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 regulator of tomorrow

Curated on Posted on by Stefaan Verhulst

Shrupti Shah, Rachel Brody, & Nick Olson at Deloitte: “…Disruptive trends are making it difficult for regulators to achieve their missions. But what if this changing business landscape presented opportunities to help regulators overcome the challenges they face? In the balance of this report, we explore the potential for regulators to embrace the opportunities presented by technical and business model innovation, the increasingly digital nature of their constituents, and industries’ and consumers’ changing attitudes and behaviors to help them meet key challenges across their two main functions: rulemaking (part one) and oversight and enforcement (part two).

PART ONE: RULEMAKING

Regulators are often the agencies responsible for implementing policy mandates. These mandates can vary from being highly prescriptive to giving regulators great freedom to determine how to implement a policy. In some cases, regulatory agencies have been granted authority by Congress to monitor entire industries, with discretion as to determining how to protect citizens and fair markets.

The business of rulemaking is governed by its own laws and regulations, from the Administrative Procedures Act to approvals of proposed rules by the Office of Management and Budget. All of these processes are designed as a safeguard to protect our citizens while not unduly burdening the regulated businesses or entities.

The process of formal and informal rulemaking is well defined,11incorporates input from citizens and industry, and can take time. Given the challenges previously described, it becomes essential for regulators to think creatively about their rulemaking activities to meet their policy objectives. In this section, we explore several rulemaking opportunities for the regulator of tomorrow:

  • Rethinking outreach
  • Sensing
  • Guidelines and statements versus regulations
  • Tomorrow’s talent
  • Consultation 2.0…

PART TWO: OVERSIGHT AND ENFORCEMENT

In addition to rulemaking, regulators oversee compliance with the published rules, taking enforcement action when violations occur. Today’s regulators have access to significant amounts of data. Larger data sets combined with increasingly sophisticated analytical tools and the power of the crowd can help regulators better utilize limited resources and reduce the burden of compliance on citizens and business.

This section will explore several oversight and enforcement opportunities for the regulator of tomorrow:

  • Correlate to predict
  • Citizen as regulator
  • Open data
  • Collaborative regulating
  • Retrospective review…(More)”

Understanding the smart city Domain: A Literature Review

Curated on Posted on by Stefaan Verhulst

Paper by Leonidas G. Anthopoulos: “Smart Cities appeared in literature in late ‘90s and various approaches have been developed so far. Until today, smart city does not describe a city with particular attributes but it is used to describe different cases in urban spaces: web portals that virtualize cities or city guides; knowledge bases that address local needs; agglomerations with Information and Communication Technology (ICT) infrastructure that attract business relocation; metropolitan-wide ICT infrastructures that deliver e-services to the citizens; ubiquitous environments; and recently ICT infrastructure for ecological use. Researchers, practicians, businessmen and policy makers consider smart city from different perspectives and most of them agree on a model that measures urban economy, mobility, environment, living, people and governance. On the other hand, ICT and construction industries stress to capitalize smart city and a new market seems to be generated in this domain. This chapter aims to perform a literature review, discover and classify the particular schools of thought, universities and research centres as well as companies that deal with smart city domain and discover alternative approaches, models, architecture and frameworks with this regard….(More)

Who knew contracts could be so interesting?

Curated on Posted on by Stefaan Verhulst

 at Transparency International UK: “…Despite the UK Government’s lack of progress, it wouldn’t be completely unreasonable to ask “who actually publishes these things, anyway?” Well, back in 2011, when the UK Government committed to publish all new contracts and tenders over £10,000 in value, the Slovakian Government decided to publish more or less everything. Faced by mass protests over corruption in the public sector, their government committed to publishing almost all public sector contracts online (there are some exemptions). You can now browse through the details of a significant amount of government business via the country’s online portal (so long as you can read Slovak, of course).

Who actually reads these things?

According to research by Transparency International Slovakia, at least 11% of the Slovakian adult population have looked at a government contract since they were first published back in 2011. That’s around 480,000 people. Although some of these spent more time than others browsing through the documents in-depth, this is undeniably an astounding amount of people taking a vague interest in government procurement.

Why does this matter?

Before Slovakia opened-up its contracts there was widespread mistrust in public institutions and officials. According to Transparency International’s global Corruption Perceptions Index, which measures impressions of public sector corruption, Slovakia was ranked 66th out of 183 countries in 2011. By 2014 it had jumped 12 places – a record achievement – to 54th, which must in some part be due to the Government’s commitment to opening-up public contracts to greater scrutiny.

Since the contracts were published, there also seems to have been a spike in media reports on government tenders. This suggests there is greater scrutiny of public spending, which should hopefully translate into less wasted expenditure.

Elsewhere, proponents of open contracting have espoused other benefits, such as greater commitment by both parties to following the agreement and protecting against malign private interests. Similar projects inGeorgia have also turned clunky bureaucracies into efficient, data-savvy administrations. In short, there are quite a few reasons why more openness in public sector procurement is a good thing.

Despite these benefits, opponents cite a number of downsides, including the administrative costs of publishing contracts online and issues surrounding commercially sensitive information. However, TI Slovakia’s research suggests the former is minimal – and presumably preferable to rooting around through paper mountains every time a Freedom of Information (FOI) request is received about a contract – whilst the latter already has to be disclosed under the FOI Act except in particular circumstances…(More)”

The Trust Imperative: A Framework for Ethical Data Use

Curated on Posted on by Stefaan Verhulst

New report by Susan Etlinger: “The way organizations use data use is affecting consumer trust, and that trust affects not just a brand’s reputation, but its business performance as well. As a result, chief executives who wish to sustain the trust of their customers and constituents must take a hard look at how their organizations collect and use customer data, and the effect of those practices on customer relationships, reputation, risk and revenue.

This report by Altimeter Group analyst Susan Etlinger lays out key drivers and principles for ethical data use. It discusses emerging best practices, and—most  importantly—a pragmatic framework that organizations can use to earn—and build—the trust of customers and consumers. This framework lists the questions that need to be asked at each stage of collecting and analyzing data, helping brands earn the trust of their customers, and safeguarding against both legal and ethical transgressions….(More)”

Transforming Government Information

Curated on Posted on by Stefaan Verhulst

Sharyn Clarkson at the (Interim) Digital Transformation Office (Australia): “Our challenge: How do we get the right information and services to people when and where they need it?

The public relies on Government for a broad range of information – advice for individuals and businesses, what services are available and how to access them, and how various rules and laws impact our lives.

The government’s digital environment has grown organically over the last couple of decades. At the moment, information is largely created and managed within agencies and published across more than 1200 disparate gov.au websites, plus a range of social media accounts, apps and other digital formats.

This creates some difficulties for people looking for government information. By publishing within agency silos we are presenting people with an agency-centric view of government information. This is a problem because people largely don’t understand or care about how government organises itself and the structure of government does not map to the needs of people. Having a baby or travelling overseas? Up to a dozen government agencies may have information relevant to you. And as people’s needs span more than one agency, they end up with a disjointed and confusing user experience as they have to navigate across disparate government sites. And even if you begin at your favourite search engine how do you know which of the many government search results is the right place to start?

There are two government entry points already in place to help users – Australia.gov.au and business.gov.au – but they largely act as an umbrella across the 1200+ sites and currently only provide a very thin layer of whole of government information and mainly refer people off to other websites.

The establishment of the DTO has provided the first opportunity for people to come together and better understand how our underlying structural landscape is impacting people’s experience with government. It’s also given us an opportunity to take a step back and ask some of the big questions about how we manage information and what problems can only really be solved through whole of government transformation.

How do we make information and services easier to find? How do we make sure we provide information that people can trust and rely upon at times of need? How should the gov.au landscape be organised to make it easier for us to meet user’s needs and expectations? How many websites should we have – assuming 1200 is too many? What makes up a better user experience – does it mean all sites should look and feel the same? How can we provide government information at the places people naturally go looking for assistance – even if these are not government sites?

As we asked these questions we started to come across some central ideas:

  • What if we could decouple the authoring and management of information from the publishing process, so the subject experts in government still manage their content but we have flexibility to present it in more user-centric ways?
  • What if we unleashed government information? Making it possible for state and local governments, non-profit groups and businesses to deliver content and services alongside their own information to give better value users.
  • Should we move the bureaucratic content (information about agencies and how they are managed such as annual reports, budget statements and operating rules) out of the way of core content and services for people? Can we simplify our environment and base it around topics and life events instead of agencies? What if we had people in government responsible for curating these topics and life events across agencies and creating simpler pathways for users?…(More)”

Please, Corporations, Experiment on Us

Curated on Posted on by Stefaan Verhulst

Michelle N. Meyer and Christopher Chabris in the New York Times: ” Can it ever be ethical for companies or governments to experiment on their employees, customers or citizens without their consent?

The conventional answer — of course not! — animated public outrage last year after Facebook published a study in which it manipulated how much emotional content more than half a million of its users saw. Similar indignation followed the revelation by the dating site OkCupid that, as an experiment, it briefly told some pairs of users that they were good matches when its algorithm had predicted otherwise.

But this outrage is misguided. Indeed, we believe that it is based on a kind of moral illusion.

Companies — and other powerful actors, including lawmakers, educators and doctors — “experiment” on us without our consent every time they implement a new policy, practice or product without knowing its consequences. When Facebook started, it created a radical new way for people to share emotionally laden information, with unknown effects on their moods. And when OkCupid started, it advised users to go on dates based on an algorithm without knowing whether it worked.

Why does one “experiment” (i.e., introducing a new product) fail to raise ethical concerns, whereas a true scientific experiment (i.e., introducing a variation of the product to determine the comparative safety or efficacy of the original) sets off ethical alarms?

In a forthcoming article in the Colorado Technology Law Journal, one of us (Professor Meyer) calls this the “A/B illusion” — the human tendency to focus on the risk, uncertainty and power asymmetries of running a test that compares A to B, while ignoring those factors when A is simply imposed by itself.

Consider a hypothetical example. A chief executive is concerned that her employees are taking insufficient advantage of the company’s policy of matching contributions to retirement savings accounts. She suspects that telling her workers how many others their age are making the maximum contribution would nudge them to save more, so she includes this information in personalized letters to them.

If contributions go up, maybe the new policy worked. But perhaps contributions would have gone up anyhow (say, because of an improving economy). If contributions go down, it might be because the policy failed. Or perhaps a declining economy is to blame, and contributions would have gone down even more without the letter.

You can’t answer these questions without doing a true scientific experiment — in technology jargon, an “A/B test.” The company could randomly assign its employees to receive either the old enrollment packet or the new one that includes the peer contribution information, and then statistically compare the two groups of employees to see which saved more.

Let’s be clear: This is experimenting on people without their consent, and the absence of consent is essential to the validity of the entire endeavor. If the C.E.O. were to tell the workers that they had been randomly assigned to receive one of two different letters, and why, that information would be likely to distort their choices.

Our chief executive isn’t so hypothetical. Economists do help corporations run such experiments, but many managers chafe at debriefing their employees afterward, fearing that they will be outraged that they were experimented on without their consent. A company’s unwillingness to debrief, in turn, can be a deal-breaker for the ethics boards that authorize research. So those C.E.O.s do what powerful people usually do: Pick the policy that their intuition tells them will work best, and apply it to everyone….(More)”

Big Data’s Impact on Public Transportation

Curated on Posted on by Stefaan Verhulst

InnovationEnterprise: “Getting around any big city can be a real pain. Traffic jams seem to be a constant complaint, and simply getting to work can turn into a chore, even on the best of days. With more people than ever before flocking to the world’s major metropolitan areas, the issues of crowding and inefficient transportation only stand to get much worse. Luckily, the traditional methods of managing public transportation could be on the verge of changing thanks to advances in big data. While big data use cases have been a part of the business world for years now, city planners and transportation experts are quickly realizing how valuable it can be when making improvements to city transportation. That hour long commute may no longer be something travelers will have to worry about in the future.

In much the same way that big data has transformed businesses around the world by offering greater insight in the behavior of their customers, it can also provide a deeper look at travellers. Like retail customers, commuters have certain patterns they like to keep to when on the road or riding the rails. Travellers also have their own motivations and desires, and getting to the heart of their actions is all part of what big data analytics is about. By analyzing these actions and the factors that go into them, transportation experts can gain a better understanding of why people choose certain routes or why they prefer one method of transportation over another. Based on these findings, planners can then figure out where to focus their efforts and respond to the needs of millions of commuters.

Gathering the accurate data needed to make knowledgeable decisions regarding city transportation can be a challenge in itself, especially considering how many people commute to work in a major city. New methods of data collection have made that effort easier and a lot less costly. One way that’s been implemented is through the gathering of call data records (CDR). From regular transactions made from mobile devices, information about location, time, and duration of an action (like a phone call) can give data scientists the necessary details on where people are traveling to, how long it takes them to get to their destination, and other useful statistics. The valuable part of this data is the sample size, which provides a much bigger picture of the transportation patterns of travellers.

That’s not the only way cities are using big data to improve public transportation though. Melbourne in Australia has long been considered one of the world’s best cities for public transit, and much of that is thanks to big data. With big data and ad hoc analysis, Melbourne’s acclaimed tram system can automatically reconfigure routes in response to sudden problems or challenges, such as a major city event or natural disaster. Data is also used in this system to fix problems before they turn serious.Sensors located in equipment like tram cars and tracks can detect when maintenance is needed on a specific part. Crews are quickly dispatched to repair what needs fixing, and the tram system continues to run smoothly. This is similar to the idea of the Internet of Things, wherein embedded sensors collect data that is then analyzed to identify problems and improve efficiency.

Sao Paulo, Brazil is another city that sees the value of using big data for its public transportation. The city’s efforts concentrate on improving the management of its bus fleet. With big data collected in real time, the city can get a more accurate picture of just how many people are riding the buses, which routes are on time, how drivers respond to changing conditions, and many other factors. Based off of this information, Sao Paulo can optimize its operations, providing added vehicles where demand is genuine whilst finding which routes are the most efficient. Without big data analytics, this process would have taken a very long time and would likely be hit-or-miss in terms of accuracy, but now, big data provides more certainty in a shorter amount of time….(More)”

Handbook: How to Catalyze Humanitarian Innovation in Computing Research Institutes

Curated on Posted on by Stefaan Verhulst

Patrick Meier: “The handbook below provides practical collaboration guidelines for both humanitarian organizations & computing research institutes on how to catalyze humanitarian innovation through successful partnerships. These actionable guidelines are directly applicable now and draw on extensive interviews with leading humanitarian groups and CRI’s including the International Committee of the Red Cross (ICRC), United Nations Office for the Coordination of Humanitarian Affairs (OCHA), United Nations Children’s Fund (UNICEF), United Nations High Commissioner for Refugees (UNHCR), UN Global Pulse, Carnegie Melon University (CMU), International Business Machines (IBM), Microsoft Research, Data Science for Social Good Program at the University of Chicago and others.

This handbook, which is the first of its kind, also draws directly on years of experience and lessons learned from the Qatar Computing Research Institute’s (QCRI) active collaboration and unique partnerships with multiple international humanitarian organizations. The aim of this blog post is to actively solicit feedback on this first, complete working draft, which is available here as an open and editable Google Doc. …(More)”

Government data does not mean data governance: Lessons learned from a public sector application audit

Curated on Posted on by Stefaan Verhulst

Paper by Nik Thompson, Ravi Ravindran, and Salvatore Nicosia: “Public sector agencies routinely store large volumes of information about individuals in the community. The storage and analysis of this information benefits society, as it enables relevant agencies to make better informed decisions and to address the individual’s needs more appropriately. Members of the public often assume that the authorities are well equipped to handle personal data; however, due to implementation errors and lack of data governance, this is not always the case. This paper reports on an audit conducted in Western Australia, focusing on findings in the Police Firearms Management System and the Department of Health Information System. In the case of the Police, the audit revealed numerous data protection issues leading the auditors to report that they had no confidence in the accuracy of information on the number of people licensed to possess firearms or the number of licensed firearms. Similarly alarming conclusions were drawn in the Department of Health as auditors found that they could not determine which medical staff member was responsible for clinical data entries made. The paper describes how these issues often do not arise from existing business rules or the technology itself, but a lack of sound data governance. Finally, a discussion section presents key data governance principles and best practices that may guide practitioners involved in data management. These cases highlight the very real data management concerns, and the associated recommendations provide the context to spark further interest in the applied aspects of data protection….(More)”