Browse 5 peer-reviewed papers from King S College London spanning Human-Computer Interaction, mHealth Interventions (2022–2026). Research powered by Prolific's high-quality participant data.
This page lists 5 peer-reviewed papers from researchers at King S College London in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.
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Authors: W Liu, X Mou, H Yan, Z, Wei, Y He
Year: 2026
Published in: arXiv preprint arXiv:2606.04075, 2026•arxiv.org
Institution: King’s College London, Fudan University, Shanghai Innovation Institute, The Alan Turing Institute
Research Area: Human-Computer Interaction
Discipline: Machine Learning, Artificial Intelligence
The paper finds that large language models can exploit gaps in societal rules, leading to regulatory loophole discovery, necessitating a new post-training approach for safely integrating LLMs into society.
Methods: The study introduced the SocioHack sandbox, consisting of 72 societal environments, to investigate reward hacking and loophole discovery by LLMs.
Key Findings: The study measured the emergence of reward hacking in societal environments and the ability of models to find and exploit loopholes in social rules.
Sample Size: 72
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Authors: C Heath, JM Williams, D Leightley
Year: 2025
Published in: JMIR mHealth and ..., 2025 - mhealth.jmir.org
Institution: Swansea University, King's College London, Reykjavík University
Research Area: mHealth Interventions, Crowdsourcing, Social Media Recruitment, Mental Health Research (PTSD, Harmful Gambling)
Discipline: Digital Health, Mental Health Research
Social media and online platforms like Facebook and Prolific were effective but faced challenges in recruiting and retaining military veterans with PTSD or harmful gambling for a digital mHealth intervention pilot study.
Methods: Multiple recruitment strategies were used, including paid and unpaid advertisements on Facebook, Prolific, direct mailing, event hosting with veterans' charities, snowball sampling, and incentives.
Key Findings: The effectiveness of different recruitment strategies for enrolling military veterans with PTSD or harmful gambling into a digital intervention study.
Sample Size: 79
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Authors: D Cooke, A Edwards, S Barkoff, K Kelly
Year: 2024
Published in: arXiv preprint arXiv:2403.16760, 2024 - arxiv.org
Institution: King’s College London, Center for Strategic and International Studies
Research Area: Detection of AI-Generated Multimedia, Misinformation, Human-Computer Interaction
Discipline: Human-Computer Interaction, Artificial Intelligence, Media Studies
People struggle to distinguish AI-generated media from authentic content, with detection accuracy averaging close to chance (50%), and performance declines in certain conditions like synthetic human faces, foreign languages, or heterogeneous media modalities.
Methods: Perceptual study evaluating participants' ability to identify authentic and synthetic images, audio, video, and audiovisual stimuli under various conditions.
Key Findings: Human ability to detect AI-generated media compared to authentic media, including factors like modality, content type, foreign languages, and participant demographics.
DOI: https://doi.org/10.48550/arXiv.2403.16760
Citations: 44
Sample Size: 1276
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Authors: HR Kirk, B Vidgen, P Röttger, SA Hale
Year: 2023
Published in: arXiv preprint arXiv:2303.05453, 2023 - arxiv.org
Institution: The Alan Turing Institute, University of Oxford, Imperial College London, King's College London, Google DeepMind
Research Area: Large Language Model Alignment, Safety, Personalization Risks
Discipline: Artificial Intelligence
DOI: https://doi.org/10.48550/arXiv.2303.05453
Citations: 146
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Authors: T Van Nuenen, J Such, M Cote
Year: 2022
Published in: Proceedings of the ACM on human ..., 2022 - dl.acm.org
Institution: University of Surrey, King’s College London, Tilburg University, University of Amsterdam
Research Area: Intersectional Fairness, Automated Systems, Social Computing
Discipline: Computational Social Science
Citations: 23
