Stefaan Verhulst

Marc Santolini at the Conversation: “All around the world, scientists and practitioners are relentlessly harnessing data on the pandemic to model its progression, predict the impact of possible interventions and develop solutions to medical equipment shortages, generating open-source data and codes to be reused by others.

Research and innovation is now in a collaborative frenzy just as contagious as the coronavirus. Is this the rise of the famous “collective intelligence” supposed to solve our major global problems?

The rise of a global collective intelligence

The beginning of the epidemic saw “traditional” research considerably accelerate and open its means of production, with journals such as Science, Nature and The Lancet immediately granting public access to publications on the coronavirus and Covid-19.

The academic world is in ebullition. Every day, John Hopkins University updates an open and collaborative stream of data on the epidemic, which have already been reused more than 11,000 times. Research results are published immediately on pre-print servers or laboratory websites. Algorithms and interactive visualizations are flourishing on GitHub; outreach videos on YouTube. The figures are staggering, with nearly 9,000 academic articles published on the subject to date.

More recently, popular initiatives bringing together a variety of actors have emerged outside institutional frameworks, using online platforms. For example, a community of biologists, engineers and developers has emerged on the Just One Giant Lab (JOGL) collaborative platform to develop low-cost, open-source solutions against the virus. This platform, which we developed with Leo Blondel (Harvard University) and Thomas Landrain (La Paillasse, PILI) over the past three years, is designed as a virtual, open and distributed research institute aimed at developing solutions to the Sustainable Development Goals (SDGs) defined by the United Nations. Communities use it to self-organize and provide innovative solutions to urgent problems requiring fundamentally interdisciplinary skills and knowledge. The platform facilitates coordination by linking needs and resources within the community, animating research programs, and organising challenges….(More)”.

Aakash Desai et al in Nature Medicine: “Crowdsourcing efforts are currently underway to collect and analyze data from patients with cancer who are affected by the COVID-19 pandemic. These community-led initiatives will fill key knowledge gaps to tackle crucial clinical questions on the complexities of infection with the causative coronavirus SARS-Cov-2 in the large, heterogeneous group of vulnerable patients with cancer…(More)”

Stefaan G. Verhulst at Open Data Policy Lab: “The belief that we are living in a data age — one characterized by unprecedented amounts of data, with unprecedented potential — has become mainstream. We regularly read phrases such as “data is the most valuable commodity in the global economy” or that data provides decision-makers with an “ever-swelling flood of information.”

Without a doubt, there is truth in such statements. But they also leave out a major shortcoming — the fact that much of the most useful data continue to remain inaccessible, hidden in silos, behind digital walls, and in untapped “treasuries.”

For close to a decade, the technology and public interest community have pushed the idea of open data. At its core, open data represents a new paradigm of data availability and access. The movement borrows from the language of open source and is rooted in notions of a “knowledge commons”, a concept developed, among others, by scholars like Nobel Prize winner Elinor Ostrom.

Milestones and Limitations in Open Data

Significant milestones have been achieved in the short history of the open data movement. Around the world, an ever-increasing number of governments at the local, state and national levels now release large datasets for the public’s benefit. For example, New York City requires that all public data be published on a single web portal. The current portal site contains thousands of datasets that fuel projects on topics as diverse as school bullying, sanitation, and police conduct. In California, the Forest Practice Watershed Mapper allows users to track the impact of timber harvesting on aquatic life through the use of the state’s open data. Similarly, Denmark’s Building and Dwelling Register releases address data to the public free of charge, improving transparent property assessment for all interested parties.

A growing number of private companies have also initiated or engaged in “Data Collaborative”projects to leverage their private data toward the public interest. For example, Valassis, a direct-mail marketing company, shared its massive address database with community groups in New Orleans to visualize and track block-by-block repopulation rates after Hurricane Katrina. A wide number of data collaboratives are also currently being launched to respond to the COVID-19 pandemic. Through its COVID-19 Data Collaborative Program, the location-intelligence company Cuebiq is providing researchers access to the company’s data to study, for instance, the impacts of social distancing policies in Italy and New York City. The health technology company Kinsa Health’s US Health Weather initiative is likewise visualizing the rate of fever across the United States using data from its network of Smart Thermometers, thereby providing early indications regarding the location of likely COVID-19 outbreaks.

Yet despite such initiatives, many open data projects (and data collaboratives) remain fledgling — especially those at the state and local level.

Among other issues, the field has trouble scaling projects beyond initial pilots, and many potential stakeholders — private sector and government “owners” of data, as well as public beneficiaries — remain skeptical of open data’s value. In addition, terabytes of potentially transformative data remain inaccessible for re-use. It is absolutely imperative that we continue to make the case to all stakeholders regarding the importance of open data, and of moving it from an interesting idea to an impactful reality. In order to do this, we need a new resource — one that can inform the public and data owners, and that would guide decision-makers on how to achieve open data in a responsible manner, without undermining privacy and other rights.

Purpose of the Open Data Policy Lab

Today, with support from Microsoft and under the counsel of a global advisory board of open data leaders, The GovLab is launching an initiative designed precisely to build such a resource.

Our Open Data Policy Lab will draw on lessons and experiences from around the world to conduct analysis, provide guidance, build community, and take action to accelerate the responsible re-use and opening of data for the benefit of society and the equitable spread of economic opportunity…(More)”.

Article by Alan Marcus: “…The best responses to Covid-19 have harmonised top-down policies and grassroots organisation. In the UK, more than 700,000 volunteers for the National Health Service are being organised through GoodSAM—an app that, like many gig economy platforms, allows individuals to switch on availability for delivering supplies to vulnerable people.

Perhaps the best example is Taiwan, where officials have kept the rate of infection to a fraction of even highly-rated Singapore. Coordinating public and private groups, the country has deployed a range of online services, including a system for mapping and allocating rationed face masks developed by Digital Minister Audrey Tang and members of an online hacktivist chatroom. …

Effective responses to the crisis show the value of inclusive government and hint at more resilient models for managing our communities. So far, governments, businesses and individuals have pooled resources to deliver country-wide responses. However, this model should be pushed further. Digital tools should be provided to communities to organise themselves, develop locally tailored solutions and get involved in the governance of their town or neighbourhood.

This model requires open communication between local people and the organisations responsible for administrating neighbourhoods—be they governments or businesses. … 

The platform provides significant opportunities for optimising crisis response and elevating quality of life. For example, a popular solution for market vendors forced to close by Covid-19 has been offering delivery services. As well as the businesses, this benefits local people, who can bypass overcrowded superstores or overcapacity online grocery deliveries. While grassroots movements are largely left to organise themselves, this is a missed opportunity for collaboration with local administrators.

By communicating with vendors, the administrator can not only establish an online platform to coordinate their services, but also connect them with local people to help deliver the service, such as van owners who can loan their vehicles. Moreover, the administrator can collect feedback on local infrastructure needed to improve services, such as communal cold lockers for receiving groceries when no-one is home.

By integrating this model into the day-to-day governance of our communities, we can unite community action with top-down resources, empowering local people to co-own the evolution of their neighbourhoods and helping administrators prioritise projects that maximise quality of life.

As Solnit wrote: “A disaster is a lot like a revolution when it comes to disruption and improvisation.” Pushed to their limits, countries are pioneering ways of coordinating local and national action. From this wave of innovation, we can empower communities to become more resilient in crises, more inclusive in their governance and more engaged in the determination of their future….(More)”.

The GovLab: “In response to the COVID-19 pandemic, legislatures at the national, state and local level are adapting to keep the lawmaking process going while minimizing the need for face-to-face meetings. While some have simply lowered quorum thresholds or reduced the number of sessions while continuing to meet in person, others are trialing more ambitious remote participation systems where lawmakers convene, deliberate, and vote virtually. Still others have used shift as an opportunity to create mechanisms for greater civic engagement.

For a short overview of how legislatures in Brazil, Chile, France, and other countries are using technology to convene, deliberate and vote remotely, see the GovLab’s short video, Continuity of Congress.”

Paper by Sarah Giest & Annemarie Samuels: “Policy and data scientists have paid ample attention to the amount of data being collected and the challenge for policymakers to use and utilize it. However, far less attention has been paid towards the quality and coverage of this data specifically pertaining to minority groups. The paper makes the argument that while there is seemingly more data to draw on for policymakers, the quality of the data in combination with potential known or unknown data gaps limits government’s ability to create inclusive policies. In this context, the paper defines primary, secondary, and unknown data gaps that cover scenarios of knowingly or unknowingly missing data and how that is potentially compensated through alternative measures.

Based on the review of the literature from various fields and a variety of examples highlighted throughout the paper, we conclude that the big data movement combined with more sophisticated methods in recent years has opened up new opportunities for government to use existing data in different ways as well as fill data gaps through innovative techniques. Focusing specifically on the representativeness of such data, however, shows that data gaps affect the economic opportunities, social mobility, and democratic participation of marginalized groups. The big data movement in policy may thus create new forms of inequality that are harder to detect and whose impact is more difficult to predict….(More)“.

Paper by Leonardo Bursztyn et al: “We study the effects of news coverage of the novel coronavirus by the two most widely-viewed cable news shows in the United States – Hannity and Tucker Carlson Tonight, both on Fox News – on viewers’ behavior and downstream health outcomes. Carlson warned viewers about the threat posed by the coronavirus from early February, while Hannity originally dismissed the risks associated with the virus before gradually adjusting his position starting late February. We first validate these differences in content with independent coding of show transcripts. In line with the differences in content, we present novel survey evidence that Hannity’s viewers changed behavior in response to the virus later than other Fox News viewers, while Carlson’s viewers changed behavior earlier. We then turn to the effects on the pandemic itself, examining health outcomes across counties.

First, we document that greater viewership of Hannity relative to Tucker Carlson Tonight is strongly associated with a greater number of COVID-19 cases and deaths in the early stages of the pandemic. The relationship is stable across an expansive set of robustness tests. To better identify the effect of differential viewership of the two shows, we employ a novel instrumental variable strategy exploiting variation in when shows are broadcast in relation to local sunset times. These estimates also show that greater exposure to Hannity relative to Tucker Carlson Tonight is associated with a greater number of county-level cases and deaths. Furthermore, the results suggest that in mid-March, after Hannity’s shift in tone, the diverging trajectories on COVID-19 cases begin to revert. We provide additional evidence consistent with misinformation being an important mechanism driving the effects in the data. While our findings cannot yet speak to long-term effects, they indicate that provision of misinformation in the early stages of a pandemic can have important consequences for how a disease ultimately affects the population….(More)”.

Blog by Steven Aftergood: “Hobbled by secrecy and timidity, the U.S. intelligence community has been conspicuously absent from efforts to combat the COVID-19 pandemic, the most serious national and global security challenge of our time.

The silence of intelligence today represents a departure from the straightforward approach of then-Director of National Intelligence Dan Coats who offered the clearest public warning of the risk of a pandemic at the annual threat hearing of the Senate Intelligence Committee in January 2019:

“We assess that the United States and the world will remain vulnerable to the next flu pandemic or large-scale outbreak of a contagious disease that could lead to massive rates of death and disability, severely affect the world economy, strain international resources, and increase calls on the United States for support,” DNI Coats testified.

But this year, for the first time in recent memory, the annual threat hearing was canceled, reportedly to avoid conflict between intelligence testimony and White House messaging. Though that seems humiliating to everyone involved, no satisfactory alternative explanation has been provided. The 2020 worldwide threat statement remains classified, according to an ODNI denial of a Freedom of Information Act request for a copy. And intelligence agencies have been reduced to recirculating reminders from the Centers for Disease Control to wash your hands and practice social distancing.

The US intelligence community evidently has nothing useful to say to the nation about the origins of the COVID-19 pandemic, its current spread or anticipated development, its likely impact on other security challenges, its effect on regional conflicts, or its long-term implications for global health.

These are all topics perfectly suited to open source intelligence collection and analysis. But the intelligence community disabled its open source portal last year. And the general public was barred even from that.

It didn’t — and doesn’t — have to be that way.

In 1993, the Federation of American Scientists created an international email network called ProMED — Program for Monitoring Emerging Diseases — which was intended to help discover and provide early warning about new infectious diseases.

Run on a shoestring budget and led by Stephen S. Morse, Barbara Hatch Rosenberg, Jack Woodall and Dorothy Preslar, ProMED was based on the notion that “public intelligence” is not an oxymoron. That is to say, physicians, scientists, researchers, and other members of the public — not just governments — have the need for current threat assessments that can be readily shared, consumed and analyzed. The initiative quickly proved its worth….(More)”.

Paper by Henry Chesbrough: “Covid-19 has severely tested our public health systems. Recovering from Covid-19 will soon test our economic systems. Innovation will have an important role to play in recovering from the aftermath of the coronavirus. This article discusses both how to manage innovation as part of that recovery, and also derives some lessons from how we have responded to the virus so far, and what those lessons imply for managing innovation during the recovery.

Covid-19’s assault has prompted a number of encouraging developments. One development has been the rapid mobilization of scientists, pharmaceutical companies and government officials to launch a variety of scientific initiatives to find an effective response to the virus. As of the time of this writing, there are tests underway of more than 50 different compounds as possible vaccines against the virus.¹ Most of these will ultimately fail, but the severity of the crisis demands that we investigate every plausible candidate. We need rapid, parallel experimentation, and it must be the test data that select our vaccine, not internal political or bureaucratic processes.

A second development has been the release of copious amounts of information about the virus, its spread, and human responses to various public health measures. The Gates Foundation, working with the Chan-Zuckerberg Foundation and the White House Office of Science and Technology Policy have joined forces to publish all of the known medical literature on the coronavirus, in machine-readable form. This was done with the intent to accelerate the analysis of the existing research to identify possible new avenues of attack against Covid-19. The coronavirus itself was synthesized early on in the outbreak by scientists in China, providing the genetic sequence of the virus, and showing where it differed from earlier viruses such as SARS and MERS. This data was immediately shared widely with scientists and researchers around the world. At the same time, GITHUB and the Humanitarian Data Exchange each have an accumulating series of datasets on the geography of the spread of the disease (including positive test cases, hospitalizations, and deaths).

What these developments have in common is openness. In fighting a pandemic, speed is crucial, and the sooner we know more and are able to take action, the better for all of us. Opening up mobilizes knowledge from many different places, causing our learning to advance and our progress against the disease to accelerate. Openness unleashes a volunteer army of researchers, working in their own facilities, across different time zones, and different countries. Openness leverages the human capital available in the world to tackle the disease, and also accesses the physical capital (such as plant and equipment) already in place to launch rapid testing of possible solutions. This openness corresponds well to an academic body of work called open innovation (Chesbrough, 2003; Chesbrough, 2019).

Innovation is often analyzed in terms of costs, and the question of whether to “make or buy” often rests on which approach costs less. But in a pandemic, time is so valuable and essential, that the question of costs is far less important than the ability to get to a solution sooner. The Covid-19 disease appears to be doubling every 3–5 days, so a delay of just a few weeks in the search for a new vaccine (they normally take 1–2 years to develop, or more) might witness multiple doublings of size of the population infected with the disease. It is for this reason that Bill Gates is providing funds to construct facilities in advance for producing the leading vaccine candidates. Though the facilities for the losing candidates will not be used, it will save precious time to make the winning vaccine in high volume, once it is found.

Open innovation can help speed things up….(More)”.

Paper by Daniel Goldstein and Johannes Wiedemann: “To combat the novel coronavirus, there must be relatively uniform implementation of preventative measures, e.g., social distancing and stay-at-home orders, in order to minimize continued spread. We analyze cellphone mobility data to measure county-level compliance with these critical public health policies. Leveraging staggered roll-out, we estimate the causal effect of stay-at-home orders on mobility using a difference-in-differences strategy, which we find to have significantly curtailed movement.

However, examination of descriptive heterogeneous effects suggests the critical role that several sociopolitical attributes hold for producing asymmetrical compliance across society. We examine measures of partisanship, partisan identity being shared with government leaders, and trust in government (measured by the proxies of voter turnout and social capital). We find that Republican counties comply less, but comply relatively more when directives are given by co-partisan leaders, suggesting citizens are more trusting in the authority of co-partisans. Furthermore, our proxy measures suggest that trust in government increases overall compliance. However, when trust (as measured by social capital) is interacted with county-level partisanship, which we interpret as community-level trust, we find that trust amplifies compliance or noncompliance, depending upon the prevailing community sentiment.

We argue that these results align with a theory of public policy compliance in which individual behavior is informed by one’s level of trust in the experts who craft policy and one’s trust in those who implement it, i.e., politicians and bureaucrats. Moreover, this evaluation is amplified by local community sentiments. Our results are supportive of this theory and provide a measure of the real-world importance of trust in government to citizen welfare. Moreover, our results illustrate the role that political polarization plays in creating asymmetrical compliance with mitigation policies, an outcome that may prove severely detrimental to successful containment of the COVID-19 pandemic….(More)”.