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AI models assess urban robot safety perceptions in Seoul

By PulseAugur Editorial · [1 sources] ·

A new research paper explores how the presence of robots in urban environments affects human perceptions of safety. Using two multimodal large language models, Qwen3.8-27B and Gemma4-26B, researchers presented them with images of Seoul streets under various conditions, including the presence and type of robot. Both models, when conditioned on synthetic personas, generally preferred streets without robots and favored delivery robots over humanoid ones. The models' judgments, particularly Gemma4-26B's response to humanoid robots at night, showed some divergence from human respondents, highlighting the nuances in AI's understanding of safety perceptions. AI

IMPACT Investigates AI's capacity to understand nuanced human perceptions of safety in urban environments, potentially informing future robot integration.

RANK_REASON Academic paper on AI models' perceptions of urban robots. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI models assess urban robot safety perceptions in Seoul

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Academic paper on AI models' perceptions of urban robots. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Keonhee Jang, Kanghoon Lee, Seokwoo Yun, Namwoo Kim, Yoonjin Yoon ·

    Robots in the City: Persona-Based Perceptions of Urban Robots

    arXiv:2611.05954v1 Announce Type: cross Abstract: Pedestrians increasingly encounter robots in urban public spaces without interacting with them, but how robots change the perceived safety of a street remains unclear. We examine how robot presence and type affect perceived safety…

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