Paper by Tanja Aitamurto: “…shows how the two virtues of collective intelligence – cognitive diversity and large crowds –turn into perils in crowdsourced policymaking. That is because of a conflict between the logic of the crowds and the logic of policymaking. The crowd’s logic differs from that of traditional policymaking in several aspects. To mention some of those: In traditional policymaking it is a small group of experts making proposals to the policy, whereas in crowdsourced policymaking, it is a large, anonymous crowd with a mixed level of expertise. The crowd proposes atomic ideas, whereas traditional policymaking is used to dealing with holistic and synthesized proposals. By drawing on data from a crowdsourced law-making process in Finland, the paper shows how the logics of the crowds and policymaking collide in practice. The conflict prevents policymaking fully benefiting from the crowd’s input, and it also hinders governments from adopting crowdsourcing more widely as a practice for deploying open policymaking practices….(More)”
Open data set to reshape charity and activism in 2016
The Guardian: “In 2015 the EU launched the world’s first international data portal, the Chinese government pledged to make state data public, and the UK lost its open data crown to Taiwan. Troves of data were unlocked by governments around the world last year, but the usefulness of much of that data is still to be determined by the civic groups, businesses and governments who use it. So what’s in the pipeline? And how will the open data ecosystem grow in 2016? We asked the experts.
1. Data will be seen as infrastructure (Heather Savory, director general for data capability, Office for National Statistics)….
2. Journalists, charities and civil society bodies will embrace open data (Hetan Shah, executive director, the Royal Statistical Society)…3. Activists will take it upon themselves to create data
3. Activists will take it upon themselves to create data (Pavel Richter, chief executive, Open Knowledge International)….
4. Data illiteracy will come at a heavy price (Sir Nigel Shadbolt, principal, Jesus College, Oxford, professorial research fellow in computer science, University of Oxford and chairman and co-founder of the Open Data Institute…)
5. We’ll create better tools to build a web of data (Dr Elena Simperl, associate professor, electronics and computer science, University of Southampton) …(More)”
Daedalus Issue on “The Internet”
Press release: “Thirty years ago, the Internet was a network that primarily delivered email among academic and government employees. Today, it is rapidly evolving into a control system for our physical environment through the Internet of Things, as mobile and wearable technology more tightly integrate the Internet into our everyday lives.
How will the future Internet be shaped by the design choices that we are making today? Could the Internet evolve into a fundamentally different platform than the one to which we have grown accustomed? As an alternative to big data, what would it mean to make ubiquitously collected data safely available to individuals as small data? How could we attain both security and privacy in the face of trends that seem to offer neither? And what role do public institutions, such as libraries, have in an environment that becomes more privatized by the day?
These are some of the questions addressed in the Winter 2016 issue of Daedalus on “The Internet.” As guest editors David D. Clark (Senior Research Scientist at the MIT Computer Science and Artificial Intelligence Laboratory) and Yochai Benkler (Berkman Professor of Entrepreneurial Legal Studies at Harvard Law School and Faculty Co-Director of the Berkman Center for Internet and Society at Harvard University) have observed, the Internet “has become increasingly privately owned, commercial, productive, creative, and dangerous.”
Some of the themes explored in the issue include:
- The conflicts that emerge among governments, corporate stakeholders, and Internet users through choices that are made in the design of the Internet
- The challenges—including those of privacy and security—that materialize in the evolution from fixed terminals to ubiquitous computing
- The role of public institutions in shaping the Internet’s privately owned open spaces
- The ownership and security of data used for automatic control of connected devices, and
- Consumer demand for “free” services—developed and supported through the sale of user data to advertisers….
Essays in the Winter 2016 issue of Daedalus include:
- The Contingent Internet by David D. Clark (MIT)
- Degrees of Freedom, Dimensions of Power by Yochai Benkler (Harvard Law School)
- Edge Networks and Devices for the Internet of Things by Peter T. Kirstein (University College London)
- Reassembling Our Digital Selves by Deborah Estrin (Cornell Tech and Weill Cornell Medical College) and Ari Juels (Cornell Tech)
- Choices: Privacy and Surveillance in a Once and Future Internet by Susan Landau (Worcester Polytechnic Institute)
- As Pirates Become CEOs: The Closing of the Open Internet by Zeynep Tufekci (University of North Carolina at Chapel Hill)
- Design Choices for Libraries in the Digital-Plus Era by John Palfrey (Phillips Academy)…(More)
See also: Introduction
Developing Global Norms for Sharing Data and Results during Public Health Emergencies
Paper by Kayvon Modjarrad et al in PLOS Med: “…When a new or re-emergent pathogen causes a major outbreak, rapid access to both raw and analysed data or other pertinent research findings becomes critical to developing a rapid and effective public health response. Without the timely exchange of information on clinical, epidemiologic, and molecular features of an infectious disease, informed decisions about appropriate responses cannot be made, particularly those that relate to fielding new interventions or adapting existing ones. Failure to share information in a timely manner can have disastrous public health consequences, leading to unnecessary suffering and death. The 2014–2015 Ebola epidemic in West Africa revealed both successful practices and important deficiencies within existing mechanisms for information sharing. For example, trials of two Ebola vaccine candidates (ChAd3-ZEBOV and rVSV-ZEBOV) benefited greatly from an open collaboration between investigators and institutions in Africa, Europe, and North America . These teams, coordinated by the WHO, were able to generate and exchange critical data for the development of urgently needed, novel vaccines along faster timelines than have ever before been achieved. Similarly, some members of the genome sequencing community made viral sequence data publicly available within days of accessing samples , thus adhering to their profession’s long-established principles of rapid, public release of sequence data in any setting. In contrast, the dissemination of surveillance data early in the epidemic was comparatively slow, and in some cases, the criteria for sharing were unclear.
In recognition of the need to streamline mechanisms of data dissemination—globally and in as close to real-time as possible—the WHO held a consultation in Geneva, Switzerland, on 1–2 September 2015 to advance the development of data sharing norms, specifically in the context of public health emergencies….
preservation of global health requires prioritization of and support for international collaboration. These and other principles were affirmed at the consultation (Table 1) and codified into a consensus statement that was published on the WHO website immediately following the meeting (http://www.who.int/medicines/ebola-treatment/data-sharing_phe/en/). A more comprehensive set of principles and action items was made available in November 2015, including the consensus statement made by the editorial staff of journals that attended the meeting (http://www.who.int/medicines/ebola-treatment/blueprint_phe_data-share-results/en/). The success of prior initiatives to accelerate timelines for reporting clinical trial results has helped build momentum for a broader data sharing agenda. As the quick and transparent dissemination of information is the bedrock of good science and public health practice, it is important that the current trends in data sharing carry over to all matters of acute public health need. Such a global norm would advance the spirit of open collaboration, simplify current mechanisms of information sharing, and potentially save many lives in subsequent outbreaks….(More)”
The Power of the Nudge to Change Our Energy Future
Sebastian Berger in the Scientific American: “More than ever, psychology has become influential not only in explaining human behavior, but also as a resource for policy makers to achieve goals related to health, well-being, or sustainability. For example, President Obama signed an executive order directing the government to systematically use behavioral science insights to “better serve the American people.” Not alone in this endeavor, many governments – including the UK, Germany, Denmark, or Australia – are turning to the insights that most frequently stem from psychological researchers, but also include insights from behavioral economics, sociology, or anthropology.
Particularly relevant are the analysis and the setting of “default-options.” A default is the option that a decision maker receives if he or she does not specifically state otherwise. Are we automatically enrolled in a 401(k), are we organ donors by default, or is the flu-shot a standard that is routinely given to all citizens? Research has given us many examples of how and when defaults can promote public safety or wealth.
One of the most important questions facing the planet, however, is how to manage the transition into a carbon-free economy. In a recent paper, Felix Ebeling of the University of Cologne and I tested whether defaults could nudge consumers into choosing a green energy contract over one that relies on conventional energy. The results were striking: setting the default to green energy increased participation nearly tenfold. This is an important result because it tells us that subtle, non-coercive changes in the decision making environment are enough to show substantial differences in consumers’ preferences in the domain of clean energy. It changes green energy participation from “hardly anyone” to “almost everyone”. Merely within the domain of energy behavior, one can think of many applications where this finding can be applied: For instance, default engines of new cars could be set to hybrid and customers would need to actively switch to standard options. Standard temperatures of washing machines could be low, etc….(More)”
This Is How Visualizing Open Data Can Help Save Lives
Alexander Howard at the Huffington Post: “Cities are increasingly releasing data that they can use to make life better for their residents online — enabling journalists and researchers to better inform the public.
Los Angeles, for example, has analyzed data about injuries and deaths on its streets and published it online. Now people can check its conclusions and understand why LA’s public department prioritizes certain intersections.
The impact from these kinds of investments can lead directly to saving lives and preventing injuries. The work is part of a broader effort around the world to make cities safer.
Like New York City, San Francisco and Portland, Oregon, Los Angeles has adopted Sweden’s “Vision Zero” program as part of its strategy for eliminating traffic deaths. California led the nation in bicycle deaths in 2014.
At visionzero.lacity.org, you can see that the City of Los Angeles is using data visualization to identify the locations of “high injury networks,” or the 6 percent of intersections that account for 65 percent of the severe injuries in the area.
The work is the result of LA’s partnership with University of South California graduate students. As a result of these analyses, the Los Angeles Police Department has been cracking down on jaywalking near the University of Southern California.
Abhi Nemani, the former chief data officer for LA, explained why the city needed to “go back to school” for help.
“In resource-constrained environments — the environment most cities find themselves in these days — you often have to beg, borrow, and steal innovation; particularly so, when it comes to in-demand resources such as data science expertise,” he told the Huffington Post.
“That’s why in Los Angeles, we opted to lean on the community for support: both the growing local tech sector and the expansive academic base. The academic community, in particular, was eager to collaborate with the city. In fact, most — if not all — local institutions reached out to me at some point asking to partner on a data science project with their graduate students.”
The City of Los Angeles is now working with another member of its tech sector toeliminate traffic deaths. DataScience, based in Culver City, California, received $22 million dollars in funding in December to make predictive insights for customers.
“The City of Los Angeles is very data-driven,” DataScience CEO Ian Swanson told HuffPost. “I commend Mayor Eric Garcetti and the City of Los Angeles on the openness, transparency, and availability of city data initiatives, like Vision Zero, put the City of Los Angeles‘ data into action and improve life in this great city.”
DataScience created an interactive online map showing the locations of collisions involving bicycles across the city….(More)”
The Routledge Companion to Social Media and Politics
Book edited by Axel Bruns, Gunn Enli, Eli Skogerbo, Anders Olof Larsson, Christian Christensen: “Social media are now widely used for political protests, campaigns, and communication in developed and developing nations, but available research has not yet paid sufficient attention to experiences beyond the US and UK. This collection tackles this imbalance head-on, compiling cutting-edge research across six continents to provide a comprehensive, global, up-to-date review of recent political uses of social media.
Drawing together empirical analyses of the use of social media by political movements and in national and regional elections and referenda, The Routledge Companion to Social Media and Politics presents studies ranging from Anonymous and the Arab Spring to the Greek Aganaktismenoi, and from South Korean presidential elections to the Scottish independence referendum. The book is framed by a selection of keystone theoretical contributions, evaluating and updating existing frameworks for the social media age….(More)”
Privacy by design in big data
An overview of privacy enhancing technologies in the era of big data analytics by the European Union Agency for Network and Information Security (ENISA) : “The extensive collection and further processing of personal information in the context of big data analytics has given rise to serious privacy concerns, especially relating to wide scale electronic surveillance, profiling, and disclosure of private data. In order to allow for all the benefits of analytics without invading individuals’ private sphere, it is of utmost importance to draw the limits of big data processing and integrate the appropriate data protection safeguards in the core of the analytics value chain. ENISA, with the current report, aims at supporting this approach, taking the position that, with respect to the underlying legal obligations, the challenges of technology (for big data) should be addressed by the opportunities of technology (for privacy). To this end, in the present study we first explain the need to shift the discussion from “big data versus privacy” to “big data with privacy”, adopting the privacy and data protection principles as an essential value of big data, not only for the benefit of the individuals, but also for the very prosperity of big data analytics. In this respect, the concept of privacy by design is key in identifying the privacy requirements early at the big data analytics value chain and in subsequently implementing the necessary technical and organizational measures. Therefore, after an analysis of the proposed privacy by design strategies in the different phases of the big data value chain, we provide an overview of specific identified privacy enhancing technologies that we find of special interest for the current and future big data landscape. In particular, we discuss anonymization, the “traditional” analytics technique, the emerging area of encrypted search and privacy preserving computations, granular access control mechanisms, policy enforcement and accountability, as well as data provenance issues. Moreover, new transparency and access tools in big data are explored, together with techniques for user empowerment and control. Following the aforementioned work, one immediate conclusion that can be derived is that achieving “big data with privacy” is not an easy task and a lot of research and implementation is still needed. Yet, we find that this task can be possible, as long as all the involved stakeholders take the necessary steps to integrate privacy and data protection safeguards in the heart of big data, by design and by default. To this end, ENISA makes the following recommendations:
- Privacy by design applied …
- Decentralised versus centralised data analytics …
- Support and automation of policy enforcement
- Transparency and control….
- User awareness and promotion of PETs …
- A coherent approach towards privacy and big data ….(More)”
Privacy in Public Spaces: What Expectations of Privacy Do We Have in Social Media Intelligence?
Paper by Edwards, Lilian and Urquhart, Lachlan: “In this paper we give a basic introduction to the transition in contemporary surveillance from top down traditional police surveillance to profiling and “pre-crime” methods. We then review in more detail the rise of open source (OSINT) and social media (SOCMINT) intelligence and its use by law enforcement and security authorities. Following this we consider what if any privacy protection is currently given in UK law to SOCMINT. Given the largely negative response to the above question, we analyse what reasonable expectations of privacy there may be for users of public social media, with reference to existing case law on art 8 of the ECHR. Two factors are in particular argued to be supportive of a reasonable expectation of privacy in open public social media communications: first, the failure of many social network users to perceive the environment where they communicate as “public”; and secondly, the impact of search engines (and other automated analytics) on traditional conceptions of structured dossiers as most problematic for state surveillance. Lastly, we conclude that existing law does not provide adequate protection foropen SOCMINT and that this will be increasingly significant as more and more personal data is disclosed and collected in public without well-defined expectations of privacy….(More)”
Data Science ethics
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)”