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Enhancing Complementary Team Performance through Intelligent Helping
Full text linkEffectively leveraging artificial intelligence (AI) requires aligning human reliance on AI with humans’ cognitive strengths and limitations. Despite the objective advantages of AI in performing specific tasks, humans often struggle to correctly rely on help from AI to maximize the Complementary Team Performance (CTP), exceeding the individual performances by either humans or AI. To address this challenge, we propose the design feature Intelligent Helping, which steers human behavior by strategically providing different types of AI help and thus aligning reliance with AI’s superior judgment while ensuring that humans retain full control. We designed an experiment with four archetypes of task performances and four treatments to modulate human interaction with AI. Our results show that reliance on AI can be shaped by tailored treatments, significantly improving CTP. Intelligent Helping enables high-performing AI in which humans retain full control over decisions, providing new opportunities for effective collaboration between humans and AI
Social Media Influencers: A Systematic Review and Consolidated Definition
Full text linkSocial media influencers (SMIs) have emerged as powerful actors shaping brand awareness and consumer behavior. However, their impact is expanding beyond purely economic functions into areas such as politics, public health, and disaster communication. Existing literature tends to define the concept of SMIs rather narrowly, focusing either on their relevance within specific academic disciplines (e.g., marketing) or on categories of reach (e.g., micro, meso, and macro influencers). Narrow or inconsistent definitions and conceptualizations of SMIs across disciplines hinder theoretical development and limit comparability between studies. Therefore, this paper aims to establish a consolidated definition of SMIs. Using a seven-stage review methodology, we systematically derive a definition that captures the essential characteristics of SMIs, reflects their transformative role in societal discourse, and remains applicable to emerging artificial incarnations of the phenomenon
Introducing GAMUT - A Game-based Assessment for Measuring User Types: Evaluation of Game Design for Satisfying Psychological Needs to Enhance User Engagement and Flow
Full text linkDespite the growing relevance of game-based assessment in higher education, many approaches lack theoretical grounding and motivational design. This study introduces GAMUT, a theory-driven game-based assessment that embeds user type assessment into interactive, narrative gameplay. Based on the Self-System Model of Motivational Development and the Hexad model, GAMUT incorporates achievement, social, and immersion game elements to satisfy the core psychological needs: competence, autonomy, relatedness. Implemented as a mobile adventure simulation, it transforms the Hexad scale into decision-based scenarios for authentic self-assessment. Empirical evaluation with higher education students shows that social and immersive game elements significantly promoted autonomy, competence and relatedness, enhancing engagement and flow. Achievement game elements had limited effects, emphasizing the need for context-sensitive game design. GAMUT achieved an 85% accuracy rate in user type classification and was preferred over traditional questionnaires. These findings offer a systematic, motivational GBA approach, contributing to assessment validity, learner engagement and self-directed learning
Facilitating Better Deliberation about Smart Cities: Designing a Meta-deliberation Instrument
Full text linkIn smart cities, deliberation between public professionals and discontented citizens risks devolving into a ‘dialogue of the deaf’, where parties talk past each other due to differing perceptions of what constitutes good deliberation. Meta-deliberation offers a promising direction to raise awareness of this risk, encourage reflection on differing perceptions, and anticipate tensions. However, its potential remains unexplored, and practical instruments are lacking. Therefore, Design Science Research (DSR) was used to develop a practice-oriented, academically grounded meta-deliberation instrument guided by six standards of deliberative quality, for public professionals in smart city contexts. The instrument is informed by academic insights and interviews with public professionals (n=17), and was evaluated by experts (n=9) and professionals (n=2x3). This study contributes academically by showcasing the potential of meta-deliberation to address a dialogue of the deaf, methodologically by applying DSR to smart city governance challenges, and practically by designing an instrument to improve government-citizen interactions
The Developmental Bypass: How AI Assistance Undermines Human Growth
Full text linkThis study examines how AI writing assistance affects human development, revealing a fundamental paradox: while AI tools improve immediate output quality, they undermine the psychological processes through which writers grow. Drawing on self- determination theory, we conducted an experiment (N=206) comparing self-editing to varying levels of AI assistance. Results demonstrate that self-editing produced significantly greater gains in writer identity (M=0.88) compared to low (M=0.54) and high (M=0.43) AI contribution conditions. Self-efficacy gains showed even starker differences, with self-editing yielding meaningful growth (M=0.41) while AI conditions produced negligible gains (<0.10). Most surprisingly, domain expertise transformed from an asset in self-editing to a liability under AI assistance, as experts defensively disengaged to protect their threatened identity. These findings suggest AI creates a "developmental bypass"—eliminating the productive struggle necessary for growth. We discuss implications for designing AI systems that enhance rather than diminish human potential, arguing for preserving developmental experiences in human-AI collaboration
AI with a Heart: THE Pillars of Technology, Humanity and Environment for Responsible Integration of AI along the Patient Journey
Full text linkArtificial Intelligence (AI) holds great promise for transforming patient care, yet its integration often neglects the lived experiences of patients. This paper explores how AI can be responsibly applied to support patient-centered care across the patient journey. Drawing on twelve expert interviews with researchers and practitioners from the fields of AI and healthcare, we identify both critical potentials and challenges of AI deployment across care phases – as from symptom awareness to aftercare. Findings reveal three foundational pillars – Technology, Humanity, and Environment (THE) – that frame responsible AI use. Results emphasize the importance of explainability, human-in-the-loop systems, inclusive design, and institutional alignment. We develop a conceptual framework that maps context-specific AI applications along the patient journey and derive guiding principles for their responsible use. The study contributes by complementing socio-technical perspectives with relational and ethical dimensions, and offers practical orientation for aligning AI deployment with clinical realities and infrastructural constraints in healthcare
Introduction to the Minitrack on Collaboration in Online Communities: Information Processing and Decision Making
No full textA Comprehensive Study on the Role of Mental Health Advocates on Instagram and Their Effects on User Engagement
Full text linkThis paper examines the role of mental health advocates on Instagram, focusing on how professional status and content type impact engagement. It analyzes a large sample of posts created by licensed professionals (e.g., psychologists) and unlicensed influencers (e.g., wellness coaches, advocates), including branded and non-branded content. Using Natural Language Processing (NLP) and Top2Vec Topic Modelling, the study identifies key mental health-related themes and examines which terms and topics are more frequently linked to higher engagement metrics like likes and comments. The analysis reveals differences in engagement patterns based on advocate credentials and whether content is commercially affiliated. Terms related to anxiety, depression, and trauma are more prominent among high-engagement content. Licensed professionals emphasize clinical support, while unlicensed influencers frequently use motivational or emotionally resonant language. These findings offer insights for mental health communicators, brands, and platform designers aiming to foster more credible and engaging mental health discourse on social media
“I want to talk to a human!” – Perceived Humanness Increases Satisfaction with an AI-driven Customer Service Chatbot
Full text linkCustomer service chatbots have massively benefitted from the introduction of generative artificial intelligence (AI) models. The technological leap provides companies an opportunity to increasingly serve customers with AI agents, focusing human resources to train, oversee and intervene AI-driven chatbot conversations instead of performing them in person. Nevertheless, customers might still prefer to speak with a human instead of an AI agent. This study compares the effect of AI and human-AI hybrid chat conversations on customer satisfaction. An experiment concerning 208 chat conversations in an online store reveals that customers were as satisfied with the AI- and human-AI hybrid conversations, regardless of the disclaimer used. However, in AI-driven conversations, perceived humanness of the customer service system mediated the relationship between the disclaimer and customer satisfaction − when less was told about the underlying technological system, customers were more satisfied because the service was perceived as more human
