Health Insurers Are Vacuuming Up Details About You — And It Could Raise Your Rates

Curated on Posted on by Stefaan Verhulst

Marshall Allen at ProPublica: “With little public scrutiny, the health insurance industry has joined forces with data brokers to vacuum up personal details about hundreds of millions of Americans, including, odds are, many readers of this story. The companies are tracking your race, education level, TV habits, marital status, net worth. They’re collecting what you post on social media, whether you’re behind on your bills, what you order online. Then they feed this information into complicated computer algorithms that spit out predictions about how much your health care could cost them.

Are you a woman who recently changed your name? You could be newly married and have a pricey pregnancy pending. Or maybe you’re stressed and anxious from a recent divorce. That, too, the computer models predict, may run up your medical bills.

Are you a woman who’s purchased plus-size clothing? You’re considered at risk of depression. Mental health care can be expensive.

Low-income and a minority? That means, the data brokers say, you are more likely to live in a dilapidated and dangerous neighborhood, increasing your health risks.

“We sit on oceans of data,” said Eric McCulley, director of strategic solutions for LexisNexis Risk Solutions, during a conversation at the data firm’s booth. And he isn’t apologetic about using it. “The fact is, our data is in the public domain,” he said. “We didn’t put it out there.”

Insurers contend they use the information to spot health issues in their clients — and flag them so they get services they need. And companies like LexisNexis say the data shouldn’t be used to set prices. But as a research scientist from one company told me: “I can’t say it hasn’t happened.”

At a time when every week brings a new privacy scandal and worries abound about the misuse of personal information, patient advocates and privacy scholars say the insurance industry’s data gathering runs counter to its touted, and federally required, allegiance to patients’ medical privacy. The Health Insurance Portability and Accountability Act, or HIPAA, only protects medical information.

“We have a health privacy machine that’s in crisis,” said Frank Pasquale, a professor at the University of Maryland Carey School of Law who specializes in issues related to machine learning and algorithms. “We have a law that only covers one source of health information. They are rapidly developing another source.”…(More)”.

‘Data is a fingerprint’: why you aren’t as anonymous as you think online

Curated on Posted on by Stefaan Verhulst

Olivia Solon at The Guardian: “In August 2016, the Australian government released an “anonymised” data set comprising the medical billing records, including every prescription and surgery, of 2.9 million people.

Names and other identifying features were removed from the records in an effort to protect individuals’ privacy, but a research team from the University of Melbourne soon discovered that it was simple to re-identify people, and learn about their entire medical history without their consent, by comparing the dataset to other publicly available information, such as reports of celebrities having babies or athletes having surgeries.

The government pulled the data from its website, but not before it had been downloaded 1,500 times.

This privacy nightmare is one of many examples of seemingly innocuous, “de-identified” pieces of information being reverse-engineered to expose people’s identities. And it’s only getting worse as people spend more of their lives online, sprinkling digital breadcrumbs that can be traced back to them to violate their privacy in ways they never expected.

Nameless New York taxi logs were compared with paparazzi shots at locations around the city to reveal that Bradley Cooper and Jessica Alba were bad tippers. In 2017 German researchers were able to identify people based on their “anonymous” web browsing patterns. This week University College London researchers showed how they could identify an individual Twitter user based on the metadata associated with their tweets, while the fitness tracking app Polar revealed the homes and in some cases names of soldiers and spies.

“It’s convenient to pretend it’s hard to re-identify people, but it’s easy. The kinds of things we did are the kinds of things that any first-year data science student could do,” said Vanessa Teague, one of the University of Melbourne researchers to reveal the flaws in the open health data.

One of the earliest examples of this type of privacy violation occurred in 1996 when the Massachusetts Group Insurance Commission released “anonymised” data showing the hospital visits of state employees. As with the Australian data, the state removed obvious identifiers like name, address and social security number. Then the governor, William Weld, assured the public that patients’ privacy was protected….(More)”.

Big Data for the Greater Good

Curated on Posted on by Stefaan Verhulst

Book edited by Ali Emrouznejad and Vincent Charles: “This book highlights some of the most fascinating current uses, thought-provoking changes, and biggest challenges that Big Data means for our society. The explosive growth of data and advances in Big Data analytics have created a new frontier for innovation, competition, productivity, and well-being in almost every sector of our society, as well as a source of immense economic and societal value. From the derivation of customer feedback-based insights to fraud detection and preserving privacy; better medical treatments; agriculture and food management; and establishing low-voltage networks – many innovations for the greater good can stem from Big Data. Given the insights it provides, this book will be of interest to both researchers in the field of Big Data, and practitioners from various fields who intend to apply Big Data technologies to improve their strategic and operational decision-making processes….(More)”.

Balancing Act: Innovation vs. Privacy in the Age of Data Portability

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Thursday, July 12, 2018 @ 2 MetroTech Center, Brooklyn, NY 11201

RSVP here.

The ability of people to move or copy data about themselves from one service to another — data portability — has been hailed as a way of increasing competition and driving innovation. In many areas, such as through the Open Banking initiative in the United Kingdom, the practice of data portability is fully underway and propagating. The launch of GDPR in Europe has also elevated the issue among companies and individuals alike. But recent online security breaches and other experiences of personal data being transferred surreptitiously from private companies, (e.g., Cambridge Analytica’s appropriation of Facebook data), highlight how data portability can also undermine people’s privacy.

The GovLab at the NYU Tandon School of Engineering is pleased to present Jeni Tennison, CEO of the Open Data Institute, for its next Ideas Lunch, where she will discuss how data portability has been regulated in the UK and Europe, and what governments, businesses and people need to do to strike the balance between its risks and benefits.

—

Jeni Tennison is the CEO of the Open Data Institute. She gained her PhD from the University of Nottingham then worked as an independent consultant, specialising in open data publishing and consumption, before joining the ODI in 2012. Jeni was awarded an OBE for services to technology and open data in the 2014 New Year Honours.

Before joining the ODI, Jeni was the technical architect and lead developer for legislation.gov.uk. She worked on the early linked data work on data.gov.uk, including helping to engineer new standards for publishing statistics as linked data. She continues her work within the UK’s public sector as a member of the Open Standards Board.

Jeni also works on international web standards. She was appointed to serve on the W3C’s Technical Architecture Group from 2011 to 2015 and in 2014 she started to co-chair the W3C’s CSV on the Web Working Group. She also sits on the Advisory Boards for Open Contracting Partnership and the Data Transparency Lab.

Twitter handle: @JeniT

Personal Data v. Big Data: Challenges of Commodification of Personal Data

Curated on Posted on by Stefaan Verhulst

Maria Bottis and  George Bouchagiar in the Open Journal of Philosophy: “Any firm today may, at little or no cost, build its own infrastructure to process personal data for commercial, economic, political, technological or any other purposes. Society has, therefore, turned into a privacy-unfriendly environment. The processing of personal data is essential for multiple economically and socially useful purposes, such as health care, education or terrorism prevention. But firms view personal data as a commodity, as a valuable asset, and heavily invest in processing for private gains. This article studies the potential to subject personal data to trade secret rules, so as to ensure the users’ control over their data without limiting the data’s free movement, and examines some positive scenarios of attributing commercial value to personal data….(More)”.

Data Protection and e-Privacy: From Spam and Cookies to Big Data, Machine Learning and Profiling

Curated on Posted on by Stefaan Verhulst

Chapter by Lilian Edwards in L Edwards ed Law, Policy and the Internet (Hart , 2018): “In this chapter, I examine in detail how data subjects are tracked, profiled and targeted by their activities on line and, increasingly, in the “offline” world as well. Tracking is part of both commercial and state surveillance, but in this chapter I concentrate on the former. The European law relating to spam, cookies, online behavioural advertising (OBA), machine learning (ML) and the Internet of Things (IoT) is examined in detail, using both the GDPR and the forthcoming draft ePrivacy Regulation. The chapter concludes by examining both code and law solutions which might find a way forward to protect user privacy and still enable innovation, by looking to paradigms not based around consent, and less likely to rely on a “transparency fallacy”. Particular attention is drawn to the new work around Personal Data Containers (PDCs) and distributed ML analytics….(More)”.

Why Do We Care So Much About Privacy?

Curated on Posted on by Stefaan Verhulst

Louis Menand in The New Yorker: “…Possibly the discussion is using the wrong vocabulary. “Privacy” is an odd name for the good that is being threatened by commercial exploitation and state surveillance. Privacy implies “It’s nobody’s business,” and that is not really what Roe v. Wade is about, or what the E.U. regulations are about, or even what Katz and Carpenter are about. The real issue is the one that Pollak and Martin, in their suit against the District of Columbia in the Muzak case, said it was: liberty. This means the freedom to choose what to do with your body, or who can see your personal information, or who can monitor your movements and record your calls—who gets to surveil your life and on what grounds.

As we are learning, the danger of data collection by online companies is not that they will use it to try to sell you stuff. The danger is that that information can so easily fall into the hands of parties whose motives are much less benign. A government, for example. A typical reaction to worries about the police listening to your phone conversations is the one Gary Hart had when it was suggested that reporters might tail him to see if he was having affairs: “You’d be bored.” They were not, as it turned out. We all may underestimate our susceptibility to persecution. “We were just talking about hardwood floors!” we say. But authorities who feel emboldened by the promise of a Presidential pardon or by a Justice Department that looks the other way may feel less inhibited about invading the spaces of people who belong to groups that the government has singled out as unpatriotic or undesirable. And we now have a government that does that….(More)”.

I want your (anonymized) social media data

Curated on Posted on by Stefaan Verhulst

Anthony Sanford at The Conversation: “Social media sites’ responses to the Facebook-Cambridge Analytica scandal and new European privacy regulations have given users much more control over who can access their data, and for what purposes. To me, as a social media user, these are positive developments: It’s scary to think what these platforms could do with the troves of data available about me. But as a researcher, increased restrictions on data sharing worry me.

I am among the many scholars who depend on data from social media to gain insights into people’s actions. In a rush to protect individuals’ privacy, I worry that an unintended casualty could be knowledge about human nature. My most recent work, for example, analyzes feelings people express on Twitter to explain why the stock market fluctuates so much over the course of a single day. There are applications well beyond finance. Other scholars have studied mass transit rider satisfaction, emergency alert systems’ function during natural disasters and how online interactions influence people’s desire to lead healthy lifestyles.

This poses a dilemma – not just for me personally, but for society as a whole. Most people don’t want social media platforms to share or sell their personal information, unless specifically authorized by the individual user. But as members of a collective society, it’s useful to understand the social forces at work influencing everyday life and long-term trends. Before the recent crises, Facebook and other companies had already been making it hard for legitimate researchers to use their data, including by making it more difficult and more expensive to download and access data for analysis. The renewed public pressure for privacy means it’s likely to get even tougher….

It’s true – and concerning – that some presumably unethical people have tried to use social media data for their own benefit. But the data are not the actual problem, and cutting researchers’ access to data is not the solution. Doing so would also deprive society of the benefits of social media analysis.

Fortunately, there is a way to resolve this dilemma. Anonymization of data can keep people’s individual privacy intact, while giving researchers access to collective data that can yield important insights.

There’s even a strong model for how to strike that balance efficiently: the U.S. Census Bureau. For decades, that government agency has collected extremely personal data from households all across the country: ages, employment status, income levels, Social Security numbers and political affiliations. The results it publishes are very rich, but also not traceable to any individual.

It often is technically possible to reverse anonymity protections on data, using multiple pieces of anonymized information to identify the person they all relate to. The Census Bureau takes steps to prevent this.

For instance, when members of the public access census data, the Census Bureau restricts information that is likely to identify specific individuals, such as reporting there is just one person in a community with a particularly high- or low-income level.

For researchers the process is somewhat different, but provides significant protections both in law and in practice. Scholars have to pass the Census Bureau’s vetting process to make sure they are legitimate, and must undergo training about what they can and cannot do with the data. The penalties for violating the rules include not only being barred from using census data in the future, but also civil fines and even criminal prosecution.

Even then, what researchers get comes without a name or Social Security number. Instead, the Census Bureau uses what it calls “protected identification keys,” a random number that replaces data that would allow researchers to identify individuals.

Each person’s data is labeled with his or her own identification key, allowing researchers to link information of different types. For instance, a researcher wanting to track how long it takes people to complete a college degree could follow individuals’ education levels over time, thanks to the identification keys.

Social media platforms could implement a similar anonymization process instead of increasing hurdles – and cost – to access their data…(More)” .

User Perceptions of Privacy in Smart Homes

Curated on Posted on by Stefaan Verhulst

Paper by Serena Zheng, Marshini Chetty, and Nick Feamster: “Despite the increasing presence of Internet of Things (IoT) devices inside the home, we know little about how users feel about their privacy living with Internet-connected devices that continuously monitor and collect data in their homes. To gain insight into this state of affairs, we conducted eleven semi-structured interviews with owners of smart homes, investigating privacy values and expectations.

In this paper, we present the findings that emerged from our study: First, users prioritize the convenience and connectedness of their smart homes, and these values dictate their privacy opinions and behaviors. Second, user opinions about who should have access to their smart home data depend on the perceived benefit. Third, users assume their privacy is protected because they trust the manufacturers of their IoT devices. Our findings bring up several implications for IoT privacy, which include the need for design for privacy and evaluation standards….(More)”.

Data Detectives: More data and surveillance are transforming justice systems

Curated on Posted on by Stefaan Verhulst

Special issue by The Economist: “…the relationship between information and crime has changed in two ways, one absolute, one relative. In absolute terms, people generate more searchable information than they used to. Smartphones passively track and record where people go, who they talk to and for how long; their apps reveal subtler personal information, such as their political views, what they like to read and watch and how they spend their money. As more appliances and accoutrements become networked, so the amount of information people inadvertently create will continue to grow.

To track a suspect’s movements and conversations, police chiefs no longer need to allocate dozens of officers for round-the-clock stakeouts. They just need to seize the suspect’s phone and bypass its encryption. If he drives, police cars, streetlights and car parks equipped with automatic number-plate readers (ANPRs, known in America as automatic licence-plate readers or ALPRs) can track all his movements.

In relative terms, the gap between information technology and policy gapes ever wider. Most privacy laws were written for the age of postal services and fixed-line telephones. Courts give citizens protection from governments entering their homes or rifling through their personal papers. The law on people’s digital presence is less clear. In most liberal countries, police still must convince a judge to let them eavesdrop on phone calls.

But mobile-phone “metadata”—not the actual conversations, but data about who was called and when—enjoy less stringent protections. In 2006 the European Union issued a directive requiring telecom firms to retain customer metadata for up to two years for use in potential crime investigations. The European Court of Justice invalidated that law in 2014, after numerous countries challenged it in court, saying that it interfered with “the fundamental rights to respect for private life”. Today data-retention laws vary widely in Europe. Laws, and their interpretation, are changing in America, too. A case before the Supreme Court will determine whether police need a warrant to obtain metadata.

Less shoe leather

If you drive in a city anywhere in the developed world, ANPRs are almost certainly tracking you. This is not illegal. Police do not generally need a warrant to follow someone in public. However, people not suspected of committing a crime do not usually expect authorities to amass terabytes of data on every person they have met and every business visited. ANPRs offer a lot of that.

To some people, this may not matter. Toplines, an Israeli ANPR firm, wants to add voice- and facial-recognition to its Bluetooth-enabled cameras, and install them on private vehicles, turning every car on the road into a “mobile broadcast system” that collects and transmits data to a control centre that security forces can access. Its founder posits that insurance-rate discounts could incentivise drivers to become, in effect, freelance roving crime-detection units for the police, subjecting unwitting citizens to constant surveillance. In answer to a question about the implications of such data for privacy, a Toplines employee shrugs: Facebook and WhatsApp are spying on us anyway, he says. If the stream of information keeps people safer, who could object? “Privacy is dead.”

It is not. But this dangerously complacent attitude brings its demise ever closer….(More)”.