Paper by Daxton Stewart: “In the early weeks of the new presidential administration, White House staffers were communicating among themselves and leaking to journalists using apps such as Signal and Confide, which allow users to encrypt messages or to make them vanish after being received. By using these apps, government officials are “going dark” by avoiding detection of their communications in a way that undercuts freedom of information laws. In this paper, the author explores the challenges presented by encrypted and ephemeral messaging apps when used by government employees, examining three policy approaches – banning use of the apps, enhancing existing archiving and record-keeping practices, or legislatively expanding quasi-government body definitions – as potential ways to manage the threat to open records laws these “killer apps” present….(More)”.
Digital Participation in an Open Innovation Platform : An Empirical Study on Smart Cities
Paper by J. Ojasalo and L. Tähtinen as part of the INTED2017 Proceedings: “The purpose of this paper is to increase knowledge of participation in collaborative innovation of cities with digital channels, as well as propose a model of digital participation system in an open innovation platform of a city. There is very little knowledge of this area is available in the existing research literature. This paper empirically addresses this knowledge gap and contributes to the literature on digital participation in collaborative innovation, innovation intermediaries and platforms, as well as urban development and Smart City literature. The results of this study have also clear practical implications particularly to urban policy makers and developers, companies and third sector organization collaborating with cities, as well as educators in the field of innovation and urban development. The empirical research method is qualitative and draws on data from in-depth interviews and co-creative multi-actor workshops. As the result, it proposes a model which shows the main methods of digital participation in an open innovation platform, namely information dissemination, actor recruitment, and idea generation, explains their nature….(More)”
Societal impacts of big data: challenges and opportunities in Europe
Martí Cuquet, Guillermo Vega-Gorgojo, Hans Lammerant, Rachel Finn, Umair ul Hassan at ArXiv: “This paper presents the risks and opportunities of big data and the potential social benefits it can bring. The research is based on an analysis of the societal impacts observed in a set of six case studies across different European sectors. These impacts are divided into economic, social and ethical, legal and political impacts, and affect areas such as improved efficiency, innovation and decision making, changing business models, dependency on public funding, participation, equality, discrimination and trust, data protection and intellectual property rights, private and public tensions and losing control to actors abroad. A special focus is given to the risks and opportunities coming from the legal framework and how to counter the negative impacts of big data. Recommendations are presented for four specific legal frameworks: copyright and database protection, protection of trade secrets, privacy and data protection and anti-discrimination. In addition, the potential social benefits of big data are exemplified in six domains: improved decision making and event detection; data-driven innovations and new business models; direct social, environmental and other citizen benefits; citizen participation, transparency and public trust; privacy-aware data practices; and big data for identifying discrimination. Several best practices are suggested to capture these benefits…(More)”.
Bigger data, less wisdom: the need for more inclusive collective intelligence in social service provision
Social service organizations have long used data in their efforts to support people in need for the purposes of advocacy, tracking, and intervention. Increasingly, such organizations are joining forces to provide wrap-around services to clients in order to “move the needle” on intractable social problems. Groups using these strategies, called Collective Impact, develop shared metrics to guide their work, sharing data, finances, infrastructure, and services. A major emphasis of these efforts is on tracking clients and measuring impacts. This study explores a particular type of Collective Impact strategy called Promise Neighborhoods. Based on a federal grant program, these initiatives attempt to close the achievement gap in particular geographic communities. Through an analysis of publicly available documents and information, the study analyzes the ways these strategies enact (and fail to enact) a collective intelligence for the common good. The analysis focuses specifically on issues surrounding data collection and use, youth agency, leadership and governance, and funding streams. Together, these foci develop a story of an increasingly used “intelligence” with a limited sense of “collective” and a narrow vision of a “common good.” Using this as a platform, the paper explores alternatives that might develop more robust practices around these concepts….(More)”.
Hackathons, entrepreneurship and the passionate making of smart cities
A Programmable City Working Paper by Sung-Yueh Perng, Rob Kitchin and Darach Mac Donncha: “Hackathons – quick prototyping events for commercial purposes – have become an important means to foster innovation, entrepreneurship and the start-up economy in smart cities. Smart and entrepreneurial cities have been critiqued with respect to the neoliberalization of governance and statecraft. We consider the passions, inventions and imitations in the assemblage of practices – alongside neoliberalizing and capitalist operations – that shape the economy and governance of smart cities. The paper examines hackathons as tech events that extend the passions for digital innovation and entrepreneurship and act as sites of social learning for the development of smart urbanism. We argue that passionate and imitative practices energize the desire and belief in entrepreneurial life and technocratic governance, and also engender precarious, ambiguous and uncertain future for participants and prototypes…(More)”.
Online Field Experiments: Studying Social Interactions in Context
Paper by Paolo Parigi, Jessica J. Santana and Karen S. Cook in Social Psychology Quarterly: “Thanks to the Internet and the related availability of “Big Data,” social interactions and their environmental context can now be studied experimentally. In this article, we discuss a methodology that we term the online field experiment to differentiate it from more traditional lab-based experimental designs. We explain how this experimental method can be used to capture theoretically relevant environmental conditions while also maximizing the researcher’s control over the treatment(s) of interest. We argue that this methodology is particularly well suited for social psychology because of its focus on social interactions and the factors that influence the nature and structure of these interactions. We provide one detailed example of an online field experiment used to investigate the impact of the sharing economy on trust behavior. We argue that we are fundamentally living in a new social world in which the Internet mediates a growing number of our social interactions. These highly prevalent forms of social interaction create opportunities for the development of new research designs that allow us to advance our theories of social interaction and social structure with new data sources….(More)”.
Openness as social praxis
Matthew Longshore Smith and Ruhiya Seward in First Monday: “Since the early 2000s, there has been an explosion in the usage of the term open, arguably stemming from the advent of networked technologies — including the Internet and mobile technologies. ‘Openness’ seems to be everywhere, and takes many forms: from open knowledge, open education, open data and open science, to open Internet, open medical records systems and open innovation. These applications of openness are having a profound, and sometimes transformative, effect on social, political and economic life.
This explosion of the use of the term has led to multiple interpretations, ambiguities, and even misunderstandings, not to mention countless debates and disagreements over precise definitions. The paper “Fifty shades of open” by Pomerantz and Peek (2016) highlighted the increasing ambiguity and even confusion surrounding this term. This article builds on Pomerantz and Peek’s attempt to disambiguate the term by offering an alternative understanding to openness — that of social praxis. More specifically, our framing can be broken down into three social processes: open production, open distribution, and open consumption. Each process shares two traits that make them open: you don’t have to pay (free price), and anyone can participate (non-discrimination) in these processes.
We argue that conceptualizing openness as social praxis offers several benefits. First, it provides a way out of a variety of problems that result from ambiguities and misunderstandings that emerge from the current multitude of uses of openness. Second, it provides a contextually sensitive understanding of openness that allows space for the many different ways openness is experienced — often very different from the way that more formal definitions conceptualize it. Third, it points us towards an approach to developing practice-specific theory that we believe helps us build generalizable knowledge on what works (or not), for whom, and in what contexts….(More)”.
A Data-driven Approach to Assess the Potential of Smart Cities: The Case of Open Data for Brussels Capital Region
Paper by Miguel Angel Gomez Zotano and Hugues Bersini in Energy Procedia: “The success of smart city projects is intrinsically related to the existence of large volumes of data that could be processed to achieve their objectives. For this purpose, the plethora of data stored by public administrations becomes an incredibly rich source of insight and information due to its volume and diversity. However, it was only with the Open Government Movement when governments have been concerned with the need to open their data to citizens and businesses. Thus, with the emergence of open data portals, these myriad of data enables the development of new business models. The achievement of the benefits sought by making this data available triggers new challenges to cope with the diversity of sources involved. The business potential could be jeopardized by the scarcity of relevant data in the different blocks and domains that makes a city and by the lack of a common approach to data publication, in terms of format, content, etc.
This paper introduces a holistic approach that relies on the Smart City Ontology as the cornerstone to standardise and structure data. This approach, which is proposed to be an analytical tool to assess the potential of data in a given smart city, analyses three main aspects: availability of data, the criteria that data should fulfil to be considered eligible and the model used to structure and organise data. The approach has been applied to the case of Brussels Capital Region, which first results are presented and discussed in this paper. The main conclusion that has been obtained is that, besides its commitment with open data and smart cities, Brussels is not mature enough to fully exploit the real intelligence that smart cities could provide. This maturity would be achieved in the following years with the implementation of the new Brussels’ Smart City Strategy…(More)”.
Access to New Data Sources for Statistics: Business Models and Incentives for the Corporate Sector
Report by Thilo Klein and Stefaan Verhulst: “New data sources, commonly referred to as “Big Data”, have attracted growing interest from National Statistical Institutes. They have the potential to complement official and more conventional statistics used, for instance, to determine progress towards the Sustainable Development Goals (SDGs) and other targets. However, it is often assumed that this type of data is readily available, which is not necessarily the case. This paper examines legal requirements and business incentives to obtain agreement on private data access, and more generally ways to facilitate the use of Big Data for statistical purposes. Using practical cases, the paper analyses the suitability of five generic data access models for different data sources and data uses in an emerging new data ecosystem. Concrete recommendations for policy action are presented in the conclusions….(More)”.
Will Computer Science become a Social Science?
Paper by Ingo Scholtes, Markus Strohmaier and Frank Schweitzer: “When Tay – a Twitter chatbot developed by Microsoft – was activated this March, the company was taken by surprise by what Tay had become. Within less than 24 hours of conversation with Twitter users Tay had learned to make racist, anti-semitic and misogynistic statements that have raised eyebrows in the Twitter community and beyond. What had happened? While Microsoft certainly tested the chat bot before release, planning for the reactions and the social environment in which it was deployed proved tremendously difficult. Yet, the Tay Twitter chatbot incident is just one example for the many challenges which arise when embedding algorithms and computing systems into an ever increasing spectrum of social systems. In this viewpoint we argue that, due to the resulting feedback loops by which computing technologies impact social behavior and social behavior feeds back on (learning) computing systems, we face the risk of losing control over the systems that we engineer. The result are unintended consequences that affect both the technical and social dimension of computing systems, and which computer science is currently not well-prepared to address. Highlighting exemplary challenges in core areas like (1) algorithm design, (2) cyber-physical systems, and (3) software engineering, we argue that social aspects must be turned into first-class citizens of our system models. We further highlight that the social sciences, in particular the interdisciplinary field of Computational Social Science [1], provide us with means to quantitatively analyze, model and predict human behavior. As such, a closer integration between computer science and social sciences not only provides social scientists with new ways to understand social phenomena. It also helps us to regain control over the systems that we engineer….(More)”