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Auflistung nach Autor:in "Abdenebaoui, Larbi"

1 - 2 von 2
  • Konferenzbeitrag
    Enhancing Citizen Accessibility to Public Services: A Case Study on AI-Assisted Application for Housing Entitlement Certificates
    (INFORMATIK 2024, 2024) Abdenebaoui, Larbi; Aljuneidi, Saja; Meyer, Jochen; Boll, Susanne
    Administrative forms are often complicated, presenting significant challenges for citizens and creating barriers to accessing their entitled services conveniently. This complexity adds a burden on civil servants, who must address and rectify incorrectly completed applications, leading to longer processing times and further complicating the process. This paper presents an ongoing project in Germany that addresses this issue by designing a tool, featuring a chatbot, to assist citizens in filling out complicated forms, answering their questions, and explaining specific rules when needed. In this project, we focus on one application form, the housing entitlement certificate ("Wohnberechtigungsschein"). This paper describes the project’s core strategy, which integrates state-of-the-art Artificial Intelligence (AI) technologies with human-centered and value-sensitive design approaches. Additionally, it discusses the implementation approach of this intelligent tool and some initial outcomes.
  • Workshopbeitrag
    Towards Respectful Smart Glasses through Conversation Detection
    (Mensch und Computer 2018 - Tagungsband, 2018) Meirose, Franziska; Schultze, Sven; Kuehlewind, Sebastian; Koelle, Marion; Abdenebaoui, Larbi; Boll, Susanne
    Talking to each other is personal, maybe even intimate. Thus, privacy expectations are particularly high during interpersonal conversations, and image or audio recordings are problematic in these contexts. In consequence, smart glasses and other body-worn devices with “always-on” cameras are not well accepted during interpersonal conversations. Proposing a simple-to-implement computer vision procedure, we work towards a solution to this issue. Using imagery from a head-worn camera we detect face-to-face conversations in real-time, as well as distinguish between intimate, personal and social conversations based on intrinsic camera parameters. Starting from a fictive scenario, we illustrate how this knowledge can be used for interaction designs that increase both, the users’ as well as their bystanders’ privacy, e.g., by muting audio or disabling the camera. Finally, we suggest directions for future work.