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This study offers a comprehensive discussion of the future role of robots and artificial intelligence (AI) in U.S. recycling under different policy environments and its impact on the workforce. The state of recycling in the U.S. is changing rapidly, with techno-economic developments transforming the efficacy and sustainability of recycling and the workforce it employs. This study describes the technical, social, and policy drivers that influence U.S. municipal solid waste (MSW) management and explores pathways for more sustainable outcomes by focusing on different technology options for the sorting of recyclables in material recovery facilities (MRFs). This study presents four distinct scenario storylines for U.S. recycling by 2050 that contrast recycling and robotic futures, particularly with MRFs that maximize material recovery, worker experience, and economic competitiveness, respectively. This study finds that a recycling scenario defined by strong policy support for recycling and the addition of increasingly flexible, collaborative technology in the form of robotics coupled with AI-driven vision systems, offers the greatest potential for better results. Less certain is the role of MRFs by 2050 based on the full cost for public actors and substantial changes in private industry. Insights from this study can directly inform future techno-economic analyses, technology decisions, and policy recommendations. 

If the material intensive enterprises in an urban area of several million people shared physical resources that might otherwise be wasted, what environmental and public benefits would result? This study develops an algorithm based on lifecycle assessment tools for determining a city’sindustrial symbiosis potential—that is, the sum of the wastes and byproducts from a city’s industrial enterprises that could reasonably serve as resource inputs to other local industrial processes. Rather than report, as do many previous papers, on private benefits to firms, this investigation focuses on public benefits to cities by converting the maximum quantity of resources recoverable by local enterprises into an estimate of the capacity of municipal infrastructure conserved in terms of landfill space and water demand. The results here test this novel approach for the district of Mysuru (Mysore), India. We find that the industrial symbiosis potential calculated based on analysis of the inputs and outputs of ∼1000 urban enterprises, translates into 84 000 tons of industrial waste, greater than 74 000 tons of CO₂e, and 22 million liters per day of wastewater. The method introduced here demonstrates how industrial symbiosis links private production and public infrastructure to improve the resource efficiency of a city by creating an opportunity to extend the capacity of public infrastructure and generate public health co-benefits.