Henrik Skaug Sætra

The global mental health crisis has driven the rise of apps using conversational agents (CAs) to complement or replace human professional support. Offline, the success of such interventions often depends on the relationship between the help-seeker and the support provider. Online, psychological processes elicited by specific app features relating to the CA and its unique story design might play a significant role. However, research on these processes and their consequences on user engagement and well-being is scarce. To shed light on this, we conducted a cross-sectional study with 348 active users of the mental health app Betwixt. The app integrates a scripted CA as a mentor, guiding users through levels of self-development within a dream-like fantasy narrative. We tested how perceived synthetic relationships with the CA (based on the Relational Models Theory, Fiske, 1992) and narrative transportation (i.e., the extent to which users become absorbed in the story) relate to app engagement and perceived stress. Our findings indicate that a strong sense of narrative transportation and perceiving the CA as friend-like positively predict hedonic benefits and future usage intentions. However, these factors were not significantly associated with perceived stress. Our results contribute to the emerging field of synthetic relationships and highlight the potential of narrative transportation for developers of apps using similar designs. We also discuss the ethical concerns of fostering friend-like relationships with CAs and their practical implications for developers and mental health professionals.

For years, critical AI discourse has found refuge in the "stochastic parrot" label to puncture hype. I argue this stance has become a professional comfort blanket that avoids engaging with how these systems are currently reshaping education, politics, and labor. We do not need AGI to achieve disruptive automation; we already have it. Using software engineering as an example-where agentic tools now generate a significant fraction of corporate code-I illustrate how AI increasingly functions as infrastructure rather than mere substitution. Drawing on Stephen R. Barley's sociology and historical parallels like the Linotype, I show that "bottlenecks" and power are shifting. We are witnessing the proletarianization of high-skill work, where the autonomous creator is demoted to a supervisor of a machine that has swallowed their craft. To avoid complicity by omission, we must move beyond dismissive rhetoric and look directly at how these "parrots" are rearranging the workplace.

In this article, we explore the entangled futures of global governance, artificial intelligence (AI), and climate change by developing four scenarios for the year 2045. The aim is not to predict the future, but to expand our imagination of plausible trajectories, while critically examining the political, technological, and environmental interdependencies that shape what lies ahead. Using an interdisciplinary approach grounded in futures studies and scenario analysis, we investigate how governance systems influence, and are influenced by, both AI development and climate responses. We begin by drawing on different academic fields in a conceptual and historical investigation of the three domains, identifying key dynamics and tensions. From this foundation, we construct four narrative scenarios, each articulating a distinct alignment of governance structures, climate pathways, and AI trajectories. Through these fictional-yet-grounded futures, we aim to provoke reflection and debate about which paths might lead to sustainability, justice, and collective flourishing, and which might not. Our contribution lies in the exploration and development of a method for developing and mapping potential future worlds, and using these to evaluate and make use of normative and strategic questions they pose in the present.

Advanced artificial intelligence (AI) systems capable of generating humanlike text and multimodal content are now widely available. Here we ask what impact this will have on the democratic process. We consider the consequences of AI for citizens’ ability to make educated and competent choices about political representatives and issues (epistemic impacts). We explore how AI might be used to destabilize or support the mechanisms, including elections, by which democracy is implemented (material impacts). Finally, we discuss whether AI will strengthen or weaken the principles on which democracy is based (foundational impacts). The arrival of new AI systems clearly poses substantial challenges for democracy. However, we argue that AI systems also offer new opportunities to educate and learn from citizens, strengthen public discourse, help people to find common ground, and reimagine how democracies might work better.

Generative Artificial Intelligence (Gen AI) now allows for the seeming automation of most if not all steps in the scientific research lifecycle, giving rise to what I refer to as the Research Automaton – the production of science-like output with minimal meaningful human engagement. This development is often framed through a techno-solutionist lens, promising efficiency gains by treating the traditional, often strenuous, research process as a problem to be solved. This paper challenges that perspective, arguing that the intrinsic value of science lies in this very process rather than solely in the product . Uncritically embracing automation thus entails eroding the formative experiences crucial for researcher development, particularly for early-career researchers, leading to potential skill atrophy and undermining the long-term innovative capacity of science. Drawing on both normative arguments about science as a vocation and pragmatic concerns about preserving essential cognitive and critical skills, I advocate for resisting the Research Automaton, while acknowledging the potential for AI to augment human capabilities when used judiciously within a hybrid cognitive constellation. I conclude by outlining practical implications for researchers, supervisors, institutions, policymakers, and publishers in navigating the integration of Gen AI in research.

There are several different perceptions of the proper role of an ethicist. Three of the main ones are the roles of a) impartial observer, b) a guide to what is good or bad, or c) an agent of change. In this article, I argue that the first one is impossible, the second is insufficient, and the third is important but also highly complex. Using AI ethics and the social media platform Twitter/X (X from here on out) as an example, I explore the nature and scope of a potential duty to act on one’s own research findings as an ethicist. I argue that there is a case to be made for such a duty if an ethicist identifies and recognizes a technology’s harmful potential and wishes to avoid complicity and hypocrisy.