How Taiwan Used Big Data, Transparency and a Central Command to Protect Its People from Coronavirus


Article by Beth Duff-Brown: “…So what steps did Taiwan take to protect its people? And could those steps be replicated here at home?

Stanford Health Policy’s Jason Wang, MD, PhD, an associate professor of pediatrics at Stanford Medicine who also has a PhD in policy analysis, credits his native Taiwan with using new technology and a robust pandemic prevention plan put into place at the 2003 SARS outbreak.

“The Taiwan government established the National Health Command Center (NHCC) after SARS and it’s become part of a disaster management center that focuses on large-outbreak responses and acts as the operational command point for direct communications,” said Wang, a pediatrician and the director of the Center for Policy, Outcomes, and Prevention at Stanford. The NHCC also established the Central Epidemic Command Center, which was activated in early January.

“And Taiwan rapidly produced and implemented a list of at least 124 action items in the past five weeks to protect public health,” Wang said. “The policies and actions go beyond border control because they recognized that that wasn’t enough.”

Wang outlines the measures Taiwan took in the last six weeks in an article published Tuesday in the Journal of the American Medical Association.

“Given the continual spread of COVID-19 around the world, understanding the action items that were implemented quickly in Taiwan, and the effectiveness of these actions in preventing a large-scale epidemic, may be instructive for other countries,” Wang and his co-authors wrote.

Within the last five weeks, Wang said, the Taiwan epidemic command center rapidly implemented those 124 action items, including border control from the air and sea, case identification using new data and technology, quarantine of suspicious cases, educating the public while fighting misinformation, negotiating with other countries — and formulating policies for schools and businesses to follow.

Big Data Analytics

The authors note that Taiwan integrated its national health insurance database with its immigration and customs database to begin the creation of big data for analytics. That allowed them case identification by generating real-time alerts during a clinical visit based on travel history and clinical symptoms.

Taipei also used Quick Response (QR) code scanning and online reporting of travel history and health symptoms to classify travelers’ infectious risks based on flight origin and travel history in the last 14 days. People who had not traveled to high-risk areas were sent a health declaration border pass via SMS for faster immigration clearance; those who had traveled to high-risk areas were quarantined at home and tracked through their mobile phones to ensure that they stayed home during the incubation period.

The country also instituted a toll-free hotline for citizens to report suspicious symptoms in themselves or others. As the disease progressed, the government called on major cities to establish their own hotlines so that the main hotline would not become jammed….(More)”.

Milwaukee’s Amani Neighborhood Uses Data to Target Traffic Safety and Build Trust


Article by Kassie Scott: “People in Milwaukee’s Amani neighborhood are using data to identify safety issues and build relationships with the police. It’s a story of community-engaged research at its best.

In 2017, the Milwaukee Police Department received a grant under the federal Byrne Criminal Justice Innovation program, now called the Community Based Crime Reduction Program, whose purpose is to bridge the gap between practitioners and researchers and advance the use of data in making communities safer. Because of its close ties in the Amani neighborhood, the Dominican Center was selected to lead this initiative, known as the Amani Safety Initiative, and they partnered with local churches, the district attorney’s office, LISC-Milwaukee, and others. To support the effort with data and coaching, the police department contracted with Data You Can Use.

Together with Data You Can Use, the Amani Safety Initiative team first implemented a survey to gauge perceptions of public safety and police legitimacy. Neighborhood ambassadors were trained (and paid) to conduct the survey themselves, going door to door to gather the information from nearly 300 of their neighbors. The ambassadors shared these results with their neighborhood during what they called “data chats.” They also printed summary survey results on door hangers, which they distributed throughout the neighborhood.

Neighbors and community organizations were surprised by the survey results. Though violent crime and mistrust in the police were commonly thought to be the biggest issues, the data showed that residents were most concerned about traffic safety. Ultimately, residents decided to post slow-down signs in intersections.

This project stands out for letting the people in the neighborhood lead the way. Neighbors collected data, shared results, and took action. The partnership between neighbors, police, and local organizations shows how people can drive decision-making for their neighborhood.

The larger story is one of social cohesion and mutual trust. Through participating in the initiative and learning more about their neighborhood, Amani neighbors built stronger relationships with the police. The police began coming to neighborhood community meetings, which helped them build relationships with people in the community and understand the challenges they face….(More).

Data-driven models of governance across borders: Datafication from the local to the global


Payal Arora and Hallam Stevens at First Monday: “This special issue looks closely at contemporary data systems in diverse global contexts and through this set of papers, highlights the struggles we face as we negotiate efficiency and innovation with universal human rights and social inclusion. The studies presented in these essays are situated in diverse models of policy-making, governance, and/or activism across borders. Attention to big data governance in western contexts has tended to highlight how data increases state and corporate surveillance of citizens, affecting rights to privacy. By moving beyond Euro-American borders — to places such as Africa, India, China, and Singapore — we show here how data regimes are motivated and understood on very different terms….(More)”.

The human rights impacts of migration control technologies


Petra Molnar at EDRI: “At the start of this new decade, over 70 million people have been forced to move due to conflict, instability, environmental factors, and economic reasons. As a response to the increased migration into the European Union, many states are looking into various technological experiments to strengthen border enforcement and manage migration. These experiments range from Big Data predictions about population movements in the Mediterranean to automated decision-making in immigration applications and Artificial Intelligence (AI) lie detectors at European borders. However, often these technological experiments do not consider the profound human rights ramifications and real impacts on human lives

A human laboratory of high risk experiments

Technologies of migration management operate in a global context. They reinforce institutions, cultures, policies and laws, and exacerbate the gap between the public and the private sector, where the power to design and deploy innovation comes at the expense of oversight and accountability. Technologies have the power to shape democracy and influence elections, through which they can reinforce the politics of exclusion. The development of technology also reinforces power asymmetries between countries and influence our thinking around which countries can push for innovation, while other spaces like conflict zones and refugee camps become sites of experimentation. The development of technology is not inherently democratic and issues of informed consent and right of refusal are particularly important to think about in humanitarian and forced migration contexts. For example, under the justification of efficiency, refugees in Jordan have their irises scanned in order to receive their weekly rations. Some refugees in the Azraq camp have reported feeling like they did not have the option to refuse to have their irises scanned, because if they did not participate, they would not get food. This is not free and informed consent….(More)”.

Wanted: Data Stewards: (Re-)Defining The Roles and Responsibilities of Data Stewards for an Age of Data Collaboration


Wanted: Data Stewards: (Re-)Defining The Roles and Responsibilities of Data Stewards for an Age of Data Collaboration

Stefaan G. Verhulst, Andrew Zahuranec, Andrew Young and Michelle Winowatan at Data & Policy: “As data grows increasingly prevalent in our economy, it is increasingly clear, too, that tremendous societal value can be derived from reusing and combining previously separate datasets. One avenue that holds particular promise are data collaboratives. Data collaboratives are a new form of partnership in which data (such as data owned by corporations) or data expertise is made accessible for external parties (such as academics or statistical offices) working in the public interest. By bringing together a wide range of inter-sectoral expertise to bear on the data, collaboration can result in new insights and innovations, and can help unlock the public good potential of previously siloed data or expertise.

Yet, not all data collaboratives are successful or go beyond pilots. Based on research and analysis of hundreds of data collaboratives, one factor seems to stand out as determinative of success above all others — whether there exist individuals or teams within data-holding organizations who are empowered to proactively initiate, facilitate and coordinate data collaboratives toward the public interest. We call these individuals and teams “data stewards.”

They systematize the process of partnering, and help scale efforts when there are fledgling signs of success. Data stewards are essential for accelerating the re-use of data in the public interest by providing functional access, and more generally, to unlock the potential of our data age. Data stewards form an important — and new — link in the data value chain.

In its final report, the European Commission’s High-Level Expert Group on Business-to-Government (B2G) Data Sharing also noted the need for data stewards to enable responsible, accountable data sharing for the public interest. In their report, they write:

“A key success factor in setting up sustainable and responsible B2G partnerships is the existence, within both public- and private-sector organisations, of individuals or teams that are empowered to proactively initiate, facilitate and coordinate B2G data sharing when necessary. As such, ‘data stewards’ should become a recognised function.”

The report goes on further to acknowledge the need to scope, design, and establish a network or a community of practice around data stewardship.

Wanted: Data Stewards

A new position paper, released by The GovLab within the context of the UN Statistical Commission High-Level Forum on Official Statistics which focused on “Data stewardship — a solution for official statistics’ predicament?” seeks to begin that work. The paper, titled “Wanted: Data Stewards: (Re-)Defining The Roles and Responsibilities of Data Stewards for an Age of Data Collaboration” tackles questions regarding the profile and potential of data stewards. It aims to provide an operational roadmap to support the implementation (or expansion) of data stewardship functions in public- and private-sector entities; and to start building a community of expertise.

Moreover, it addresses the tendency to conflate the roles of data stewards with those of individuals or groups who might better be described as chief privacy, chief data or chief security officers. This slippage is perhaps understandable, we need to redefine the role that is somewhat broader. While data management, privacy and security are key components of trusted and effective data collaboratives, the real goal is to re-use data for broader social goals (while preventing any potential harms that may result from sharing).

In particular the position paper — which captures lived experience of numerous data stewards- seeks to provide more clarity on how data stewards can accomplish these duties by:

  • Defining the responsibilities of a data steward; and
  • Identifying the roles which a data steward must fill to achieve these responsibilities…(More)”.

Is Your Data Being Collected? These Signs Will Tell You Where


Flavie Halais at Wired: “Alphabet’s Sidewalk Labs is testing icons that provide “digital transparency” when information is collected in public spaces….

As cities incorporate digital technologies into their landscapes, they face the challenge of informing people of the many sensors, cameras, and other smart technologies that surround them. Few people have the patience to read through the lengthy privacy notice on a website or smartphone app. So how can a city let them know how they’re being monitored?

Sidewalk Labs, the Google sister company that applies technology to urban problems, is taking a shot. Through a project called Digital Transparency in the Public Realm, or DTPR, the company is demonstrating a set of icons, to be displayed in public spaces, that shows where and what kinds of data are being collected. The icons are being tested as part Sidewalk Labs’ flagship project in Toronto, where it plans to redevelop a 12-acre stretch of the city’s waterfront. The signs would be displayed at each location where data would be collected—streets, parks, businesses, and courtyards.

Data collection is a core feature of the project, called Sidewalk Toronto, and the source of much of the controversy surrounding it. In 2017, Waterfront Toronto, the organization in charge of administering the redevelopment of the city’s eastern waterfront, awarded Sidewalk Labs the contract to develop the waterfront site. The project has ambitious goals: It says it could create 44,000 direct jobs by 2040 and has the potential to be the largest “climate-positive” community—removing more CO2 from the atmosphere than it produces—in North America. It will make use of new urban technology like modular street pavers and underground freight delivery. Sensors, cameras, and Wi-Fi hotspots will monitor and control traffic flows, building temperature, and crosswalk signals.

All that monitoring raises inevitable concerns about privacy, which Sidewalk aims to address—at least partly—by posting signs in the places where data is being collected.

The signs display a set of icons in the form of stackable hexagons, derived in part from a set of design rules developed by Google in 2014. Some describe the purpose for collecting the data (mobility, energy efficiency, or waste management, for example). Others refer to the type of data that’s collected, such as photos, air quality, or sound. When the data is identifiable, meaning it can be associated with a person, the hexagon is yellow. When the information is stripped of personal identifiers, the hexagon is blue…(More)”.

Eurobarometer survey shows support for sustainability and data sharing


Press Release: “Europeans want their digital devices to be easier to repair or recycle and are willing to share their personal information to improve public services, as a special Eurobarometer survey shows. The survey, released today, measured attitudes towards the impact of digitalisation on daily lives of Europeans in 27 EU Member States and the United Kingdom. It covers several different areas including digitalisation and the environment, sharing personal information, disinformation, digital skills and the use of digital ID….

Overall, 59% of respondents would be willing to share some of their personal information securely to improve public services. In particular, most respondents are willing to share their data to improve medical research and care (42%), to improve the response to crisis (31%) or to improve public transport and reduce air pollution (26%).

An overwhelming majority of respondents who use their social media accounts to log in to other online services (74%) want to know how their data is used. A large majority would consider it useful to have a secure single digital ID that could serve for all online services and give them control over the use of their data….

In addition to the Special Eurobarometer report, the last iteration of the Standard Eurobarometer conducted in November 2019 also tested public perceptions related to Artificial Intelligence. The findings also published in a separate report today.

Around half of the respondents (51%) said that public policy intervention is needed to ensure ethical applications. Half of the respondents (50%) mention the healthcare sector as the area where AI could be most beneficial. A strong majority (80%) of the respondents think that they should be informed when a digital service or mobile application uses AI in various situations….(More)”.

The Power of Experiments: Decision Making in a Data-Driven World


Book by By Michael Luca and Max H. Bazerman: “Have you logged into Facebook recently? Searched for something on Google? Chosen a movie on Netflix? If so, you’ve probably been an unwitting participant in a variety of experiments—also known as randomized controlled trials—designed to test the impact of different online experiences. Once an esoteric tool for academic research, the randomized controlled trial has gone mainstream. No tech company worth its salt (or its share price) would dare make major changes to its platform without first running experiments to understand how they would influence user behavior. In this book, Michael Luca and Max Bazerman explain the importance of experiments for decision making in a data-driven world.

Luca and Bazerman describe the central role experiments play in the tech sector, drawing lessons and best practices from the experiences of such companies as StubHub, Alibaba, and Uber. Successful experiments can save companies money—eBay, for example, discovered how to cut $50 million from its yearly advertising budget—or bring to light something previously ignored, as when Airbnb was forced to confront rampant discrimination by its hosts. Moving beyond tech, Luca and Bazerman consider experimenting for the social good—different ways that governments are using experiments to influence or “nudge” behavior ranging from voter apathy to school absenteeism. Experiments, they argue, are part of any leader’s toolkit. With this book, readers can become part of “the experimental revolution.”…(More)”.

Facebook Ads as a Demographic Tool to Measure the Urban-Rural Divide


Paper by Daniele Rama, Yelena Mejova, Michele Tizzoni, Kyriaki Kalimeri, and Ingmar Weber: “In the global move toward urbanization, making sure the people remaining in rural areas are not left behind in terms of development and policy considerations is a priority for governments worldwide. However, it is increasingly challenging to track important statistics concerning this sparse, geographically dispersed population, resulting in a lack of reliable, up-to-date data. In this study, we examine the usefulness of the Facebook Advertising platform, which offers a digital “census” of over two billions of its users, in measuring potential rural-urban inequalities.

We focus on Italy, a country where about 30% of the population lives in rural areas. First, we show that the population statistics that Facebook produces suffer from instability across time and incomplete coverage of sparsely populated municipalities. To overcome such limitation, we propose an alternative methodology for estimating Facebook Ads audiences that nearly triples the coverage of the rural municipalities from 19% to 55% and makes feasible fine-grained sub-population analysis. Using official national census data, we evaluate our approach and confirm known significant urban-rural divides in terms of educational attainment and income. Extending the analysis to Facebook-specific user “interests” and behaviors, we provide further insights on the divide, for instance, finding that rural areas show a higher interest in gambling. Notably, we find that the most predictive features of income in rural areas differ from those for urban centres, suggesting researchers need to consider a broader range of attributes when examining rural wellbeing. The findings of this study illustrate the necessity of improving existing tools and methodologies to include under-represented populations in digital demographic studies — the failure to do so could result in misleading observations, conclusions, and most importantly, policies….(More)”.

Beyond Randomized Controlled Trials


Iqbal Dhaliwal, John Floretta & Sam Friedlander at SSIR: “…In its post-Nobel phase, one of J-PAL’s priorities is to unleash the treasure troves of big digital data in the hands of governments, nonprofits, and private firms. Primary data collection is by far the most time-, money-, and labor-intensive component of the vast majority of experiments that evaluate social policies. Randomized evaluations have been constrained by simple numbers: Some questions are just too big or expensive to answer. Leveraging administrative data has the potential to dramatically expand the types of questions we can ask and the experiments we can run, as well as implement quicker, less expensive, larger, and more reliable RCTs, an invaluable opportunity to scale up evidence-informed policymaking massively without dramatically increasing evaluation budgets.

Although administrative data hasn’t always been of the highest quality, recent advances have significantly increased the reliability and accuracy of GPS coordinates, biometrics, and digital methods of collection. But despite good intentions, many implementers—governments, businesses, and big NGOs—aren’t currently using the data they already collect on program participants and outcomes to improve anti-poverty programs and policies. This may be because they aren’t aware of its potential, don’t have the in-house technical capacity necessary to create use and privacy guidelines or analyze the data, or don’t have established partnerships with researchers who can collaborate to design innovative programs and run rigorous experiments to determine which are the most impactful. 

At J-PAL, we are leveraging this opportunity through a new global research initiative we are calling the “Innovations in Data and Experiments for Action” Initiative (IDEA). IDEA supports implementers to make their administrative data accessible, analyze it to improve decision-making, and partner with researchers in using this data to design innovative programs, evaluate impact through RCTs, and scale up successful ideas. IDEA will also build the capacity of governments and NGOs to conduct these types of activities with their own data in the future….(More)”.