LATIDIA · Ciberseguridad

Modelos de lenguaje grandes y democracia aumentada

arXiv: 2610.04412v1Tipo de anuncio: cruz Resumen: La inteligencia artificial permite a los agentes computacionales representar preferencias políticas y participar en la toma de decisiones colectivas. En esta tesis, investigo el opp

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arXiv:2610.04412v1 Announce Type: cross Abstract: Artificial intelligence enables computational agents to represent political preferences and take part in collective decision-making. In this thesis, I investigate the opportunities and challenges of digital twins (DTs) based on Large Language Models (LLMs) as intermediaries in augmented democracy, focusing on individual preference representation, collective representation of political organizations, and the vulnerability of those representations to attackers. First, using data from an online experiment in Brazil, I examine whether personalized DTs can predict citizens' preferences for unseen policy proposals. Second, I extend the DT framework from individuals to political organizations. Using Swiss parliamentary data, I build topic-specific knowledge graphs from lawmakers' legislative records and connect