Bots as Virtual Confederates: Design and Ethics

The use of bots as virtual confederates in online field experiments holds extreme promise as a new methodological tool in computational social science. However, this potential tool comes with inherent ethical challenges. Informed consent can be difficult to obtain in many cases, and the use of confederates necessarily implies the use of deception. In this work we outline a design space for bots as virtual confederates, and we propose a set of guidelines for meeting the status quo for ethical experimentation. We draw upon examples from prior work in the CSCW community and the broader social science literature for illustration. While a handful of prior researchers have used bots in online experimentation, our work is meant to inspire future work in this area and raise awareness of the associated ethical issues.Comment: Forthcoming in CSCW 201

Data Science for Social Good

Data science has been described as the fourth paradigm of scientific discovery. The latest wave of data science research, pertaining to machine learning and artificial intelligence (AI), is growing exponentially and garnering millions of annual citations. However, this growth has been accompanied by a diminishing emphasis on social good challenges—our analysis reveals that the proportion of data science research focusing on social good is less than it has ever been. At the same time, the proliferation of machine learning and generative AI has sparked debates about the sociotechnical prospects and challenges associated with data science for human flourishing, organizations, and society. Against this backdrop, we present a framework for “data science for social good” (DSSG) research that considers the interplay between relevant data science research genres, social good challenges, and different levels of sociotechnical abstraction. We perform an analysis of the literature to empirically demonstrate the paucity of work on DSSG in information systems (and other related disciplines) and highlight current impediments. We then use our proposed framework to introduce the articles appearing in the JAIS special issue on data science for social good. We hope that this editorial and the special issue will spur future DSSG research and help reverse the alarming trend across data science research over the past 30-plus years in which social good challenges are attracting proportionately less attention with each passing day

Does \u2018bigger\u2019mean \u2018better\u2019? Pitfalls and shortcuts associated with big data for social research

\u2018Big data is here to stay.\u2019 This key statement has a double value: is an assumption as well as the reason why a theoretical reflection is needed. Furthermore, Big data is something that is gaining visibility and success in social sciences even, overcoming the division between humanities and computer sciences. In this contribution some considerations on the presence and the certain persistence of Big data as a socio-technical assemblage will be outlined. Therefore, the intriguing opportunities for social research linked to such interaction between practices and technological development will be developed. However, despite a promissory rhetoric, fostered by several scholars since the birth of Big data as a labelled concept, some risks are just around the corner. The claims for the methodological power of bigger and bigger datasets, as well as increasing speed in analysis and data collection, are creating a real hype in social research. Peculiar attention is needed in order to avoid some pitfalls. These risks will be analysed for what concerns the validity of the research results \u2018obtained through Big data. After a pars distruens, this contribution will conclude with a pars construens; assuming the previous critiques, a mixed methods research design approach will be described as a general proposal with the objective of stimulating a debate on the integration of Big data in complex research projecting

The ethics of digital well-being: a multidisciplinary perspective

This chapter serves as an introduction to the edited collection of the same name, which includes chapters that explore digital well-being from a range of disciplinary perspectives, including philosophy, psychology, economics, health care, and education. The purpose of this introductory chapter is to provide a short primer on the different disciplinary approaches to the study of well-being. To supplement this primer, we also invited key experts from several disciplines—philosophy, psychology, public policy, and health care—to share their thoughts on what they believe are the most important open questions and ethical issues for the multi-disciplinary study of digital well-being. We also introduce and discuss several themes that we believe will be fundamental to the ongoing study of digital well-being: digital gratitude, automated interventions, and sustainable co-well-being

We are bitter, but we are better off: Case study of the implementation of an electronic health record system into a mental health hospital in England

In contrast to the acute hospital sector, there have been relatively few implementations of integrated electronic health record (EHR) systems into specialist mental health settings. The National Programme for Information Technology (NPfIT) in England was the most expensive IT-based transformation of public services ever undertaken, which aimed amongst other things, to implement integrated EHR systems into mental health hospitals. This paper describes the arrival, the process of implementation, stakeholders' experiences and the local consequences of the implementation of an EHR system into a mental health hospital

Multi-layered discourse shaping military AI: the cases of Germany and the UK

Artificial intelligence (AI) is being increasingly utilized by militaries across the globe, with major powers like the USA and China leading the way. Indeed, from the perspective of various realist theories, it can be expected that all countries with sufficient resources for developing military AI capabilities will do so. However, there are instances of countries with sufficient resources not showing any substantial military AI practices, defying realist expectations. This study proposes an alternative explanation to realist theories for the differences in the scope of military AI practices by states, arguing that ideational conditions like norms, ethics, and identity are decisive rather than structural pressures. To answer the research question “What explains difference in the scope of military AI practices by states?”, the study formulates a theoretical framework integrating Strategic Culture and Sociotechnical Imaginaries as a country’s deeper discourse layers within Ole Wæver’s multi-layered discourse analysis model. This framework is then applied within a most similar systems design, controlling for realist conditions and selecting Germany and the UK as case studies with differing dominant discourses on military AI. Thereafter, detailed discourse analysis on dominant discourses on military AI is conducted for both cases, and their scope of military AI practices is determined based on the number of military AI applications, expert assessments, and specific instructions, policies, and doctrines for military AI. Germany showed a cautious dominant discourse on military AI and a limited scope of military AI practices, while the UK showed an embracing dominant discourse on military AI and a comprehensive scope of military AI practices. Hence, the discourse- theoretical framework developed in this study offers an explanation superior to realist accounts and contributes to the literature on military and security studies more broadly by offering an innovative approach to studying general enabling technologies. It also has important policy implications for AI arms control and diplomacy