Dark Sides and Criminal Uses of Digital and Intelligent Technologies

Permanent URI for this collectionhttps://hdl.handle.net/10125/112535

Browse

Recent Submissions

Now showing 1 - 5 of 5
  • Thumbnail Image
    Item type: Item ,
    Dark Personalities at Work: How Service Employees’ Dark Triad Traits Shape Acceptance of Generative AI
    (2026-01-06) Boy, Firat; Xhigoli, Dugaxhin; Schaarschmidt, Mario
    As generative AI (Gen-AI) tools are increasingly used in service settings, understanding what drives or hinders individual employees’ acceptance is essential for successful implementation. While technical readiness and ethical concerns are frequently discussed, little is known about how personality traits such as narcissism, Machiavellianism, and psychopathy shape trust and acceptance of Gen-AI at work. This study investigates the influence of Dark Triad traits on trust in Gen-AI—differentiated as human-like vs. functional trust—and their impact on acceptance in the service sector. A mixed-methods design was applied, combining a quantitative survey (N = 329, analyzed via SEM and PROCESS) with ten follow-up expert interviews, analyzed using thematic analysis. Narcissism was positively linked to both trust dimensions and Gen-AI acceptance, while Machiavellianism reduced trust and acceptance. Psychopathy showed more complex and partially contradictory effects. Expert interviews provided deeper insights, suggesting that narcissists embrace Gen-AI for self-promotion, while Machiavellians remain skeptical due to control concerns. The findings highlight the importance of personality-aware AI adoption strategies. Organizations should foster transparency and support trust-building to address different personality-driven motivations and barriers.
  • Thumbnail Image
    Item type: Item ,
    The Dark Side of Biometric Technologies: How Shared Control of the Body Elicits Job Insecurity
    (2026-01-06) Killoran, Jay; Park, Andrew; Manseau, Jasmin; Kietzmann, Jan
    Technological advancement is associated with job insecurity, which refers to threats to the stability and continuity of work. The recent emergence of biometric technologies, which can collect, store, and analyze physiological and behavioral human data, have led to a new form of managerial control over workers: shared control of the body. Biometric technologies have the potential to infringe upon human rights and elicit job insecurity, but the mechanisms through which this occurs are not well understood. In this conceptual paper, we propose three pathways of how shared control of the body elicits job insecurity. First, shared control of the body threatens job autonomy, which elicits job insecurity. Second, perceived creepiness mediates the relationship between shared control of the body and job insecurity. Finally, shared control of the body erodes inherent and meritocratic dignity, which elicits job insecurity. We contribute to scholarly discussions regarding technology agency, surveillance, and human wellbeing.
  • Thumbnail Image
    Item type: Item ,
    A Taxonomy of Collusion in Information Systems
    (2026-01-06) Armbruster, Kevin; Kannengießer, Niclas; Beyene, Mikael; Ciolacu, Gabriela; Sunyaev, Ali
    Collusion poses a pervasive threat to information systems (IS), undermining fairness, trust, and system integrity. Existing research, however, often focuses narrowly on specific cases or emphasizes either social or technical aspects, resulting in fragmented insights and limited generalizability. This narrow scope hampers the development of broadly effective protection strategies. Recognizing collusion as a sociotechnical phenomenon shaped by the interplay between social actors and technical artifacts, we developed a case-agnostic taxonomy that helps uncover and classify various forms of collusion in IS. Using an iterative approach, we synthesized insights from multidisciplinary academic literature and descriptive legal cases. Grounded in general systems theory, the taxonomy offers a robust structural foundation for analyzing collusion in IS. This taxonomy benefits practice by capturing the structural characteristics of collusion, enabling more systematic analysis, detection, and mitigation.
  • Thumbnail Image
    Item type: Item ,
    Exposure, Skepticism, and Switching: A Behavioral Model of Narrative Diffusion
    (2026-01-06) Amure, Ridwan; Agarwal, Nitin
    This study presents a computational framework for understanding how competing narratives spread on social media, using Brazil’s 2022–2023 post-election protests as a case study. We extend the SEIZ epidemiological model to incorporate key behavioral dynamics—exposure, skepticism, resistance, and narrative switching—that influence how narratives evolve in contested digital spaces. Drawing on over half a million posts across Instagram, X (formerly Twitter), and YouTube, we apply physics-informed neural networks (PINNs) to estimate diffusion parameters directly from observed online behavior. Our results show that exposure drives reach, switching reshapes alignment, skepticism slows diffusion, and entrenchment reinforces ideological divides. By capturing these dynamics, our framework offers a behaviorally grounded, data-driven approach to studying narrative competition. The model not only advances diffusion theory but also provides insights for policymakers, platform designers, and researchers seeking to better understand and respond to the spread of divisive or manipulative content online.
  • Thumbnail Image
    Item type: Item ,
    Introduction to the Minitrack on Dark Sides and Criminal Uses of Digital and Intelligent Technologies
    (2026-01-06) Vaghefi, Isaac; Siuda, Piotr; Qahri-Saremi, Hamed; Turel, Ofir