Sharing Private Data for Public Good


Stefaan G. Verhulst at Project Syndicate: “After Hurricane Katrina struck New Orleans in 2005, the direct-mail marketing company Valassis shared its database with emergency agencies and volunteers to help improve aid delivery. In Santiago, Chile, analysts from Universidad del Desarrollo, ISI Foundation, UNICEF, and the GovLab collaborated with Telefónica, the city’s largest mobile operator, to study gender-based mobility patterns in order to design a more equitable transportation policy. And as part of the Yale University Open Data Access project, health-care companies Johnson & Johnson, Medtronic, and SI-BONE give researchers access to previously walled-off data from 333 clinical trials, opening the door to possible new innovations in medicine.

These are just three examples of “data collaboratives,” an emerging form of partnership in which participants exchange data for the public good. Such tie-ups typically involve public bodies using data from corporations and other private-sector entities to benefit society. But data collaboratives can help companies, too – pharmaceutical firms share data on biomarkers to accelerate their own drug-research efforts, for example. Data-sharing initiatives also have huge potential to improve artificial intelligence (AI). But they must be designed responsibly and take data-privacy concerns into account.

Understanding the societal and business case for data collaboratives, as well as the forms they can take, is critical to gaining a deeper appreciation the potential and limitations of such ventures. The GovLab has identified over 150 data collaboratives spanning continents and sectors; they include companies such as Air FranceZillow, and Facebook. Our research suggests that such partnerships can create value in three main ways….(More)”.

The Ethics of Hiding Your Data From the Machines


Molly Wood at Wired: “…But now that data is being used to train artificial intelligence, and the insights those future algorithms create could quite literally save lives.

So while targeted advertising is an easy villain, data-hogging artificial intelligence is a dangerously nuanced and highly sympathetic bad guy, like Erik Killmonger in Black Panther. And it won’t be easy to hate.

I recently met with a company that wants to do a sincerely good thing. They’ve created a sensor that pregnant women can wear, and it measures their contractions. It can reliably predict when women are going into labor, which can help reduce preterm births and C-sections. It can get women into care sooner, which can reduce both maternal and infant mortality.

All of this is an unquestionable good.

And this little device is also collecting a treasure trove of information about pregnancy and labor that is feeding into clinical research that could upend maternal care as we know it. Did you know that the way most obstetricians learn to track a woman’s progress through labor is based on a single study from the 1950s, involving 500 women, all of whom were white?…

To save the lives of pregnant women and their babies, researchers and doctors, and yes, startup CEOs and even artificial intelligence algorithms need data. To cure cancer, or at least offer personalized treatments that have a much higher possibility of saving lives, those same entities will need data….

And for we consumers, well, a blanket refusal to offer up our data to the AI gods isn’t necessarily the good choice either. I don’t want to be the person who refuses to contribute my genetic data via 23andMe to a massive research study that could, and I actually believe this is possible, lead to cures and treatments for diseases like Parkinson’s and Alzheimer’s and who knows what else.

I also think I deserve a realistic assessment of the potential for harm to find its way back to me, because I didn’t think through or wasn’t told all the potential implications of that choice—like how, let’s be honest, we all felt a little stung when we realized the 23andMe research would be through a partnership with drugmaker (and reliable drug price-hiker) GlaxoSmithKline. Drug companies, like targeted ads, are easy villains—even though this partnership actually couldproduce a Parkinson’s drug. But do we know what GSK’s privacy policy looks like? That deal was a level of sharing we didn’t necessarily expect….(More)”.

After Technopoly


Alan Jacobs at the New Atlantis: “Technocratic solutionism is dying. To replace it, we must learn again the creation and reception of myth….
What Neil Postman called “technopoly” may be described as the universal and virtually inescapable rule of our everyday lives by those who make and deploy technology, especially, in this moment, the instruments of digital communication. It is difficult for us to grasp what it’s like to live under technopoly, or how to endure or escape or resist the regime. These questions may best be approached by drawing on a handful of concepts meant to describe a slightly earlier stage of our common culture.

First, following on my earlier essay in these pages, “Wokeness and Myth on Campus” (Summer/Fall 2017), I want to turn again to a distinction by the Polish philosopher Leszek Kołakowski between the “technological core” of culture and the “mythical core” — a distinction he believed is essential to understanding many cultural developments.

“Technology” for Kołakowski is something broader than we usually mean by it. It describes a stance toward the world in which we view things around us as objects to be manipulated, or as instruments for manipulating our environment and ourselves. This is not necessarily meant in a negative sense; some things ought to be instruments — the spoon I use to stir my soup — and some things need to be manipulated — the soup in need of stirring. Besides tools, the technological core of culture includes also the sciences and most philosophy, as those too are governed by instrumental, analytical forms of reasoning by which we seek some measure of control.

By contrast, the mythical core of culture is that aspect of experience that is not subject to manipulation, because it is prior to our instrumental reasoning about our environment. Throughout human civilization, says Kołakowski, people have participated in myth — they may call it “illumination” or “awakening” or something else — as a way of connecting with “nonempirical unconditioned reality.” It is something we enter into with our full being, and all attempts to describe the experience in terms of desire, will, understanding, or literal meaning are ways of trying to force the mythological core into the technological core by analyzing and rationalizing myth and pressing it into a logical order. This is why the two cores are always in conflict, and it helps to explain why rational argument is often a fruitless response to people acting from the mythical core….(More)”.

We Need a New Science of Progress


Patrick Collison and Tyler Cowen in The Atlantic: “In 1861, the American scientist and educator William Barton Rogers published a manifesto calling for a new kind of research institution. Recognizing the “daily increasing proofs of the happy influence of scientific culture on the industry and the civilization of the nations,” and the growing importance of what he called “Industrial Arts,” he proposed a new organization dedicated to practical knowledge. He named it the Massachusetts Institute of Technology.

Rogers was one of a number of late-19th-century reformers who saw that the United States’ ability to generate progress could be substantially improved. These reformers looked to the successes of the German university models overseas and realized that a combination of focused professorial research and teaching could be a powerful engine for advance in research. Over the course of several decades, the group—Rogers, Charles Eliot, Henry Tappan, George Hale, John D. Rockefeller, and others—founded and restructured many of what are now America’s best universities, including Harvard, MIT, Stanford, Caltech, Johns Hopkins, the University of Chicago, and more. By acting on their understanding, they engaged in a kind of conscious “progress engineering.”

Progress itself is understudied. By “progress,” we mean the combination of economic, technological, scientific, cultural, and organizational advancement that has transformed our lives and raised standards of living over the past couple of centuries. For a number of reasons, there is no broad-based intellectual movement focused on understanding the dynamics of progress, or targeting the deeper goal of speeding it up. We believe that it deserves a dedicated field of study. We suggest inaugurating the discipline of “Progress Studies.”…(More)”

The World Is Complex. Measuring Charity Has to Be Too


Joy Ito at Wired: “If you looked at how many people check books out of libraries these days, you would see failure. Circulation, an obvious measure of success for an institution established to lend books to people, is down. But if you only looked at that figure, you’d miss the fascinating transformation public libraries have undergone in recent years. They’ve taken advantage of grants to become makerspaces, classrooms, research labs for kids, and trusted public spaces in every way possible. Much of the successful funding encouraged creative librarians to experiment and scale when successful, iterating and sharing their learnings with others. If we had focused our funding to increase just the number of books people were borrowing, we would have missed the opportunity to fund and witness these positive changes.

I serve on the boards of the MacArthur Foundation and the Knight Foundation, which have made grants that helped transform our libraries. I’ve also worked over the years with dozens of philanthropists and investors—those who put money into ventures that promise environmental and public health benefits in addition to financial returns. All of us have struggled to measure the effectiveness of grants and investments that seek to benefit the community, the environment, and so forth. My own research interest in the practice of change has converged with the research of those who are trying to quantify this change, and so recently, my colleague Louis Kang and I have begun to analyse the ways in which people are currently measuring impact and perhaps find methods to better measure the impact of these investments….(More)”.

How Can We Use Administrative Data to Prevent Homelessness among Youth Leaving Care?


Article by Naomi Nichols: “In 2017, I was part of a team of people at the Canadian Observatory on Homelessness and A Way Home Canada who wrote a policy brief titled, Child Welfare and Youth Homelessness in Canada: A proposal for action. Drawing on the results of the first pan-Canadian survey on youth homelessness, Without a Home: The National Youth Homelessness Surveythe brief focused on the disproportionate number of young people who had been involved with child protection services and then later became homeless. Indeed, 57.8% of homeless youth surveyed reported some type of involvement with child protection services over their lifetime. By comparison, in the general population, only 0.3% of young people receive child welfare service. This means, youth experiencing homelessness are far more likely to report interactions with the child welfare system than young people in the general population. 

Where research reveals systematic patterns of exclusion and neglect – that is, where findings reveal that one group is experiencing disproportionately negative outcomes (relative to the general population) in a particular public sector context – this suggests the need for changes in public policy, programming and practice. Since producing this brief, I have been working with an incredibly talented and passionate McGill undergraduate student (who also happens to be the Vice President of Youth in Care Canada), Arisha Khan. Together, we have been exploring just uses of data to better serve the interests of those young people who depend on the state for their access to basic services (e.g., housing, healthcare and food) as well as their self-efficacy and status as citizens. 

One component of this work revolved around a grant application that has just been funded by the Social Sciences and Humanities Research Council of Canada (Data Justice: Fostering equitable data-led strategies to prevent, reduce and end youth homelessness). Another aspect of our work revolved around a policy brief, which we co-wrote and published with the Montreal data-for-good organization, Powered by Data. The brief outlines how a rights-based and custodial approach to administrative data could a) effectively support young people in and leaving care to participate more actively in their transition planning and engage in institutional self-advocacy; and b) enable systemic oversight of intervention implementation and outcomes for young people in and leaving the provincial care system. We produced this brief with the hope that it would be useful to government decision-makers, service providers, researchers, and advocates interested in understanding how institutional data could be used to improve outcomes for youth in and leaving care. In particular, we wanted to explore whether a different orientation to data collection and use in child protection systems could prevent young people from graduating from provincial child welfare systems into homelessness. In addition to this practical concern, we also undertook to think through the ethical and human rights implications of more recent moves towards data-driven service delivery in Canada, focusing on how we might make this move with the best interests of young people in mind. 

As data collection, management and use practices have become more popularresearch is beginning to illuminate how these new monitoring, evaluative and predictive technologies are changing governance processes within and across the public sector, as well as in civil society. ….(More)”.

The New York Times thinks a blockchain could help stamp out fake news


MIT Technology Review: “Blockchain technology is at the core of a new research project the New York Times has launched, aimed at making “the origins of journalistic content clearer to [its] audience.”

The news: The Times has launched what it calls The News Provenance Project, which will experiment with ways to combat misinformation in the news media. The first project will focus on using a blockchain—specifically a platform designed by IBM—to prove that photos are authentic.

Blockchain? Really? Rumors and speculation swirled in March, after CoinDesk reported that the New York Times was looking for someone to help it develop a “blockchain-based proof-of-concept for news publishers.” Though the newspaper removed the job posting after the article came out, apparently it was serious. In a new blog post, project lead Sasha Koren explains that by using a blockchain, “we might in theory provide audiences with a way to determine the source of a photo, or whether it had been edited after it was published.”

Unfulfilled promise: Using a blockchain to prove the authenticity of journalistic content has long been considered a potential application of the technology, but attempts to do it so far haven’t gotten much traction. If the New York Times can develop a compelling application, it has enough influence to change that….(More)”.

“Anonymous” Data Won’t Protect Your Identity


Sophie Bushwick at Scientific American: “The world produces roughly 2.5 quintillion bytes of digital data per day, adding to a sea of information that includes intimate details about many individuals’ health and habits. To protect privacy, data brokers must anonymize such records before sharing them with researchers and marketers. But a new study finds it is relatively easy to reidentify a person from a supposedly anonymized data set—even when that set is incomplete.

Massive data repositories can reveal trends that teach medical researchers about disease, demonstrate issues such as the effects of income inequality, coach artificial intelligence into humanlike behavior and, of course, aim advertising more efficiently. To shield people who—wittingly or not—contribute personal information to these digital storehouses, most brokers send their data through a process of deidentification. This procedure involves removing obvious markers, including names and social security numbers, and sometimes taking other precautions, such as introducing random “noise” data to the collection or replacing specific details with general ones (for example, swapping a birth date of “March 7, 1990” for “January–April 1990”). The brokers then release or sell a portion of this information.

“Data anonymization is basically how, for the past 25 years, we’ve been using data for statistical purposes and research while preserving people’s privacy,” says Yves-Alexandre de Montjoye, an assistant professor of computational privacy at Imperial College London and co-author of the new study, published this week in Nature Communications.  Many commonly used anonymization techniques, however, originated in the 1990s, before the Internet’s rapid development made it possible to collect such an enormous amount of detail about things such as an individual’s health, finances, and shopping and browsing habits. This discrepancy has made it relatively easy to connect an anonymous line of data to a specific person: if a private detective is searching for someone in New York City and knows the subject is male, is 30 to 35 years old and has diabetes, the sleuth would not be able to deduce the man’s name—but could likely do so quite easily if he or she also knows the target’s birthday, number of children, zip code, employer and car model….(More)”

Battling Information Illiteracy


Article by Paul T. Jaeger and Natalie Greene Taylor on “How misinformation affects the future of policy…“California wildfires are being magnified and made so much worse by the bad environmental laws which aren’t allowing massive amounts of readily available water to be properly utilized. It is being diverted into the Pacific Ocean. Must also tree clear to stop fire from spreading!”

This tweet was a statement by a US president about a major event, suggesting changes to existing policies. It is also not true. Every element of the tweet—other than the existence of California, the Pacific Ocean, and wildfires—is false. And it was not a simple misunderstanding, because a tweet from Trump the next day reiterated these themes and blamed the state’s governor personally for holding back water to fight the fires.

So how does this pertain to information policy, since the tweet is about environmental policy issues? The answer is in the information. The use and misuse of information in governance and policymaking may be turning into the biggest information policy issue of all. And as technologies and methods of communication evolve, a large part of engaging with and advocating for information policy will consist of addressing the new challenges of teaching information literacy and behavior.

Misinformation literacy

The internet has made it easy for people to be information illiterate in new ways. Anyone can create information now—regardless of quality—and get it in front of a large number of people. The ability of social media to spread information as fast as possible, and to as many people as possible, challenges literacy, as does the ability to manipulate images, sounds, and video with ease….(More)”

The internet is rotting – let’s embrace it


Viktor Mayer-Schönberger in The Conversation: “Every year, some thousands of sites – including ones with unique information – go offline. Countless further webpages become inaccessible; instead of information, users encounter error messages.

Where some commentators may lament yet another black hole in the slowly rotting Internet, I actually feel okay. Of course, I, too, dread broken links and dead servers. But I also know: Forgetting is important.

In fact, as I argued in my book, “Delete: The Virtue of Forgetting in the Digital Age,” all through human history, humans reserved remembering for the things that really mattered to them and forgot the rest. Now the internet is making forgetting a lot harder.

Built to forget

Humans are accustomed to a world in which forgetting is the norm, and remembering is the exception.

This isn’t necessarily a bug in human evolution. The mind forgets what is no longer relevant to our present. Human memory is constantly reconstructed – it isn’t preserved in pristine condition, but becomes altered over time, helping people overcome cognitive dissonances. For example, people may see an awful past as rosier than it was, or devalue memories of past conflict with a person with whom they are close in the present.

Forgetting also helps humans to focus on current issues and to plan for the future. Research shows that those who are too tethered to their past find it difficult to live and act in the present. Forgetting creates space for something new, enabling people to go beyond what they already know.

Organizations that remember too much ossify in their processes and behavior. Learning something new requires forgetting something old – and that is hard for organizations that remember too much. There’s a growing literature on the importance of “unlearning,” or deliberately purging deeply rooted processes or practices from an organization – a fancy way to say that forgetting fulfills a valuable purpose….(More)”.