privacy

The Architecture of Privacy

Curated on January 28, 2015November 15, 2018 by Stefaan Verhulst

Book by Courtney Bowman, Ari Gesher, John K Grant, and Daniel Slate: “Technology’s influence on privacy has become a matter of everyday concern for millions of people, from software architects designing new products to political leaders and consumer groups. This book explores the issue from the perspective of technology itself: how privacy-protective features can become a core part of product functionality, rather than added on late in the development process.
The Architecture of Privacy will not only help empower software engineers, but also show policymakers, academics, and advocates that, through an arsenal of technical tools, engineers can form the building blocks of nuanced policies that maximize privacy protection and utility—a menu of what to demand in new technology.
Topics include:

How technology and privacy policy interact and influence one another
Privacy concerns about government and corporate data collection practices
Approaches to federated systems as a component of privacy-protecting architecture
Alternative approaches to compartmentalized access to data
Methods to limit the amount of data revealed in searches, sidestepping all-or-nothing choices
Techniques for data purging and responsible data retention
Keeping and analyzing audit logs as part of a program of comprehensive system oversight
… (More)“

The Cathedral of Computation

Curated on January 28, 2015November 15, 2018 by Stefaan Verhulst

Ian Bogost at the Atlantic: “We’re not living in an algorithmic culture so much as a computational theocracy. Algorithms are everywhere, supposedly. We are living in an “algorithmic culture,” to use the author and communication scholar Ted Striphas’s name for it. Google’s search algorithms determine how we access information. Facebook’s News Feed algorithms determine how we socialize. Netflix’s and Amazon’s collaborative filtering algorithms choose products and media for us. You hear it everywhere. “Google announced a change to its algorithm,” a journalist reports. “We live in a world run by algorithms,” a TED talk exhorts. “Algorithms rule the world,” a news report threatens. Another upgrades rule to dominion: “The 10 Algorithms that Dominate Our World.”…
It’s part of a larger trend. The scientific revolution was meant to challenge tradition and faith, particularly a faith in religious superstition. But today, Enlightenment ideas like reason and science are beginning to flip into their opposites. Science and technology have become so pervasive and distorted, they have turned into a new type of theology.
The worship of the algorithm is hardly the only example of the theological reversal of the Enlightenment—for another sign, just look at the surfeit of nonfiction books promising insights into “The Science of…” anything, from laughter to marijuana. But algorithms hold a special station in the new technological temple because computers have become our favorite idols….
Once you adopt skepticism toward the algorithmic- and the data-divine, you can no longer construe any computational system as merely algorithmic. Think about Google Maps, for example. It’s not just mapping software running via computer—it also involves geographical information systems, geolocation satellites and transponders, human-driven automobiles, roof-mounted panoramic optical recording systems, international recording and privacy law, physical- and data-network routing systems, and web/mobile presentational apparatuses. That’s not algorithmic culture—it’s just, well, culture….(More).”

Would You Share Private Data for the Good of City Planning?

Curated on January 28, 2015August 3, 2018 by Stefaan Verhulst

Henry Grabar at NextCity: “The proliferation of granular data on automobile movement, drawn from smartphones, cab companies, sensors and cameras, is sharpening our sense of how cars travel through cities. Panglossian seers believe the end of traffic jams is nigh.
This information will change cities beyond their roads. Real-time traffic data may lead to reworked intersections and new turning lanes, but understanding cars is in some ways a stand-in for understanding people. There’s traffic as traffic and traffic as proxy, notes Brett Goldstein, an urban science fellow at the University of Chicago who served as that city’s first data officer from 2011 to 2013. “We’d be really naive, in thinking about how we make cities better,” he says, “to only consider traffic for what it is.”
Even a small subset of a city’s car data goes a long way. Consider the raft of discrete findings that have emerged from the records of New York City taxis.
Researchers at the Massachusetts Institute of Technology, led by Paolo Santi, showed that cab-sharing could reduce taxi mileage by 40 percent. Their counterparts at NYU, led by Claudio Silva, mapped activity around hubs like train stations and airports and during hurricanes.
“You start to build actual models of how people move, and where they move,” observes Silva, the head of disciplines at NYU’s Center for Science and Urban Progress (CUSP). “The uses of this data for non-traffic engineering are really substantial.”…
Many of these ideas are hypothetical, for the moment, because so-called “granular” data is so hard to come by. That’s one reason the release of New York’s taxi cab data spurred so many studies — it’s an oasis of information in a desert of undisclosed records. Corporate entreaties, like Uber’s pending data offering to Boston, don’t always meet researchers’ standards. “It’s going to be a lot of superficial data, and it’s not clear how usable it’ll be at this point,” explains Sarah Kaufman, the digital manager at NYU’s Rudin Center for Transportation….
Yet Americans seem much more alarmed by the collection of location data than other privacy breaches.
How can data utopians convince the hoi polloi to share their comings and goings? One thought: Make them secure. Mike Flowers, the founder of New York City’s Office of Data Analytics and a fellow at NYU’s CUSP, told me it might be time to consider establishing a quasi-governmental body that people would trust to make their personal data anonymous before they are channeled into government projects. (New York City’s Taxi and Limousine Commission did not do a very good job at this, which led to Gawker publishing a dozen celebrity cab rides.)
Another idea is to frame open data as a beneficial trade-off. “When people provide information, they want to realize the benefit of the information,” Goldstein says.
Users tell the routing company Waze where they are and get a smoother commute in return. Progressive Insurance offers drivers a “Snapshot” tracker. If it likes the way you drive, the company will lower your rates. It’s not hard to imagine that, in the long run, drivers will be penalized for refusing such a device…. (More).”

Big Data Now

Curated on January 27, 2015August 15, 2018 by Stefaan Verhulst

Timothy McGovern at Radar – O’Reilly: “In the four years we’ve been producing Big Data Now, our wrap-up of important developments in the big data field, we’ve seen tools and applications mature, multiply, and coalesce into new categories. This year’s free wrap-up of Radar coverage is organized around seven themes:

Cognitive augmentation: As data processing and data analytics become more accessible, jobs that can be automated will go away. But to be clear, there are still many tasks where the combination of humans and machines produce superior results.
Intelligence matters: Artificial intelligence is now playing a bigger and bigger role in everyone’s lives, from sorting our email to rerouting our morning commutes, from detecting fraud in financial markets to predicting dangerous chemical spills. The computing power and algorithmic building blocks to put AI to work have never been more accessible.
The convergence of cheap sensors, fast networks, and distributed computation: The amount of quantified data available is increasing exponentially — and aside from tools for centrally handling huge volumes of time-series data as it arrives, devices and software are getting smarter about placing their own data accurately in context, extrapolating without needing to ‘check in’ constantly.
Reproducing, managing, and maintaining data pipelines: The coordination of processes and personnel within organizations to gather, store, analyze, and make use of data.
The evolving, maturing marketplace of big data components: Open-source components like Spark, Kafka, Cassandra, and ElasticSearch are reducing the need for companies to build in-house proprietary systems. On the other hand, vendors are developing industry-specific suites and applications optimized for the unique needs and data sources in a field.
The value of applying techniques from design and social science: While data science knows human behavior in the aggregate, design works in the particular, where A/B testing won’t apply — you only get one shot to communicate your proposal to a CEO, for example. Similarly, social science enables extrapolation from sparse data. Both sets of tools enable you to ask the right questions, and scope your problems and solutions realistically.
The importance of building a data culture: An organization that is comfortable with gathering data, curious about its significance, and willing to act on its results will perform demonstrably better than one that doesn’t. These priorities must be shared throughout the business.
The perils of big data: From poor analysis (driven by false correlation or lack of domain expertise) to intrusiveness (privacy invasion, price profiling, self-fulfilling predictions), big data has negative potential.

Download our free snapshot of big data in 2014, and follow the story this year on Radar.”

Open Data Barometer (second edition)

Curated on January 21, 2015August 15, 2018 by Stefaan Verhulst

The second edition of the Open Data Barometer: “A global movement to make government “open by default” picked up steam in 2013 when the G8 leaders signed an Open Data Charter – promising to make public sector data openly available, without charge and in re-useable formats. In 2014 the G20 largest industrial economies followed up by pledging to advance open data as a tool against corruption, and the UN recognized the need for a “Data Revolution” to achieve global development goals.
However, this second edition of the Open Data Barometer shows that there is still a long way to go to put the power of data in the hands of citizens. Core data on how governments are spending our money and how public services are performing remains inaccessible or paywalled in most countries. Information critical to fight corruption and promote fair competition, such as company registers, public sector contracts, and land titles, is even harder to get. In most countries, proactive disclosure of government data is not mandated in law or policy as part of a wider right to information, and privacy protections are weak or uncertain.
Our research suggests some of the key steps needed to ensure the “Data Revolution” will lead to a genuine revolution in the transparency and performance of governments:

High-level political commitment to proactive disclosure of public sector data, particularly the data most critical to accountability
Sustained investment in supporting and training a broad cross-section of civil society and entrepreneurs to understand and use data effectively
Contextualizing open data tools and approaches to local needs, for example by making data visually accessible in countries with lower literacy levels.
Support for city-level open data initiatives as a complement to national-level programmes
Legal reform to ensure that guarantees of the right to information and the right to privacy underpin open data initiatives

Over the next six months, world leaders have several opportunities to agree these steps, starting with the United Nation’s high-level data revolution in Africa conference in March, Canada’s global International Open Data Conference in May and the G7 summit in Germany this June. It is crucial that these gatherings result in concrete actions to address the political and resource barriers that threaten to stall open data efforts….(More)”.

Donated Personal Data Could Aid Lifestyle Researchers

Curated on January 14, 2015August 15, 2018 by Stefaan Verhulst

Anya Skatova and James Goulding at Scientific American: “In the future it will be possible to donate our personal data to charitable causes. All sorts of data is recorded about us as we go about our daily lives—what we buy, where we go, who we call on the phone and our use of the internet. The time is approaching when we could liberate that data in support of good causes. Given many people already donate precious resources such as money or even blood for the benefit of society at large, this step might not be far away.
How could donated data help our society? Data is a rich source of people’s habits—shopping data from loyalty cards, for example, can reflect our diet. If people donate their personal data for research, analysis of it can provide scope to improve everything from understandings of the dietary pre-cursors to diabetes to the impact of lifestyle on heart disease.
But there are vital issues around the collection and use of personal data that must be addressed. Donation rests on trust: would people give their data away knowing that researchers will examine it, even if anonymously? Would they want others scrutinising their diet, or their shopping habits? Would people feel their privacy was being invaded, even if they had chosen to donate to help medical research?
Who would donate data to research?
Our recent research has found that around 60% of people are willing to donate their data for uses that will benefit the public. In some ways this is not surprising. As previous research demonstrated, people help others and take part in various pro-social activities. People voluntarily give to benefit society at large: they donate money to charities, or run marathons to raise money without knowing exactly who will benefit; they give blood, bone marrow, or even organs. They often do so out of concern for the welfare of others, or in other cases for more selfish reasons, such as enhancing their reputation, professional benefit, or just to feel good about themselves….
Donating data is certainly different from donating money or blood—there is very little obvious cost to us when donating our data. Unlike blood or money, data is something for which most of us have no use, nor has it any real monetary value to those of us that generate it, but it becomes valuable when combined with the data of others.
Currently companies leverage personal data to make money because it provides them with sophisticated understanding of consumer behaviour, from which they in turn can profit. But shouldn’t our data benefit us too?…(More)”

Driving Solutions To Build Smarter Cities

Curated on January 13, 2015November 15, 2018 by Stefaan Verhulst

Uber Blogpost: “Since day one, Uber’s mission has been to improve city life by connecting people with safe, reliable, hassle-free rides through the use of technology. As we have grown, so has our ability to share information that can serve a greater good. By sharing data with municipal partners we can help cities become more liveable, resilient, and innovative.
Today, Boston joins Uber in a first-of-its-kind partnership to help expand the city’s capability to solve problems by leveraging data provided by Uber. The data will provide new insights to help manage urban growth, relieve traffic congestion, expand public transportation, and reduce greenhouse gas emissions….
Uber is committed to sharing data, compiled in a manner that protects the privacy of riders and drivers, that can help cities target solutions for their unique challenges. This initiative presents a new standard for the future development of our cities – in communities big or small we can bridge data and policy to build sophisticated solutions for a stronger society. For this effort, we will deliver anonymized trip-level data by ZIP Code Tabulation Area (ZCTA) which is the U.S. Census’ geographical representation of zip codes….

How Can This Data Help Cities?

To date, most cities have not had access to granular data describing the flows and trends of private traffic. The data provided by Uber will help policymakers and city planners develop a more detailed understanding of where people in the city need to go and how to improve traffic flows and congestion to get them there, with data-driven decisions about:

Vision Zero-related passenger safety policies
Traffic planning
Congestion reduction
Flow of residents across the City
Impact of events, disasters and other activities on City transportation
Identification of zoning changes and needs
Creation or reduction of parking
Facilitation of additional transportation solutions for marquee City initiatives

This data can be utilized to help cities achieve their transportation and planning goals without compromising personal privacy. By helping cities understand the way their residents move, we can work together to make our communities stronger. Smart Cities can benefit from smart data and we will champion municipal efforts devoted to achieving data-driven urban growth, mobility and safety for communities (More).”

Transparency isn’t what keeps government from working

Curated on January 4, 2015May 29, 2019 by Stefaan Verhulst

Gary D. Bass, Danielle Brian and Norman Eisen in the Washington Post: “In 2014, a number of big thinkers made the surprising claim that government openness and transparency are to blame for today’s gridlock. They have it backward: Not only is there no relationship between openness and dysfunction, but more secrecy can only add to that dysfunction.

As transparency advocates, we never take openness for granted. The latest example of the dangers of secrecy was the “cromnibus” bill, with its surprise lifting of campaign finance limits for political parties to an astonishing $3 million per couple per cycle, and its suddenly revealed watering down of Dodd-Frank’s derivatives safeguards. And in parallel to the controversy over the release of the CIA’s torture report, that agency proposed to delete e-mail from nearly all employees and contractors, destroying potential documentary evidence of wrongdoing. Openness doesn’t happen without a struggle…..

Academics, such as Francis Fukuyama, make the case that politicians need privacy and discretion — back-door channels — to get the business of government done. “The obvious solution to this problem would be to roll back some of the would-be democratizing reforms, but no one dares suggest that what the country needs is a bit less participation and transparency,” writes Fukuyama in his newest book. At a time when voter participation is as low as during World War II, it seems strange to call for less participation and democracy. And more secrecy in Congress isn’t going to suddenly create dealmaking. The 2011 congressional “supercommittee” tasked with developing a $1.5 trillion deficit reduction deal operated almost entirely in secret. The problem wasn’t transparency or openness. Instead, as the committee’s Republican co-chairman, Jeb Hensarling, stated, the real problem was “two dramatically competing visions of the role [of] government.” These are the real issues, not openness….
We are not transparency absolutists. Not everything government and Congress do should occur in a fishbowl; that said, there is already plenty of room today for private deliberations. The problem isn’t transparency. It is that the political landscape punishes those who try to work together. And if various accountability measures create procedural challenges, let’s fix them. When it comes to holding government accountable, it is in the nation’s best interest to allow the media, nonprofit groups and the public full access to decision-making.”