Work with AI and Work for AI: Autonomous Vehicle Safety Drivers’ Lived Experiences

要旨

The development of Autonomous Vehicle (AV) has created a novel job, the safety driver, recruited from experienced drivers to supervise and operate AV in numerous driving missions. Safety drivers usually work with non-perfect AV in high-risk real-world traffic environments for road testing tasks. However, this group of workers is under-explored in the HCI community. To fill this gap, we conducted semi-structured interviews with 26 safety drivers. Our results present how safety drivers cope with defective algorithms and shape and calibrate their perceptions while working with AV. We found that, as front-line workers, safety drivers are forced to take risks accumulated from the AV industry upstream and are also confronting restricted self-development in working for AV development. We contribute the first empirical evidence of the lived experience of safety drivers, the first passengers in the development of AV, and also the grassroots workers for AV, which can shed light on future human-AI interaction research.

著者
Mengdi Chu
Tsinghua University, Beijing, China
Keyu Zong
Tsinghua University, Beijing, China
Xin Shu
Tsinghua Huniversity, Beijing, Beijing, China
Jiangtao Gong
Tsinghua University, Beijing, China
Zhicong Lu
City University of Hong Kong, Hong Kong, China
Kaimin Guo
Tsinghua university, Beijing, China
Xinyi Dai
Tsinghua University, Beijing, China
Guyue Zhou
Tsinghua University, Beijing, China
論文URL

https://doi.org/10.1145/3544548.3581564

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Transportation and AI/ML

Hall G1
5 件の発表
2023-04-26 18:00:00
2023-04-26 19:30:00