FW-HTF-R/Collaborative Research: FAIR4WISE: Future AI and Robotics for Women in Smart Engineering

这项人类技术前沿研究(FW-HTF-R)拨款的未来工作将开发一种基于深度学习和区块链认证的新机器人遥操作方法，以增强建筑工人的能力，并促进工作场所的多样性、公平性和包容性。据估计，未来很大一部分建筑工作将通过机器人实现自动化和遥操作。这一过渡可以实现远离危险建筑工地的安全和远程工作，有可能减少妇女进入该行业的障碍，同时也创造一个包容各方的工作环境。与此同时，改善建筑业的性别多样性也很重要，在建筑业，妇女和其他少数族裔工人在劳动力中所占比例不到10%。有鉴于此，该项目将调查在协作和遥控机器人方面的性别差异，并利用所达成的谅解，制定对所有性别都可获得和公平的机器人学习和遥控方法。还将创建一种基于区块链的新机制来评估工人的能力和表现，以提高未来建筑工作的公平性。这项研究还将衡量发达技术对未来建筑工作的影响，表征对工人和组织的预期潜在和意想不到的后果。如果成功，开发的技术生态系统将有助于提高工人的生产率、安全和健康，并使美国工人能够以性别包容的方式在建筑业改革中发挥带头作用。该项目可以打破女性和其他代表性不足的工人面临的许多障碍，打开新的平等工作机会，帮助她们参与劳动力大军，并引导她们过渡到机器人和人工智能时代。这将有利于建筑业和其他多样性较小的领域，如制造业和农业，并导致美国经济增长。该项目汇集了一支跨学科团队，在工程、计算机和信息科学、人为因素、工业和组织心理学、教育和成人培训以及法律事务方面拥有深厚和交叉的专业知识，以实现多种融合目标。首先，该项目将1)开发一个包容性的机器人遥操作界面，适合建筑工人，考虑到与性别相关的多样性和经验，以提高工人的表现；2)设计一个联邦学习机制，用于聚合来自未被充分代表的工人的有限数据，以减轻人工智能和机器人智能开发中的偏见；以及3)开发一个基于区块链的平台，以认证工人的技能能力和表现，以实现可信和公平的招聘、招聘和留住。第二，通过深入的行业参与，本研究将开发一个理论框架和多维影响模型，以1)定量衡量包容性远程操作在多大程度上可以支持性别多样性，并通过工作和任务分析增强工人的能力；2)了解在代表不足的工人更广泛参与的情况下，对建筑工作结构、工作设计和工人自我效能和职业发展的影响；以及3)评估组织层面上从综合技术、经济、社会和法律方面进行适应的机会和障碍。第三，该项目将开发一个新的平台，整合成人学习理论、创新的工程课程以及开发的人工智能和机器人技术，以打破包容性学生学习、劳动力培训和行业网络的界限。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 Future of Work at the Human-Technology Frontier Research (FW-HTF-R) grant will develop a new robot teleoperation method based on deep learning and blockchain certification to augment construction workers’ capability and promote diversity, equity, and inclusiveness in the workplace. By some estimates, a large fraction of construction jobs will be automated and teleoperated with robots in the future. This transition can enable safe and remote work away from hazardous construction sites with the potential to reduce obstacles for women to join the industry while also creating an inclusive work environment. At the same time, it is also important to improve the gender diversity of the construction industry, where women and other minority workers represent less than 10% of the workforce. In light of this, the project will investigate gender differences in collaborating and teleoperating robots, and capitalize on the understandings to develop robot learning and teleoperation methods that are accessible and equitable across genders. A novel blockchain-based mechanism will also be created to assess workers’ competence and performance to improve fairness and equity in future construction jobs. This research will also measure the impacts of developed technologies on future construction work, characterizing the intended potential and unintended consequences on workers and organizations. If successful, the developed technology ecosystem will help improve worker productivity, safety, and health, and equip the U.S. workers to lead the way in the construction industry reform in a gender-inclusive manner. This project can break down many barriers facing women and other underrepresented workers, opening new and equal work opportunities, helping them participate in the workforce, and navigating them in the transitions to the era of robots and artificial intelligence. This will benefit the construction industry and other domains with less diversity such as manufacturing and agriculture and result in U.S. economic growth.This project brings together an interdisciplinary team with deep and cross-cutting expertise in engineering, computer and information science, human factors, industrial and organizational psychology, education and adult training, and legal affairs to achieve multiple convergent objectives. First, this project will 1) develop an inclusive robot teleoperation interface adaptive to construction workers considering gender-related diversity and experience to augment workers’ performance; 2) design a federated learning mechanism for aggregating limited data from underrepresented workers to mitigate bias in AI and robot intelligence development; and 3) develop a blockchain-based platform in certifying workers’ skill competence and performance for trusted and equitable recruitment, hiring, and retaining. Second, with deep industry engagement, this research will develop a theoretical framework and multidimensional impact models to 1) quantitatively measure to what extent inclusive teleoperation can support gender diversity and augment workers’ capability via job and task analysis; 2) understand the impacts on construction work structure, job design, and worker self-efficacy and career development with broader participation of underrepresented workers; and 3) assess the opportunities and barriers at the organizational level for adaptations from integrated technological, economic, social, and legal aspects. Third, this project will develop a new platform integrating adult learning theories, innovative engineering curricula, and the developed artificial intelligence and robot technologies to break the boundaries for inclusive student learning, workforce training, and industry networking.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.