Behzad Esmaeili, Assistant Professor, Civil, Environmental and Infrastructure Engineering; Lap-Fai (Craig) Yu, Associate Professor, Computer Science; Maurice Kugler, Professor, Public Policy; and Brenda Bannan, Professor, Learning Design and Technology, Division of Learning Technologies, received funding from the National Science Foundation for the project: "FW-HTF-R: Collaborative Research: Worker-AI Teaming to Enable ADHD Workforce Participation in the Construction Industry of the Future."
While people with attention-deficit/hyperactivity disorder (ADHD) 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 lay the necessary foundations for building this human-AI teaming workspace for construction workers with neurodiversity, this proof-of-concept project will translate noninvasive biomechanical (e.g., posture, gait) and psychophysiological metrics (e.g., brain signals, eye movements, etc.) into information a personalized AI-based training system can assess, model, and leverage to predict workers' behaviors for improved worker-machine teaming.
To achieve this goal, this project will: (1) Use mixed-reality simulated future jobsite settings and biomechanical/psychophysiological metrics to understand ADHD workers' technology interactions during human-machine collaborative tasks; (2) Develop and test AI algorithms to automatically capture interactions and performance and to select and provide optimal real-time feedback interventions in a timely manner to prevent injuries; (3) Examine the negative impacts of wearable technologies and AI, including privacy, security, integrity, usability, and other ethical issues within teaming context; (4) Determine and measure the social and economic impacts of the proposed worker-AI teaming system to enable diverse workforce participation; and (5) Produce an AI-informed training teammate to promote active, cooperative learning and to demonstrate feasibility of human-AI teaming technology. Data collection will take place in a multi-sensor immersive mixed-reality environment consisting of a virtual projection of the environment, passive haptics simulating future construction sites, and environmental modalities that will capture their realistic responses to their AI-teammates and examine human performance measures. The collected data will then be used to develop a multidimensional predictive model to prevent potential incidents. This study will also investigate 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 percent of workers are diagnosed with 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," Esmaeili said.
The researchers received $1,200,000 from NSF for this work. Funding began in October 2021 and will end in late September 2025.
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