DATA – Page 410 – The Living Library

The Moral Failure of Computer Scientists

Curated on December 15, 2015August 3, 2018 by Stefaan Verhulst

Kaveh Waddell at the Atlantic: “Computer scientists and cryptographers occupy some of the ivory tower’s highest floors. Among academics, their work is prestigious and celebrated. To the average observer, much of it is too technical to comprehend. The field’s problems can sometimes seem remote from reality.

But computer science has quite a bit to do with reality. Its practitioners devise the surveillance systems that watch over nearly every space, public or otherwise—and they design the tools that allow for privacy in the digital realm. Computer science is political, by its very nature.

That’s at least according to Phillip Rogaway, a professor of computer science at the University of California, Davis, who has helped create some of the most important tools that secure the Internet today. Last week, Rogaway took his case directly to a roomful of cryptographers at a conference in Auckland, New Zealand. He accused them of a moral failure: By allowing the government to construct a massive surveillance apparatus, the field had abused the public trust. Rogaway said the scientists had a duty to pursue social good in their work.
He likened the danger posed by modern governments’ growing surveillance capabilities to the threat of nuclear warfare in the 1950s, and called upon scientists to step up and speak out today, as they did then.

I spoke to Rogaway about why cryptographers fail to see their work in moral terms, and the emerging link between encryption and terrorism in the national conversation. A transcript of our conversation appears below, lightly edited for concision and clarity….(More)”

China’s Biggest Polluters Face Wrath of Data-Wielding Citizens

Curated on December 14, 2015May 29, 2019 by Stefaan Verhulst

Bloomberg News: “Besides facing hefty fines, criminal punishments and the possibility of closing, the worst emitters in China risk additional public anger as new smartphone applications and lower-cost monitoring devices widen access to data on pollution sources.

The Blue Map app, developed by the Institute of Public & Environmental Affairs with support from the SEE Foundation and the Alibaba Foundation, provides pollution data from more than 3,000 large coal-power, steel, cement and petrochemical production plants. Origins Technology Ltd. in July began sale of the Laser Egg, a palm-sized air quality monitor used to track indoor and outdoor air quality by measuring fine particulate matter in the air.

“Letting people know the sources of regional pollution will help the push for control over emissions of every chimney,” said Ma Jun, the founder and director of the Beijing-based IPE.

The phone map and Laser Egg are the latest levers in prying control over information on air quality from the hands of the few to the many, and they’re beginning to weigh on how officials respond to the issue. Numerous smartphone applications, including those developed by SINA Corp. and Moji Fengyun (Beijing) Software Technology Development Co., now provide people in China with real-time access to air quality readings, essentially democratizing what was once an information pipeline available only to the government.

“China’s continuing struggle to control and reduce air pollution exemplifies the government’s fear that lifestyle issues will mutate into demands for political change,” said Mary Gallagher, an associate professor of political science at the University of Michigan.

Even the government is getting in on the act. The Ministry of Environmental Protection rolled out a smartphone application called “Nationwide Air Quality” with the help ofWuhan Juzheng Environmental Science & Technology Co. at the end of 2013.

“As citizens know more about air pollution, more pressure will be put on the government,” said Xu Qinxiang, a technology manager at Wuhan Juzheng. “This will urge the government to control pollutant sources and upgrade heavy industries.”

Laser Egg

Sources of air quality data come from the China National Environment Monitoring Center, local environmental protection bureaus and non-Chinese sources such as the U.S. Embassy’s website in Beijing, Xu said.

Air quality is a controversial subject in China. Since 2012, the public has pushed the government to move more quickly than planned to begin releasing data measuring pollution levels — especially of PM2.5, the particulates most harmful to human health.

The reading was 267 micrograms per cubic meter at 10 a.m. Monday near Tiananmen Square, according to the Beijing Municipal Environmental Monitoring Center. The World Health Organization cautions against 24-hour exposure to concentrations higher than 25.

The availability of data appears to be filling a need, especially with the arrival of colder temperatures and the associated smog that blanketed Beijing and northern Chinarecently….

“With more disclosure of the data, everyone becomes more sensitive, hoping the government can do something,” Li Yajuan, a 27-year-old office secretary, said in an interview in Beijing’s Fuchengmen area. “It’s our own living environment after all.”

Efforts to make products linked to air data continue. IBM has been developing artificial intelligence to help fight Beijing’s toxic air pollution, and plans to work with other municipalities in China and India on similar projects to manage air quality….(More)”

Opening up government data for public benefit

Curated on December 14, 2015May 29, 2019 by Stefaan Verhulst

Keiran Hardy at the Mandarin (Australia): “…This post explains the open data movement and considers the benefits and risks of releasing government data as open data. It then outlines the steps taken by the Labor and Liberal governments in accordance with this trend. It argues that the Prime Minister’stask, while admirably intentioned, is likely to prove difficult due to ongoing challenges surrounding the requirements of privacy law and a public service culture that remains reluctant to release government data into the public domain….

A key purpose of releasing government data is to improve the effectiveness and efficiency of services delivered by the government. For example, data on crops, weather and geography might be analysed to improve current approaches to farming and industry, or data on hospital admissions might be analysed alongside demographic and census data to improve the efficiency of health services in areas of need. It has been estimated that such innovation based on open data could benefit the Australian economy by up to $16 billion per year.

Another core benefit is that the open data movement is making gains in transparency and accountability, as a greater proportion of government decisions and operations are being shared with the public. These democratic values are made clear in the OGP’s Open Government Declaration, which aims to make governments ‘more open, accountable, and responsive to citizens’.

Open data can also improve democratic participation by allowing citizens to contribute to policy innovation. Events like GovHack, an annual Australian competition in which government, industry and the general public collaborate to find new uses for open government data, epitomise a growing trend towards service delivery informed by user input. The winner of the “Best Policy Insights Hack” at GovHack 2015 developed a software program for analysing which suburbs are best placed for rooftop solar investment.

At the same time, the release of government data poses significant risks to the privacy of Australian citizens. Much of the open data currently available is spatial (geographic or satellite) data, which is relatively unproblematic to post online as it poses minimal privacy risks. However, for the full benefits of open data to be gained, these kinds of data need to be supplemented with information on welfare payments, hospital admission rates and other potentially sensitive areas which could drive policy innovation.

Policy data in these areas would be de-identified — that is, all names, addresses and other obvious identifying information would be removed so that only aggregate or statistical data remains. However, debates continue as to the reliability of de-identification techniques, as there have been prominent examples of individuals being re-identified by cross-referencing datasets….

With regard to open data, a culture resistant to releasing government informationappears to be driven by several similar factors, including:

A generational preference amongst public service management for maintaining secrecy of information, whereas younger generations expect that data should be made freely available;
Concerns about the quality or accuracy of information being released;
Fear that mistakes or misconduct on behalf of government employees might be exposed;
Limited understanding of the benefits that can be gained from open data; and
A lack of leadership to help drive the open data movement.

If open data policies have a similar effect on public service culture as FOI legislation, it may be that open data policies in fact hinder transparency by having a chilling effect on government decision-making for fear of what might be exposed….

These legal and cultural hurdles will pose ongoing challenges for the Turnbull government in seeking to release greater amounts of government data as open data….(More)

Big Data Before the Web

Curated on December 14, 2015August 3, 2018 by Stefaan Verhulst

Evan Hepler-Smith in the Wall Street Journal: “Sometime in the early 1950s, on a reservation in Wisconsin, a Menominee Indian man looked at an ink blot. An anthropologist recorded the man’s reaction according to a standard Rorschach-test protocol. The researcher submitted a copy of these notes to an enormous cache of records collected over the course of decades by American social scientists working among various “societies ‘other than our own.’ ” This entire collection of social-scientific data was photographed and printed in arrays of microscopic images on 3-by-5-inch cards. Sets of these cards were shipped to research libraries around the world. They gathered dust.

In the results of this Rorschach test, the anthropologist saw evidence of a culture eroded by modernity. Sixty years later, these documents also testify to the aspirations and fate of the social-scientific project for which they were generated. Deep within this forgotten Ozymandian card file sits the Menominee man’s reaction to Rorschach card VI: “It is like a dead planet. It seems to tell the story of a people once great who have lost . . . like something happened. All that’s left is the symbol.”

In “Database of Dreams: The Lost Quest to Catalog Humanity,” Rebecca Lemov delves into the ambitious efforts of mid-20th-century social scientists to build a “capacious and reliable science of the varieties of the human being” by generating an archive of human experience through interviews and tests and by storing the information on the high-tech media of the day.

For these psychologists and anthropologists, the key to a universal human science lay in studying members of cultures in transition between traditional and modern ways of life and in rendering their individuality as data. Interweaving stories of social scientists, Native American research subjects and information technologies, Ms. Lemov presents a compelling account of “what ‘humanness’ came to mean in an age of rapid change in technological and social conditions.” Ms. Lemov, an associate professor of the history of science at Harvard University, follows two contrasting threads through a story that she calls “a parable for our time.” She shows, first, how collecting data about human experience shapes human experience and, second, how a high-tech data repository of the 1950s became, as she puts it, a “data ruin.”…(More) – See also: Database of Dreams: The Lost Quest to Catalog Humanity

OpenFDA: an innovative platform providing access to a wealth of FDA’s publicly available data

Curated on December 13, 2015August 3, 2018 by Stefaan Verhulst

Paper by Taha A Kass-Hout et al in JAMIA: “The objective of openFDA is to facilitate access and use of big important Food and Drug Administration public datasets by developers, researchers, and the public through harmonization of data across disparate FDA datasets provided via application programming interfaces (APIs).

Materials and Methods: Using cutting-edge technologies deployed on FDA’s new public cloud computing infrastructure, openFDA provides open data for easier, faster (over 300 requests per second per process), and better access to FDA datasets; open source code and documentation shared on GitHub for open community contributions of examples, apps and ideas; and infrastructure that can be adopted for other public health big data challenges.

Results:Since its launch on June 2, 2014, openFDA has developed four APIs for drug and device adverse events, recall information for all FDA-regulated products, and drug labeling. There have been more than 20 million API calls (more than half from outside the United States), 6000 registered users, 20,000 connected Internet Protocol addresses, and dozens of new software (mobile or web) apps developed. A case study demonstrates a use of openFDA data to understand an apparent association of a drug with an adverse event. Conclusion With easier and faster access to these datasets, consumers worldwide can learn more about FDA-regulated products

Conclusion: With easier and faster access to these datasets, consumers worldwide can learn more about FDA-regulated products…(More)”

Data Science ethics

Curated on December 13, 2015August 3, 2018 by Stefaan Verhulst

Gov.uk blog: “If Tesco knows day-to-day how poorly the nation is, how can Government access similar insights so it can better plan health services? If Airbnb can give you a tailored service depending on your tastes, how can Government provide people with the right support to help them back into work in a way that is right for them? If companies are routinely using social media data to get feedback from their customers to improve their services, how can Government also use publicly available data to do the same?

Data science allows us to use new types of data and powerful tools to analyse this more quickly and more objectively than any human could. It can put us in the vanguard of policymaking – revealing new insights that leads to better and more tailored interventions. And it can help reduce costs, freeing up resource to spend on more serious cases.

But some of these data uses and machine-learning techniques are new and still relatively untested in Government. Of course, we operate within legal frameworks such as the Data Protection Act and Intellectual Property law. These are flexible but don’t always talk explicitly about the new challenges data science throws up. For example, how are you to explain the decision making process of a deep learning black box algorithm? And if you were able to, how would you do so in plain English and not a row of 0s and 1s?

We want data scientists to feel confident to innovate with data, alongside the policy makers and operational staff who make daily decisions on the data that the analysts provide –. That’s why we are creating an ethical framework which brings together the relevant parts of the law and ethical considerations into a simple document that helps Government officials decide what it can do and what it should do. We have a moral responsibility to maximise the use of data – which is never more apparent than after incidents of abuse or crime are left undetected – as well as to pay heed to the potential risks of these new tools. The guidelines are draft and not formal government policy, but we want to share them more widely in order to help iterate and improve them further….

So what’s in the framework? There is more detail in the fuller document, but it is based around six key principles:

Start with a clear user need and public benefit: this will help you justify the level of data sensitivity and method you use
Use the minimum level of data necessary to fulfill the public benefit: there are many techniques for doing so, such as de-identification, aggregation or querying against data
Build robust data science models: the model is only as good as the data it contains and while machines are less biased than humans they can get it wrong. It’s critical to be clear about the confidence of the model and think through unintended consequences and biases contained within the data
Be alert to public perceptions: put simply, what would a normal person on the street think about the project?
Be as open and accountable as possible: Transparency is the antiseptic for unethical behavior. Aim to be as open as possible (with explanations in plain English), although in certain public protection cases the ability to be transparent will be constrained.
Keep data safe and secure: this is not restricted to data science projects but we know that the public are most concerned about losing control of their data….(More)”

Open Data Index 2015

Curated on December 10, 2015August 3, 2018 by Stefaan Verhulst

Open Knowledge: “….This year’s Index showed impressive gains from non-OECD countries with Taiwan topping the Index and Colombia and Uruguay breaking into the top ten at four and seven respectively. Overall, the Index evaluated 122 places and 1586 datasets and determined that only 9%, or 156 datasets, were both technically and legally open.

The Index ranks countries based on the availability and accessibility of data in thirteen key categories, including government spending, election results, procurement, and pollution levels. Over the summer, we held a public consultation, which saw contributions from individuals within the open data community as well as from key civil society organisations across an array of sectors. As a result of this consultation, we expanded the 2015 Index to include public procurement data, water quality data, land ownership data and weather data; we also decided to removed transport timetables due to the difficulties faced when comparing transport system data globally.

Open Knowledge International began to systematically track the release of open data by national governments in 2013 with the objective of measuring if governments were releasing the key datasets of high social and democratic value as open data. That enables us to better understand the current state of play and in turn work with civil society actors to address the gaps in data release. Over the course of the last three years, the Global Open Data Index has become more than just a benchmark – we noticed that governments began to use the Index as a reference to inform their open data priorities and civil society actors began to use the Index advocacy tool to encourage governments to improve their performance in releasing key datasets.

Furthermore, indices such as the Global Open Data Index are not without their challenges. The Index measures the technical and legal openness of datasets deemed to be of critical democratic and social value – it does not measure the openness of a given government. It should be clear that the release of a few key datasets is not a sufficient measure of the openness of a government. The blurring of lines between open data and open government is nothing new and has been hotly debated by civil society groups and transparency organisations since the sharp rise in popularity of open data policies over the last decade. …Index at http://index.okfn.org/”

Big Data in the Policy Cycle: Policy Decision Making in the Digital Era

Curated on December 10, 2015August 3, 2018 by Stefaan Verhulst

Paper by Johann Höchtl et al in the Journal of Organizational Computing and Electronic Commerce: “Although of high relevance to political science, the interaction between technological change and political change in the era of Big Data remains somewhat of a neglected topic. Most studies focus on the concept of e-government and e-governance, and on how already existing government activities performed through the bureaucratic body of public administration could be improved by technology. This paper attempts to build a bridge between the field of e-governance and theories of public administration that goes beyond the service delivery approach that dominates a large part of e-government research. Using the policy cycle as a generic model for policy processes and policy development, a new look on how policy decision making could be conducted on the basis of ICT and Big Data is presented in this paper….(More)”

The Upside of Slacktivism

Curated on December 10, 2015October 24, 2018 by Stefaan Verhulst

Nathan Collins in Pacific Standard: “When you think of meaningful political action, you probably think of the March on Washington for Jobs and Freedom, or perhaps ACT-UP‘s 1990 protests in San Francisco. You probably don’t think of clicking “like” or “share” on Facetwitstagram—though a new study suggests that those likes and shares may be just as important as marching in the streets, singing songs, and carrying signs.

“The efficacy of online networks in disseminating timely information has been praised by many commentators; at the same time, users are often derided as ‘slacktivists’ because of the shallow commitment involved in clicking a forwarding button,” writes a team led by Pablo Barberá, a political scientist at New York University, in the journal PLoS One.

In other words, it’s easy to argue that sharing a post about climate change and whatnot has no value, since it involves no sacrifice—no standoffs with angry police, no going to jail over taxes you didn’t pay because you opposed the Mexican-American War, not even lost shoes.

On the other hand, maybe sacrifice isn’t the point. Maybe it’s getting attention, and, Barberá and colleagues suggest, slacktivism is actually pretty good at that part—a consequence of just how easy it is to spread the word with the click of a mouse.

The team reached that conclusion after analyzing tens of millions of tweets sent by nearly three million users during the May 2013 anti-government protests in Gezi Park, Istanbul. Among other things, the team identified which tweets were originals rather than retweets, who retweeted whom, and how many followers each user had. That meant Barberá and his team could identify not only how information flowed within the network of protesters, but also how many people that information reached.

Most original tweets came from a relatively small group of protestors using hashtags such as #gezipark, suggesting that information flowed from a core group of protestors toward a less-active periphery. Geographic data backed that up: Around 18 percent of core tweeters were physically present for the Gezi Park demonstrations, compared to a quarter of a percent of peripheral tweeters…..(More)”