{"ID":2894236,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.10981","arxiv_id":"2507.10981","title":"An Exploratory Study on AI-driven Visualisation Techniques on Decision Making in Extended Reality","abstract":"The integration of extended reality (XR) with artificial intelligence (AI) introduces a new paradigm for user interaction, enabling AI to perceive user intent, stimulate the senses, and influence decision-making. We explored the impact of four AI-driven visualisation techniques -- `Inform,' `Nudge,' `Recommend,' and `Instruct' -- on user decision-making in XR using the Meta Quest Pro. To test these techniques, we used a pre-recorded 360-degree video of a supermarket, overlaying each technique through a virtual interface. We aimed to investigate how these different visualisation techniques with different levels of user autonomy impact preferences and decision-making. An exploratory study with semi-structured interviews provided feedback and design recommendations. Our findings emphasise the importance of maintaining user autonomy, enhancing AI transparency to build trust, and considering context in visualisation design.","short_abstract":"The integration of extended reality (XR) with artificial intelligence (AI) introduces a new paradigm for user interaction, enabling AI to perceive user intent, stimulate the senses, and influence decision-making. We explored the impact of four AI-driven visualisation techniques -- `Inform,' `Nudge,' `Recommend,' and `I...","url_abs":"https://arxiv.org/abs/2507.10981","url_pdf":"https://arxiv.org/pdf/2507.10981v1","authors":"[\"Ze Dong\",\"Binyang Han\",\"Jingjing Zhang\",\"Ruoyu Wen\",\"Barrett Ens\",\"Adrian Clark\",\"Tham Piumsomboon\"]","published":"2025-07-15T04:53:09Z","proceeding":"cs.HC","tasks":"[\"cs.HC\"]","methods":"[\"LoRA\"]","has_code":false}