COVID-19 is creating a democratic deficit – here’s how to reduce it


Article by Matt Ryan: “As parliaments around the country move to scale down operations and defer sittings as part of containing COVID-19 people are beginning to ring the accountability alarm bells….

The good news is that we can learn from those parliaments and politicians around the world who have already been trialling new ways of working that go beyond traditional sittings. Leveraging simple and widely available technologies, they are involving more people with more diverse backgrounds in their processes with less reliance on those people being physically present.

Select Committees in the UK Parliament, for example, have used online “evidence checks” to scrutinise the basis for policy. These one-month exercises use targeted outreach and social media strategies to invite comments from knowledgeable stakeholders and members of the public about the rigour of evidence on which a government department’s policy is based. Evidence for departmental policy is summarised in a two-page document and comments publicly displayed in a web forum that resembles a readers’ comments section in an online news article.

In Taiwan, a participatory governance process pioneered by civic rights activists at the behest of a government minister combines large-scale online participation with smaller in-person gatherings to build a “rough consensus” on legislative proposals related to the digital economy before they are introduced. Known as vTaiwan, the process has led to 26 pieces of national legislation dealing with issues such as Uber, telemedicine and online alcohol sales, and has involved 200,000 people.

The government of Mexico City has raised the stakes even higher, involving more than 400,000 people in a process to draft a new constitution. It included a novel partnership between Change.org and the city mayor that enabled residents to create petition-backed proposals which, once they reached a certain threshold of support, bound the mayor to include them in the draft he submitted to a special constitutional assembly.

Processes like these can also offer relief for politicians and parliamentary officials managing the strain of examining an ever-increasing number of issues of greater complexity with limited personnel and budget. Evidence checks provide access to a wider pool of experts who can bolster existing research capacity. vTaiwan helps to find workable ways forward in industries being rapidly transformed by digital technologies. By “crowdsourcing” the city’s constitution, Mexico City’s mayor retained the trust of residents while undertaking reform at a grand scale….(More)”.

Ask a Scientist


NYU Press Release: “Unreliable tips on how to protect oneself from the novel coronavirus and fake news about the COVID-19 pandemic are spreading as quickly as the virus itself.

The Governance Lab (The GovLab) at the New York University Tandon School of Engineering has collaborated with the Federation of American Scientists (FAS) and the State of New Jersey Office of Innovation to launch a free, interactive tool aimed at cutting through the noise and presenting clear, scientist-led, and evidence-based information and advice to the public.

Available in English and Spanish, “Ask a Scientist,” allows users to find answers to a wide range of commonly asked questions about the virus, the severity of the outbreak, best methods of prevention, and steps to take in the event you fall ill. All posted content is obtained from the World Health Organization, the Centers for Disease Control and Prevention, and other rigorously verified sources.

screenshot of website that allows users to type in questions about COVID-19

“Ask a Scientist” features a free, interactive tool allowing users to submit questions to a team of FAS researchers and a crowdsourced network of vetted science experts. In English and Spanish, the site also includes top articles and the latest information, and answers to a wide range of commonly asked questions about the COVID-19 epidemic, the severity of the outbreak, best methods of prevention, and steps to take in the event you fall ill.

If users do not find an answer to their specific questions, they have the option of submitting them to a team of FAS researchers and a crowdsourced network of vetted science experts led by the National Science Policy Network. Users can expect an answer within an hour, although that timeframe is expected to shorten as the network increases in size. Every answer is reviewed to ensure accuracy and timeliness, then added to the knowledge base for the benefit of others….(More)”.

Why resilience to online disinformation varies between countries


Edda Humprecht at the Democratic Audit: “The massive spread of online disinformation, understood as content intentionally produced to mislead others, has been widely discussed in the context of the UK Brexit referendum and the US general election in 2016. However, in many other countries online disinformation seems to be less prevalent. It seems certain countries are better equipped to face the problems of the digital era, demonstrating a resilience to manipulation attempts. In other words, citizens in these countries are better able to adapt to overcome challenges such as the massive spread of online disinformation and their exposure to it. So, do structural conditions render countries more or less resilient towards online disinformation?

As a first step to answering this question, in new research with Frank Esser and Peter Van Aelst, we identified the structural conditions that are theoretically linked to resilience to online disinformation, which relate to different political, media and economic environments. To test these expectations, we then identified quantifiable indicators for these theoretical conditions, which allowed us to measure their significance for 18 Western democracies. A cluster analysis then yielded three country groups: one group with high resilience to online disinformation (including the Northern European countries) and two country groups with low resilience (including Southern European countries and the US).

Conditions for resilience: political, media and economic environments

In polarised political environments, citizens are confronted with different deviating representations of reality and therefore it becomes increasingly difficult for them to distinguish between false and correct information. Thus, societal polarisation is likely to decrease resilience to online disinformation. Moreover, research has shown that both populism and partisan disinformation share a binary Manichaeanworldview, comprising anti-elitism, mistrust of expert knowledge and a belief in conspiracy theories. As a consequence of these combined influences, citizens can obtain inaccurate perceptions of reality. Thus, in environments with high levels of populist communication, online users are exposed to more disinformation.

Another condition that has been linked to resilience to online disinformation in previous research is trust in news media. Previous research has shown that in environments in which distrust in news media is higher, people are less likely to be exposed to a variety of sources of political information and to critically evaluate those. In this vein,the level of knowledge that people gain is likely to play an important role when confronted with online disinformation. Research has shown that in countries with wide-reaching public service media, citizens’ knowledge about public affairs is higher compared to countries with marginalised public service media. Therefore, it can be assumed that environments with weak public broadcasting services (PBS) are less resilient to online disinformation….

Looking at the economic environment, false social media content is often produced in pursuit of advertising revenue, as was the case with the Macedonian ‘fake news factories’ during the 2016 US presidential election. It is especially appealing for producers to publish this kind of content if the potential readership is large. Thus, large-size advertising markets with a high number of potential users are less resistant to disinformation than smaller-size markets….(More)”.

Disinformation is particularly prevalent on social media and in countries with very many social media users, it is easier for rumour-spreaders to build partisan follower networks. Moreover, it has been found that a media diet mainly consisting of news from social media limits political learning and leads to less knowledge of public affairs compared to other media source. From this, societies with a high rate of social media users are more vulnerable to online disinformation spreading rapidly than other societies…(More)”.

Mediated Democracy – Linking Digital Technology to Political Agency


Paper by Jeanette Hofmann: “Although the relationship between digitalisation and democracy is subject of growing public attention, the nature of this relationship is rarely addressed in a systematic manner. The common understanding is that digital media are the driver of the political change we are facing today. This paper argues against such a causal approach und proposes a co-evolutionary perspective instead. Inspired by Benedict Anderson’s “Imagined Communities” and recent research on mediatisation, it introduces the concept of mediated democracy. This concept reflects the simple idea that representative democracy requires technical mediation, and that the rise of modern democracy and of communication media are therefore closely intertwined. Hence, mediated democracy denotes a research perspective, not a type of democracy. It explores the changing interplay of democratic organisation and communication media as a contingent constellation, which could have evolved differently. Specific forms of communication media emerge in tandem with larger societal formations and mutually enable each other. Following this argument, the current constellation reflects a transformation of representative democracy and the spread of digital media. The latter is interpreted as a “training ground” for experimenting with new forms of democratic agency….(More)”.

Using Technology to ‘Co-Create’ EU Policies


Paper by Gianluca Sgueo: “What will European Union (EU) decision-making look like in the next decade and beyond? Is technological progress promoting more transparent, inclusive and participatory decision-making at EU level?

Technology has dramatically changed both the number and quality of connections between citizens and public administrations. With technological progress, citizens have gained improved access to public authorities through new digital communication channels. Innovative, tech-based, approaches to policy-making have become the subject of a growing debate between academics and politicians. Theoretical approaches such as ‘CrowdLaw’, ‘Policy-Making 3.0’, ‘liquid’, ‘do-it- yourself’ or ‘technical’ democracy and ‘democratic innovations’ share the positive outlook towards technology; and technology is seen as the medium through which policies can be ‘co-created’ by decision-makers and stakeholders. Co-creation is mutually beneficial. Decision-makers gain legitimacy by incorporating the skills, knowledge and expertise of citizens, who in turn have the opportunity to shape new policies according to their needs and expectations.

EU institutions are at the forefront of experimentation with technologically innovative approaches to make decision-making more transparent and accessible to stakeholders. Efforts in modernising EU participatory channels through technology have evolved over time: from redressing criticism on democratic deficits, through fostering digital interactions with stakeholders, up to current attempts at designing policy-making in a friendly and participative manner.

While technological innovation holds the promise of making EU policy-making even more participatory, it is not without challenges. To begin with, technology is resource consuming. There are legal challenges associated with both over- and under-regulation of the use of technology in policy-making. Furthermore, technological innovation raises ethical concerns. It may increase inequality, for instance, or infringe personal privacy… (More)“.

How scientists are crowdsourcing a coronavirus treatment


Article by Evan Nicole Brown: “… There’s currently no cure for COVID-19, but scientists are working on drugs that could help slow its spread. Fortunately, citizens can get involved in the process.

Foldit is an online video game that challenges players to fold various proteins into shapes where they are stable. Generally, folding proteins allows scientists (and citizens) to design new proteins from scratch, but in the case of coronavirus, Foldit players are trying to design the drugs to combat it. “Coronavirus has a ‘spike’ protein that it uses to recognize human cells,” says Brian Koepnick, a biochemist and researcher with the University of Washington’s Institute for Protein Design who has been using Foldit for protein research for six years. “Foldit players are designing new protein drugs that can bind to the COVID spike and block this recognition, [which could] potentially stop the virus from infecting more cells in an individual who has already been exposed to the virus.”

“In Foldit, you change the shape of a protein model to optimize your score. This score is actually a sophisticated calculation of the fold’s potential energy,” says Koepnick, adding that professional researchers use an identical score function in their work. “The coronavirus puzzles are set up such that high-scoring models have a better chance of actually binding to the target spike protein.” Ultimately, high-scoring solutions are analyzed by researchers and considered for real-world use….(More)”.

Collaborative Е-Rulemaking, Democratic Bots, and the Future of Digital Democracy


Essay by Oren Perez: “This article focuses on “deliberative e-rulemaking”: digital consultation processes that seek to facilitate public deliberation over policy or regulatory proposals [1, 2]. The main challenge of е-rulemaking platforms is to support an “intelligent” deliberative process that enables decision makers to identify a wide range of options, weigh the relevant considerations, and develop epistemically responsible solutions.

This article discusses and critiques two approaches to this challenge: The Cornell Regulation Room project and model of computationally assisted regulatory participation by Livermore et al. It then proceeds to explore two alternative approaches to e-rulemaking: One is based on the implementation of collaborative, wiki-styled tools. This article discusses the findings of an experiment, which was conducted at Bar-Ilan University and explored various aspects of a wiki-based collaborative е-rulemaking system. The second approach follows a more futuristic Approach, focusing on the potential development of autonomous, artificial democratic agents. This article critically discusses this alternative, also in view of the recent debate regarding the idea of “augmented democracy.”…(More)”.

Crowdsourcing hypothesis tests: making transparent how design choices shape research results


Paper by J.F. Landy and Leonid Tiokhin: “To what extent are research results influenced by subjective decisions that scientists make as they design studies?

Fifteen research teams independently designed studies to answer five original research questions related to moral judgments, negotiations, and implicit cognition. Participants from two separate large samples (total N > 15,000) were then randomly assigned to complete one version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: materials from different teams rendered statistically significant effects in opposite directions for four out of five hypotheses, with the narrowest range in estimates being d = -0.37 to +0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for two hypotheses, and a lack of support for three hypotheses.

Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, while considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim….(More)”.

Why no one is reading your coronavirus emails


Opinion by Todd Rogers: “…As a behavioral scientist, I study how people make decisions and process information, and I develop communications to change behavior for the better. And if there’s one lesson all the coronavirus email writers should take, it’s this: Messages should be as easy to understand as possible. This is difficult in normal times — and is no doubt much more so with facts on the ground changing as rapidly as they are….

As an illustration of how potent simplifying messaging can be, Carly Robinson at Harvard, Jessica Lasky-Fink of the University of California, Berkeley, Hedy Chang of Attendance Works and I conducted an experiment with a large school district, in which we rewrote a state-required notification about attendance.All schools in California are required to send a truancy notification to families after a student is late or absent three times. The state legislature offered recommended language for the notice that was written at a college-reading level and contained 342 words in seven-point font. We rewrote the letter at a 5th grade reading level, in 14-point font and with half as many words. We then randomly assigned 131,312 families to either receive the state-recommended language or a version of our simplified letter.The best version of our simplified letters was an estimated 40% more effective at reducing absences during the subsequent 30 days than the state-recommended language. Writing with an understanding of how humans work turns out to be more effective than writing with the sole goal of complying with the delivery of mandatory written information.So, what can be done to make coronavirus messages, so critical to the functioning of our country right now, easier to understand — and more likely to be read?

  • Write in the most accessible way possible. Use the Flesch-Kincaid readability test (built into Microsoft Word and Google Docs) to test the reading-level complexity of your writing.
  • Use as few words as possible. Shorter messages are more likely to be read (see the long email in your inbox from three months ago that you still have not read).
  • Write in a larger font. This makes long messages look ridiculous and makes it easier to read for recipients with eyesight issues. It also reduces the chance of the accidental — but way too common — occurrence of emails appearing in inboxes with absurdly small font.
  • Eliminate gratuitous borders and images. These can often distract from the message you are trying to send.
  • Use a clear structure. People skim, so help them. As opposed to a multi-paragraph email written in normal prose, consider categorizing information under headings like, “What we want you to know” (or just “KNOW”) and “what we would like you to do” (or, concisely, “DO”). Consider putting content within each category in bullet points….(More)”

Coronavirus: seven ways collective intelligence is tackling the pandemic


Article by Kathy Peach: “Tackling the emergence of a new global pandemic is a complex task. But collective intelligence is now being used around the world by communities and governments to respond.

At its simplest, collective intelligence is the enhanced capacity created when distributed groups of people work together, often with the help of technology, to mobilise more information, ideas and insights to solve a problem.

Advances in digital technologies have transformed what can be achieved through collective intelligence in recent years – connecting more of us, augmenting human intelligence with machine intelligence, and helping us to generate new insights from novel sources of data. It is particularly suited to addressing fast-evolving, complex global problems such as disease outbreaks.

Here are seven ways it is tackling the coronavirus pandemic:

1. Predicting and modelling outbreaks

On the December 31, 2019, health monitoring platform Blue Dot alerted its clients to the outbreak of a flu-like virus in Wuhan, China – nine days before the World Health Organization (WHO) released a statement about it. It then correctly predicted that the virus would jump from Wuhan to Bangkok, Seoul, Taipei and Tokyo.

Blue Dot combines existing data sets to create new insights. Natural language processing, the AI methods that understand and translate human-generated text, and machine learning techniques that learn from large volumes of data, sift through reports of disease outbreaks in animals, news reports in 65 languages, and airline passenger information. It supplements the machine-generated model with human intelligence, drawing on diverse expertise from epidemiologists to veterinarians and ecologists to ensure that its conclusions are valid.

2. Citizen science

The BBC carried out a citizen science project in 2018, which involved members of the public in generating new scientific data about how infections spread. People downloaded an app that monitored their GPS position every hour, and asked them to report who they had encountered or had contact with that day….(More).