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Government use of digital technology is often accompanied by high hopes of generating beneficial outcomes. Previous research has identified several instances where such initiatives have failed to meet expectations. Despite this, optimistic narratives about the potential of digital technology in government persist across policy, media, and academic discourses. Against this backdrop, this paper critically examines narratives regarding the benefits of using digital technology in the public sector. It analyzes Swedish government policy documents and evaluations published between 1961 and 2023. The study highlights recurring patterns over time and identifies three “eras” of digital government: automatic data processing, information technology, and digitalization. The findings reveal optimism in visionary policy documents that draw on contemporary and emergent technological discourses. However, evaluations of these policies present limited evidence of their enactment, leading to disillusionment about transformational outcomes. These findings situate current narratives about digital technology within a broader historical context and open pathways toward more reflective digital government policymaking.

This essay explores the emerging relationship between the Metaverse and generative AI (GenAI). “The Metaverse” is a term used to describe 3D virtual worlds that offer potential immersive spaces for interaction, entertainment, and business. However, these worlds are often hampered by a lack of dynamic content and tend to become static over time. Concurrently, GenAI, with its ability to facilitate content creation and simulate intelligent behaviors, redefines the boundaries between creativity and automation. By using the notion of non-player characters (NPCs) in virtual worlds as an example, it is highlighted how GenAI can facilitate a more dynamic and responsive Metaverse. While this technological combination holds promise, it also raises severe ethical concerns, calling for a renewed engagement with earlier literature on what constitutes a ‘good’ life online. Based on this literature, managerial implications to promote sustainable development of these technologies are presented: creation of AI architectures that facilitate creativity, ethical governance, and new mechanisms for value generation. The discussion concludes by stating that technology-wise, we have the tools needed to create an immersive Metaverse, while ethically, more work is needed to align these technologies with human values.

As generative artificial intelligence (GenAI) systems become increasingly incorporated into creative processes, they present both opportunities and challenges in terms of redefining creativity. This article provides a perspective on the dual nature of AI hallucinations from a divergent thinking perspective where GenAI creates something unexpected when given a prompt, and examines its role as both a facilitator and an inhibitor of the creative process. Although AI hallucinations can yield new ideas and break from established patterns of thinking to generate creativity, they can also create a dependency which could result in the stalling of creative output. This study uses a qualitative research approach based on the experiences of master’s students who incorporate GenAI and engage with it in their creative work. The findings from the study reveal a relationship between divergent thinking and AI-generated responses, showing GenAI can work both as a collaborator and a disruptor in the creative context. In addressing the duality of hallucinations produced by AI, this research contributes to the larger dialogue surrounding the changing relationship between AI and creativity, highlighting ways in which AI might both promote and disrupt human creativity.

In this position paper we propose what we here call a CodeNoCode (CNC) approach to the creation and evaluation of predictive models. NoCode tools are increasingly becoming more powerful, but there is a lack of understanding about the practical/industry adoption of predictive modeling NoCode tools such as KNIME or Orange. To speed-up adoption-in particular for non-technical users- we find this a good time to investigate the LLM-supported co-development of code and GUI (NoCode) for Machine Learning (ML) tasks. ML code follows a rather sequential structure which limits the complexity of the automatic creation of modeling code and as a consequence also the representations and integrations of the modeling process and analysis within a graphical interface. CNC avoids intermediate model formats (transparency), and, in support of LLMs, can be made programming language agnostic while opening up for collaboration between coders and non-coders, in support of LLM assistants (inclusivity).

In this extended abstract, we combine perspectives from sustainability studies, retrogaming cultures, and theories of imaginaries. The purpose is to explore new ways ofthinking about technology to promote environmental sustainability. First, we argue for the need for a contrast to contemporary perspectives where not-yet-existingtechnologies are believed to solve issues such as the climate crisis. Second, we propose that mindsets and practices from gaming cultures can aid us in thinkingdifferently about the relationship between technology and sustainability.

Generative artificial intelligence (GAI) systems, such as ChatGPT and DALL-E, enable the automatic creation of content that closely resembles human-produced work, allowing for both constructive and potentially harmful applications. This study investigates the impact of GAI on digital resilience in society, focusing on the opportunities and challenges these technologies present. Digital resilience is defined as the capacity to maintain societal functions despite disruptions to or by digital systems. This study draws on a systematic literature review of 164 research articles, with findings categorized into three key perspectives: technology, organization, and governance. Within each perspective, themes for further research are identified. The results highlight the importance of recognizing GAI’s dual nature to both support and threaten digital resilience. To promote secure digitalization, our study calls for more empirical research on the risks associated with GAI applications, transparent artificial intelligence usage, and the establishment of ethical guidelines. The study also advocates for increased interdisciplinary research to ensure that new technologies and resilience can coexist as foundational elements of a resilient, democratic society.

Ongoing efforts to regulate artificial intelligence (AI), such as the recently adopted European AI Act, are affecting organizations that are already hard-pressed to increase their AI readiness. While many fear that such regulations will stifle AI innovation, we argue that they instead set guardrails for, rather than present barriers to, AI initiatives. Thus, organizations need to urgently start preparations for compliance with the AI Act and similar regulations while ensuring continued AI initiative success. In this article, we provide the “AI Act Readiness Framework”, a 2x2 matrix to help organizations map their current AI Act readiness and outline four strategies toward compliant AI initiatives. The framework provides a structured approach to move from low to high AI Act readiness by focusing on achieving clarity regarding legal obligations and compliance. We outline five managerial recommendations that organizations could employ for increased AI Act readiness. In doing so, this paper contributes not only with a framework for organizations aiming to assess their readiness in relation to AI regulation, but also to a future where AI is developed in responsible ways.

Technological developments have enabled private and public actors to access near-Earth space. Space systems are both critical infrastructure and important sub-systems of other critical infrastructures (e.g., GPS and weather forecasting) dependent on space technology. However, unlike other critical infrastructures, space systems are relatively unexplored from a security perspective. The paper presents a system model based on a synthesis of the current research front discussed in national and international research literature, reports, and studies. The soft systems methodology is used to develop the model useful for actors concerned with risk management to increase the understanding of systemic dependencies of space systems and strengthen the resilience in critical infrastructures and services. This paper provides insights into digital risks for space systems, highlighting serious societal consequences and areas for enhanced space security. Based on the system model and the analysis provided for a better understanding of the relationships among these systems, future research needs to strengthen cybersecurity in space systems as exemplified.

AI systems, such as neural-network-based deep learning (DL) and other machine learning (ML) algorithms, can extract valuable insights from data. A major downside of these algorithms is dependence on the availability of sufficient amounts of relevant and structured data. This is clearly problematic for uses in settings where data are scarce and may hamper the development of innovative, creative ML solutions. Hence, there are tensions between ambitions expressed in previous studies to build “universal” solutions based on available (big) data, and the need to contextualize data for specific uses in distinct domains. However, in this paper, we argue that recent advances in ML reduce these tensions and call for more understanding of how these systems can facilitate human creativity. To contribute to such understanding, we present an illustrative application of transfer learning (TL) to facilitate conceptual leaps by broadening algorithmic affordances. This application, involving the use of data on the shapes of lunar craters to identify archeological remains in Swedish forests, highlights how TL can act as a catalyst for cross-domain idea generation through a practical example. By doing so, we theoretically link research on ML development with creativity research, while also demonstrating this connection in practice.