FW-HTF-R: Collaborative Research: Worker-AI Teaming to Enable ADHD Workforce Participation in the Construction Industry of the Future

虽然由于潜在的更高受伤风险，具有神经多样性的人在建筑工作场所被边缘化，但他们独特的才能可以通过人工智能（AI）驱动的合作机器人生态系统来利用。为了让人类和机器成为真正的队友，也为了让技术为具有这种神经多样性的人提供职业机会，智能机器必须评估、适应和响应工人及其环境。这种敏捷性需要一种相互协作的能力，在这种能力下，工作人员可以让他们的人工智能同行不仅仅是工具，人工智能系统可以通过预测他们的行为与工作人员无缝协作。为了扩大神经多样性人群未来的就业机会，该项目建立了一个人工智能驱动的学习平台，使人工智能队友能够分布在建筑工作场所，以支持具有不同能力的建筑工人的就业机会和安全结果。本研究还调查了人工智能团队的预期工作场景，人工智能团队对工人的意外后果以及社会福祉。考虑到4.2%的工人被诊断患有注意力缺陷/多动障碍（ADHD）-这种疾病与美国每年超过1.2亿个工作日的损失有关，相当于195亿美元的人力资本价值-该项目致力于使建筑行业的多元化劳动力参与将产生积极的社会和经济影响。此外，该项目还将培养新一代人工智能团队领导者，并将在学术界和工业界之间建立合作伙伴关系。为了为具有神经多样性的建筑工人建立这种人类-人工智能团队工作空间奠定必要的基础，该概念验证项目将把非侵入性生物力学和神经心理生理反应转化为基于人工智能的个性化培训系统可以评估，建模，并利用预测工人的行为，以改善工人-机器团队，而不会培养技术过度依赖或对隐私的威胁。在这个项目中，一个多学科的研究团队整合了土木工程，计算机科学，认知和行为心理学，工业工程，公共政策和经济学的专业知识，以解决有关ADHD工人的冒险行为和认知过程的基本问题，采用人工智能和可穿戴技术的障碍，以及改善ADHD诊断工人获得建筑工作的社会经济影响，特别是在相互依赖的人类-人工智能伙伴关系的背景下。随着该项目的全球范式朝着更深层次的人机合作方向发展，通过该项目获得的知识推动了科学和技术的发展，从而影响了工人和整个社会的多样化劳动力发展，教育和积极的工作成果。通过展示这个人工智能驱动的平台的有效性，该项目展示了人机团队如何在工作现场和各个领域的社区内取得进展，以增强人类的认知能力。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

While people with neurodiversity have been marginalized in the construction workplace due to potentially higher risks of injuries, their unique talents could be leveraged using an ecosystem of co-bots driven by artificial intelligence (AI). For humans and machines to become true teammates—and correlatively, for technology to extend occupational opportunities to people with such neurodiversity—intelligent machines must assess, adapt, and respond to both workers and their environment. Such agility requires a reciprocal teaming capability wherein workers can engage their AI counterparts as more than tools, and AI systems can collaborate with workers seamlessly by predicting their behaviors. To extend future occupational opportunities for people with neurodiversity, this project builds an AI-driven learning platform to enable distribution of AI teammates in construction workplaces to support employment opportunities and safety outcomes for construction workers with varying abilities. This study also investigates the intended work scenarios of worker-AI teaming, the unintended consequences of AI-teaming for workers, and the well-being of society. Considering that 4.2% of workers are diagnosed with attention-deficit/hyperactivity disorder (ADHD)—a disorder that is associated with more than 120 million lost workdays in the USA each year, equating to a human capital value of $19.5 billion—this project’s efforts to enable diverse workforce participation in the construction industry will have positive social and economic impacts. Additionally, this project will educate a new generation of leaders in worker-AI teaming and will create partnerships between academia and industry.To lay the necessary foundations for building this human-AI teaming workspace for construction workers with neurodiversity, this proof-of-concept project will translate non‐invasive biomechanical and neuro-psychophysiological responses into information a personalized AI-based training systems can assess, model, and leverage to predict workers’ behaviors for improved worker‐machine teaming without cultivating technological over-reliance or threats to privacy. In this project, a multidisciplinary team of researchers integrates expertise in civil engineering, computer science, cognitive and behavioral psychology, industrial engineering, and public policy and economics to address fundamental questions regarding the risk taking behavior and cognitive processes of workers with ADHD, barriers to adopting AI and wearable technologies, and the socioeconomic impacts of improved access to construction jobs for ADHD-diagnosed workers, especially in the context of interdependent human-AI partnerships. As this project’s global paradigm moves toward deeper human-machine teaming, the knowledge gained through this project advances the science and technology that influences diverse workforce development, education, and positive work outcomes for workers and society at large. By demonstrating the effectiveness of this AI-driven platform, this project illustrates how human-machine teams can progress on job sites and within communities across all sectors to augment human cognitive capabilities.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.