Innovation Contests: How to Engage Citizens in Solving Urban Problems?

Curated on Posted on by Stefaan Verhulst

Chapter by Sarah Hartmann, Agnes Mainka and Wolfgang G. Stock in Enhancing Knowledge Discovery and Innovation in the Digital Era: “Cities all over the world are challenged with problems evolving from increasing urbanity, population growth, and density. For example, one prominent issue that is addressed in many cities is mobility. To develop smart city solutions, governments are trying to introduce open innovation. They have started to open their governmental and city related data as well as awake the citizens’ awareness on urban problems through innovation contests.

Citizens are the users of the city and therefore, have a practical motivation to engage in innovation contests as for example in hackathons and app competitions. The collaboration and co-creation of civic services by means of innovation contests is a cultural development of how governments and citizens work together in an open governmental environment. A qualitative analysis of innovation contests in 24 world cities reveals this global trend. In particular, such events increase the awareness of citizens and local businesses for identifying and solving urban challenges and are helpful means to transfer the smart city idea into practicable solutions….(More)”.

Big Data Challenge for Social Sciences: From Society and Opinion to Replications

Curated on Posted on by Stefaan Verhulst

Symposium Paper by Dominique Boullier: “When in 2007 Savage and Burrows pointed out ‘the coming crisis of empirical methods’, they were not expecting to be so right. Their paper however became a landmark, signifying the social sciences’ reaction to the tremendous shock triggered by digital methods. As they frankly acknowledge in a more recent paper, they did not even imagine the extent to which their prediction might become true, in an age of Big Data, where sources and models have to be revised in the light of extended computing power and radically innovative mathematical approaches.They signalled not just a debate about academic methods but also a momentum for ‘commercial sociology’ in which platforms acquire the capacity to add ‘another major nail in the coffin of academic sociology claims to jurisdiction over knowledge of the social’, because ‘research methods (are) an intrinsic feature of contemporary capitalist organisations’ (Burrows and Savage, 2014, p. 2). This need for a serious account of research methods is well tuned with the claims of Social Studies of Science that should be applied to the social sciences as well.

I would like to build on these insights and principles of Burrows and Savage to propose an historical and systematic account of quantification during the last century, following in the footsteps of Alain Desrosières, and in which we see Big Data and Machine Learning as a major shift in the way social science can be performed. And since, according to Burrows and Savage (2014, p. 5), ‘the use of new data sources involves a contestation over the social itself’, I will take the risk here of identifying and defining the entities that are supposed to encapsulate the social for each kind of method: beyond the reign of ‘society’ and ‘opinion’, I will point at the emergence of the ‘replications’ that are fabricated by digital platforms but are radically different from previous entities. This is a challenge to invent not only new methods but also a new process of reflexivity for societies, made available by new stakeholders (namely, the digital platforms) which transform reflexivity into reactivity (as operational quantifiers always tend to)….(More)”.

Even Imperfect Algorithms Can Improve the Criminal Justice System

Curated on Posted on by Stefaan Verhulst

Sam Corbett-Davies, Sharad Goel and Sandra González-Bailón in the The New York Times: “In courtrooms across the country, judges turn to computer algorithms when deciding whether defendants awaiting trial must pay bail or can be released without payment. The increasing use of such algorithms has prompted warnings about the dangers of artificial intelligence. But research shows that algorithms are powerful tools for combating the capricious and biased nature of human decisions.

Bail decisions have traditionally been made by judges relying on intuition and personal preference, in a hasty process that often lasts just a few minutes. In New York City, the strictest judges are more than twice as likely to demand bail as the most lenient ones.

To combat such arbitrariness, judges in some cities now receive algorithmically generated scores that rate a defendant’s risk of skipping trial or committing a violent crime if released. Judges are free to exercise discretion, but algorithms bring a measure of consistency and evenhandedness to the process.

The use of these algorithms often yields immediate and tangible benefits: Jail populations, for example, can decline without adversely affecting public safety.

In one recent experiment, agencies in Virginia were randomly selected to use an algorithm that rated both defendants’ likelihood of skipping trial and their likelihood of being arrested if released. Nearly twice as many defendants were released, and there was no increase in pretrial crime….(More)”.

Computational Propaganda and Political Big Data: Moving Toward a More Critical Research Agenda

Curated on Posted on by Stefaan Verhulst

Gillian Bolsover and Philip Howard in the Journal Big Data: “Computational propaganda has recently exploded into public consciousness. The U.S. presidential campaign of 2016 was marred by evidence, which continues to emerge, of targeted political propaganda and the use of bots to distribute political messages on social media. This computational propaganda is both a social and technical phenomenon. Technical knowledge is necessary to work with the massive databases used for audience targeting; it is necessary to create the bots and algorithms that distribute propaganda; it is necessary to monitor and evaluate the results of these efforts in agile campaigning. Thus, a technical knowledge comparable to those who create and distribute this propaganda is necessary to investigate the phenomenon.

However, viewing computational propaganda only from a technical perspective—as a set of variables, models, codes, and algorithms—plays into the hands of those who create it, the platforms that serve it, and the firms that profit from it. The very act of making something technical and impartial makes it seem inevitable and unbiased. This undermines the opportunities to argue for change in the social value and meaning of this content and the structures in which it exists. Big-data research is necessary to understand the socio-technical issue of computational propaganda and the influence of technology in politics. However, big data researchers must maintain a critical stance toward the data being used and analyzed so as to ensure that we are critiquing as we go about describing, predicting, or recommending changes. If research studies of computational propaganda and political big data do not engage with the forms of power and knowledge that produce it, then the very possibility for improving the role of social-media platforms in public life evaporates.

Definitionally, computational propaganda has two important parts: the technical and the social. Focusing on the technical, Woolley and Howard define computational propaganda as the assemblage of social-media platforms, autonomous agents, and big data tasked with the manipulation of public opinion. In contrast, the social definition of computational propaganda derives from the definition of propaganda—communications that deliberately misrepresent symbols, appealing to emotions and prejudices and bypassing rational thought, to achieve a specific goal of its creators—with computational propaganda understood as propaganda created or disseminated using computational (technical) means…(More) (Full Text HTML; Full Text PDF)

Could Bitcoin technology help science?

Curated on Posted on by Stefaan Verhulst

Andy Extance at Nature: “…The much-hyped technology behind Bitcoin, known as blockchain, has intoxicated investors around the world and is now making tentative inroads into science, spurred by broad promises that it can transform key elements of the research enterprise. Supporters say that it could enhance reproducibility and the peer review process by creating incorruptible data trails and securely recording publication decisions. But some also argue that the buzz surrounding blockchain often exceeds reality and that introducing the approach into science could prove expensive and introduce ethical problems.

A few collaborations, including Scienceroot and Pluto, are already developing pilot projects for science. Scienceroot aims to raise US$20 million, which will help pay both peer reviewers and authors within its electronic journal and collaboration platform. It plans to raise the funds in early 2018 by exchanging some of the science tokens it uses for payment for another digital currency known as ether. And the Wolfram Mathematica algebra program — which is widely used by researchers — is currently working towards offering support for an open-source blockchain platform called Multichain. Scientists could use this, for example, to upload data to a shared, open workspace that isn’t controlled by any specific party, according to Multichain….

Claudia Pagliari, who researches digital health-tracking technologies at the University of Edinburgh, UK, says that she recognizes the potential of blockchain, but researchers have yet to properly explore its ethical issues. What happens if a patient withdraws consent for a trial that is immutably recorded on a blockchain? And unscrupulous researchers could still add fake data to a blockchain, even if the process is so open that everyone can see who adds it, says Pagliari. Once added, no-one can change that information, although it’s possible they could label it as retracted….(More)”.

New York City moves to create accountability for algorithms

Curated on Posted on by Stefaan Verhulst

Lauren Kirchner at ArsTechnica: “The algorithms that play increasingly central roles in our lives often emanate from Silicon Valley, but the effort to hold them accountable may have another epicenter: New York City. Last week, the New York City Council unanimously passed a bill to tackle algorithmic discrimination—the first measure of its kind in the country.

The algorithmic accountability bill, waiting to be signed into law by Mayor Bill de Blasio, establishes a task force that will study how city agencies use algorithms to make decisions that affect New Yorkers’ lives, and whether any of the systems appear to discriminate against people based on age, race, religion, gender, sexual orientation, or citizenship status. The task force’s report will also explore how to make these decision-making processes understandable to the public.

The bill’s sponsor, Council Member James Vacca, said he was inspired by ProPublica’s investigation into racially biased algorithms used to assess the criminal risk of defendants….

A previous, more sweeping version of the bill had mandated that city agencies publish the source code of all algorithms being used for “targeting services” or “imposing penalties upon persons or policing” and to make them available for “self-testing” by the public. At a hearing at City Hall in October, representatives from the mayor’s office expressed concerns that this mandate would threaten New Yorkers’ privacy and the government’s cybersecurity.

The bill was one of two moves the City Council made last week concerning algorithms. On Thursday, the committees on health and public safety held a hearing on the city’s forensic methods, including controversial tools that the chief medical examiner’s office crime lab has used for difficult-to-analyze samples of DNA.

As a ProPublica/New York Times investigation detailed in September, an algorithm created by the lab for complex DNA samples has been called into question by scientific experts and former crime lab employees.

The software, called the Forensic Statistical Tool, or FST, has never been adopted by any other lab in the country….(More)”.

Normative Challenges of Identification in the Internet of Things: Privacy, Profiling, Discrimination, and the GDPR

Curated on Posted on by Stefaan Verhulst

Paper by Sandra Wachter: “In the Internet of Things (IoT), identification and access control technologies provide essential infrastructure to link data between a user’s devices with unique identities, and provide seamless and linked up services. At the same time, profiling methods based on linked records can reveal unexpected details about users’ identity and private life, which can conflict with privacy rights and lead to economic, social, and other forms of discriminatory treatment. A balance must be struck between identification and access control required for the IoT to function and user rights to privacy and identity. Striking this balance is not an easy task because of weaknesses in cybersecurity and anonymisation techniques.

The EU General Data Protection Regulation (GDPR), set to come into force in May 2018, may provide essential guidance to achieve a fair balance between the interests of IoT providers and users. Through a review of academic and policy literature, this paper maps the inherit tension between privacy and identifiability in the IoT.

It focuses on four challenges: (1) profiling, inference, and discrimination; (2) control and context-sensitive sharing of identity; (3) consent and uncertainty; and (4) honesty, trust, and transparency. The paper will then examine the extent to which several standards defined in the GDPR will provide meaningful protection for privacy and control over identity for users of IoT. The paper concludes that in order to minimise the privacy impact of the conflicts between data protection principles and identification in the IoT, GDPR standards urgently require further specification and implementation into the design and deployment of IoT technologies….(More)”.

The nation state goes virtual

Curated on Posted on by Stefaan Verhulst

Tom Symons at Nesta’s Predictions for 2018: “As the world changes, people expect their governments and public services to do so too. When it’s easy to play computer games with someone on the other side of the world, or set up a company bank account in five minutes, there is an expectation that paying taxes, applying for services or voting should be too…..

To add to this, large political upheavals such as Brexit and the election of Donald Trump have left some people feeling alienated from their national identity. Since the the UK voted to leave the EU, demand for Irish passports has increased by 50 per cent, a sign that people feel dissatisfied by the constraints of geographically determined citizenship when they can no longer relate to their national identity.

In response, some governments see these changes as an opportunity to reconceptualise what we mean by a nation state.

The e-Residency offer

The primary actor in this disruption is Estonia, which leads the world in digital government. In 2015 they introduced an e-Residency, allowing anyone anywhere in the world to receive a government-issued digital identity. The e-Residency gives people access to digital public services and the ability to register and run online businesses from the country, in exactly the same way as someone born in Estonia. As of November 2017, over 27,000 people have applied to be Estonian e-Residents, and they have established over 4,200 companies. Estonia aims to have ten million virtual residents by 2025….

While Estonia is a sovereign nation using technology to redefine itself, there are movements taking advantage of decentralising technologies in a bid to do away with the nation state altogether. Bitnation is a blockchain-based technology which enables people to create and join virtual nations. This allows people to agree their own social contracts between one another, using smart contract technology, removing the need for governments as an administrator or mediator. Since it began in 2014, it has been offering traditional government services, such as notaries, dispute resolution, marriages and voting systems, without the need for a middleman.

As of November 2017, there are over 10,000 Bitnation citizens. …

As citizens, we may be able to educate our children in Finland, access healthcare from South Korea and run our businesses in New Zealand, all without having to leave the comfort of our homes. Governments may see this as means of financial sustainability in the longer term, generating income by selling such services to a global population instead of centralised taxation systems levied on a geographic population.

Such a model has been described as ‘nation-as-a-service’, and could mean countries offering different tiers of citizenship, with taxes based on the number of services used, or tier of citizenship chosen. This could also mean multiple citizenships, including of city-states, as well as nations….

This is the moment for governments to start taking the full implications of the digital age seriously. From electronic IDs and data management through to seamless access to services, citizens will only demand better digital services. Countries such as Azerbaijan, are already developing their own versions of the e-Residency. Large internet platforms such as Amazon are gearing up to replace entire government functions. If governments don’t grasp the nettle, they may find themselves left behind by technology and other countries which won’t wait around for them….(More)”.

Civic Technology: Open Data and Citizen Volunteers as a Resource for North Carolina Local Governments

Curated on Posted on by Stefaan Verhulst

Report by John B. Stephens: “Civic technology is an emergent area of practice where IT experts and citizens without specialized IT skills volunteer their time using government-provided open data to improve government services or otherwise create public benefit. Civic tech, as it is often referred to, draws on longer-standing practices, particularly e-government and civic engagement. It is also a new form of citizen–government co-production, building on the trend of greater government transparency.

This report is designed to help North Carolina local government leaders:

  • Define civic technology practices and describing North Carolina civic tech resources
  • Highlight accomplishments and ongoing projects in civic tech (in North Carolina and beyond)
  • Identify opportunities and challenges for North Carolina local governments in civic tech
  • Provide a set of resources for education and involvement in civic tech….(More)”.

Research reveals de-identified patient data can be re-identified

Curated on Posted on by Stefaan Verhulst

Vanessa Teague, Chris Culnane and Ben Rubinstein in PhysOrg: “In August 2016, Australia’s federal Department of Health published medical billing records of about 2.9 million Australians online. These records came from the Medicare Benefits Scheme (MBS) and the Pharmaceutical Benefits Scheme (PBS) containing 1 billion lines of historical health data from the records of around 10 per cent of the population.

These longitudinal records were de-identified, a process intended to prevent a person’s identity from being connected with information, and were made public on the government’s open data website as part of its policy on accessible public …

We found that patients can be re-identified, without decryption, through a process of linking the unencrypted parts of the  with known information about the individual.

Our findings replicate those of similar studies of other de-identified datasets:

  • A few mundane facts taken together often suffice to isolate an individual.
  • Some patients can be identified by name from publicly available information.
  • Decreasing the precision of the data, or perturbing it statistically, makes re-identification gradually harder at a substantial cost to utility.

The first step is examining a patient’s uniqueness according to medical procedures such as childbirth. Some individuals are unique given public information, and many patients are unique given a few basic facts, such as year of birth or the date a baby was delivered….

The second step is examining uniqueness according to the characteristics of commercial datasets we know of but cannot access directly. There are high uniqueness rates that would allow linking with a commercial pharmaceutical dataset, and with the billing data available to a bank. This means that ordinary people, not just the prominent ones, may be easily re-identifiable by their bank or insurance company…

These de-identification methods were bound to fail, because they were trying to achieve two inconsistent aims: the protection of individual privacy and publication of detailed individual records. De-identification is very unlikely to work for other rich datasets in the government’s care, like census data, tax records, mental health records, penal information and Centrelink data.

While the ambition of making more data more easily available to facilitate research, innovation and sound public policy is a good one, there is an important technical and procedural problem to solve: there is no good solution for publishing sensitive complex individual records that protects privacy without substantially degrading the usefulness of the data.

Some data can be safely published online, such as information about government, aggregations of large collections of material, or data that is differentially private. For sensitive, complex data about individuals, a much more controlled release in a secure research environment is a better solution. The Productivity Commission recommends a “trusted user” model, and techniques like dynamic consent also give patients greater control and visibility over their personal information….(More).