The Importance of Global Policy, Public-Private Partnerships and Equity in the Development of a Pilot AI-Based Predictive Tool as Part of the U.S Circular Economy

Kazue Chinen, Bureau of Oceans and International Environmental and Scientific Affairs/Office of Science, Technology and Cooperation
Supercomputer showdown

Description: According to a 2020 National Geographic article, the U.S. produces the most plastic worldwide. Despite a strong interest from U.S.-based industry to reduce plastic pollution, plastic production and pollution continue to fill our landfills and marine environment with vulnerable nations bearing the brunt of the negative impacts.  Several technical approaches to control plastic waste have gained traction. Green chemistry has helped to increase biodegradability though also decreases recycling potential. In silico models such as quantitative structure-activity relationship (QSAR) and AI models use data to either train a model or an algorithm to predict endpoints for untested chemicals. Yet, despite the benefits of this cutting-edge technology, plastic waste continues to build and seep into our environment due to policy loopholes and non-standardized toxicity criteria[KC4] . I propose an AI-based regulatory tool that is designed in conjunction with science for society and contributes to the movement of a global plastics treaty.  This cost-effective tool will be designed in collaboration with and for a single-use plastic source such as DOW, [KC5] drawing on input from vulnerable communities, and with interagency and international consultation including OSTP’s new energy division, the USEPA and UNEP.

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