Detecting the Undetectable: Human Judgments and the Challenge of Synthetic Voices

Synthetic voices generated using artificial intelligence (AI) are becoming increasingly indistinguishable from human voices, raising important concerns about trust, deception, and detection in digital communication. This preliminary work synthesizes the current landscape of research on human perception in detecting synthetic voices. We reviewed 13 papers from databases including ACM, IEEE, Springer, and MDPI, and identified five main types of perceptual cues that users rely on to detect voice synthesis: Intuition/Gut Feeling, Liveliness, Emotions, Linguistic Features, and Acoustic and Environmental Features. Our findings highlight the need for further empirical user studies to better understand how individuals perceive and assess the risks posed by synthetic voices. Such research can inform both educational and regulatory strategies aimed at increasing awareness and mitigating the potential harms of synthetic voice technologies

Dimensions of Human-Machine Combination: Prompting the Development of Deployable Intelligent Decision Systems for Situated Clinical Contexts

Whilst it is commonly reported that healthcare is set to benefit from advances in Artificial Intelligence (AI), there is a consensus that, for clinical AI, a gulf exists between conception and implementation. Here we advocate the increased use of situated design and evaluation to close this gap, showing that in the literature there are comparatively few prospective situated studies. Focusing on the combined human-machine decision-making process - modelling, exchanging and resolving - we highlight the need for advances in exchanging and resolving. We present a novel relational space -contextual dimensions of combination - a means by which researchers, developers and clinicians can begin to frame the issues that must be addressed in order to close the chasm. We introduce a space of eight initial dimensions, namely participating agents, control relations, task overlap, temporal patterning, informational proximity, informational overlap, input influence and output representation coverage. We propose that our awareness of where we are in this space of combination will drive the development of interactions and the designs of AI models themselves. Designs that take account of how user-centered they will need to be for their performance to be translated into societal and individual benefit

Beyond the Screen: Exploring the Emotional and Social Impact of Otome Games on Global Players

Following the growing popularity of Otome games in 2024, this late-breaking study combines qualitative interviews with existing literature to provide an initial understanding of the gaming experiences and reflections of six global male and female players. The research investigates the dynamics of parasocial interactions between players and in-game characters, examining how these interactions influence offline relationships and exploring the motivations and emotional needs of otome game players. It also considers how Otome game settings impact players’ emotional and mental wellbeing. Based on these insights, the study proposes implications for game design, encouraging developers to consider inclusivity, player agency, and player-disengagement factors in creating Otome games that foster both player empowerment and personal growth, rather than purely focusing on profit. Additionally, concerns about teenage players and their potential vulnerabilities are raised. The study concludes with suggestions for future research directions to further explore these issues

2nd International Workshop on Hybrid Collaboration–Analyzing Collaborative Interaction

Hybrid collaboration, where co-located participants are working together with remote participants, is increasingly established as a de-facto standard practice in our everyday professional lives. Since the first edition of this workshop in 2019, the pool of research has considerably increased. However, studying such collaborative practices is still met with skepticism by researchers due to the considerable effort that is connected to the according empirical endeavors. In this workshop, we aim at bringing together researchers and practitioners who are interested in the analysis of collaborative practices in general (i.e., co-located or remote), and/or a domain transfer to hybrid collaboration in particular

Integrating Social Care into Digital Knowledge Infrastructures in Dementia Care

This paper presents initial findings from an ongoing Danish PhD design research study that investigates the integration of different types of knowledge and data, with a particular focus on the often-neglected social care within digital knowledge infrastructures. The study employs ethnographic and participatory design activities to investigate how existing knowledge infrastructures facilitate care workers in identifying and understanding unmet needs among people with dementia in two Danish nursing homes. This paper presents three identified barriers that hinder effective knowledge sharing in social care: the availability of knowledge within EHR systems, 2) the ease of documentation processes in EHR, and 3) the accessibility of EHR for specific professional groups. Consequently, the focus on nursing care in documentation leads to a corresponding emphasis on nursing care delivery. To enhance the prioritization of social care, this paper argues that it is essential to provide care workers with improved support from knowledge infrastructures that address these three barriers

ORCID and the Fediverse: What Can We Do with Public Information?

ORCID is an identification scheme and bibliographic database for academics that aims to make information about researchers’ works widely and easily accessible. The Fediverse is a collection of interoperable social media platforms where people can follow each other across platform boundaries to read and share text posts or other media. Between these two environments, we observe contrasting social norms around “public data” and conflicting expectations on how personal information may be stored and republished. During the early design phase of a tool to bridge ORCID data into the Fediverse and make individual ORCID records followable on open social platforms, we face a need to connect and resolve these differences to prevent avoidable conflicts. This article documents these norms and expectations as well as our approach to connect and bridge them

Mitigating the anxiety emotion on consuming personalised feed in Chinese social media

Algorithmic social media feeds curate personalised content, often exposing users to anxiety-inducing posts. While anxiety is typically seen as a negative outcome, my research reveals that many users on RedNote (Xiaohongshu) continue engaging with such content for self-improvement and preparatory coping. However, excessive exposure can disrupt well-being, and existing feed control mechanisms are often ineffective or difficult to navigate. My PhD explores design interventions to help users better understand and manage their anxiety in algorithmic feeds. I investigate LLM-powered anxiety trigger awareness tools, self-tracking visualisations, and tangible reflection devices to support self-awareness, emotional regulation, and more intentional engagement. Through empirical studies and user-centered design, I aim to foster healthier interactions with algorithmic feeds. At ECSCW, I seek feedback on my design decisions and ethical considerations, particularly regarding moderate vs. radical interventions in anxiety-inducing content consumption and the ethical implications of applying LLM technology to non-participant user-generated content

Awareness, Motivation and Leadership in Production Systems: A Socio-Technical Perspective

With the remarkable structural changes that many sectors of the industry arecurrently experiencing with the advent and introduction of new digital technologiesand the push that they are receiving from assorted agendas concerningindustrial developments – as those connected with digital transformation andthe so-called Industry 5.0 – it sensible to think that different aspects concerningcooperative work will be subject to changes, especially when it comes to issuesassociated with the use and appropriation of digital technologies. In this contribution,we address the concept of awareness and how it has been impacted by thecontinuous process of digitalisation and digital transformation within the industryunder a practice-centred computing perspective. The study is based on anin-depth interview study featuring 19 participants across 11 different-sized manufacturingcompanies from the metalworking industry and other related sectors.The data was transcribed and subjected to thematic analysis. Subsequently, wediscuss how not only awareness, but also motivation and leadership in productionsystems have been continuously impacted by these structural changes, at timesin a negative way. We elaborate on our findings and reflect upon how existingCSCW notions, as coordination mechanisms, common information spaces and articulation spaces can be used to inform the design of new technologies thatcould enhance awareness and mitigate potentially negative impacts. In particular,we extend the notion of articulation spaces to include the role of a group mediator,which has been found relevant to support cooperation in industrial settingsundergoing digital transformation

Exploring AI Integration in SME Production Planning: Design Spaces and the Role of Workers

The pressure to improve products, services, and processes to remain competitive in the global market has fueled demand for affordable, high-quality, customized products with excellent availability and customer service. Production Planning and Scheduling (PPS) considers a wide range of internal and external factors in its attempts to align production with market demand. Advanced Planning and Scheduling (APS) systems have emerged to support PPS but suffer from issues such as deterministic views and practical uncertainties. Expectations are high that Artificial Intelligence (AI) and Machine Learning (ML) will support complex production planning tasks by analyzing operational data to generate optimal plans. However, there is currently little empirical research on production planning practices and what role AI might play. Our paper highlights current challenges in production planning practices and outlines design spaces for using AI and ML to support these practices. Based on an empirical study of three German small and medium-sized enterprises (SMEs) in the metal processing industry, we uncover how AI might estimate processing time and rework probability and thus we outline current design spaces for AI in production planning

How Data Work Transforms the Management of Primary Care

Primary healthcare institutions are incentivized to become more data-driven, as digital health data hold promises of being a gold mine for governance and service delivery. However, data go beyond being simple collections of raw information; they are influenced by social processes and established infrastructures. Hence, data acquire use value in context, through so-called ‘data practices’, or ‘data work’. This PhD project, a contribution to the emerging field of ‘data work studies’, looks into how healthcare managers are utilizing information systems and digital data for decision-making and planning. I’m interested in what happens in the backstage of healthcare institutions, when secondary data is used to support managerial processes. Adopting an ethnographic approach to these practices, I have conducted fieldwork in four Norwegian municipalities. Preliminary results imply that data work has substantial implications for managers and their staff. It often requires highly varied skillsets, which are not accounted for in terms of resources and recognition. This PhD project will enrich our understanding of managerial data practices in healthcare, and how they potentially can be improved - a crucial issue for the quality of future healthcare services