Autonomous driving paper index
Talking to a tutor or typing to a tool? A qualitative study of anthropomorphism in conversations between students and an AI tutor
One-line summary
This study utilizes a qualitative methodology informed by phenomenology to examine student–machine interactions in higher education, investigating whether students interpret AI responses as impersonal outputs or attribute human-like qualities to them.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
This study utilizes a qualitative methodology informed by phenomenology to examine student–machine interactions in higher education, investigating whether students interpret AI responses as impersonal outputs or attribute human-like qualities to them. Drawing on Edmund Husserl’s concepts of active and passive consciousness, alongside recent phenomenological and anthropological work on AI, we analyze a substantial body of data tracking student–AI tutor interactions across various disciplines using a sociolinguistic approach. Our findings reveal a near-universal pattern of low-level instrumental anthropomorphization. Students frequently employ conversational norms, like politeness and personal pronouns, while remaining fully cognizant of the AI’s nonhuman nature. However, clear disciplinary differences emerged based on distinct epistemological perspectives. Computer science students primarily treated the tutor as a technical tool, whereas social science students engaged in more human-like dialogues, occasionally framing the AI as a “machine oracle”. These dynamics further interact with speech act types. Notably, friendlier, anthropomorphic language elicited more socially responsive answers from the tutor, whereas technical prompts produced mechanical replies. We also identified playful, meta-aware anthropomorphism, where students tested system limits through role-play. Ultimately, these findings demonstrate that anthropomorphization operates at both passive and active levels of consciousness, heavily influenced by linguistic conventions and disciplinary norms. While this humanization may support learning, it raises critical ethical concerns regarding overtrust, contributing to theoretical discussions of anthropomorphism and AI-supported educational design.
Links and sources
Need this topic turned into a technical roadmap?
Full Self Driving can prepare a custom autonomous driving literature review, code map, dataset map, and B2B technology assessment.
Request B2B research
Comments