Tomorrow’s Data Heroes


Article by Florian GrönePierre Péladeau, and Rawia Abdel Samad: “Telecom companies are struggling to find a profitable identity in today’s digital sphere. What about helping customers control their information?…

By 2025, Alex had had enough. There no longer seemed to be any distinction between her analog and digital lives. Everywhere she went, every purchase she completed, and just about every move she made, from exercising at the gym to idly surfing the Web, triggered a vast flow of data. That in turn meant she was bombarded with personalized advertising messages, targeted more and more eerily to her. As she walked down the street, messages appeared on her phone about the stores she was passing. Ads popped up on her all-purpose tablet–computer–phone pushing drugs for minor health problems she didn’t know she had — until the symptoms appeared the next day. Worse, she had recently learned that she was being reassigned at work. An AI machine had mastered her current job by analyzing her use of the firm’s productivity software.

It was as if the algorithms of global companies knew more about her than she knew herself — and they probably did. How was it that her every action and conversation, even her thoughts, added to the store of data held about her? After all, it was her data: her preferences, dislikes, interests, friendships, consumer choices, activities, and whereabouts — her very identity — that was being collected, analyzed, profited from, and even used to manage her. All these companies seemed to be making money buying and selling this information. Why shouldn’t she gain some control over the data she generated, and maybe earn some cash by selling it to the companies that had long collected it free of charge?

So Alex signed up for the “personal data manager,” a new service that promised to give her control over her privacy and identity. It was offered by her U.S.-based connectivity company (in this article, we’ll call it DigiLife, but it could be one of many former telephone companies providing Internet services in 2025). During the previous few years, DigiLife had transformed itself into a connectivity hub: a platform that made it easier for customers to join, manage, and track interactions with media and software entities across the online world. Thanks to recently passed laws regarding digital identity and data management, including the “right to be forgotten,” the DigiLife data manager was more than window dressing. It laid out easy-to-follow choices that all Web-based service providers were required by law to honor….

Today, in 2019, personal data management applications like the one Alex used exist only in nascent form, and consumers have yet to demonstrate that they trust these services. Nor can they yet profit by selling their data. But the need is great, and so is the opportunity for companies that fulfill it. By 2025, the total value of the data economy as currently structured will rise to more than US$400 billion, and by monetizing the vast amounts of data they produce, consumers can potentially recapture as much as a quarter of that total.

Given the critical role of telecom operating companies within the digital economy — the central position of their data networks, their networking capabilities, their customer relationships, and their experience in government affairs — they are in a good position to seize this business opportunity. They might not do it alone; they are likely to form consortia with software companies or other digital partners. Nonetheless, for legacy connectivity companies, providing this type of service may be the most sustainable business option. It may also be the best option for the rest of us, as we try to maintain control in a digital world flooded with our personal data….(More)”.

Dirty Data, Bad Predictions: How Civil Rights Violations Impact Police Data, Predictive Policing Systems, and Justice


Paper by Rashida Richardson, Jason Schultz, and Kate Crawford: “Law enforcement agencies are increasingly using algorithmic predictive policing systems to forecast criminal activity and allocate police resources. Yet in numerous jurisdictions, these systems are built on data produced within the context of flawed, racially fraught and sometimes unlawful practices (‘dirty policing’). This can include systemic data manipulation, falsifying police reports, unlawful use of force, planted evidence, and unconstitutional searches. These policing practices shape the environment and the methodology by which data is created, which leads to inaccuracies, skews, and forms of systemic bias embedded in the data (‘dirty data’). Predictive policing systems informed by such data cannot escape the legacy of unlawful or biased policing practices that they are built on. Nor do claims by predictive policing vendors that these systems provide greater objectivity, transparency, or accountability hold up. While some systems offer the ability to see the algorithms used and even occasionally access to the data itself, there is no evidence to suggest that vendors independently or adequately assess the impact that unlawful and bias policing practices have on their systems, or otherwise assess how broader societal biases may affect their systems.

In our research, we examine the implications of using dirty data with predictive policing, and look at jurisdictions that (1) have utilized predictive policing systems and (2) have done so while under government commission investigations or federal court monitored settlements, consent decrees, or memoranda of agreement stemming from corrupt, racially biased, or otherwise illegal policing practices. In particular, we examine the link between unlawful and biased police practices and the data used to train or implement these systems across thirteen case studies. We highlight three of these: (1) Chicago, an example of where dirty data was ingested directly into the city’s predictive system; (2) New Orleans, an example where the extensive evidence of dirty policing practices suggests an extremely high risk that dirty data was or will be used in any predictive policing application, and (3) Maricopa County where despite extensive evidence of dirty policing practices, lack of transparency and public accountability surrounding predictive policing inhibits the public from assessing the risks of dirty data within such systems. The implications of these findings have widespread ramifications for predictive policing writ large. Deploying predictive policing systems in jurisdictions with extensive histories of unlawful police practices presents elevated risks that dirty data will lead to flawed, biased, and unlawful predictions which in turn risk perpetuating additional harm via feedback loops throughout the criminal justice system. Thus, for any jurisdiction where police have been found to engage in such practices, the use of predictive policing in any context must be treated with skepticism and mechanisms for the public to examine and reject such systems are imperative….(More)”.

Hundreds of Bounty Hunters Had Access to AT&T, T-Mobile, and Sprint Customer Location Data for Years


Joseph Cox at Motherboard: ” In January, Motherboard revealed that AT&T, T-Mobile, and Sprint were selling their customers’ real-time location data, which trickled down through a complex network of companies until eventually ending up in the hands of at least one bounty hunter. Motherboard was also able to purchase the real-time location of a T-Mobile phone on the black market from a bounty hunter source for $300. In response, telecom companies said that this abuse was a fringe case.

In reality, it was far from an isolated incident.

Around 250 bounty hunters and related businesses had access to AT&T, T-Mobile, and Sprint customer location data, with one bail bond firm using the phone location service more than 18,000 times, and others using it thousands or tens of thousands of times, according to internal documents obtained by Motherboard from a company called CerCareOne, a now-defunct location data seller that operated until 2017. The documents list not only the companies that had access to the data, but specific phone numbers that were pinged by those companies.

In some cases, the data sold is more sensitive than that offered by the service used by Motherboard last month, which estimated a location based on the cell phone towers that a phone connected to. CerCareOne sold cell phone tower data, but also sold highly sensitive and accurate GPS data to bounty hunters; an unprecedented move that means users could locate someone so accurately so as to see where they are inside a building. This company operated in near-total secrecy for over 5 years by making its customers agree to “keep the existence of CerCareOne.com confidential,” according to a terms of use document obtained by Motherboard.

Some of these bounty hunters then resold location data to those unauthorized to handle it, according to two independent sources familiar with CerCareOne’s operations.

The news shows how widely available Americans’ sensitive location data was to bounty hunters. This ease-of-access dramatically increased the risk of abuse….(More)”.

Using Personal Informatics Data in Collaboration among People with Different Expertise


Dissertation by Chia-Fang Chung: “Many people collect and analyze data about themselves to improve their health and wellbeing. With the prevalence of smartphones and wearable sensors, people are able to collect detailed and complex data about their everyday behaviors, such as diet, exercise, and sleep. This everyday behavioral data can support individual health goals, help manage health conditions, and complement traditional medical examinations conducted in clinical visits. However, people often need support to interpret this self-tracked data. For example, many people share their data with health experts, hoping to use this data to support more personalized diagnosis and recommendations as well as to receive emotional support. However, when attempting to use this data in collaborations, people and their health experts often struggle to make sense of the data. My dissertation examines how to support collaborations between individuals and health experts using personal informatics data.

My research builds an empirical understanding of individual and collaboration goals around using personal informatics data, current practices of using this data to support collaboration, and challenges and expectations for integrating the use of this data into clinical workflows. These understandings help designers and researchers advance the design of personal informatics systems as well as the theoretical understandings of patient-provider collaboration.

Based on my formative work, I propose design and theoretical considerations regarding interactions between individuals and health experts mediated by personal informatics data. System designers and personal informatics researchers need to consider collaborations occurred throughout the personal tracking process. Patient-provider collaboration might influence individual decisions to track and to review, and systems supporting this collaboration need to consider individual and collaborative goals as well as support communication around these goals. Designers and researchers should also attend to individual privacy needs when personal informatics data is shared and used across different healthcare contexts. With these design guidelines in mind, I design and develop Foodprint, a photo-based food diary and visualization system. I also conduct field evaluations to understand the use of lightweight data collection and integration to support collaboration around personal informatics data. Findings from these field deployments indicate that photo-based visualizations allow both participants and health experts to easily understand eating patterns relevant to individual health goals. Participants and health experts can then focus on individual health goals and questions, exchange knowledge to support individualized diagnoses and recommendations, and develop actionable and feasible plans to accommodate individual routines….(More)”.

Privacy concerns collide with the public interest in data


Gillian Tett in the Financial Times: “Late last year Statistics Canada — the agency that collects government figures — launched an innovation: it asked the country’s banks to supply “individual-level financial transactions data” for 500,000 customers to allow it to track economic trends. The agency argued this was designed to gather better figures for the public interest. However, it tipped the banks into a legal quandary. Under Canadian law (as in most western countries) companies are required to help StatsCan by supplying operating information. But data privacy laws in Canada also say that individual bank records are confidential. When the StatsCan request leaked out, it sparked an outcry — forcing the agency to freeze its plans. “It’s a mess,” a senior Canadian banker says, adding that the laws “seem contradictory”.

Corporate boards around the world should take note. In the past year, executive angst has exploded about the legal and reputational risks created when private customer data leak out, either by accident or in a cyber hack. Last year’s Facebook scandals have been a hot debating topic among chief executives at this week’s World Economic Forum in Davos, as has the EU’s General Data Protection Regulation. However, there is another important side to this Big Data debate: must companies provide private digital data to public bodies for statistical and policy purposes? Or to put it another way, it is time to widen the debate beyond emotive privacy issues to include the public interest and policy needs. The issue has received little public debate thus far, except in Canada. But it is becoming increasingly important.

Companies are sitting on a treasure trove of digital data that offers valuable real-time signals about economic activity. This information could be even more significant than existing statistics, because they struggle to capture how the economy is changing. Take Canada. StatsCan has hitherto tracked household consumption by following retail sales statistics, supplemented by telephone surveys. But consumers are becoming less willing to answer their phones, which undermines the accuracy of surveys, and consumption of digital services cannot be easily pursued. ...

But the biggest data collections sit inside private companies. Big groups know this, and some are trying to respond. Google has created its own measures to track inflation, which it makes publicly available. JPMorgan and other banks crunch customer data and publish reports about general economic and financial trends. Some tech groups are even starting to volunteer data to government bodies. LinkedIn has offered to provide anonymised data on education and employment to municipal and city bodies in America and beyond, to help them track local trends; the group says this is in the public interest for policy purposes, as “it offers a different perspective” than official data sources. But it is one thing for LinkedIn to offer anonymised data when customers have signed consent forms permitting the transfer of data; it is quite another for banks (or other companies) who have operated with strict privacy rules. If nothing else, the CanStat saga shows there urgently needs to be more public debate, and more clarity, around these rules. Consumer privacy issues matter (a lot). But as corporate data mountains grow, we will need to ask whether we want to live in a world where Amazon and Google — and Mastercard and JPMorgan — know more about economic trends than central banks or finance ministries. Personally, I would say “no”. But sooner or later politicians will need to decide on their priorities in this brave new Big Data world; the issue cannot be simply left to the half-hidden statisticians….(More)”.

Google’s Sidewalk Labs Plans to Package and Sell Location Data on Millions of Cellphones


Ava Kofman at the Intercept: “Most of the data collected by urban planners is messy, complex, and difficult to represent. It looks nothing like the smooth graphs and clean charts of city life in urban simulator games like “SimCity.” A new initiative from Sidewalk Labs, the city-building subsidiary of Google’s parent company Alphabet, has set out to change that.

The program, known as Replica, offers planning agencies the ability to model an entire city’s patterns of movement. Like “SimCity,” Replica’s “user-friendly” tool deploys statistical simulations to give a comprehensive view of how, when, and where people travel in urban areas. It’s an appealing prospect for planners making critical decisions about transportation and land use. In recent months, transportation authorities in Kansas City, Portland, and the Chicago area have signed up to glean its insights. The only catch: They’re not completely sure where the data is coming from.

Typical urban planners rely on processes like surveys and trip counters that are often time-consuming, labor-intensive, and outdated. Replica, instead, uses real-time mobile location data. As Nick Bowden of Sidewalk Labs has explained, “Replica provides a full set of baseline travel measures that are very difficult to gather and maintain today, including the total number of people on a highway or local street network, what mode they’re using (car, transit, bike, or foot), and their trip purpose (commuting to work, going shopping, heading to school).”

To make these measurements, the program gathers and de-identifies the location of cellphone users, which it obtains from unspecified third-party vendors. It then models this anonymized data in simulations — creating a synthetic population that faithfully replicates a city’s real-world patterns but that “obscures the real-world travel habits of individual people,” as Bowden told The Intercept.

The program comes at a time of growing unease with how tech companies use and share our personal data — and raises new questions about Google’s encroachment on the physical world….(More)”.

Survey: Majority of Americans Willing to Share Their Most Sensitive Personal Data


Center for Data Innovation: “Most Americans (58 percent) are willing to allow third parties to collect at least some sensitive personal data, according to a new survey from the Center for Data Innovation.

While many surveys measure public opinions on privacy, few ask consumers about their willingness to make tradeoffs, such as sharing certain personal information in exchange for services or benefits they want. In this survey, the Center asked respondents whether they would allow a mobile app to collect their biometrics or location data for purposes such as making it easier to sign into an account or getting free navigational help, and it asked whether they would allow medical researchers to collect sensitive data about their health if it would lead to medical cures for their families or others. Only one-third of respondents (33 percent) were unwilling to let mobile apps collect either their biometrics or location data under any of the described scenarios. And overall, nearly 6 in 10 respondents (58 percent) were willing to let a third party collect at least one piece of sensitive personal data, such as biometric, location, or medical data, in exchange for a service or benefit….(More)”.

Research Handbook on Human Rights and Digital Technology


Book edited by Ben Wagner, Matthias C. Kettemann and Kilian Vieth: “In a digitally connected world, the question of how to respect, protect and implement human rights has become unavoidable. This contemporary Research Handbook offers new insights into well-established debates by framing them in terms of human rights. It examines the issues posed by the management of key Internet resources, the governance of its architecture, the role of different stakeholders, the legitimacy of rule making and rule-enforcement, and the exercise of international public authority over users. Highly interdisciplinary, its contributions draw on law, political science, international relations and even computer science and science and technology studies…(More)”.

The Internet of Bodies: A Convenient—and, Yes, Creepy—New Platform for Data Discovery


David Horrigan at ALM: “In the Era of the Internet of Things, we’ve become (at least somewhat) comfortable with our refrigerators knowing more about us than we know about ourselves and our Apple watches transmitting our every movement. The Internet of Things has even made it into the courtroom in cases such as the hot tub saga of Amazon Echo’s Alexa in State v. Bates and an unfortunate wife’s Fitbit in State v. Dabate.

But the Internet of Bodies?…

The Internet of Bodies refers to the legal and policy implications of using the human body as a technology platform,” said Northeastern University law professor Andrea Matwyshyn, who works also as co-director of Northeastern’s Center for Law, Innovation, and Creativity (CLIC).

“In brief, the Internet of Things (IoT) is moving onto and inside the human body, becoming the Internet of Bodies (IoB),” Matwyshyn added….


The Internet of Bodies is not merely a theoretical discussion of what might happen in the future. It’s happening already.

Former U.S. Vice President Dick Cheney revealed in 2013 that his physicians ordered the wireless capabilities of his heart implant disabled out of concern for potential assassin hackers, and in 2017, the U.S. Food and Drug Administration recalled almost half a million pacemakers over security issues requiring a firmware update.

It’s not just former vice presidents and heart patients becoming part of the Internet of Bodies. Northeastern’s Matwyshyn notes that so-called “smart pills” with sensors can report back health data from your stomach to smartphones, and a self-tuning brain implant is being tested to treat Alzheimer’s and Parkinson’s.

So, what’s not to like?

Better with Bacon?

“We are attaching everything to the Internet whether we need to or not,” Matwyshyn said, calling it the “Better with Bacon” problem, noting that—as bacon has become a popular condiment in restaurants—chefs are putting it on everything from drinks to cupcakes.

“It’s great if you love bacon, but not if you’re a vegetarian or if you just don’t like bacon. It’s not a bonus,” Matwyshyn added.

Matwyshyn’s bacon analogy raises interesting questions: Do we really need to connect everything to the Internet? Do the data privacy and data protection risks outweigh the benefits?

The Northeastern Law professor divides these IoB devices into three generations: 1) “body external” devices, such as Fitbits and Apple watches, 2) “body internal” devices, including Internet-connected pacemakers, cochlear implants, and digital pills, and 3) “body embedded” devices, hardwired technology where the human brain and external devices meld, where a human body has a real time connection to a remote machine with live updates.

Chip Party for Chipped Employees

A Wisconsin company, Three Square Market, made headlines in 2017—including an appearance on The Today Show—when the company microchipped its employees, not unlike what veterinarians do with the family pet. Not surprisingly, the company touted the benefits of implanting microchips under the skin of employees, including being able to wave one’s hand at a door instead of having to carry a badge or use a password….(More)”.

The Age of Surveillance Capitalism


Book by Shoshana Zuboff: “The challenges to humanity posed by the digital future, the first detailed examination of the unprecedented form of power called “surveillance capitalism,” and the quest by powerful corporations to predict and control our behavior.

Shoshana Zuboff’s interdisciplinary breadth and depth enable her to come to grips with the social, political, business, and technological meaning of the changes taking place in our time. We are at a critical juncture in the confrontation between the vast power of giant high-tech companies and government, the hidden economic logic of surveillance capitalism, and the propaganda of machine supremacy that threaten to shape and control human life. Will the brazen new methods of social engineering and behavior modification threaten individual autonomy and democratic rights and introduce extreme new forms of social inequality? Or will the promise of the digital age be one of individual empowerment and democratization?

The Age of Surveillance Capitalism is neither a hand-wringing narrative of danger and decline nor a digital fairy tale. Rather, it offers a deeply reasoned and evocative examination of the contests over the next chapter of capitalism that will decide the meaning of information civilization in the twenty-first century. The stark issue at hand is whether we will be the masters of information and machines or its slaves. …(More)”.