Future Impact

Research on future impact focuses on predicting and assessing the consequences of various factors, from technological advancements like AI and machine learning to societal shifts in food security and scientific progress. Current efforts involve developing sophisticated models, including graph neural networks and vector autoregression, to analyze complex datasets like citation networks and time series data on food security indicators. These analyses aim to improve forecasting accuracy and provide actionable insights for diverse fields, ranging from cybersecurity threat prioritization to optimizing human-tool interaction in robotics. Ultimately, this research strives to enhance decision-making and resource allocation by providing quantitative assessments of potential future outcomes.