—even when foresight’s price-tag is small. It is an abdication of responsibility and a betrayal of the future.

Covid-19 offers a tragic example. Virologists, epidemiologists and ecologists have warned for decades of the dangers of a flu-like disease spilling over from wild animals. But when sarscov-2 began to spread very few countries had the winning combination of practical plans, the kit those plans required in place and the bureaucratic capacity to enact them. Those that did benefited greatly. Taiwan has, to date, seen just seven covid-19 deaths; its economy has suffered correspondingly less.

Pandemics are disasters that governments have experience of. What therefore of truly novel threats? The blazing hot corona which envelops the Sun—seen to spectacular effect during solar eclipses—intermittently throws vast sheets of charged particles out into space. These cause the Northern and Southern Lights and can mess up electric grids and communications. But over the century or so in which electricity has become crucial to much of human life, the Earth has never been hit by the largest of these solar eructations. If a coronal mass ejection (cme) were to hit, all sorts of satellite systems needed for navigation, communications and warnings of missile attacks would be at risk. Large parts of the planet could face months or even years without reliable grid electricity (see Briefing). The chances of such a disaster this century are put by some at better than 50:50. Even if they are not that high, they are still higher than the chances of a national leader knowing who in their government is charged with thinking about such things.

The fact that no governments have ever seen a really big cme, or a volcanic eruption large enough to affect harvests around the world—the most recent was Tambora, in 1815—may explain their lack of forethought. It does not excuse it. Keeping an eye on the future is part of what governments are for. Scientists have provided them with the tools for such efforts, but few academics will undertake the work unbidden, unfunded and unsung. Private business may take some steps when it perceives specific risks, but it will not put together plans for society at large….(More)”.

Opportunities of Artificial Intelligence


Report for the European Parliament: “A vast range of AI applications are being implemented by European industry, which can be broadly grouped into two categories: i) applications that enhance the performance and efficiency of processes through mechanisms such as intelligent monitoring, optimisation and control; and ii) applications that enhance human-machine collaboration.

At present, such applications are being implemented across a broad range of European industrial sectors. However, some sectors (e.g. automotive, telecommunications, healthcare) are more advanced in AI deployment than others (e.g. paper and pulp, pumps, chemicals). The types of AI applications
implemented also differ across industries. In less digitally mature sectors, clear barriers to adoption have been identified, including both internal (e.g. cultural resistance, lack of skills, financial considerations) and external (e.g. lack of venture capital) barriers. For the most part, and especially for SMEs, barriers to the adoption of AI are similar to those hindering digitalisation. The adoption of such AI applications is anticipated to deliver a wide range of positive impacts, for individual firms, across value chains, as well as at the societal and macroeconomic levels. AI applications can bring efficiency, environmental and economic benefits related to increased production output and quality, reduced maintenance costs, improved energy efficiency, better use of raw materials and reduced waste. In addition, AI applications can add value through product personalisation, improve customer service and contribute to the development of new product classes, business models and even sectors. Workforce benefits (e.g. improved workplace safety) are also being delivered by AI applications.

Alongside these firm-level benefits and opportunities, significant positive societal and economy-wide impacts are envisaged. More specifically, substantial increases in productivity, innovation, growth and job creation have been forecasted. For example, one estimate anticipates labour productivity increases of 11-37% by 2035. In addition, AI is expected to positively contribute to the UN Sustainable Development Goals and the capabilities of AI and machine learning to address major health challenges, such as the current COVID-19 health pandemic, are also noteworthy. For instance, AI systems have the potential to accelerate the lead times for the development of vaccines and drugs.

However, AI adoption brings a range of challenges…(More)”.