Harnessing Mistrust for Civic Action

Curated on Posted on by Stefaan Verhulst

Ethan Zuckerman: “…One predictable consequence of mistrust in institutions is a decrease in participation. Fewer than 37% of eligible US voters participated in the 2014 Congressional election. Participation in European parliamentary and national elections across Europe is higher than the US’s dismal rates, but has steadily declined since 1979, with turnout for the 2014 European parliamentary elections dropping below 43%. It’s a mistake to blame low turnout on distracted or disinterested voters, when a better explanation exists: why vote if you don’t believe the US congress or European Parliament is capable of making meaningful change in the world?

In his 2012 book, “Twilight of the Elites”, Christopher Hayes suggests that the political tension of our time is not between left and right, but between institutionalists and insurrectionists. Institutionalists believe we can fix the world’s problems by strengthening and revitalizing the institutions we have. Insurrectionists believe we need to abandon these broken institutions we have and replace them with new, less corrupted ones, or with nothing at all. The institutionalists show up to vote in elections, but they’re being crowded out by the insurrectionists, who take to the streets to protest, or more worryingly, disengage entirely from civic life.

Conventional wisdom suggests that insurrectionists will grow up, stop protesting and start voting. But we may have reached a tipping point where the cultural zeitgeist favors insurrection. My students at MIT don’t want to work for banks, for Google or for universities – they want to build startups that disrupt banks, Google and universities.

The future of democracy depends on finding effective ways for people who mistrust institutions to make change in their communities, their nations and the world as a whole. The real danger is not that our broken institutions are toppled by a wave of digital disruption, but that a generation disengages from politics and civics as a whole.

It’s time to stop criticizing youth for their failure to vote and time to start celebrating the ways insurrectionists are actually trying to change the world. Those who mistrust institutions aren’t just ignoring them. Some are building new systems designed to make existing institutions obsolete. Others are becoming the fiercest and most engaged critics of of our institutions, while the most radical are building new systems that resist centralization and concentration of power.

Those outraged by government and corporate complicity in surveillance of the internet have the option of lobbying their governments to forbid these violations of privacy, or building and spreading tools that make it vastly harder for US and European governments to read our mail and track our online behavior. We need both better laws and better tools. But we must recognize that the programmers who build systems like Tor, PGP and Textsecure are engaged in civics as surely as anyone crafting a party’s political platform. The same goes for entrepreneurs building better electric cars, rather than fighting to legislate carbon taxes. As people lose faith in institutions, they seek change less through passing and enforcing laws, and more through building new technologies and businesses whose adoption has the same benefits as wisely crafted and enforced laws….(More)”

‘Smart Cities’ Will Know Everything About You

Curated on Posted on by Stefaan Verhulst

Mike Weston in the Wall Street Journal: “From Boston to Beijing, municipalities and governments across the world are pledging billions to create “smart cities”—urban areas covered with Internet-connected devices that control citywide systems, such as transit, and collect data. Although the details can vary, the basic goal is to create super-efficient infrastructure, aid urban planning and improve the well-being of the populace.

A byproduct of a tech utopia will be a prodigious amount of data collected on the inhabitants. For instance, at the company I head, we recently undertook an experiment in which some staff volunteered to wear devices around the clock for 10 days. We monitored more than 170 metrics reflecting their daily habits and preferences—including how they slept, where they traveled and how they felt (a fast heart rate and no movement can indicate excitement or stress).

If the Internet age has taught us anything, it’s that where there is information, there is money to be made. With so much personal information available and countless ways to use it, businesses and authorities will be faced with a number of ethical questions.

In a fully “smart” city, every movement an individual makes can be tracked. The data will reveal where she works, how she commutes, her shopping habits, places she visits and her proximity to other people. You could argue that this sort of tracking already exists via various apps and on social-media platforms, or is held by public-transport companies and e-commerce sites. The difference is that with a smart city this data will be centralized and easy to access. Given the value of this data, it’s conceivable that municipalities or private businesses that pay to create a smart city will seek to recoup their expenses by selling it….

Recent history—issues of privacy and security on social networks and chatting apps, and questions about how intellectual-property regulations apply online—has shown that the law has been slow to catch up with digital innovations. So businesses that can purchase smart-city data will be presented with many strategic and ethical concerns.

What degree of targeting is too specific and violates privacy? Should businesses limit the types of goods or services they offer to certain individuals? Is it ethical for data—on an employee’s eating habits, for instance—to be sold to employers or to insurance companies to help them assess claims? Do individuals own their own personal data once it enters the smart-city system?

With or without stringent controlling legislation, businesses in a smart city will need to craft their own policies and procedures regarding the use of data. A large-scale misuse of personal data could provoke a consumer backlash that could cripple a company’s reputation and lead to monster lawsuits. An additional problem is that businesses won’t know which individuals might welcome the convenience of targeted advertising and which will find it creepy—although data science could solve this equation eventually by predicting where each individual’s privacy line is.

A smart city doesn’t have to be as Orwellian as it sounds. If businesses act responsibly, there is no reason why what sounds intrusive in the abstract can’t revolutionize the way people live for the better by offering services that anticipates their needs; by designing ultraefficient infrastructure that makes commuting a (relative) dream; or with a revolutionary approach to how energy is generated and used by businesses and the populace at large….(More)”

The case for data ethics

Curated on Posted on by Stefaan Verhulst

Steven Tiell at Accenture: “Personal data is the coin of the digital realm, which for business leaders creates a critical dilemma. Companies are being asked to gather more types of data faster than ever to maintain a competitive edge in the digital marketplace; at the same time, however, they are being asked to provide pervasive and granular control mechanisms over the use of that data throughout the data supply chain.

The stakes couldn’t be higher. If organizations, or the platforms they use to deliver services, fail to secure personal data, they expose themselves to tremendous risk—from eroding brand value and the hard-won trust of established vendors and customers to ceding market share, from violating laws to costing top executives their jobs.

To distinguish their businesses in this marketplace, leaders should be asking themselves two questions. What are the appropriate standards and practices our company needs to have in place to govern the handling of data? And how can our company make strong data controls a value proposition for our employees, customers and partners?

Defining effective compliance activities to support legal and regulatory obligations can be a starting point. However, mere compliance with existing regulations—which are, for the most part, focused on privacy—is insufficient. Respect for privacy is a byproduct of high ethical standards, but it is only part of the picture. Companies need to embrace data ethics, an expansive set of practices and behaviors grounded in a moral framework for the betterment of a community (however defined).

 RAISING THE BAR

Why ethics? When communities of people—in this case, the business community at large—encounter new influences, the way they respond to and engage with those influences becomes the community’s shared ethics. Individuals who behave in accordance with these community norms are said to be moral, and those who are exemplary are able to gain the trust of their community.

Over time, as ethical standards within a community shift, the bar for trustworthiness is raised on the assumption that participants in civil society must, at a minimum, adhere to the rule of law. And thus, to maintain moral authority and a high degree of trust, actors in a community must constantly evolve to adopt the highest ethical standards.

Actors in the big data community, where security and privacy are at the core of relationships with stakeholders, must adhere to a high ethical standard to gain this trust. This requires them to go beyond privacy law and existing data control measures. It will also reward those who practice strong ethical behaviors and a high degree of transparency at every stage of the data supply chain. The most successful actors will become the platform-based trust authorities, and others will depend on these platforms for disclosure, sharing and analytics of big data assets.

Data ethics becomes a value proposition only once controls and capabilities are in place to granularly manage data assets at scale throughout the data supply chain. It is also beneficial when a community shares the same behavioral norms and taxonomy to describe the data itself, the ethical decision points along the data supply chain, and how those decisions lead to beneficial or harmful impacts….(More)”

Why Protecting Data Privacy Matters, and When

Curated on Posted on by Stefaan Verhulst

Anne Russell at Data Science Central: “It’s official. Public concerns over the privacy of data used in digital approaches have reached an apex. Worried about the safety of digital networks, consumers want to gain control over what they increasingly sense as a loss of power over how their data is used. It’s not hard to wonder why. Look at the extent of coverage on the U.S. Government data breach last month and the sheer growth in the number of attacks against government and others overall. Then there is the increasing coverage on the inherent security flaws built into the internet, through which most of our data flows. The costs of data breaches to individuals, industries, and government are adding up. And users are taking note…..
If you’re not sure whether the data fueling your approach will raise privacy and security flags, consider the following. When it comes to data privacy and security, not all data is going to be of equal concern. Much depends on the level of detail in data content, data type, data structure, volume, and velocity, and indeed how the data itself will be used and released.

First there is the data where security and privacy has always mattered and for which there is already an existing and well galvanized body of law in place. Foremost among these is classified or national security data where data usage is highly regulated and enforced. Other data for which there exists a considerable body of international and national law regulating usage includes:

  • Proprietary Data – specifically the data that makes up the intellectual capital of individual businesses and gives them their competitive economic advantage over others, including data protected under copyright, patent, or trade secret laws and the sensitive, protected data that companies collect on behalf of its customers;
  • Infrastructure Data – data from the physical facilities and systems – such as roads, electrical systems, communications services, etc. – that enable local, regional, national, and international economic activity; and
  • Controlled Technical Data – technical, biological, chemical, and military-related data and research that could be considered of national interest and be under foreign export restrictions….

The second group of data that raises privacy and security concerns is personal data. Commonly referred to as Personally Identifiable Information (PII), it is any data that distinguishes individuals from each other. It is also the data that an increasing number of digital approaches rely on, and the data whose use tends to raise the most public ire. …

A third category of data needing privacy consideration is the data related to good people working in difficult or dangerous places. Activists, journalists, politicians, whistle-blowers, business owners, and others working in contentious areas and conflict zones need secure means to communicate and share data without fear of retribution and personal harm.  That there are parts of the world where individuals can be in mortal danger for speaking out is one of the reason that TOR (The Onion Router) has received substantial funding from multiple government and philanthropic groups, even at the high risk of enabling anonymized criminal behavior. Indeed, in the absence of alternate secure networks on which to pass data, many would be in grave danger, including those such as the organizers of the Arab Spring in 2010 as well as dissidents in Syria and elsewhere….(More)”

 

The Data Revolution

Curated on Posted on by Stefaan Verhulst

Review of Rob Kitchin’s The Data Revolution: Big Data, Open Data, Data Infrastructures & their Consequences by David Moats in Theory, Culture and Society: “…As an industry, academia is not immune to cycles of hype and fashion. Terms like ‘postmodernism’, ‘globalisation’, and ‘new media’ have each had their turn filling the top line of funding proposals. Although they are each grounded in tangible shifts, these terms become stretched and fudged to the point of becoming almost meaningless. Yet, they elicit strong, polarised reactions. For at least the past few years, ‘big data’ seems to be the buzzword, which elicits funding, as well as the ire of many in the social sciences and humanities.

Rob Kitchin’s book The Data Revolution is one of the first systematic attempts to strip back the hype surrounding our current data deluge and take stock of what is really going on. This is crucial because this hype is underpinned by very real societal change, threats to personal privacy and shifts in store for research methods. The book acts as a helpful wayfinding device in an unfamiliar terrain, which is still being reshaped, and is admirably written in a language relevant to social scientists, comprehensible to policy makers and accessible even to the less tech savvy among us.

The Data Revolution seems to present itself as the definitive account of this phenomena but in filling this role ends up adopting a somewhat diplomatic posture. Kitchin takes all the correct and reasonable stances on the matter and advocates all the right courses of action but he is not able to, in the context of this book, pursue these propositions fully. This review will attempt to tease out some of these latent potentials and how they might be pushed in future work, in particular the implications of the ‘performative’ character of both big data narratives and data infrastructures for social science research.

Kitchin’s book starts with the observation that ‘data’ is a misnomer – etymologically data should refer to phenomena in the world which can be abstracted, measured etc. as opposed to the representations and measurements themselves, which should by all rights be called ‘capta’. This is ironic because the worst offenders in what Kitchin calls “data boosterism” seem to conflate data with ‘reality’, unmooring data from its conditions of production and making relationship between the two given or natural.

As Kitchin notes, following Bowker (2005), ‘raw data’ is an oxymoron: data are not so much mined as produced and are necessarily framed technically, ethically, temporally, spatially and philosophically. This is the central thesis of the book, that data and data infrastructures are not neutral and technical but also social and political phenomena. For those at the critical end of research with data, this is a starting assumption, but one which not enough practitioners heed. Most of the book is thus an attempt to flesh out these rapidly expanding data infrastructures and their politics….

Kitchin is at his best when revealing the gap between the narratives and the reality of data analysis such as the fallacy of empiricism – the assertion that, given the granularity and completeness of big data sets and the availability of machine learning algorithms which identify patterns within data (with or without the supervision of human coders), data can “speak for themselves”. Kitchin reminds us that no data set is complete and even these out-of-the-box algorithms are underpinned by theories and assumptions in their creation, and require context specific knowledge to unpack their findings. Kitchin also rightly raises concerns about the limits of big data, that access and interoperability of data is not given and that these gaps and silences are also patterned (Twitter is biased as a sample towards middle class, white, tech savy people). Yet, this language of veracity and reliability seems to suggest that big data is being conceptualised in relation to traditional surveys, or that our population is still the nation state, when big data could helpfully force us to reimagine our analytic objects and truth conditions and more pressingly, our ethics (Rieder, 2013).

However, performativity may again complicate things. As Kitchin observes, supermarket loyalty cards do not just create data about shopping, they encourage particular sorts of shopping; when research subjects change their behaviour to cater to the metrics and surveillance apparatuses built into platforms like Facebook (Bucher, 2012), then these are no longer just data points representing the social, but partially constitutive of new forms of sociality (this is also true of other types of data as discussed by Savage (2010), but in perhaps less obvious ways). This might have implications for how we interpret data, the distribution between quantitative and qualitative approaches (Latour et al., 2012) or even more radical experiments (Wilkie et al., 2014). Kitchin is relatively cautious about proposing these sorts of possibilities, which is not the remit of the book, though it clearly leaves the door open…(More)”

When Guarding Student Data Endangers Valuable Research

Curated on Posted on by Stefaan Verhulst

Susan M. Dynarski  in the New York Times: “There is widespread concern over threats to privacy posed by the extensive personal data collected by private companies and public agencies.

Some of the potential danger comes from the government: The National Security Agency has swept up the telephone records of millions of people, in what it describes as a search for terrorists. Other threats are posed by hackers, who have exploited security gaps to steal data from retail giantslike Target and from the federal Office of Personnel Management.

Resistance to data collection was inevitable — and it has been particularly intense in education.

Privacy laws have already been strengthened in some states, and multiple bills now pending in state legislatures and in Congress would tighten the security and privacy of student data. Some of this proposed legislation is so broadly written, however, that it could unintentionally choke off the use of student data for its original purpose: assessing and improving education. This data has already exposed inequities, allowing researchers and advocates to pinpoint where poor, nonwhite and non-English-speaking children have been educated inadequately by their schools.

Data gathering in education is indeed extensive: Across the United States, large, comprehensive administrative data sets now track the academic progress of tens of millions of students. Educators parse this data to understand what is working in their schools. Advocates plumb the data to expose unfair disparities in test scores and graduation rates, building cases to target more resources for the poor. Researchers rely on this data when measuring the effectiveness of education interventions.

To my knowledge there has been no large-scale, Target-like theft of private student records — probably because students’ test scores don’t have the market value of consumers’ credit card numbers. Parents’ concerns have mainly centered not on theft, but on the sharing of student data with third parties, including education technology companies. Last year, parentsresisted efforts by the tech start-up InBloom to draw data on millions of students into the cloud and return it to schools as teacher-friendly “data dashboards.” Parents were deeply uncomfortable with a third party receiving and analyzing data about their children.

In response to such concerns, some pending legislation would scale back the authority of schools, districts and states to share student data with third parties, including researchers. Perhaps the most stringent of these proposals, sponsored by Senator David Vitter, a Louisiana Republican, would effectively end the analysis of student data by outside social scientists. This legislation would have banned recent prominent research documenting the benefits of smaller classes, the value of excellent teachersand the varied performance of charter schools.

Under current law, education agencies can share data with outside researchers only to benefit students and improve education. Collaborations with researchers allow districts and states to tap specialized expertise that they otherwise couldn’t afford. The Boston public school district, for example, has teamed up with early-childhood experts at Harvard to plan and evaluate its universal prekindergarten program.

In one of the longest-standing research partnerships, the University of Chicago works with the Chicago Public Schools to improve education. Partnerships like Chicago’s exist across the nation, funded by foundations and the United States Department of Education. In one initiative, a Chicago research consortium compiled reports showing high school principals that many of the seniors they had sent off to college swiftly dropped out without earning a degree. This information spurred efforts to improve high school counseling and college placement.

Specific, tailored information in the hands of teachers, principals or superintendents empowers them to do better by their students. No national survey could have told Chicago’s principals how their students were doing in college. Administrative data can provide this information, cheaply and accurately…(More)”

In The Information Debate, Openness and Privacy Are The Same Thing

Curated on Posted on by Stefaan Verhulst

 at TechCrunch: “We’ve been framing the debate between openness and privacy the wrong way.

Rather than positioning privacy and openness as opposing forces, the fact is they’re different sides of the same coin – and equally important. This might seem simple, but it might also be the key to moving things forward around this crucial debate.

Open data advocates often suggest that openness should be the default for all human knowledge. We should share, re-use and compare data freely and in doing so reap the benefits of innovation, cost savings and increased citizen participation — to name a just a few gains.

And although it might sound a little utopian, the promise is being realized in many corners of the world….But as we all know, even if we accept all the possible benefits of open data, concerns about privacy, especially personal information, still exist as a counter weight to the open data evangelists. People worry that the path of openness could lead to an Orwellian world where all our information is shared with everyone, permanently.

There is a way to turn the conversation from the face-value clash between openness and privacy to how they can be complementary forces. Gus Hosein, CEO of Privacy International, has explained that privacy is “the governing framework to control access to, collection and usage of information.” Basically, privacy laws enable knowledge and control of data about citizens and their surroundings.

Even if we accept all the possible benefits of open data, concerns about privacy, especially personal information, still exist as a counter weight to the open data evangelists.

This is strikingly similar to the argument that open data increases service delivery efficiency and personalization. Openness and privacy both share the same impulse: I want to be in control of my life, I want to know and choose whether a hospital or school is a good hospital or school and be in control of my choice of services.

Another strong thread in conversations around open data is that transparency should be proportionate to power. This makes sense on one level and seems simple enough: Politicians should be held accountable which means a heightened level of transparency.

But who is ‘powerful’, how do you define ‘power’ and who is in charge of defining this?

Politicians have chosen to run for public office and submit themselves to public scrutiny, but what about the CEO of a listed company, the leader of a charity, the anonymous owner of a Cayman-islands’ registered corporation? In practice, it is very difficult to apply the ‘transparency is proportionate to power’ rule outside democratic politics.

We need to stop making a binary distinction between freedom of information laws and data protection; between open data policies and privacy policies. We need one single policy framework that controls as well as encourages the use ‘open’ data.

The closest we get is with so-called PEPs (politically exposed persons) databases: Individuals who are the close family and kin, and close business associates of politicians. But even that defines power as derivative from political power, and not commercial, social or other forms of power.

 And what about personal data?  Should personal data ever be open?

Omidyar Network asked this question to 200 guests at a convention on openness and privacy last year. The audience was split down the middle: 50% thought personal data could never be open data. 50% thought that it should, and that foregoing the opportunity to release it would block the promise of economic gains, better services and other benefits. Open data experts, including the 1,000 who attended a recent meeting in Ottawa, ultimately disagree on this fundamental issue.

Herein lies the challenge. Many of us, including the general public, are uncomfortable with open personal data, even despite the gains it can bring….(More)”

The privacy paradox: The privacy benefits of privacy threats

Curated on Posted on by Stefaan Verhulst

Paper by Benjamin Wittes and Jodie Liu: “In this paper, Wittes and Liu argue that how we balance the relative value of different forms of privacy is a function of how much we fear the potential audiences from whom we want to keep certain information secret.

Some basic principles these authors propose regarding the nature of privacy are as follows:

  1. Most new technologies often both enhance and diminish privacy depending on how it is used, who is using it, and what sorts of privacy that person values.
  2. Individual concern with privacy often will not involve privacy in the abstract, but rather vis à vis specific audiences – that is to say that the question of privacyfrom whom matters.
  3. At least some modern technologies that we commonly think of as privacy-eroding may in fact enhance privacy from the people in our immediate surroundings.

From Google searches to online shopping to Kindle readers, the privacy equation is seldom as simple as a trade of convenience for privacy. It is far more often a tradeoff among different types of privacy, Wittes and Liu suggest. In conclusion, the privacy debate does not pay much attention to aggregated consumer preferences as a metric against which to measure privacy, and the authors venture to suggest that it should….(More)”

Social Dimensions of Privacy

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New book edited by Dorota Mokrosinska and Beate Roessler: “Written by a select international group of leading privacy scholars, Social Dimensions of Privacy endorses and develops an innovative approach to privacy. By debating topical privacy cases in their specific research areas, the contributors explore the new privacy-sensitive areas: legal scholars and political theorists discuss the European and American approaches to privacy regulation; sociologists explore new forms of surveillance and privacy on social network sites; and philosophers revisit feminist critiques of privacy, discuss markets in personal data, issues of privacy in health care and democratic politics. The broad interdisciplinary character of the volume will be of interest to readers from a variety of scientific disciplines who are concerned with privacy and data protection issues.

  • Takes an innovative approach to privacy which focuses on the social dimensions and value of privacy in contrast to the value of privacy for individuals
  • Addresses readers from a variety of disciplines, including law, philosophy, media studies, gender studies and political science
  • Addresses new privacy-sensitive areas triggered by recent technological developments (More)”

CMS announces entrepreneurs and innovators to access Medicare data

Curated on Posted on by Stefaan Verhulst

Centers for Medicare and Medicaid Services Press Release: “…the acting Centers for Medicare & Medicaid Services (CMS) Administrator, Andy Slavitt, announced a new policy that for the first time will allow innovators and entrepreneurs to access CMS data, such as Medicare claims. As part of the Administration’s commitment to use of data and information to drive transformation of the healthcare delivery system, CMS will allow innovators and entrepreneurs to conduct approved research that will ultimately improve care and provide better tools that should benefit health care consumers through a greater understanding of what the data says works best in health care. The data will not allow the patient’s identity to be determined, but will provide the identity of the providers of care. CMS will begin accepting innovator research requests in September 2015.

“Data is the essential ingredient to building a better, smarter, healthier system. Today’s announcement is aimed directly at shaking up health care innovation and setting a new standard for data transparency,” said acting CMS Administrator Andy Slavitt. “We expect a stream of new tools for beneficiaries and care providers that improve care and personalize decision-making.”

Innovators and entrepreneurs will access data via the CMS Virtual Research Data Center (VRDC) which provides access to granular CMS program data, including Medicare fee-for-service claims data, in an efficient and cost effective manner. Researchers working in the CMS VRDC have direct access to approved privacy-protected data files and are able to conduct their analysis within a secure CMS environment….

Examples of tools or products that innovators and entrepreneurs might develop include care management or predictive modeling tools, which could greatly benefit the healthcare system, in the form of healthier people, better quality, or lower cost of care. Even though all data is privacy-protected, researchers also will not be allowed to remove patient-level data from the VRDC. They will only be able to download aggregated, privacy-protected reports and results to their own personal workstation.  …(More)”