Crowdfunding site aims to get homeless back into work


Springwise: “Beam is a new crowdfunding website that has been launched to try and help homeless people based in London get back into work. The idea behind the website is that people donate money online to homeless individuals, which will then be used to give them the qualifications and training that they will need to become fully employed and therefore able to also get themselves secure in their own accommodation.

A new member of Beam is allocated a Member Manager, who works with them to find the best employment avenue for them to take based on their likes and experience. The Member Manager helps them prepare their fundraising campaign, and even helps members with childcare costs while they’re training.

Beam was founded by Alex Stephany, who is also board advisor of car parking app, JustPark, with a pilot scheme in September 2017 and has the full support of Sadiq Khan, the Mayor of London, and the innovation promotors, Nesta.

There are many ways that technology is helping the homeless. Recently, blockchain tech has been used to connect the homeless in New York with valuable services. And new keycard-accessed vending machines are to be installed in safe spaces to provide the homeless with 24-hour access to essential items….(More)”.

The Modern Research Data Portal: a design pattern for networked, data-intensive science


 et al in PeerJ Computer Science: “We describe best practices for providing convenient, high-speed, secure access to large data via research data portals. We capture these best practices in a new design pattern, the Modern Research Data Portal, that disaggregates the traditional monolithic web-based data portal to achieve orders-of-magnitude increases in data transfer performance, support new deployment architectures that decouple control logic from data storage, and reduce development and operations costs.

We introduce the design pattern; explain how it leverages high-performance data enclaves and cloud-based data management services; review representative examples at research laboratories and universities, including both experimental facilities and supercomputer sites; describe how to leverage Python APIs for authentication, authorization, data transfer, and data sharing; and use coding examples to demonstrate how these APIs can be used to implement a range of research data portal capabilities. Sample code at a companion web site, https://docs.globus.org/mrdp, provides application skeletons that readers can adapt to realize their own research data portals….(More)”.

Studying Migrant Assimilation Through Facebook Interests


Antoine DuboisEmilio ZagheniKiran Garimella, and Ingmar Weber at arXiv: “Migrants’ assimilation is a major challenge for European societies, in part because of the sudden surge of refugees in recent years and in part because of long-term demographic trends. In this paper, we use Facebook’s data for advertisers to study the levels of assimilation of Arabic-speaking migrants in Germany, as seen through the interests they express online. Our results indicate a gradient of assimilation along demographic lines, language spoken and country of origin. Given the difficulty to collect timely migration data, in particular for traits related to cultural assimilation, the methods that we develop and the results that we provide open new lines of research that computational social scientists are well-positioned to address….(More)”.

Rights-Based and Tech-Driven: Open Data, Freedom of Information, and the Future of Government Transparency


Beth Noveck at the Yale Human Rights and Development Journal: “Open data policy mandates that government proactively publish its data online for the public to reuse. It is a radically different approach to transparency than traditional right-to-know strategies as embodied in Freedom of Information Act (FOIA) legislation in that it involves ex ante rather than ex post disclosure of whole datasets. Although both open data and FOIA deal with information sharing, the normative essence of open data is participation rather than litigation. By fostering public engagement, open data shifts the relationship between state and citizen from a monitorial to a collaborative one, centered around using information to solve problems together. This Essay explores the theory and practice of open data in comparison to FOIA and highlights its uses as a tool for advancing human rights, saving lives, and strengthening democracy. Although open data undoubtedly builds upon the fifty-year legal tradition of the right to know about the workings of one’s government, open data does more than advance government accountability. Rather, it is a distinctly twenty-first century governing practice borne out of the potential of big data to help solve society’s biggest problems. Thus, this Essay charts a thoughtful path toward a twenty-first century transparency regime that takes advantage of and blends the strengths of open data’s collaborative and innovation-centric approach and the adversarial and monitorial tactics of freedom of information regimes….(More)”.

How AI Could Help the Public Sector


Emma Martinho-Truswell in the Harvard Business Review: “A public school teacher grading papers faster is a small example of the wide-ranging benefits that artificial intelligence could bring to the public sector. A.I could be used to make government agencies more efficient, to improve the job satisfaction of public servants, and to increase the quality of services offered. Talent and motivation are wasted doing routine tasks when they could be doing more creative ones.

Applications of artificial intelligence to the public sector are broad and growing, with early experiments taking place around the world. In addition to education, public servants are using AI to help them make welfare payments and immigration decisions, detect fraud, plan new infrastructure projects, answer citizen queries, adjudicate bail hearings, triage health care cases, and establish drone paths.  The decisions we are making now will shape the impact of artificial intelligence on these and other government functions. Which tasks will be handed over to machines? And how should governments spend the labor time saved by artificial intelligence?

So far, the most promising applications of artificial intelligence use machine learning, in which a computer program learns and improves its own answers to a question by creating and iterating algorithms from a collection of data. This data is often in enormous quantities and from many sources, and a machine learning algorithm can find new connections among data that humans might not have expected. IBM’s Watson, for example, is a treatment recommendation-bot, sometimes finding treatments that human doctors might not have considered or known about.

Machine learning program may be better, cheaper, faster, or more accurate than humans at tasks that involve lots of data, complicated calculations, or repetitive tasks with clear rules. Those in public service, and in many other big organizations, may recognize part of their job in that description. The very fact that government workers are often following a set of rules — a policy or set of procedures — already presents many opportunities for automation.

To be useful, a machine learning program does not need to be better than a human in every case. In my work, we expect that much of the “low hanging fruit” of government use of machine learning will be as a first line of analysis or decision-making. Human judgment will then be critical to interpret results, manage harder cases, or hear appeals.

When the work of public servants can be done in less time, a government might reduce its staff numbers, and return money saved to taxpayers — and I am sure that some governments will pursue that option. But it’s not necessarily the one I would recommend. Governments could instead choose to invest in the quality of its services. They can re-employ workers’ time towards more rewarding work that requires lateral thinking, empathy, and creativity — all things at which humans continue to outperform even the most sophisticated AI program….(More)”.

U.S. soldiers are revealing sensitive and dangerous information by jogging


Liz Sly at Washington Post: “An interactive map posted on the Internet that shows the whereabouts of people who use fitness devices such as Fitbit also reveals highly sensitive information about the locations and activities of soldiers at U.S. military bases, in what appears to be a major security oversight.

The Global Heat Map, published by the GPS tracking company Strava, uses satellite information to map the locations and movements of subscribers to the company’s fitness service over a two-year period, by illuminating areas of activity.

Strava says it has 27 million users around the world, including people who own widely available fitness devices such as Fitbit and Jawbone, as well as people who directly subscribe to its mobile app. The map is not live — rather, it shows a pattern of accumulated activity between 2015 and September 2017.

Most parts of the United States and Europe, where millions of people use some type of fitness tracker, show up on the map as blazes of light because there is so much activity.

In war zones and deserts in countries such as Iraq and Syria, the heat map becomes almost entirely dark — except for scattered pinpricks of activity. Zooming in on those areas brings into focus the locations and outlines of known U.S. military bases, as well as of other unknown and potentially sensitive sites — presumably because American soldiers and other personnel are using fitness trackers as they move around.

The U.S.-led coalition against the Islamic State said on Monday it is revising its guidelines on the use of all wireless and technological devices on military facilities as a result of the revelations….(More)”.

Eight great applications of simulation in the policymaking process


Florence Engasser and Sonia Nasser at Nesta: “In a context where complexity and unpredictability increasingly form part of the decision-making process, our policymakers need new tools to help them experiment, explore different scenarios and weigh the trade-offs of a decision in a safe, pressure-free environment.

Simulation brings the potential for more creative, efficient and effective policymaking

The best way to understand how simulation can be used as a policy method is to look at examples. We’ve found eight really great examples from around the world, giving us a sense of the broad range of applications simulation can have in the policymaking process, from board games through to more traditional modelling techniques applied to new fields, and all the way to virtual reality….(More)”.

Algorithms show potential in measuring diagnostic errors using big data


Greg Slabodkin at Information Management: “While the problem of diagnostic errors is widespread in medicine, with an estimated 12 million Americans affected annually, a new approach to quantifying and monitoring these errors has the potential to prevent serious patient injuries, including disability or death.

“The single biggest impediment to making progress is the lack of operational measures of diagnostic errors,” says David Newman-Toker, MD, director of the Johns Hopkins Armstrong Institute Center for Diagnostic Excellence. “It’s very difficult to measure because we haven’t had the tools to look for it in a systematic way. And most of the methods that look for diagnostics errors involve training people to do labor-intensive chart reviews.”

However, a new method—called the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE)—uncovers misdiagnosis-related harms using specific algorithms and big data. The automated approach could replace labor-intensive reviews of medical records by hospital staff, which researchers contend are limited by poor clinical documentation, low reliability and inherent bias.

According to Newman-Toker, SPADE utilizes statistical analyses to identify critical patterns that measure the rate of diagnostic error by analyzing large, existing clinical and claims datasets containing hundreds of thousands of patient visits. Specifically, algorithms are leveraged to look for common symptoms prompting a physician visit and then pairing them with one or more diseases that could be misdiagnosed in those clinical contexts….(More)”.

Can a reality TV show discourage corruption?


The Economist: “The timing could not have been better. In the same week as two civil servants in Nigeria appeared in court for embezzling funds earmarked for International Anti-Corruption Day, the finalists of “Integrity Idol” were announced. In this reality television show, honest civil servants working in corrupt countries compete for glory, fame and, occasionally, a live chicken. The show is a hit: over 10m people have watched it and more than 400,000 have cast their votes in favour of their Integrity Idols.

“Integrity Idol” started in Nepal in 2014 and has since spread to Pakistan, Mali, Liberia, Nigeria and South Africa. Five finalists, vetted by a panel of judges, are chosen to be interviewed. They explain why they deserve the prize. “I come to work late. My boss could ask ‘Why are you late?’ (…) I say I slept a little longer. Say it the way it is! Face the consequences!” one nominee exhorts.

It is not always easy to find good contestants. The Nigerian nomination period was extended because of the poor quality of entrants. “People were nominating their auntie because she gave them money,” says Odeh Friday, who runs the campaign. Others thought they qualified because they came to work on time. One policeman was surprised by his nomination because, he explained, he was involved in shady contracts. Another nominee resigned after he realised that background checks might dig up old dirt.

“Integrity Idol” claims to steer clear of politics. Elected officials may not be nominated. Nor, in some countries, may people in the army. Even so, the show delivers a punch in the face to crooked politicians and their cronies, sometimes just by its timing: in Liberia last year, it aired while presidential elections were embroiled in fraud investigations.

It is difficult to know what impact the show is having, though the Massachusetts Institute of Technology has begun to measure it. Change may be gradual. Gareth Newham at the Institute of Security Studies in South Africa thinks its greatest contribution will be in changing attitudes. “Too many young people believe that you can only get a job if you belong to the [ruling party]. What has been missing is a focus on the ordinary people who do good work.”…(More)”.

Handbook on Participatory Governance


Book edited by Hubert Heinelt: “Can participatory governance really improve the quality of democracy? Concentrating on democracy beyond governmental structures, this Handbook argues that it is a political task to engage individuals at all levels of governance.

The Handbook on Participatory Governance reveals that transforming governance arrangements does in fact enhance democracy and that the democratic quality of participatory governance is crucial. The contributors reflect on the notion of democracy and participatory governance and how they relate to each other. Case studies are presented from regional, national and international levels, to identify how governance can be turned into a participatory form. With chapters reviewing participatory governance’s role alongside power, science and employment relations, innovative ideas for future progress in participatory governance are presented….(More)”.