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In this interview, Juliane Jarke and Teresa Cerratto Pargman discuss the implications of AI for the postdigital future(s) of education with Dan McQuillan. They start off with an introduction to the main ideas of Dan’s recent book (McQuillan 2022) and ask why we need to resist AI in education. Dan argues that the answer to the question is partly based on our understanding of education, what it means to us and how we imagine its future. He points to the harmful effects of AI and the narratives that perpetuate and boost its use in education and beyond. In the last part of the interview, Dan considers ways of resisting AI in education and sketches alternative educational futures. The interview took place end of March 2023 through an online video conference system and was subsequently transcribed and edited.

AI chatbots have recently fuelled debate regarding education practices in higher education institutions worldwide. Focusing on Generative AI and ChatGPT in particular, our study examines how AI chatbots impact university teachers' assessment practices, exploring teachers' perceptions about how ChatGPT performs in response to home examination prompts in undergraduate contexts. University teachers (n = 24) from four different departments in humanities and social sciences participated in Turing Test-inspired experiments, where they blindly assessed student and ChatGPT-written responses to home examination questions. Additionally, we conducted semi-structured interviews in focus groups with the same teachers examining their reflections about the quality of the texts they assessed. Regarding chatbot-generated texts, we found a passing rate range across the cohort (37.5 - 85.7%) and a chatbot-written suspicion range (14-23%). Regarding the student-written texts, we identified patterns of downgrading, suggesting that teachers were more critical when grading student-written texts. Drawing on post-phenomenology and mediation theory, we discuss AI chatbots as a potentially disruptive technology in higher education practices.

The design of civic tech is often confronted with impediments, barriers, and a lack of resources. These and other causes may lead to the discontinuation and even abandonment of initiatives. Since seemingly failed projects are much more difficult to publish as articles, this workshop will provide academics and practitioners with a rare opportunity to exchange experiences and insights on discontinued civic tech initiatives. The goal of the workshop is to develop a better understanding of why some civic tech initiatives fail and ask whether discontinued initiatives may still somehow contribute to social change and the growth of digital civics. A variety of sub-questions around discontinued civic tech will be addressed in the workshop, including matters of participation, citizen science, public management, power structures and biases, and communication.

theoretical and methodological approaches that have provided us with useful tools to see things differently and make space for change. Since its inception over a decade ago, feminist HCI has progressed from the margins to mainstream HCI, with numerous references in the literature. Feminist HCI has also evolved to incorporate other critical HCI practices such as Queer HCI, participatory design, and speculative design. While feminist approaches have grown in popularity and become mainstream, it is getting more difficult to distinguish the feminist emancipatory core from other attempts of developing and improving society in various ways. In this workshop, we therefore want to revisit our feminist roots, where theory is a liberatory and creative practice, motivated by affect, curiosity, and wonder. From this standpoint, we consider which of our feminist tools can make a significant difference today, in a highly datafied world. The goal of this workshop is to; 1) create an inventory of feminist theories and concepts that have had an impact on our work as designers, educators, researchers, and activists; 2) develop a feminist toolbox for the CSCW community to strengthen our feminist literacy.

Emerging automated-decision making (ADM) technologies invite scholars to engage with future points in time and contexts that have not yet arisen. This particular state of not knowing yet implies the methodological challenge of examining images of the future and how such images will materialize in practice. In this respect, we ask the following: what are appropriate research methods for studying emerging ADM technologies in education? How do researchers explore sociotechnical practices that are in the making? Guided by these questions, we investigate the increasing adoption of ADM in teachers’ assessment practices. This constitutes a case in point for reflecting on the research methods applied to address the future of assessment in education. In this context, we distinguish between representational methods oriented to recounting past experiences and future(s) methods oriented to making futures. Studying the literature on speculative methods in digital education, we illustrate four categories of future(s)-oriented methods and reflect on their characteristics through a backcasting workshop conducted with teachers. We conclude by discussing the need to reconsider the methodological choices made for studying emerging technologies in critical assessment practices and generate new knowledge on methods able to contribute to alternative imaginaries of automation in education.

Purpose - The purpose of this commentary is to comment on Fischer's et al. (2022) Design/methodology/approach - This commentary responds to Fischer's et al. (2022) call on envisioning alternate conceptualizations of learning for the digital era. In doing so, the author argues for reconsidering learning in its socio-material condition, situated and made of a web of social and technological relations. In this context, the author takes a relational lens on learning to interrogate taken-for-granted views of (1) personalizing data increasingly used for student learning, (2) emerging educational infrastructures for higher education and (3) the student–teacher relationship mediated by data and algorithms. Findings - In this commentary, the author suggested unpacking assumptions about learning that get reflected in the design and discourses about socio-technical arrangements and transformations in education. Taking the example of personalized learning, the author has illustrated a relational mode of thinking that leads the author to argue that, renewed definitions of learning must be discussed multidimensionally and, most importantly, situated in the material world that learning is already part of. Research limitations/implications - Following Fischer et al. (2022, this issue), the author agrees that the focus should be on finding “new ways of organizing learning by exploring opportunities for radically new conceptualizations and practices.” In order to do that it is of utmost importance to problematize the social and material conditions that actively configure learning today and infrastructure tomorrow's learning. Hopefully, these observations will entice others to discuss further the educational transformations at stake in the age of datafication and algorithmic decision-making. Originality/value - The author argues for reconsidering learning in its socio-material condition, which is situated and made of a web of social and technological relations. In this context, the au

Privacy is one of the key challenges to the adoption and implementation of online proctoring systems (OPS) in higher education. To better understand this challenge, we adopt privacy as contextual integrity theory to conduct a scoping review of 17 papers. The results show different types of students’ personal and sensitive information are collected and disseminated; this raises considerable privacy concerns. As well as the governing principles including transparency and fairness, consent and choice, information minimization, accountability, and information security and accuracy have been identified to address privacy problems. This study notifies a need to clarify how these principles should be implemented and sustained, and what privacy concerns and actors they relate to. Further, it calls for the need to clarify the responsibility of key actors in enacting and sustaining responsible adoption and use of OPS in higher education.

The focus of ethics in learning analytics (LA) frameworks and guidelines is predominantly on procedural elements of data management and accountability. Another, less represented focus is on the duty to act and LA as a moral practice. Data feminism as a critical theoretical approach to data science practices may offer LA research and practitioners a valuable lens through which to consider LA as a moral practice. This paper examines what data feminism can offer the LA community. It identifies critical questions for further developing and enabling a responsible stance in LA research and practice taking one particular case — algorithmic decision-making — as a point of departure.

This paper engages with the meanings and practices of digital sovereignty that four social collectives are building and enacting in Latin America. Through a qualitative methodological approach based on semi-structured interviews with founding members of the selected collectives, we sought to know how they conceive and carry out activities of digital sovereignty on a daily basis. Among the research findings, the identification of five articulating axes in the work of these organizations stands out, namely: 1) conception / proposal of particular digital sovereignty; 2.) ways to achieve/achieve digital sovereignty; 3.) criticism and resignification in the ways of making digital sovereignty; 4.) agents involved and 5.) relationship with other groups and/ or organizations interested in digital sovereignty., Este artículo analiza los significados y prácticas sobresoberanía digital quecuatro colectivos sociales están construyendo en América Latina. A través de unaaproximación metodológica cualitativa basada en entrevistas semiestructuradasa fundadores de los colectivos seleccionados se buscó conocer cómo conciben yrealizan cotidianamente actividades desoberanía digital. Entre los hallazgos dela investigación se destacan la identificación de cinco ejes articuladores en eltrabajo de estas organizaciones, a saber: 1) concepción/propuesta de soberaníadigital particular; 2.) vías para alcanzar/hacer la soberanía digital; 3.) crítica yresignificación en los modos de hacer soberanía digital; 4.) agentes involucradosy 5.) relación con otros colectivos y/o organizaciones interesadas en la soberaníadigital., Este artigo analisa os significados e práticas sobre a soberania digital quequatro grupos sociais estão construindo na América Latina. Por meio de umaabordagem metodológica qualitativa baseada em entrevistas semiestruturadascom os membros fundadores dos grupos selecionados, buscou-se saber comoeles concebem e realizam atividades de soberania digital no cotidiano. Dentreos achados da pesquisa, destaca-se a identificação de cinco eixos articuladoresna atuação dessas organizações, a saber: 1) concepção / proposição de particularsoberania digital; 2.) formas de alcançar / alcançar a soberania digital; 3.) críticae ressignificação nas formas de fazer soberania digital; 4.) agentes envolvidose 5.) relacionamento com outros grupos e / ou organizações interessadas nasoberania digital.

The increasing use of Artificial Intelligence (AI) systems has sparked discussions regarding developing ethically responsible technology. Consequently, various organizations have released high-level AI ethics frameworks to assist in AI design. However, we still know too little about how AI ethics principles are perceived and work in practice, especially in public organizations. This study examines how AI practitioners perceive ethical issues in their work concerning AI design and how they interpret and put them into practice. We conducted an empirical study consisting of semi-structured qualitative interviews with AI practitioners working in or for public organizations. Taking the lens provided by the “In-Action Ethics” framework and previous studies on ethical tensions, we analyzed practitioners’ interpretations of AI ethics principles and their application in practice. We found tensions between practitioners’ interpretation of ethical principles in their work and ‘ethos tensions.’ In this vein, we argue that understanding the different tensions that can occur in practice and how they are tackled is key to studying ethics in practice. Understanding how AI practitioners perceive and apply ethical principles is necessary for practical ethics to contribute toward an empirically grounded, Responsible AI.