The increasing surveillance by big tech companies or/and governments has raised concerns about the democratic and participatory structure of the datafied society. Meanwhile, over the course of the past decade, various bottom-up civic tech and digital civic initiatives have emerged to tackle pressing local issues, such as air pollution and disaster response, often via technology-mediated data collection, curation, analysis, design and visualisations, thus promoting democratic participation. In this article, we discuss how these data are understood in diverse contexts beyond the realm of civic tech and digital civics. In doing so, we explore the potential and limits of civic data by exploring the intersections of and differences between civic data and adjacent data-related concepts often used by civic tech communities themselves: counterdata and open data. Through our discursive exploration of these three data concepts, we conclude that understanding is limited when it comes to determining which data are 'civic', and that discussion of questions related to power structures, diversity and inclusion and infrastructuring of civic data has been minimal.

Artificial intelligence (AI) chatbots trained on large language models are an example of generative AI which brings promises and threats to the higher education sector. In this study, we examine the emerging research area of AI chatbots in higher education (HE), focusing specifically on empirical studies conducted since the release of ChatGPT. Our review includes 23 research articles published between December 2022 and December 2023 exploring the use of AI chatbots in HE settings. We take a three-pronged approach to the empirical data. We first examine the state of the emerging field of AI chatbots in HE. Second, we identify the theories of learning used in the empirical studies on AI chatbots in HE. Third, we scrutinise the discourses of AI in HE framing the latest empirical work on AI chatbots. Our findings contribute to a better understanding of the eclectic state of the nascent research area of AI chatbots in HE, the lack of common conceptual groundings about human learning, and the presence of both dystopian and utopian discourses about the future role of AI chatbots in HE.

 Emerging AI technologies are changing teachers’ assessment practices and posing higher education institutions with novel ethical dilemmas. While frameworks and guidelines promise to align technology with moral and human values, the dilemma of how AI may impact existing valuing practices is often overlooked. To examine this gap, we conducted an interview study with university teachers from different disciplines at a university in Sweden. Following a semi-structured study design, we explored university teachers’ anticipations of AI in assessment and examined how emerging AI technologies may reconfigure the fit between values, challenges, and activities situated in everyday assessment contexts. Our findings suggest that anticipated AI, including automation and AI-mediated communication and grading, may amplify and reduce teachers’ possibilities to align activities with professional, pedagogical, and relational values and solve current challenges. In light of the study’s findings, the paper discusses potential ethical issues in the anticipated shifts from human to automated assessment and possible new and reinforced challenges brought by AI for education. 

The emergence of generative artificial intelligence (GAI) has given rise to diverse narratives about its transformative potential in higher education. Despite widespread speculation about how GAI might change teaching and learning, there is a significant gap in understanding how GAI artefacts are perceived in educational practices, particularly from the perspective of university teachers. This study investigates how GAI mediates teachers’ practices and reconfigures professional roles. Drawing on post-phenomenology and technological mediation theory, we focus on university teachers’ experiences and perceptions of GAI in higher education. Twenty-four university teachers participated in workshops involving assessment exercises with GAI-generated outputs, followed by focus group interviews discussing the challenges and opportunities posed by GAI. Findings reveal that GAI prompts teachers to reassess established practices, particularly in relation to assessment, while confronting ethical concerns regarding fairness, trust, and quality. Teachers described their initial engagement with GAI as transformative yet challenging, as they navigated uncertainties about their roles while prioritising students’ learning and development. By capturing teachers’ voices during this pivotal period, the study contributes to the growing body of research on AI's role in higher education and provides a nuanced understanding of its impact on teaching and learning.

The latest technical innovations in computing technologies and big data analytics have led the way for integrating Artificial Intelligence in Education (AIED), enabling the development and deployment of unprecedented tools and applications. Today, AI has firmly entered the public discourse on education, positioning itself as a transformative force poised to play an increasingly pivotal role in shaping the use of educational services across both K-12 and higher education contexts. AIED technologies in the form of chatbots, intelligent tutoring systems, automated grading systems, and other algorithmic facilitated decision support systems are expected to provide personalized guidance, support, and feedback to students and assist teachers and policymakers in decision-making in a wide range of formal educational contexts (Hwang et al., 2020). However, emerging research suggests that while the use of AI in educational contexts has the potential to support teaching and learning as well as improve human performance, to date, there seems to be little empirical work to support these claims (McGrath et al., 2024). At the same time, the misuse of AI due to algorithm bias and a lack of governance constitutes a risk, potentially inhibiting human rights and solidifying existing inequalities (Prinsloo, 2020; Yang et al., 2021). In this context, research on responsible AI in education underscores the need to integrate ethical considerations into AI literacy programs, equipping educators to evaluate tools based on fairness, accountability, and transparency principles, as well as frameworks that advocate for explainable and socially responsible AI (Floridi & Cowls, 2019), enabling educators to serve as ethical guardians in their adoption and use. However, responsibility regarding the use of AI in education also extends to the development of AIED systems, which may or may not align with fundamental human principles and values to safeguard human flourishing and well-being (Dignum, 2019). In this vein, reflecting on the meaning of responsible AI in education, its challenges and implications for education research and practice, prompts critical questions about autonomy, agency, and academic freedom in the age of AI and its role in contributing to equity in society (Cerratto-Pargman & McGrath, 2021; Macgilchrist, 2019; Nguyen et al., 2023; Prinsloo, 2020; Slade & Prinsloo, 2013; Velander et al., 2021; Williamson & Eynon, 2020).

Interested in emerging technologies in higher education, we look at AI chatbots through the lens of human–technology mediations. We argue for shifting the focus from what higher education can do with AI chatbots to why AI chatbots are compelling for higher education’s raison-d’être. We call for a critical debate examining the power of AI chatbots in configuring students as civic actors in an increasingly complex and digitalized society. We welcome a continuous and rigorous examination of generative AI chatbots and their impact on teaching practices and student learning in higher education.

Designing technology for education is never only a problem-solving practice. It is always already about creating spaces for inherently political and affective sociotechnical future relations (Light and Akama 2014). These can point towards ‘big futures’, i.e. radical ruptures and epochal change, or ‘little futures’, emergent processes in mundane, everyday practices (Michael 2017; Pink et al. 2022). Beginning with these assumptions, this commentary identifies key issues for concern at the nexus of futures, education, and design in the postdigital condition, in which digital technologies are embedded throughout educational spaces, but no longer conceived as a panacea for socio-economic-ecological ills. Instead, power relations and tensions lie at the heart of assumptions about designing futures. In the midst of the inequitable ‘planetary ruins’ in which we now live, learn, and teach (Tsing et al. 2017), we need new narratives about the future (Facer 2019).

Exploring these old and new narratives, this commentary suggests that practitioners, researchers, and others impacted by sociotechnical systems need to design futures and think about how to design futures that matter to them; otherwise, they (we) hand over design decisions to dominant actors. These design decisions impact not only technicalities, but also how education — and thus the future — will be configured. Yet there is no unanimous understanding of what ‘good design’ or a ‘desirable future’ looks like. As soon as ‘we’ begin to design, tensions and struggles unfold. This commentary fundamentally questions whether educational futures can be designed at all, given that education is inherently uncertain and beautifully risky (Biesta 2013). Tangled up in our own contradictions, we (the authors of this commentary) simultaneously question a sense of design optimism while also optimistically designing educational interventions and research.

Against this background, this commentary highlights three issues: (1) What possibilities emerge from decentring an engineering approach to designing postdigital futures? We explore alternative approaches to design that avoid the engineering logic predominant in education today. (2) What drives innovation in design? Drawing on feminist approaches to innovation, we reflect on the role of care in postdigital futures and extend care to a damaged planet. (3) Where are the limits of design in education? A critique of design practices means turning critical analysis onto the very concept of design and interrogating the limits of design.

Overall, the commentary illustrates how ‘design’ is contested today, with significant implications for the future. Far from a solutionist Silicon Valley approach to designing digital futures, we flag a ‘postdigital’ design that assumes — as does postdigital research more broadly (Jandrić et al. 2018; Knox 2019; Macgilchrist 2021) — that realities are messy, muddy, noisy; that nothing is purely, smoothly digital; and that the very idea of ‘designing futures’ signals how design is entangled with epistemological and ontological groundings, with political and affective relations, with historical legacies of exclusion and oppression, and with sociomaterial and planetary impact.