Marijn Janssen and Natalie Helbig in Government Information Quarterly: “Many policy-makers are struggling to understand participatory governance in the midst of technological changes. Advances in information and communication technologies (ICTs) continue to have an impact on the ways that policy-makers and citizens engage with each other throughout the policy-making process. A set of developments in the areas of opening government data, advanced analytics, visualization, simulation, and gaming, and ubiquitous citizen access using mobile and personalized applications is shaping the interactions between policy-makers and citizens. Yet the impact of these developments on the policy-makers is unclear. The changing roles and need for new capabilities required from the government are analyzed in this paper using two case studies. Salient new roles for policy-makers are outlined focused on orchestrating the policy-making process. Research directions are identified including understand the behavior of users, aggregating and analyzing content from scattered resources, and the effective use of the new tools. Understanding new policy-makers roles will help to bridge the gap between the potential of tools and technologies and the organizational realities and political contexts. We argue that many examples are available that enable learning from others, in both directions, developed countries experiences are useful for developing countries and experiences from the latter are valuable for the former countries…(More)”
Collective Intelligence in Law Reforms: When the Logic of the Crowds and the Logic of Policymaking Collide
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)”
Privacy, security and data protection in smart cities: a critical EU law perspective
CREATe Working Paper by Lilian Edwards: “Smart cities” are a buzzword of the moment. Although legal interest is growing, most academic responses at least in the EU, are still from the technological, urban studies, environmental and sociological rather than legal, sectors2 and have primarily laid emphasis on the social, urban, policing and environmental benefits of smart cities, rather than their challenges, in often a rather uncritical fashion3 . However a growing backlash from the privacy and surveillance sectors warns of the potential threat to personal privacy posed by smart cities . A key issue is the lack of opportunity in an ambient or smart city environment for the giving of meaningful consent to processing of personal data; other crucial issues include the degree to which smart cities collect private data from inevitable public interactions, the “privatisation” of ownership of both infrastructure and data, the repurposing of “big data” drawn from IoT in smart cities and the storage of that data in the Cloud.
This paper, drawing on author engagement with smart city development in Glasgow as well as the results of an international conference in the area curated by the author, argues that smart cities combine the three greatest current threats to personal privacy, with which regulation has so far failed to deal effectively; the Internet of Things(IoT) or “ubiquitous computing”; “Big Data” ; and the Cloud. While these three phenomena have been examined extensively in much privacy literature (particularly the last two), both in the US and EU, the combination is under-explored. Furthermore, US legal literature and solutions (if any) are not simply transferable to the EU because of the US’s lack of an omnibus data protection (DP) law. I will discuss how and if EU DP law controls possible threats to personal privacy from smart cities and suggest further research on two possible solutions: one, a mandatory holistic privacy impact assessment (PIA) exercise for smart cities: two, code solutions for flagging the need for, and consequences of, giving consent to collection of data in ambient environments….(More)
A Taxonomy of Open Government Data Research Areas and Topics
Paper by Yannis Charalabidis, Charalampos Alexopoulos & Euripidis Loukis in the Journal of Organizational Computing and Electronic Commerce: “The opening of government data, in order to have both social and economic value generated from them, has attracted the attention and interest of both researchers and practitioners from various disciplines, such as information systems, management sciences, political and social sciences, and law. Despite the rapid growth of this multidisciplinary research domain, which has led to the emergence and continuous evolution of technologies and management approaches for open government data (OGD), a detailed analysis of the specific areas and topics of this research is still missing. In this paper, a detailed taxonomy of research areas and corresponding research topics of the OGD domain is presented: it includes four main research areas (ODG management & policies, infrastructures, interoperability and usage & value), which are further analysed into 35 research topics. An important advantage of this taxonomy, beyond its high level of detail, is that it has been developed through extraction and combination of relevant knowledge from three different kinds of sources: important relevant government policy documents, research literature, and experts. For each of the 35 research topics we have identified, its research literature is summarized and main research objectives and directions are highlighted. Based on the above taxonomy, an extension of the extant OGD lifecycle is advanced; also, under-researched topics that require further research are identified….(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
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)”
Digilantism: An Analysis of Crowdsourcing and the Boston Marathon Bombings
Paper by Johnny Nhan et al: “This paper explores the aftermath of the Boston Marathon bombing incident and how members of the general public, through the online community Reddit, attempted to provide assistance to law enforcement through conducting their own parallel investigations. As we document through an analysis of user posts, Reddit members shared information about the investigation, searched for information that would identify the perpetrators and, in some cases, drew on their own expert knowledge to uncover clues concerning key aspects of the attack. Although it is the case that the Reddit cyber-sleuths’ did not ultimately solve this case, or provide significant assistance to the police investigation, their actions suggest the potential role the public could play within security networks….(More)”
Stretching science: why emotional intelligence is key to tackling climate change
Faith Kearns at the Conversation: “…some environmental challenges are increasingly taking on characteristics of intractable conflicts, which may remain unresolved despite good faith efforts.
In the case of climate change, conflicts ranging from debates over how to lower emissions to denialism are obvious and ongoing -– the science community has often approached them as something to be defeated or ignored.
While some people love it and others hate it, conflict is often an indicator that something important is happening; we generally don’t fight about things we don’t care about.
Working with conflict is a challenging proposition, in part because while it manifests in interactions with others, much of the real effort comes in dealing with our own internal conflicts.
However, beginning to accept and even value conflict as a necessary part of large-scale societal transformation has the potential to generate new approaches to climate change engagement. For example, understanding that in some cases denial by another person is protective may lead to new approaches to engagement.
As we connect more deeply with conflict, we may come to see it not as a flame to be fanned or put out, but as a resource.
A relational approach to climate change
Indeed, because of the emotion and conflict involved, the concept of a relational approach is one that offers a great deal of promise in the climate change arena. It is, however, vastly underexplored.
Relationship-centered approaches have been taken up in law, medicine, and psychology.
A common thread among these fields is a shift from expert-driven to more collaborative modes of working together. Navigating the personal and emotional elements of this kind of work asks quite a bit more of practitioners than subject-matter expertise.
In medicine, for example, relationship-centered care is a framework examining how relationships – between patients and clinicians, among clinicians, and even with broader communities – impact health care. It recognizes that care may go well beyond technical competency.
This kind of framework can demonstrate how a relational approach is different from more colloquial understandings of relationships; it can be a way to intentionally and transparently attend to conflict and power dynamics as they arise.
Although this is a simplified view of relational work, many would argue that an emphasis on emergent and transformative properties of relationships has been revolutionary. And one of the key challenges, and opportunities, of a relationship-centered approach to climate work is that we truly have no idea what the outcomes will be.
We have long tried to motivate action around climate change by decreasing scientific uncertainty, so introducing social uncertainty feels risky. At the same time it can be a relief because, in working together, nobody has to have the answer.
Learning to be comfortable with discomfort
A relational approach to climate change may sound basic to some, and complicated to others. In either case, it can be useful to know there is evidence that skillful relational capacity can be taught and learned.
The medical and legal communities have been developing relationship-centered training for years.
It is clear that relational skills and capacities like conflict resolution, empathy, and compassion can be enhanced through practices including active listening and self-reflection. Although it may seem an odd fit, climate change invites ability to work together in new ways that include acknowledging and working with the strong emotions involved.
With a relationship-centered approach, climate change issues become less about particular solutions, and more about transforming how we work together. It is both risky and revolutionary in that it asks us to take a giant leap into trusting not just scientific information, but each other….(More)”
Opening up government data for public benefit
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)
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)”