What Ever Happened to Digital Contact Tracing?


Chas Kissick, Elliot Setzer, and Jacob Schulz at Lawfare: “In May of this year, Prime Minister Boris Johnson pledged the United Kingdom would develop a “world beating” track and trace system by June 1 to stop the spread of the novel coronavirus. But on June 18, the government quietly abandoned its coronavirus contact-tracing app, a key piece of the “world beating” strategy, and instead promised to switch to a model designed by Apple and Google. The delayed app will not be ready until winter, and the U.K.’s Junior Health Minister told reporters that “it isn’t a priority for us at the moment.” When Johnson came under fire in Parliament for the abrupt U-turn, he replied: “I wonder whether the right honorable and learned Gentleman can name a single country in the world that has a functional contact tracing app—there isn’t one.”

Johnson’s rebuttal is perhaps a bit reductive, but he’s not that far off.

You probably remember the idea of contact-tracing apps: the technological intervention that seemed to have the potential to save lives while enabling a hamstrung economy to safely inch back open; it was a fixation of many public health and privacy advocates; it was the thing that was going to help us get out of this mess if we could manage the risks.

Yet nearly three months after Google and Apple announced with great fanfare their partnership to build a contact-tracing API, contact-tracing apps have made an unceremonious exit from the front pages of American newspapers. Countries, states and localities continue to try to develop effective digital tracing strategies. But as Jonathan Zittrain puts it, the “bigger picture momentum appears to have waned.”

What’s behind contact-tracing apps’ departure from the spotlight? For one, there’s the onset of a larger pandemic apathy in the U.S; many politicians and Americans seem to have thrown up their hands or put all their hopes in the speedy development of a vaccine. Yet, the apps haven’t even made much of a splash in countries that havetaken the pandemic more seriously. Anxieties about privacy persist. But technical shortcomings in the apps deserve the lion’s share of the blame. Countries have struggled to get bespoke apps developed by government technicians to work on Apple phones. The functionality of some Bluetooth-enabled models vary widely depending on small changes in phone positioning. And most countries have only convinced a small fraction of their populace to use national tracing apps.

Maybe it’s still possible that contact-tracing apps will make a miraculous comeback and approach the level of efficacy observers once anticipated.

But even if technical issues implausibly subside, the apps are operating in a world of unknowns.

Most centrally, researchers still have no real idea what level of adoption is required for the apps to actually serve their function. Some estimates suggest that 80 percent of current smartphone owners in a given area would need to use an app and follow its recommendations for digital contact tracing to be effective. But other researchers have noted that the apps could slow the rate of infections even if little more than 10 percent of a population used a tracing app. It will be an uphill battle even to hit the 10 percent mark in America, though. Survey data show that fewer than three in 10 Americans intend to use contact-tracing apps if they become available…(More).

Reinventing Public Administration for a Dangerous Century


Paper by Alasdair S. Roberts: “The first two decades of this century have shown there is no simple formula for governing well. Leaders must make difficult choices about national priorities and the broad lines of policy – that is, about the substance of their strategy for governing. These strategic choices have important implications for public administration. Scholars in this field should study the processes by which strategy is formulated and executed more closely than they have over the last thirty years. A new agenda for public administration should emphasize processes of top-level decision-making, mechanisms to improve foresight and the management of societal risks, and problems of large-scale reorganization and inter-governmental coordination, among other topics. Many of these themes have been examined more closely by researchers in Canada than by those abroad. This difference should be recognized an advantage rather than a liability….(More)”.

Covid-19 data is a public good. The US government must start treating it like one.


Ryan Panchadsaramarchive at MIT Technology Review: “…When the Trump administration stripped the Centers for Disease Control and Prevention (CDC) of control over coronavirus data, it also took that information away from the public….

This is also an opportunity for HHS to make this data machine readable and thereby more accessible to data scientists and data journalists. The Open Government Data Act, signed into law by President Trump, treats data as a strategic asset and makes it open by default. This act builds upon the Open Data Executive Order, which recognized that the data sets collected by the government are paid for by taxpayers and must be made available to them. 

As a country, the United States has lagged behind in so many dimensions of response to this crisis, from the availability of PPE to testing to statewide mask orders. Its treatment of data has lagged as well. On March 7, as this crisis was unfolding, there was no national testing data. Alexis Madrigal, Jeff Hammerbacher, and a group of volunteers started the COVID Tracking Project to aggregate coronavirus information from all 50 state websites into a single Google spreadsheet. For two months, until the CDC began to share data through its own dashboard, this volunteer project was the sole national public source of information on cases and testing. 

With more than 150 volunteers contributing to the effort, the COVID Tracking Project sets the bar for how to treat data as an asset. I serve on the advisory board and am awed by what this group has accomplished. With daily updates, an API, and multiple download formats, they’ve made their data extraordinarily useful. Where the CDC’s data is cited 30 times in Google Scholar and approximately 10,000 times in Google search results, the COVID Tracking Project data is cited 299 times in Google Scholar and roughly 2 million times in Google search results.

Sharing reliable data is one of the most economical and effective interventions the United States has to confront this pandemic. With the Coronavirus Task Force daily briefings a thing of the past, it’s more necessary than ever for all covid-related data to be shared with the public. The effort required to defeat the pandemic is not just a federal response. It is a federal, state, local, and community response. Everyone needs to work from the same trusted source of facts about the situation on the ground. Data is not a partisan affair or a bureaucratic preserve. It is a public trust—and a public resource….(More)”.

Are Food Labels Good?


Paper by Cass Sunstein: “Do people from benefit from food labels? When? By how much? Public officials face persistent challenges in answering these questions. In various nations, they use four different approaches: they refuse to do so on the ground that quantification is not feasible; they engage in breakeven analysis; they project end-states, such as economic savings or health outcomes; and they estimate willingness-to-pay for the relevant information. Each of these approaches runs into strong objections. In principle, the willingness-to-pay question has important advantages. But for those who has that question, there is a serious problem. In practice, people often lack enough information to give a sensible answer to the question how much they would be willing to pay for (more) information. People might also suffer from behavioral biases (including present bias and optimistic bias). And when preferences are labile or endogenous, even an informed and unbiased answer to the willingness to pay question may fail to capture the welfare consequences, because people may develop new tastes and values as a result of information….(More)”.

The National Cancer Institute Cancer Moonshot Public Access and Data Sharing Policy—Initial assessment and implications


Paper by Tammy M. Frisby and Jorge L. Contreras: “Since 2013, federal research-funding agencies have been required to develop and implement broad data sharing policies. Yet agencies today continue to grapple with the mechanisms necessary to enable the sharing of a wide range of data types, from genomic and other -omics data to clinical and pharmacological data to survey and qualitative data. In 2016, the National Cancer Institute (NCI) launched the ambitious $1.8 billion Cancer Moonshot Program, which included a new Public Access and Data Sharing (PADS) Policy applicable to funding applications submitted on or after October 1, 2017. The PADS Policy encourages the immediate public release of published research results and data and requires all Cancer Moonshot grant applicants to submit a PADS plan describing how they will meet these goals. We reviewed the PADS plans submitted with approximately half of all funded Cancer Moonshot grant applications in fiscal year 2018, and found that a majority did not address one or more elements required by the PADS Policy. Many such plans made no reference to the PADS Policy at all, and several referenced obsolete or outdated National Institutes of Health (NIH) policies instead. We believe that these omissions arose from a combination of insufficient education and outreach by NCI concerning its PADS Policy, both to potential grant applicants and among NCI’s program staff and external grant reviewers. We recommend that other research funding agencies heed these findings as they develop and roll out new data sharing policies….(More)”.

The Computermen


Podcast Episode by Jill Lepore: “In 1966, just as the foundations of the Internet were being imagined, the federal government considered building a National Data Center. It would be a centralized federal facility to hold computer records from each federal agency, in the same way that the Library of Congress holds books and the National Archives holds manuscripts. Proponents argued that it would help regulate and compile the vast quantities of data the government was collecting. Quickly, though, fears about privacy, government conspiracies, and government ineptitude buried the idea. But now, that National Data Center looks like a missed opportunity to create rules about data and privacy before the Internet took off. And in the absence of government action, corporations have made those rules themselves….(More)”.

The Data Assembly


Press Release: “The Governance Lab (The GovLab), an action research center at New York University Tandon School of Engineering, with the support of the Henry Luce Foundation, announced the creation of The Data Assembly. Beginning in New York City, the effort will explore how communities perceive the risks and benefits of data re-use for COVID-19. Understanding that policymakers often lack information about the concerns of different stakeholders, The Data Assembly’s deliberations will inform the creation of a responsible data re-use framework to guide the use of data and technology at the city and state level to fight COVID-19’s many consequences.

The Data Assembly will hold deliberations with civil rights organizations, key data holders and policymakers, and the public at large. Consultations with these stakeholders will take place through a series of remote engagements, including surveys and an online town hall meeting. This work will allow the project to consider the perspectives of people from different strata of society and how they might exercise some control over the flow of data.

After the completion of these data re-use deliberations, The Data Assembly will create a path forward for using data responsibly to solve public challenges. The first phases of the project will commence in New York City, seeking to engage with city residents and their leaders on data governance issues. 

“Data is increasingly the primary format for sharing information to understand crises and plan recovery efforts; empowering everyone to better understand how data is collected and how it should be used is paramount,” said Adrienne Schmoeker, Director of Civic Engagement & Strategy and Deputy Chief Analytics Officer at the NYC Mayor’s Office of Data Analytics. “We look forward to learning from the insights gathered by the GovLab through The Data Assembly work they are conducting in New York City.”…(More)”.

Wrongfully Accused by an Algorithm


Kashmir Hill at the New York Times: “In what may be the first known case of its kind, a faulty facial recognition match led to a Michigan man’s arrest for a crime he did not commit….

The Shinola shoplifting occurred in October 2018. Katherine Johnston, an investigator at Mackinac Partners, a loss prevention firm, reviewed the store’s surveillance video and sent a copy to the Detroit police, according to their report.

Five months later, in March 2019, Jennifer Coulson, a digital image examiner for the Michigan State Police, uploaded a “probe image” — a still from the video, showing the man in the Cardinals cap — to the state’s facial recognition database. The system would have mapped the man’s face and searched for similar ones in a collection of 49 million photos.

The state’s technology is supplied for $5.5 million by a company called DataWorks Plus. Founded in South Carolina in 2000, the company first offered mug shot management software, said Todd Pastorini, a general manager. In 2005, the firm began to expand the product, adding face recognition tools developed by outside vendors.

When one of these subcontractors develops an algorithm for recognizing faces, DataWorks attempts to judge its effectiveness by running searches using low-quality images of individuals it knows are present in a system. “We’ve tested a lot of garbage out there,” Mr. Pastorini said. These checks, he added, are not “scientific” — DataWorks does not formally measure the systems’ accuracy or bias.

“We’ve become a pseudo-expert in the technology,” Mr. Pastorini said.

In Michigan, the DataWorks software used by the state police incorporates components developed by the Japanese tech giant NEC and by Rank One Computing, based in Colorado, according to Mr. Pastorini and a state police spokeswoman. In 2019, algorithms from both companies were included in a federal study of over 100 facial recognition systems that found they were biased, falsely identifying African-American and Asian faces 10 times to 100 times more than Caucasian faces….(More)“.

The Data Dividend Project


About: “The Data Dividend Project is a movement dedicated to taking back control of our personal data: our data is our property, and if we allow companies to use it, we should get paid for it. The DDP is the brainchild of former presidential candidate Andrew Yang. Its primary objective is to establish and enforce data property rights under laws such as the California Consumer Privacy Act (CCPA), which went into effect on January 1, 2020.

Every day, people are generating data simply by going about the business of living in an ever connected and digital world. Unbeknownst to most people, technology companies are tracking their every move online, extracting this data, and then buying and selling it for big money. The sale and resale of consumer data is called data brokering, which is itself a $200 billion industry.

For example, technology companies can extract location data from your mobile phone and sell it to advertisers who can then turn around and post local ads to you in real time. Until recently, the data collector – in this case, the technology company – was deemed to own the data. As the owner, the technology company could sell that data and profit handsomely. Meanwhile, you generated the data but received no share of those profits. DDP plans to change that.

Until this year, you, as the American consumer, had little recourse against technology companies who were profiting off your data without your consent or knowledge. Now, under the CCPA, Californians are endowed with a collection of unalienable data rights: the right to know what information is being collected on you, the right to delete that information, and the right to opt-out from technology companies collecting your data. These rights, however, are ignored and abused by technology companies. And unfortunately, individual consumers don’t have the leverage to be able to go up against these companies. That’s where DDP comes in….(More)

Best Practices to Cover Ad Information Used for Research, Public Health, Law Enforcement & Other Uses


Press Release: “The Network Advertising Initiative (NAI) released privacy Best Practices for its members to follow if they use data collected for Tailored Advertising or Ad Delivery and Reporting for non-marketing purposes, such as sharing with research institutions, public health agencies, or law enforcement entities.

“Ad tech companies have data that can be a powerful resource for the public good if they follow this set of best practices for consumer privacy,” said Leigh Freund, NAI President and CEO. “During the COVID-19 pandemic, we’ve seen the opportunity for substantial public health benefits from sharing aggregate and de-identified location data.”

The NAI Code of Conduct – the industry’s premier self-regulatory framework for privacy, transparency, and consumer choice – covers data collected and used for Tailored Advertising or Ad Delivery and Reporting. The NAI Code has long addressed certain non-marketing uses of data collected for Tailored Advertising and Ad Delivery and Reporting by prohibiting any
eligibility uses of such data, including uses for credit, insurance, healthcare, and employment decisions.

The NAI has always firmly believed that data collected for advertising purposes should not have a negative effect on consumers in their daily lives. However, over the past year, novel data uses have been introduced, especially during the recent health crisis. In the case of opted-in data such as Precise Location Information, a company may determine a user would benefit from more detailed disclosure in a just-in-time notice about non-marketing uses of the data being collected….(More)”.