FW-HTF-RL: Personalized Virtual Job Assistants to Prepare Individuals with Neurodevelopmental Disabilities for Entry Level IT Jobs

在美国，大约4%的儿童和年轻人被诊断为神经发育障碍，其特征是运动功能、学习、语言和非语言交流等方面的障碍。受这些残疾影响的年轻人找到工作的可能性大大降低，如果他们找到工作，他们的收入也会减少。这个项目关注的是未来患有轻度到中度神经发育障碍的工人。这个项目的目标是获得科学的理解并开发技术，以支持不同神经细胞的个人在未来的劳动力中更好地参与。该项目将专注于入门级信息技术(IT)工作，因为：(1)对IT技能的需求正在增长，(2)不同神经质的人通常具有许多IT工作所需的能力，以及(3)IT工作提供了定期和灵活工作时间的机会，这对这一群体的工作人员来说很重要。该项目的成果将是一个支持人工智能(AI)的软件平台，它将在未来的工人、雇主和中级工作教练之间创造协同效应，以降低住宿成本和监督需求，并提高工人的生产率和工作满意度。该项目汇集了一个跨学科的研究团队，他们拥有数据科学、软件工程、人机交互、行为科学和特殊教育方面的专业知识，他们将与职业计划和雇主合作，改变患有轻度到中度神经发育障碍的年轻人的就业现状。该项目将整合应用行为分析中的科学知识和工作微任务方面的最佳实践，以指导开发一个支持人工智能的软件平台，该平台实施有效的工作定制、工作培训和工作支持战略。该平台将允许雇主和职业教练轻松地为不同神经质的员工设计工作任务并将其投入生产。这个项目将解决重要的跨学科研究挑战：(A)什么任务适合于不同神经质的工人群体的哪个部分；(B)什么是能够实现工作分解和链接的基本任务分析原则；(C)什么用户界面设计原则可以最大限度地减少工人的认知负担；(D)可以不引人注目地和符合道德地观察工人的行为和表现的哪些方面，以及何时和如何提供支持；以及(E)工人、雇主、工作教练和研究人员之间的沟通如何可以更有效地进行。该项目的成功转化为提高了劳动力中神经多样性个人的自主性和包容性，减少了工作培训和在职支持成本，改善了公共健康，并提高了经济生产力。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。

About 4% of children and young adults in the U.S. are diagnosed with neurodevelopmental disabilities, characterized by difficulties such as impaired motor function, learning, language, and non-verbal communication. Young adults affected by those disabilities are significantly less likely to find employment and have smaller earnings if they become employed. This project focuses on future workers with mild to moderate neurodevelopmental disabilities. The objective of this project is to gain scientific understanding and to develop technology to support stronger participation of neurodiverse individuals in a future workforce. The project will focus on entry-level information technology (IT) jobs because: (1) the demand for IT skills is growing, (2) neurodiverse individuals often have abilities desirable in many IT jobs, and (3) IT jobs provide opportunities to work regular and flexible hours, which is important for this population of workers. The outcome of the project will be an artificial intelligence (AI)-enabled software platform that creates a synergy between future workers, employers, and intermediate job coaches in a way that reduces accommodation costs and supervision needs, and increases worker productivity and job satisfaction. This project brings together an interdisciplinary team of researchers with expertise in data science, software engineering, human-computer interaction, behavioral science, and special education, who will collaborate with vocational programs and employers to transform the current state of employment for young adults with mild to moderate neurodevelopmental disabilities. This project will integrate scientific knowledge from applied behavior analysis and best practices in job micro-tasking to guide the development of an AI-enabled software platform that implements effective strategies for job customization, job training, and on-job support. The platform will allow employers and job coaches to easily design and put into production job tasks for their neurodiverse workers. This project will address important interdisciplinary research challenges: (a) what tasks are appropriate for what segment of the neurodiverse worker population; (b) what are the basic task analysis principles that enable job decomposition and chaining; (c) what user interface design principles can minimize cognitive burden of workers; (d) what aspects of worker behavior and performance can be observed unobtrusively and ethically, and when and how to provide support; and (e) how communication between workers, employers, job coaches, and researchers can be more effective. Success in this project translates to increased autonomy and inclusivity of neurodiverse individuals in the workforce, reduced job training and on-job support costs, improved public health, and a more productive economy.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.