This Future of Work at the Human-Technology Frontier (FW-HTF) project will investigate the appropriate development and deployment of collaborative robots to transform profitability, productivity, safety, sustainability, and worker quality of life in the seafood processing industry, where harsh conditions and demanding and dangerous tasks challenge the capabilities of humans and robots alike. The result will be designs, tools, methods, and datasets to facilitate seamless human-robot collaboration. Soft robot manipulators will augment the safe and reliable handling of slippery, scaly, and flexible objects. Emerging capabilities in artificial intelligence will assist in identifying and inspecting varieties of fish and shellfish. Critical to the project is understanding how best to allocate specific tasks among robot and human workers, integrating a complex set of desired outcomes, across scales of individual workers, independent businesses, domestic and migrant labor markets, national economic sectors, and global trade, while respecting environmental and ethical constraints. Associated educational and outreach programs will empower engineers, design experts, and social scientists how to address challenges at the convergence of robotics and manipulation, artificial intelligence, human-robot collaboration, ethics, and labor economics. Training programs will develop a new cadre of learners and researchers in data, technology and human literacies. In 2017, the US imported record amounts of seafood, corresponding to a trade deficit of more than $17 billion. Due to low domestic unemployment and obstacles to employing migrant labor, the US seafood processing industry has been unable to meet US consumer demand. This project will advance US leadership in a globally competitive and domestically underserved industry, while simultaneously advancing understanding of key scientific, engineering, and societal challenges.
The research goals of the project will impact five interconnected and convergent areas, namely (i) collaborative robotics and shared autonomy, (ii) interaction design with data visualizations, (iii) labor economics in seafood industry, (iv) ethics of autonomy in the workplace, (v) workforce training and new skills learning. To address shortcomings of today?s human-robot co-worker teams, the research plan aims to dramatically enhance productivity in complex environments, while paying specific attention to factors affecting user acceptability. The team will emphasize the integration of robotic systems in the existing socio-technical context -- existing machinery and tools and existing human work practices, including formal and informal modalities ? to develop an approach of ambient and distributed robotics, rather than individual robot interventions. The research plan develops a constellation of design requirements for systems through user-centered design and ideation activities, iteratively advancing model-based and data-driven methods, validating designs through usability studies, and assessing the societal and economic impact of technologies to impact the future of work. The project incorporates and builds upon improvisation in the everyday seafood processing plant workplace, to design and validate robot co-worker competencies. Complementing the technological objectives, the project includes human-subject studies to address ethical issues raised by the adoption of robotics in the workplace. Addressing these issues -- which include challenges specific to a labor context with immigrant labor, low wages, and harsh working conditions -- is essential to successful robotics integration and adoption. Finally, the project will evaluate the economic impact of automation on both workers and companies in this emerging socio-technological landscape to understand both the costs and the benefits of adopting new technologies that will shape the future workplace.
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.
