Cathal Doyle

Information Systems calls itself a science. It publishes in journals, conducts peer review, applies methods, builds on prior work, and claims relevance to practice. But publication is not knowledge, peer review is not verification, method is not scrutiny, citation is not cumulativeness, and implications for practice are not consequence. I argue that IS has confused the products of research with the practices of science, building an extensive publication system without building a checking system that would make its outputs scientific. Drawing on the philosophy of science, I show that IS research fails to meet the conditions its own claims require: that findings can be checked, corrected, built upon, and used by the people the research claims to inform. The result is an epistemic crisis — a largely unverified literature whose reliability we cannot assess because we never built the means to check it. Viva la IS Revolution.

The Information Systems research discipline claims to build a cumulative Knowledge Base to inform practice, yet it is organised around a closed loop of self-referential simulation. We diagnose this state as hypernormalisation-a late-Soviet condition in which official rituals are meticulously performed despite a widespread recognition that they no longer map reliably onto lived reality. We identify four escalating mechanisms that sustain this institutional order: the Simulation of Accumulation, in which the journal article functions as a proof-of-work token; the Simulation of Relevance, in which "Implications for Practice" operate as rituals of displacement; the Simulation of Problem Solving, in which Design Science Research produces perpetual prototypes; and the Simulation of the Scholar, in which researchers inhabit a split subjectivity (Living Vnye). We argue that Generative Artificial Intelligence (GenAI) constitutes the discipline's Glasnost moment. By automating the generation of methodologically fluent, theoretically compliant text at near-zero marginal cost, GenAI precipitates the collapse of the proof-of-work signalling economy not by attacking its institutions, but by exposing their performative nature. It renders the underlying logic visible, stripping the journal article of its value as a proxy for cognitive labour. Instead of offering renewal, this transparency forces a structural reweighting of epistemic authority: away from the mechanical production of form (Episteme), now inexpensive and abundant, toward judgment grounded in direct contact with reality (Phronesis) and exposure to consequence-a signal that cannot be sustained without the friction of the world.

This editorial examines whether the Information Systems discipline's publication venues create the conditions for two principles central to scientific knowledge: transparency and accessibility. I review the policies of nineteen IS journals and conferences across eight practices, organised through the OPEN framework: Outputs (open access, preprints, open artefacts), Process (open data, open materials), Evaluation (registered reports, open peer review, replication), and Norms, which emerge from the patterns across the other three. The resulting matrix shows that beyond open access, which most venues offer only as a paid option, almost none requires transparency or accessibility as a condition of publication. Closed norms dominate instead: publishing behind paywalls, withholding data, and conducting peer review privately are all practised and expected. A discipline whose findings cannot be reproduced and whose artefacts cannot be accessed cannot expect to be relevant.

Balancing research relevance and rigour has been a long-standing concern in the Information Systems (IS) discipline, crucial for advancing academic understanding and disseminating knowledge to practitioners. This paper addresses the need for effective knowledge product translation and dissemination by proposing the use of animated research briefs with visual storytelling cues. Grounded in the cognitive theory of multimedia learning and critical narrative theory, these briefs aim to make research more accessible and engaging for IS practitioners. A mixed-method approach is deployed: (1) a survey-based experiment to assess how research format influences practitioners' attitudes, which in turn affect their intentions to use academic research to solve work-related problems in the near term, and (2) in-depth interviews to explore practitioners’ perceptions of different research formats and their impact on the intention to use academic research in the near term. The paper offers new insights into the effectiveness of multimedia formats in enhancing practitioner engagement and understanding, thereby fostering a more effective dissemination and translation of research knowledge for practitioner audiences.

It has been argued that emergent AI systems should be viewed as working partners rather than tools. Building on this perspective, this study investigates the process through which academics develop a working partnership with generative AI chatbots using a relationship lens and collaborative autoethnographic methods. Based on a collaborative autoethnographic analysis of our experiences of working with AI, we identify five stages of relationship development in building a successful working partnership with generative AI: Playing Around, Infatuation, Committing, Frustration, and Enlightenment and Readjustment. In reporting each stage, we provide vignettes to illustrate the emotional and cognitive challenges and rewards involved, the developing skills, and the experienced anthropomorphic dimension of this emerging relationship. Drawing on prior theory, we identify and examine three types of work that are required in developing this working partnership: articulation work, relationship work, and identity work. We analyse how each type of work unfolds with the stages of relationship development and consider implications for research and practice.

With online citizen science (OCS) projects acting as the fulcrum for curriculum design. Across 3 years, teacher-researchers designed and implemented 16 innovative cross-curricular programmes. Our research focused on three areas: (1) mapping progressions in students’ science capabilities; (2) identifying affordances of OCS engagement for developing students’ digital technologies progress outcomes; and (3) investigating the impacts of teacher practices in relation to human–computer interactions. The project outcomes have potential to contribute significantly to both science and technology education research and teaching.

Calls have been made for information systems to go beyond supporting the instrumental outcomes traditionally associated with business imperatives to foster more humanistic outcomes. This study explores the mechanisms used by two intelligent personal assistants (IPAs) to promote humanistic goals such as pro-social behaviour. We identify four key mechanisms through which the IPAs support humanistic goals and draw on humanistic management literature to identify the humanistic goals supported. The mechanisms are (1) humanistic framing of analytics and goals, (2) persuasion, (3) automation of humanistic actions, and (4) anchoring humanistic goals to instrumental outcomes. The study raises issues about the moral implications of instrumentalising humanistic outcomes and suggests a need for theory to understand the role of Human-AI interaction in promoting humanistic outcomes. We propose a need for investigations into how and whether human-AI interactions can foster authentic humanistic outcomes in practice.