Convergence Accelerator Phase I (RAISE): Developing Intelligent Tech. for Workforce Empowerment: Credential Gap Diagnostics and Personalized Recommenders for Jobs and Retraining

NSF融合加速器支持以团队为基础的多学科努力，解决国家重要性的挑战，并在不久的将来显示出可交付成果的潜力。“融合加速器”第一阶段项目的更广泛影响/潜在效益源于其对整合研究、创新和教育以应对社会挑战的关注。它将开发新的人工智能（AI）技术和创新的教育模块，以解决多个方面的技能提升、再就业和人工智能伦理问题。我们将建立可扩展的推荐系统，以增强提高技能和再就业的公共基础设施，增加学术界与工业界的合作伙伴关系，并在人工智能招聘时代开发关于道德、可转移软技能和工作申请策略的多学科教育模块。我们的跨学科团队汇集了计算机科学、工业工程、技术通信、哲学、医疗保健和心理学方面的专业知识。我们的目标是通过开发一个免费的、可访问的个性化人工智能用户界面原型来提供再就业支持，以帮助当前和未来的工人进行再培训和技能提升。通过学术界-工业界-社区的合作，我们将整合不同的观点，开发、测试和评估面向公众的证书差距诊断、面试概率分析以及再培训和工作推荐系统。将提供一个向公众开放的门户网站，作为所有研究和教学资料的中央交换中心。这个项目的成功将使我们能够为未来的工人建立一个“再就业准备和技能提升谷歌”，并为再培训项目建立一个“服务超市优步”。这个融合加速器第一阶段项目旨在开发我们所知的第一个面向公众的人工智能平台，帮助个体工人在日益以自动化、技术颠覆和人工智能招聘为特征的劳动力市场中提高技能和再就业。为了开始一场再培训革命，我们将在现实世界的数据上开发、实施和测试一套新的自然语言处理、数据挖掘、机器学习和匹配算法。同时，将在人工智能伦理、人工智能辅助招聘、软技能转移等方面进行前沿研究，以应对劳动力赋权的挑战。以制造业为重点，该项目将为机器操作开发再就业支持，预计到2026年，机器操作将失去约20%的工作岗位。它用工作职责、能力、技能、需要互补技能的职业以及地理上分散的再培训资源等数据来训练创新的人工智能工具。然后，这些人工智能工具在提供个性化建议之前，自动进行证书差距诊断和面试概率分析。该项目承诺通过可扩展的技术解决方案、自然语言处理、算法审计和道德审查，推进劳动力赋权、专业沟通和人工智能伦理的前沿。将实施人工智能驱动工具包的原型，以探索人工智能辅助劳动力赋权的技术要求和可扩展性。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The NSF Convergence Accelerator supports team-based, multidisciplinary efforts that address challenges of national importance and show potential for deliverables in the near future. The broader impact/potential benefit of this Convergence Accelerator Phase I project results from its focus on the integration of research, innovation, and education to address societal challenges. It will develop new Artificial Intelligence (AI) technologies and innovative educational modules to tackle upskilling, reemployment, and AI ethics on multiple fronts. We will build scalable recommendation systems to enhance the public infrastructure of upskilling and reemployment, increase academia-industry partnerships, and develop multidisciplinary educational modules on ethics, transferrable soft skills, and job application strategies in the era of AI recruitment. Our interdisciplinary team brings expertise in computer science, industrial engineering, technical communication, philosophy, healthcare, and psychology. Our goal is to provide reemployment support by developing a free, accessible prototype of a personalized AI-driven user interface to help current and future workers with retraining and upskilling. Integrating diverse perspectives through academia-industry-community partnerships, we will develop, test, and evaluate public-facing credential gap diagnostics, interview probability analytics, and reskilling and job recommendation systems. A publicly accessible web portal will be provided as the central clearinghouse for all research and teaching materials. Success in this project will enable us to build a "Google of reemployment preparation and upskilling" for future workers and a "service supermarket Uber" for retraining programs. This Convergence Accelerator Phase I project aims to develop what we know to be the first public-facing AI platform that assists individual workers with upskilling and reemployment in a labor market increasingly characterized by automation, technological disruption, and AI recruiting. To start a retraining revolution, we will develop, implement, and test, on real-world data, a novel set of natural language processing, data mining, machine learning, and matching algorithms. Meanwhile, cutting-edge research will be conducted on AI ethics, AI-assisted recruiting, and soft skill transfer to address the challenges of workforce empowerment. Focusing on manufacturing, this project will develop reemployment support for machine operation, an occupation predicted to lose about 20% jobs to automation by 2026. It trains innovative AI tools with data about job responsibilities, competences, skills, occupations requiring complementary skills, and geographically scattered retraining resources. These AI tools then automate credential gap diagnostics and interview probability analysis before delivering personalized recommendations. This project promises to advance the frontier of workforce empowerment, professional communication, and AI ethics with scalable technical solutions, natural language processing, algorithm audits, and ethics reviews. A prototype of the AI-driven toolkit will be implemented to explore the technical requirements and scalability of AI-assisted workforce empowerment.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.