Social Energy System Design Incorporating AI and Lived Experience

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Many research achievements have been made under this research plan. Firstly, the theoretical underpinnings of machine learning and prediction of environmental and social equity preferences of stakeholders via existing data sets (previously undertaken surveys) was established and reported in research currently under review at Applied Energy. The manuscript details multiple machine learning algorithmic approaches to energy system design preferences and the effects of imcreasing training data toward accuracy rates. Based on these findings, a national survey was designed and deployed, specifically to achieve a low-burden, high yield predictive data set which will be leveraged in the coming year. Currently this data is being used to underpin efforts toward a prediciton and visualization tool.