Paper by Miguel Arana-Catania, Felix-Anselm van Lier and Rob Procter: “Today’s conflicts are becoming increasingly complex, fluid, and fragmented, often involving a host of national and international actors with multiple and often divergent interests. This development poses significant challenges for conflict mediation, as mediators struggle to make sense of conflict dynamics, such as the range of conflict parties and the evolution of their political positions, the distinction between relevant and less relevant actors in peace-making, or the identification of key conflict issues and their interdependence. International peace efforts appear ill-equipped to successfully address these challenges. While technology is already being experimented with and used in a range of conflict related fields, such as conflict predicting or information gathering, less attention has been given to how technology can contribute to conflict mediation. This case study contributes to emerging research on the use of state-of-the-art machine learning technologies and techniques in conflict mediation processes. Using dialogue transcripts from peace negotiations in Yemen, this study shows how machine-learning can effectively support mediating teams by providing them with tools for knowledge management, extraction and conflict analysis. Apart from illustrating the potential of machine learning tools in conflict mediation, the article also emphasizes the importance of interdisciplinary and participatory, cocreation methodology for the development of context-sensitive and targeted tools and to ensure meaningful and responsible implementation…(More)”.
Towards an international data governance framework
Paper by Steve MacFeely et al: “The CCSA argued that a Global Data Compact (GDC) could provide a framework to ensure that data are safeguarded as a global public good and as a resource to achieve equitable and sustainable development. This compact, by promoting common objectives, would help avoid fragmentation where each country or region adopts their own approach to data collection, storage, and use. A coordinated approach would give individuals and enterprises confidence that data relevant to them carries protections and obligations no matter where they are collected or used…
The universal principles and standards should set out the elements of responsible and ethical handling and sharing of data and data products. The compact should also move beyond simply establishing ethical principles and create a global architecture that includes standards and incentives for compliance. Such an architecture could be the foundation for rethinking the data economy, promoting open data, encouraging data exchange, fostering innovation and facilitating international trade. It should build upon the existing canon of international human rights and other conventions, laws and treaties that set out useful principles and compliance mechanisms.
Such a compact will require a new type of global architecture. Modern data ecosystems are not controlled by states alone, so any Compact, Geneva Convention, Commons, or Bretton Woods type agreement will require a multitude of stakeholders and signatories – states, civil society, and the private sector at the very least. This would be very different to any international agreement that currently exists. Therefore, to support a GDC, a new global institution or platform may be needed to bring together the many data communities and ecosystems, that comprise not only national governments, private sector and civil society but also participants in specific fields, such as artificial intelligence, digital and IT services. Participants would maintain and update data standards, oversee accountability frameworks, and support mechanisms to facilitate the exchange and responsible use of data. The proposed Global Digital Compact which has been proposed as part of Our Common Agenda will also need to address the challenges of bringing many different constituencies together and may point the way…(More)”
Quantum Computing
Introduction by Roman Rietsche: “Quantum computing promises to be the next disruptive technology, with numerous possible applications and implications for organizations and markets. Quantum computers exploit principles of quantum mechanics, such as superposition and entanglement, to represent data and perform operations on them. Both of these principles enable quantum computers to solve very specific, complex problems significantly faster than standard computers. Against this backdrop, this fundamental gives a brief overview of the three layers of a quantum computer: hardware, system software, and application layer. Furthermore, we introduce potential application areas of quantum computing and possible research directions for the field of information systems…(More)”.
Co-Producing Sustainability Research with Citizens: Empirical Insights from Co-Produced Problem Frames with Randomly Selected Citizens
Paper by Mareike Blum: “In sustainability research, knowledge co-production can play a supportive role at the science-policy interface (Norström et al., 2020). However, so far most projects involved stakeholders in order to produce ‘useful knowledge’ for policy-makers. As a novel approach, research projects have integrated randomly selected citizens during the knowledge co-production to make policy advice more reflective of societal perspectives and thereby increase its epistemic quality. Researchers are asked to consider citizens’ beliefs and values and integrate these in their ongoing research. This approach rests on pragmatist philosophy, according to which a joint deliberation on value priorities and anticipated consequences of policy options ideally allows to co-develop sustainable and legitimate policy pathways (Edenhofer & Kowarsch, 2015; Kowarsch, 2016). This paper scrutinizes three promises of involving citizens in the problem framing: (1) creating input legitimacy, (2) enabling social learning among citizens and researchers and (3) resulting in high epistemic quality of the co-produced knowledge. Based on empirical data the first phase of two research projects in Germany were analysed and compared: The Ariadne research project on the German Energy Transition, and the Biesenthal Forest project at the local level in Brandenburg, Germany. We found that despite barriers exist; learning was enabled by confronting researchers with problem perceptions of citizens. The step when researchers interpret and translate problem frames in the follow-up knowledge production is most important to assess learning and epistemic quality…(More)”.
The Public Good and Public Attitudes Toward Data Sharing Through IoT
Paper by Karen Mossberger, Seongkyung Cho and Pauline Cheong: “The Internet of Things has created a wealth of new data that is expected to deliver important benefits for IoT users and for society, including for the public good. Much of the literature has focused on data collection through individual adoption of IoT devices, and big data collection by companies with accompanying fears of data misuse. While citizens also increasingly produce data as they move about in public spaces, less is known about citizen support for data collection in smart city environments, or for data sharing for a variety of public-regarding purposes. Through a nationally representative survey of over 2,000 respondents as well as interviews, we explore the willingness of citizens to share their data with different parties and in various circumstances, using the contextual integrity framework, the literature on the ‘publicness’ of organizations, and public value creation. We describe the results of the survey across different uses, for data sharing from devices and for data collection in public spaces. We conduct multivariate regression to predict individual characteristics that influence attitudes toward use of IoT data for public purposes. Across different contexts, from half to 2/3 of survey respondents were willing to share data from their own IoT devices for public benefits, and 80-93% supported the use of sensors in public places for a variety of collective benefits. Yet government is less trusted with this data than other organizations with public purposes, such as universities, nonprofits and health care institutions. Trust in government, among other factors, was significantly related to data sharing and support for smart city data collection. Cultivating trust through transparent and responsible data stewardship will be important for future use of IoT data for public good…(More)”.
Trust Based Resolving of Conflicts for Collaborative Data Sharing in Online Social Networks
Paper by Nisha P. Shetty et al: “Twenty-first century, the era of Internet, social networking platforms like Facebook and Twitter play a predominant role in everybody’s life. Ever increasing adoption of gadgets such as mobile phones and tablets have made social media available all times. This recent surge in online interaction has made it imperative to have ample protection against privacy breaches to ensure a fine grained and a personalized data publishing online. Privacy concerns over communal data shared amongst multiple users are not properly addressed in most of the social media. The proposed work deals with effectively suggesting whether or not to grant access to the data which is co-owned by multiple users. Conflicts in such scenario are resolved by taking into consideration the privacy risk and confidentiality loss observed if the data is shared. For secure sharing of data, a trust framework based on the user’s interest and interaction parameters is put forth. The proposed work can be extended to any data sharing multiuser platform….(More)”.
Can Artificial Intelligence Improve Gender Equality? Evidence from a Natural Experiment
Paper by Zhengyang Bao and Difang Huang: “ Gender stereotypes and discriminatory practices in the education system are important reasons for women’s under-representation in many fields. How to create a gender-neutral learning environment when teachers’ gender composition and mindset are slow to change? Artificial intelligence (AI)’s recent development provides a way to achieve this goal. Engineers can make AI trainers appear gender neutral and not take gender-related information as input. We use data from a natural experiment where AI trainers replace some human teachers for a male-dominated strategic board game to test the effectiveness of such AI training. The introduction of AI improves boys’ and girls’ performance faster and reduces the pre-existing gender gap. Class recordings suggest that AI trainers’ gender-neutral emotional status can partly explain the improvement in gender quality. We provide the first evidence demonstrating AI’s potential to promote equality for society…(More)”.
Policy Choice and the Wisdom of Crowds
Paper by Nicholas Otis: “Using data from seven large-scale randomized experiments, I test whether crowds of academic experts can forecast the relative effectiveness of policy interventions. Eight-hundred and sixty-three academic experts provided 9,295 forecasts of the causal effects from these experiments, which span a diverse set of interventions (e.g., information provision, psychotherapy, soft-skills training), outcomes (e.g., consumption, COVID-19 vaccination, employment), and locations (Jordan, Kenya, Sweden, the United States). For each policy comparisons (a pair of policies and an outcome), I calculate the percent of crowd forecasts that correctly rank policies by their experimentally estimated treatment effects. While only 65% of individual experts identify which of two competing policies will have a larger causal effect, the average forecast from bootstrapped crowds of 30 experts identifies the better policy 86% of the time, or 92% when restricting analysis to pairs of policies who effects differ at the p < 0.10 level. Only 10 experts are needed to produce an 18-percentage point (27%) improvement in policy choice…(More)”.
Designing Digital Participatory Budgeting Platforms: Urban Biking Activism in Madrid
Paper by Maria Menendez-Blanco & Pernille Bjørn: “Civic technologies have the potential to support participation and influence decision-making in governmental processes. Digital participatory budgeting platforms are examples of civic technologies designed to support citizens in making proposals and allocating budgets. Investigating the empirical case of urban biking activists in Madrid, we explore how the design of the digital platform Decide Madrid impacted the collaborative practices involved in digital participatory budgeting. We found that the design of the platform made the interaction competitive, where individuals sought to gain votes for their single proposals, rather than consider the relations across proposals and the larger context of the city decisions, even if the institutional process rewarded collective support. In this way, the platforms’ design led to forms of individualistic, competitive, and static participation, therefore limiting the possibilities for empowering citizens in scoping and self-regulating participatory budgeting collaboratively. We argue that for digital participatory budgeting platforms to support cooperative engagements they must be revisable and reviewable while supporting accountability among participants and visibility of proposals and activities…(More)”.
Exhaustive or Exhausting? Evidence on Respondent Fatigue in Long Surveys
Paper by Dahyeon Jeong et al: “Living standards measurement surveys require sustained attention for several hours. We quantify survey fatigue by randomizing the order of questions in 2-3 hour-long in-person surveys. An additional hour of survey time increases the probability that a respondent skips a question by 10-64%. Because skips are more common, the total monetary value of aggregated categories such as assets or expenditures declines as the survey goes on, and this effect is sizeable for some categories: for example, an extra hour of survey time lowers food expenditures by 25%. We find similar effect sizes within phone surveys in which respondents were already familiar with questions, suggesting that cognitive burden may be a key driver of survey fatigue…(More)”.