Sensor Law

Curated on Posted on by Stefaan Verhulst

Paper by Sandra Braman: “For over two decades, information policy-making for human society has been increasingly supplemented, supplanted, and/or superceded by machinic decision-making; over three decades since legal decision-making has been explicitly put in place to serve machinic rather than social systems; and over four decades since designers of the Internet took the position that they were serving non-human (machinic, or daemon) users in addition to humans. As the “Internet of Things” becomes more and more of a reality, these developments increasingly shape the nature of governance itself. This paper’s discussion of contemporary trends in these diverse modes of human-computer interaction at the system level — interactions between social systems and technological systems — introduces the changing nature of the law as a sociotechnical problem in itself. In such an environment, technological innovations are often also legal innovations, and legal developments require socio-technical analysis as well as social, legal, political, and cultural approaches.

Examples of areas in which sensors are already receiving legal attention are rife. A non-comprehensive listing includes privacy concerns beginning but not ending with those raised by sensors embedded in phones and geolocation devices, which are the most widely discussed and those of which the public is most aware. Sensor issues arise in environmental law, health law, marine law, intellectual property law, and as they are raised by new technologies in use for national security purposes that include those confidence- and security-building measures intended for peacekeeping. They are raised by liability issues for objects that range from cars to ovens. And sensor issues are at the core of concerns about “telemetric policing,” as that is coming into use not only in North America and Europe, but in societies such as that of Brazil as well.

Sensors are involved in every stage of legal processes, from identification of persons of interest to determination of judgments and consequences of judgments. Their use significantly alters the historically-developed distinction among types of decision-making meant to come into use at different stages of the process, raising new questions about when, and how, human decision-making needs to dominate and when, and how, technological innovation might need to be shaped by the needs of social rather than human systems.

This paper will focus on the legal dimensions of sensors used in ubiquitous embedded computing….(More)”

Open Research, Open Data, Open Humans

Curated on Posted on by Stefaan Verhulst

Ernesto Ramirez at Quantified Self: ….“Open Humans aims to break down data silos in human health and research. We believe data has a huge potential to live and grow beyond the boundaries a single study or program. Our online portal allows members to aggregate data from the research they participate in. By connecting individuals willing to share existing research data about themselves with researchers who are interested in using that data, data can be re-used and built upon.” — OpenHumans.org

On March 24, 2015 the Open Humans Network officially opened their virtual doors and began allowing individuals to sign up and engage in a new model of participatory research. We spoke with Co-founder & Principal Investigator of the Public Data Sharing study, Madeleine Ball, Ph.D. about Open Humans, what it means for research, and what we can look foward to from this exciting initiative. The following is an edited transcript of that conversation….

What excites me about Open Humans is the potential we have to transform future research studies — from how they treat data to how they think about data sharing. We’re building our system so that participants are central to the data process. A good example of this when researchers use our member’s data they must also agree to return any new data that results from their research back to the original participant. This decentralization of data is a key component of our design. No single person, researchers, or study has all the data…(More)

Most text message health interventions were effective

Curated on Posted on by Stefaan Verhulst

Aditi Pai at MobiHealthNews: “A majority of published text message interventions between 2009 and 2014 that addressed diabetes self-management, weight loss, physical activity, smoking cessation, and medication adherence were effective, according to a systematic review of reviews published in The Annual Review of Public Health.

The review looked at 15 studies that reviewed 228 text message intervention studies addressing health promotion, disease prevention, and chronic disease self management. Study sizes ranged from 10 to 5,800 participants.

When the researchers assessed the reviews by effectiveness, they reported five of the 15 reviews — focused on a wide range of disease prevention and health promotion topics — found text messaging interventions had “statistically significant positive effects on health outcomes and/or behaviors”. These reviews looked at studies that focused on smoking cessation, physical activity, weight loss, and chronic disease self-management.

Three of the 15 reviews focused on physical activity, diet, and weight loss. One of these reviews reported that six out of 13 studies found a statistically significant clinical outcome. A meta-analysis of these studies found that participants in the study had seven times greater weight loss on average than non-SMS control participants. 

Another review focused on physical activity, diet, and weight loss found that 11 of the 14 reviewed studies reported a decrease in weight. While five of 10 studies reported a reduction in body mass index, three of six studies reported a statistically significant increase in physical activity, and two of three studies found a reduction in blood pressure….(More)”

Methods to Protect and Secure “Big Data” May Be Unknowingly Corrupting Research

Curated on Posted on by Stefaan Verhulst

New paper by John M. Abowd and Ian M. Schmutte: “…As the government and private companies increase the amount of data made available for public use (e.g. Census data, employment surveys, medical data), efforts to protect privacy and confidentiality (through statistical disclosure limitation or SDL) can often cause misleading and compromising effects on economic research and analysis, particularly in cases where data properties are unclear for the end-user.

Data swapping is a particularly insidious method of SDL and is frequently used by important data aggregators like the Census Bureau, the National Center for Health Statistics and others, which interferes with the results of empirical analysis in ways that few economists and other social scientists are aware of.

To encourage more transparency, the authors call for both government statistical agencies as well as the private sector (Amazon, Google, Microsoft, Netfix, Yahoo!, etc.) to release more information about parameters used in SDL methods, and insist that journals and editors publishing such research require documentation of the author’s entire methodological process….(More)

VIDEO:

Mission Control: A History of the Urban Dashboard

Curated on Posted on by Stefaan Verhulst

Shannon Mattern at Places: “We know what rocket science looks like in the movies: a windowless bunker filled with blinking consoles, swivel chairs, and shirt-sleeved men in headsets nonchalantly relaying updates from “Houston” to outer space. Lately, that vision of Mission Control has taken over City Hall. NASA meets Copacabana, proclaimed the New York Times, hailing Rio de Janeiro’s Operations Center as a “potentially lucrative experiment that could shape the future of cities around the world.” The Times photographed an IBM executive in front of a seemingly endless wall of screens integrating data from 30 city agencies, including transit video, rainfall patterns, crime statistics, car accidents, power failures, and more. 1

Futuristic control rooms have proliferated in dozens of global cities. Baltimore has its CitiStat Room, where department heads stand at a podium before a wall of screens and account for their units’ performance.  The Mayor’s office in London’s City Hall features a 4×3 array of iPads mounted in a wooden panel, which seems an almost parodic, Terry Gilliam-esque take on the Brazilian Ops Center. Meanwhile, British Prime Minister David Cameron commissioned an iPad app – the “No. 10 Dashboard” (a reference to his residence at 10 Downing Street) – which gives him access to financial, housing, employment, and public opinion data. As The Guardian reported, “the prime minister said that he could run government remotely from his smartphone.”

This is the age of Dashboard Governance, heralded by gurus like Stephen Few, founder of the “visual business intelligence” and “sensemaking” consultancy Perceptual Edge, who defines the dashboard as a “visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance.” A well-designed dashboard, he says — one that makes proper use of bullet graphs, sparklines, and other visualization techniques informed by the “brain science” of aesthetics and cognition — can afford its users not only a perceptual edge, but a performance edge, too. The ideal display offers a big-picture view of what is happening in real time, along with information on historical trends, so that users can divine the how and why and redirect future action. As David Nettleton emphasizes, the dashboard’s utility extends beyond monitoring “the current situation”; it also “allows a manager to … make provisions, and take appropriate actions.”….

The dashboard market now extends far beyond the corporate world. In 1994, New York City police commissioner William Bratton adapted former officer Jack Maple’s analog crime maps to create the CompStat model of aggregating and mapping crime statistics. Around the same time, the administrators of Charlotte, North Carolina, borrowed a business idea — Robert Kaplan’s and David Norton’s “total quality management” strategy known as the “Balanced Scorecard” — and began tracking performance in five “focus areas” defined by the City Council: housing and neighborhood development, community safety, transportation, economic development, and the environment. Atlanta followed Charlotte’s example in creating its own city dashboard.

In 1999, Baltimore mayor Martin O’Malley, confronting a crippling crime rate and high taxes, designed CitiStat, “an internal process of using metrics to create accountability within his government.” (This rhetoric of data-tested internal “accountability” is prevalent in early dashboard development efforts.) The project turned to face the public in 2003, when Baltimore launched a website of city operational statistics, which inspired DCStat (2005), Maryland’s StateStat (2007), and NYCStat (2008). Since then, myriad other states and metro areas — driven by a “new managerialist” approach to urban governance, committed to “benchmarking” their performance against other regions, and obligated to demonstrate compliance with sustainability agendas — have developed their own dashboards.

The Open Michigan Mi Dashboard is typical of these efforts. The state website presents data on education, health and wellness, infrastructure, “talent” (employment, innovation), public safety, energy and environment, financial health, and seniors. You (or “Mi”) can monitor the state’s performance through a side-by-side comparison of “prior” and “current” data, punctuated with a thumbs-up or thumbs-down icon indicating the state’s “progress” on each metric. Another click reveals a graph of annual trends and a citation for the data source, but little detail about how the data are actually derived. How the public is supposed to use this information is an open question….(More)”

Big Data for Social Good

Curated on Posted on by Stefaan Verhulst

Introduction to a Special Issue of the Journal “Big Data” by Catlett Charlie and Ghani Rayid: “…organizations focused on social good are realizing the potential as well but face several challenges as they seek to become more data-driven. The biggest challenge they face is a paucity of examples and case studies on how data can be used for social good. This special issue of Big Data is targeted at tackling that challenge and focuses on highlighting some exciting and impactful examples of work that uses data for social good. The special issue is just one example of the recent surge in such efforts by the data science community. …

This special issue solicited case studies and problem statements that would either highlight (1) the use of data to solve a social problem or (2) social challenges that need data-driven solutions. From roughly 20 submissions, we selected 5 articles that exemplify this type of work. These cover five broad application areas: international development, healthcare, democracy and government, human rights, and crime prevention.

“Understanding Democracy and Development Traps Using a Data-Driven Approach” (Ranganathan et al.) details a data-driven model between democracy, cultural values, and socioeconomic indicators to identify a model of two types of “traps” that hinder the development of democracy. They use historical data to detect causal factors and make predictions about the time expected for a given country to overcome these traps.

“Targeting Villages for Rural Development Using Satellite Image Analysis” (Varshney et al.) discusses two case studies that use data and machine learning techniques for international economic development—solar-powered microgrids in rural India and targeting financial aid to villages in sub-Saharan Africa. In the process, the authors stress the importance of understanding the characteristics and provenance of the data and the criticality of incorporating local “on the ground” expertise.

In “Human Rights Event Detection from Heterogeneous Social Media Graphs,” Chen and Neil describe efficient and scalable techniques to use social media in order to detect emerging patterns in human rights events. They test their approach on recent events in Mexico and show that they can accurately detect relevant human rights–related tweets prior to international news sources, and in some cases, prior to local news reports, which could potentially lead to more timely, targeted, and effective advocacy by relevant human rights groups.

“Finding Patterns with a Rotten Core: Data Mining for Crime Series with Core Sets” (Wang et al.) describes a case study with the Cambridge Police Department, using a subspace clustering method to analyze the department’s full housebreak database, which contains detailed information from thousands of crimes from over a decade. They find that the method allows human crime analysts to handle vast amounts of data and provides new insights into true patterns of crime committed in Cambridge…..(More)

Gamification harnesses the power of games to motivate

Curated on Posted on by Stefaan Verhulst

Kevin Werbach at the Conversation: “Walk through any public area and you’ll see people glued to their phones, playing mobile games like Game of War and Candy Crush Saga. They aren’t alone. 59% of Americans play video games, and contrary to stereotypes, 48% of gamers are women. The US$100 billion video game industry is among the least-appreciated business phenomena in the world today.

But this isn’t an article about video games. It’s about where innovative organizations are applying the techniques that make those games so powerfully engaging: everywhere else.

Gamification is the perhaps-unfortunate name for the growing practice of applying structural elements, design patterns, and psychological insights from game design to business, education, health, marketing, crowdsourcing and other fields. Over the past four years, gamification has gone through a cycle of (over-)hype and (overblown) disappointment common for technological trends. Yet if you look carefully, you’ll see it everywhere.

Tapping into pieces of games

Gamification involves two primary mechanisms. The first is to take design structures from games, such as levels, achievements, points, and leaderboards — in my book, For the Win, my co-author and I label them “game elements” — and incorporate them into activities. The second, more subtle but ultimately more effective, is to mine the rich vein of design techniques that game designers have developed over many years. Good games pull you in and carry you through a journey that remains engaging, using an evolving balance of challenges and a stream of well crafted, actionable feedback.

Many enterprises now use tools built on top of Salesforce.com’s customer relationship management platform to motivate employees through competitions, points and leaderboards. Online learning platforms such as Khan Academy commonly challenge students to “level up” by sprinkling game elements throughout the process. Even games are now gamified: Microsoft’s Xbox One and Sony’s PS4 consoles offer a meta-layer of achievements and trophies to promote greater game-play.

The differences between a gamified system that incorporates good design principles and one that doesn’t aren’t always obvious on the surface. They show up in the results.

Duolingo is an online language-learning app. It’s pervasively and thoughtfully gamified: points, levels, achievements, bonuses for “streaks,” visual progression indicators, even a virtual currency with various ways to spend it. The well integrated gamification is a major differentiator for Duolingo, which happens to be the most successful tool of its kind. With over 60 million registered users, it teaches languages to more people than the entire US public school system.

Most of the initial high-profile cases of gamification were for marketing: for example, USA Network ramped up its engagement numbers with web-based gamified challenges for fans of its shows, and Samsung gave points and badges for learning about its products.

Soon it became clear that other applications were equally promising. Today, organizations are using gamification to enhance employee performance, promote health and wellness activities, improve retention in online learning, help kids with cancer endure their treatment regimen, and teach people how to code, to name just a few examples. Gamification has potential anywhere that motivation is an important element of success.

Gamification works because our responses to games are deeply hard-wired into our psychology. Game design techniques can activate our innate desires to recognize patterns, solve puzzles, master challenges, collaborate with others, and be in the drivers’ seat when experiencing the world around us. They can also create a safe space for experimentation and learning. After all, why not try something new when you know that even if you fail, you’ll get another life?…(More)

What Your Tweets Say About You

Curated on Posted on by Stefaan Verhulst

at the New Yorker: “How much can your tweets reveal about you? Judging by the last nine hundred and seventy-two words that I used on Twitter, I’m about average when it comes to feeling upbeat and being personable, and I’m less likely than most people to be depressed or angry. That, at least, is the snapshot provided by AnalyzeWords, one of the latest creations from James Pennebaker, a psychologist at the University of Texas who studies how language relates to well-being and personality. One of Pennebaker’s most famous projects is a computer program called Linguistic Inquiry and Word Count (L.I.W.C.), which looks at the words we use, and in what frequency and context, and uses this information to gauge our psychological states and various aspects of our personality….

Take a study, out last month, from a group of researchers based at the University of Pennsylvania. The psychologist Johannes Eichstaedt and his colleagues analyzed eight hundred and twenty-six million tweets across fourteen hundred American counties. (The counties contained close to ninety per cent of the U.S. population.) Then, using lists of words—some developed by Pennebaker, others by Eichstaedt’s team—that can be reliably associated with anger, anxiety, social engagement, and positive and negative emotions, they gave each county an emotional profile. Finally, they asked a simple question: Could those profiles help determine which counties were likely to have more deaths from heart disease?

The answer, it turned out, was yes….

The researchers have a theory: they suggest that “the language of Twitter may be a window into the aggregated and powerful effects of the community context.” They point to other epidemiological studies which have shown that general facts about a community, such as its “social cohesion and social capital,” have consequences for the health of individuals. Broadly speaking, people who live in poorer, more fragmented communities are less healthy than people living in richer, integrated ones.“When we do a sub-analysis, we find that the power that Twitter has is in large part accounted for by community and socioeconomic variables,” Eichstaedt told me when we spoke over Skype. In short, a young person’s negative, angry, and stressed-out tweets might reflect his or her stress-inducing environment—and that same environment may have negative health repercussions for other, older members of the same community….(More)”

How to Fight the Next Epidemic

Curated on Posted on by Stefaan Verhulst

Bill Gates in the New York Times: “The Ebola Crisis Was Terrible. But Next Time Could Be Much Worse….Much of the public discussion about the world’s response to Ebola has focused on whether the World Health Organization, the Centers for Disease Control and Prevention and other groups could have responded more effectively. These are worthwhile questions, but they miss the larger point. The problem isn’t so much that the system didn’t work well enough. The problem is that we hardly have a system at all.

To begin with, most poor countries, where a natural epidemic is most likely to start, have no systematic disease surveillance in place. Even once the Ebola crisis was recognized last year, there were no resources to effectively map where cases occurred, or to use people’s travel patterns to predict where the disease might go next….

Data is another crucial problem. During the Ebola epidemic, the database that tracks cases has not always been accurate. This is partly because the situation is so chaotic, but also because much of the case reporting has been done on paper and then sent to a central location for data entry….

I believe that we can solve this problem, just as we’ve solved many others — with ingenuity and innovation.

We need a global warning and response system for outbreaks. It would start with strengthening poor countries’ health systems. For example, when you build a clinic to deliver primary health care, you’re also creating part of the infrastructure for fighting epidemics. Trained health care workers not only deliver vaccines; they can also monitor disease patterns, serving as part of the early warning systems that will alert the world to potential outbreaks. Some of the personnel who were in Nigeria to fight polio were redeployed to work on Ebola — and that country was able to contain the disease very quickly.

We also need to invest in disease surveillance. We need a case database that is instantly accessible to the relevant organizations, with rules requiring countries to share their information. We need lists of trained personnel, from local leaders to global experts, prepared to deal with an epidemic immediately. … (More)”

31 cities agree to use EU-funded open innovation platform for better smart cities’ services

Curated on Posted on by Stefaan Verhulst

European Commission Press Release: “At CEBIT, 25 cities from 6 EU countries (Belgium, Denmark, Finland, Italy, Portugal and Spain) and 6 cities from Brazil will present Open & Agile Smart Cities Task Force (OASC), an initiative making it easier for city councils  and startups to improve smart city services (such as transport, energy efficiency, environmental or e-health services). This will be achieved thanks to FIWARE, an EU-funded, open source platform and cloud-based building blocks developed in the EU that can be used to develop a huge range of applications, from Smart Cities to eHealth, and from transport to disaster management. Many applications have already been built using FIWARE – from warnings of earthquakes to preventing food waste to Smartaxi apps. Find a full list of cities in the Background.

The OASC deal will allow cities to share their open data (collected from sensors measuring, for example, traffic flows) so that startups can develop apps and tools that benefit all citizens (for example, an app with traffic information for people on the move). Moreover, these systems will be shared between cities (so, an app with transport information developed in city A can be also adopted by city B, without the latter having to develop it from scratch); FIWARE will also give startups and app developers in these cities access to a global market for smart city services.

Cities from across the globe are trying to make the most of open innovation. This will allow them to include a variety of stakeholders in their activities (services are increasingly connected to other systems and innovative startups are a big part of this trend) and encourage a competitive yet attractive market for developers, thus reducing costs, increasing quality and avoiding vendor lock-in….(More)”