Autonomous driving paper index
AI-Enabled Human-Centric Approaches for Empowering Industrial Digital Immigrants: A Systematic Literature Review
One-line summary
Digital transformation in industrial sectors has created new challenges for digital immigrants whose formative personal and professional experiences predate the advent of digital technologies.
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
Digital transformation in industrial sectors has created new challenges for digital immigrants whose formative personal and professional experiences predate the advent of digital technologies. Most industrial digital transformation initiatives fail to adequately address the technostress experienced by Industrial Digital Immigrants (IDIs). This systematic literature review identifies digital constraints from an IDI-centric perspective, which is currently lacking in the literature. This study also proposes a conceptual framework based on an Artificial Intelligence (AI)-enabled adaptive scaffolding intervention to reduce cognitive load, enhance digital self-efficacy, and improve system usability for IDIs. Within the broader context of Industry 5.0’s core principle of integrating human expertise with intelligent automation, this study proposes a theoretical digital transformation framework to achieve better organisational outcomes and reduce the marginalisation of the IDIs. Furthermore, this framework could support solutions to reduce the digital exclusion of nonindustrial digital immigrants, such as seniors, through its human-centric, adaptive, and cognitively supportive approach.
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