Examinando por Autor "Chen, Liming"

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  • Miniatura
    Ítem
    A multifaceted vision of the human-AI collaboration: a comprehensive review
    (Institute of Electrical and Electronics Engineers Inc., 2025) Puerta Beldarrain, Maite; Gómez Carmona, Oihane; Sánchez Corcuera, Rubén; Casado Mansilla, Diego; López de Ipiña González de Artaza, Diego; Chen, Liming
    Human-AI collaboration has evolved into a complex, multidimensional paradigm shaped by research in various domains. Key areas such as human-in-The-loop systems, Interactive Machine Learning (IML), Hybrid Intelligence, and Human-Agent Interaction have significantly contributed to this development. However, these fields often lack cohesion, underscoring the need for a cohesive perspective to advance. This work addresses this gap by integrating insights from diverse aspects of collaboration to present a holistic approach to fostering effective and adaptive interactions between humans and artificial agents. It emphasizes empowering end-users with greater control and involvement in decision-making processes, thereby enhancing both the levels of interactivity and adaptability within intelligent systems. Moving beyond a focus on AI training techniques, this paper presents a broader perspective on incorporating human input into AI decision-making and learning processes, highlighting the importance of flexibility in systems and user engagement. The manuscript proposes a framework encompassing five levels of human integration and examines their relationship with core collaboration aspects, including the system purpose, participant expertise, and system proactivity. By synthesizing current knowledge on human-AI collaboration and outlining essential design principles, this work aims to advance the field and foster interdisciplinary collaboration among researchers, practitioners, and designers
  • Miniatura
    Ítem
    A spatial crowdsourcing engine for harmonizing volunteers’ needs and tasks’ completion goals
    (Multidisciplinary Digital Publishing Institute (MDPI), 2024-12) Puerta Beldarrain, Maite; Gómez Carmona, Oihane; Chen, Liming; López de Ipiña González de Artaza, Diego; Casado Mansilla, Diego; Vergara, Felipe Eduardo
    This work addresses the task allocation problem in spatial crowdsensing with altruistic participation, tackling challenges like declining engagement and user fatigue from task overload. Unlike typical models relying on financial incentives, this context requires alternative strategies to sustain participation. This paper presents a new solution, the Volunteer Task Allocation Engine (VTAE), to address these challenges. This solution is not based on economic incentives, and it has two primary goals. The first one is to improve user experience by limiting the workload and creating a user-centric task allocation solution. The second goal is to create an equal distribution of tasks over the spatial locations to make the solution robust against the possible decrease in participation. Two approaches are used to test the performance of this solution against different conditions: computer simulations and a real-world experiment with real users, which include a qualitative evaluation. The simulations tested system performance in controlled environments, while the real-world experiment assessed the effectiveness and usability of the VTAE with real users. This research highlights the importance of user-centered design in citizen science applications with altruistic participation. The findings demonstrate that the VTAE algorithm ensures equitable task distribution across geographical areas while actively involving users in the decision-making process.