FW-HTF-R: Fostering Learning and Adaptability of Future Manufacturing Workers with Intelligent Extended Reality (IXR)

这项研究项目设想了精密制造工作的未来，通过与智能扩展现实(IXR)技术合作，工人的空间和因果推理以及决策能力得到增强。有证据表明，制造业的新一轮自动化浪潮与其说是为了取代工人，不如说是为了补充人工工作，以提高精度、安全性和产品质量。然而，美国制造商没有充分解决技能要求不断变化的性质，预计到2030年，将有240万个制造业工作岗位空缺。该项目将解决对突破性技术的迫切需求，这些技术能够实现基于工作场所的学习，并快速提高制造业劳动力在复杂、认知要求高和难以自动化的任务中的技能。该项目将把重点放在航空工业的精密加工和检查上，作为建立和验证iXR技术的具体工作背景，预计这也将为医疗、汽车、半导体和国防等其他行业的技术发展提供信息。融合研究团队将创造新的技术途径，实现智能Worker-XR合作，并促进对其对劳动力经济和工人学习和创新的影响的基本理解。该项目旨在创造新的视角、方法和发现，以充分释放美国制造业劳动力的潜力，从而加强精密制造业的国家繁荣和经济竞争力。该项目汇集了几个学科，包括工程学、学习科学、社会科学、经济学、计算机科学、心理学和劳动力发展。调查员团队的结构是为了在人类-技术前沿的未来工作的三个维度实现多个趋同目标：(1)未来工作维度将使用1.6亿个在线职位空缺的专有数据库，调查精密制造对雇主技能要求的变化，包括教育程度、工作经验和实际技能。专家访谈、公司层面的调查和深入的案例研究将调查在职和入门级工人的培训和提高技能的做法，探索iXR方法对某些工人和公司群体的可获得性，并确定采用iXR技术的经济障碍和机会。(2)未来技术维度将推动对如何利用XR设备、数字线程、物联网和基于云的分析捕获的多模式数据的新来源来解释、预测和指导精密制造工人的行为的基本理解。将建立并验证一种新颖的iXR技术，该技术采用计算机视觉、自然语言理解和推理引擎的科学方法，为执行复杂推理和解决问题任务的工人提供直观和个性化的帮助。(3)未来工人维度将产生关于Worker-XR团队负担能力的新知识，以支持开发工人适应日益复杂的制造任务的专业知识，建立在学习科学的研究基础上，该研究考察了与复杂推理和解决问题相关的认知过程。预计该项目所产生的知识将为设计未来协作的人类-技术系统提供新的途径，以培训XR以外的成年工人。该项目由人类-技术前沿交叉部门工作未来计划资助，旨在通过推进与人类工人和谐运作的智能工作技术的设计，促进对工作环境中相互依赖的人类-技术伙伴关系的更深层次的基本了解。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This research project imagines the future of work in precision manufacturing where the spatial and causal reasoning and decision-making abilities of workers are augmented through teaming with intelligent extended reality (IXR) technologies. Evidence suggests that the newer wave of automation in manufacturing is not so much to replace workers but rather to complement human work to increase precision, safety, and product quality. Yet, U.S. manufacturers are not adequately addressing the changing nature of skill requirements which is anticipated to leave 2.4 million manufacturing jobs unfilled by 2030. This project will address the urgent need for breakthrough technologies that enable workplace-based learning and rapid upskilling of the manufacturing workforce on complex, cognitively demanding, and hard-to-automate tasks. The project will focus on precision machining and inspection in the aviation industry as the specific work context for building and validating the IXR technologies, which is also expected to inform the technology development in other industries such as medical, automotive, semiconductor, and defense. The convergent research team will create new technological pathways to enable intelligent worker-XR teaming and advance the fundamental understanding of its impacts on labor economy and worker learning and innovation. This project aims to create new perspectives, methods, and discoveries to unleash the full potential of America’s manufacturing workforce, and as such, strengthen national prosperity and economic competitiveness in precision manufacturing.This project brings together several disciplines, including engineering, learning sciences, social sciences, economics, computer sciences, psychology, and workforce development. The investigator team is structured to achieve multiple convergent goals across the three dimensions of the Future of Work at the Human-Technology Frontier: (1) The Future Work dimension will investigate the changes in employer skill requirements for precision manufacturing including education, years of experience, and actual skills, using a proprietary database of 160 million online job vacancies. Expert interviews, firm-level surveys, and in-depth case studies will investigate training and upskilling practices for incumbent and entry-level workers, explore accessibility of the IXR approach for certain groups of workers and firms, and identify economic barriers and opportunities for adopting the IXR technology. (2) The Future Technology dimension will advance the fundamental understanding of how new sources of multimodal data captured by XR devices, digital thread, IoT, and cloud-based analytics can be harnessed to interpret, predict, and guide the behavior of precision manufacturing workers. A novel IXR technology will be built and validated that adapts the scientific methods of computer vision, natural language understanding, and inference engines to provide intuitive and personalized assistance to workers performing complex reasoning and problem-solving tasks. (3) The Future Worker dimension will generate new knowledge about the affordances of worker-XR teaming to support the development of workers’ adaptive expertise for increasingly complex manufacturing tasks, building on research from the learning sciences that examines cognitive processes associated with complex reasoning and problem solving. It is expected that the knowledge generated in this project will elicit new pathways for the design of future collaborative human-technology systems for training adult workers beyond XR. This project has been funded by the Future of Work at the Human-Technology Frontier cross-directorate program to promote a deeper basic understanding of the interdependent human-technology partnership in work contexts by advancing the design of intelligent work technologies that operate in harmony with human workers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.