Dissertation defence (Information Systems Science): MSc Rong Huang
Time
14.11.2025 12.15 – 18.00
MSc Rong Huang defends the dissertation in Information Systems Science titled “Artificial Intelligence-Based Robots for Individual Well-being: A Multiple-Case Study” at the University of Turku on 14 November 2025 at 12.15 (University of Turku, Turku School of Economics, Osuuskauppa lecture hall, Rehtorinpellonkatu 3, Turku).
The audience can participate in the defence by remote access: https://echo360.org.uk/section/4c94da61-9d13-491d-9178-4b1adf932a2a/public
Opponent: Professor Stefan Klein (University of Münster, Germany)
Custos: Professor Reima Suomi (University of Turku)
Doctoral Dissertation at UTUPub: https://www.utupub.fi/handle/10024/194320
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Summary of the Doctoral Dissertation:
Across the world, people are facing growing challenges to their well-being, such as mental health issues, social isolation, and declining life satisfaction. Artificial intelligence (AI)-based robots have emerged as promising tools to provide accessible, scalable, and personalized support for individual well-being.
This dissertation aims to investigate how people interact with AI-based robots to enhance well-being in daily life. First, this dissertation conducts two systematic literature reviews on AI-based physical robots in healthcare and virtual robots in everyday contexts. The results synthesize current knowledge on robot designs, applied contexts, and target users, as well as antecedents and consequences of AI-based robot use. The findings provide a conceptual foundation and a source of questions for subsequent empirical research.
Based on these insights, this dissertation employs a multiple-case study to examine user interactions with AI-based physical and virtual robots for well-being support in real-life scenarios. The findings reveal that human–robot interaction (HRI) is a highly contextual, dynamic, and co-constructed process, shaped by robot embodiment, functionality, contexts, and user needs. These interactions follow nonlinear trajectories, while users may delay or withdraw from interactions due to various negative experiences. Additionally, this dissertation shows positive outcomes of HRI on individual well-being across emotional, social, cognitive, and behavioral dimensions in daily life. Notably, these well-being outcomes are not only driven by robot features or technical performance but also emerge from the sustained and stable interactions between users and AI-based robots.
This study contributes to broader discussions on the evolving relationship between humans and AI-based robots and offers theoretical and practical insights into how AI-based robots can be meaningfully integrated into daily life to support human well-being.
The audience can participate in the defence by remote access: https://echo360.org.uk/section/4c94da61-9d13-491d-9178-4b1adf932a2a/public
Opponent: Professor Stefan Klein (University of Münster, Germany)
Custos: Professor Reima Suomi (University of Turku)
Doctoral Dissertation at UTUPub: https://www.utupub.fi/handle/10024/194320
***
Summary of the Doctoral Dissertation:
Across the world, people are facing growing challenges to their well-being, such as mental health issues, social isolation, and declining life satisfaction. Artificial intelligence (AI)-based robots have emerged as promising tools to provide accessible, scalable, and personalized support for individual well-being.
This dissertation aims to investigate how people interact with AI-based robots to enhance well-being in daily life. First, this dissertation conducts two systematic literature reviews on AI-based physical robots in healthcare and virtual robots in everyday contexts. The results synthesize current knowledge on robot designs, applied contexts, and target users, as well as antecedents and consequences of AI-based robot use. The findings provide a conceptual foundation and a source of questions for subsequent empirical research.
Based on these insights, this dissertation employs a multiple-case study to examine user interactions with AI-based physical and virtual robots for well-being support in real-life scenarios. The findings reveal that human–robot interaction (HRI) is a highly contextual, dynamic, and co-constructed process, shaped by robot embodiment, functionality, contexts, and user needs. These interactions follow nonlinear trajectories, while users may delay or withdraw from interactions due to various negative experiences. Additionally, this dissertation shows positive outcomes of HRI on individual well-being across emotional, social, cognitive, and behavioral dimensions in daily life. Notably, these well-being outcomes are not only driven by robot features or technical performance but also emerge from the sustained and stable interactions between users and AI-based robots.
This study contributes to broader discussions on the evolving relationship between humans and AI-based robots and offers theoretical and practical insights into how AI-based robots can be meaningfully integrated into daily life to support human well-being.
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