Autonomous driving paper index
Standing On The Shoulders Of Paperclips: A Taxonomy Of Human-Centered Ai Systems
One-line summary
To address this lack of clarity, we develop a taxonomy that systematically characterizes human‑centered AI systems based on their representation and capabilities.
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
Existing descriptions of AI roles in human‑AI collaboration remain inconsistent and often contradictory. For example, some define AI assistants as strictly reactive, while others attribute them with proactive behavior. To address this lack of clarity, we develop a taxonomy that systematically characterizes human‑centered AI systems based on their representation and capabilities. The taxonomy was created through an iterative process combining conceptual reasoning and empirical analysis of literature artifacts and comprises 10 dimensions with 37 characteristics. The findings show that most systems maintain human decision authority while varying in autonomy, personification, and transparency. Organizations increasingly employ anthropomorphic designs and natural language communication to strengthen social presence and improve task performance. The taxonomy provides a structured framework for defining AI roles within collaborative settings and offers orientation for researchers seeking conceptual clarity as well as guidance for practitioners designing effective human‑centered AI systems.
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