In a groundbreaking study, researchers explore the potential of large language models (LLMs) to create software agents that can power augmented democracy systems, enabling citizens to make informed decisions and participate more effectively in the democratic process. By leveraging LLMs' ability to process vast amounts of data, including text-based information, these digital twins can predict individual political choices and aggregate preferences with unprecedented accuracy. The findings suggest that LLMs can improve estimates of aggregate preferences, increase citizen engagement, and provide a more nuanced understanding of citizens' preferences. However, the study also raises important questions about the role of AI in democracy and the potential risks and challenges associated with its use.
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