LLM action selection approximates but does not reliably preserve a reference first-order Markov policy in OSN simulations and runs several hundred times slower.
IEEE Security & Privacy22(3), 24–36 (2024)
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
A qualitative comparison finds that features such as administrative data centralization, regulatory gaps, weak oversight, and encoding of protected traits appear in AI systems deployed in both democratic and autocratic regimes.
citing papers explorer
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Should LLM Agents Decide in Social Simulations? Comparing Finite-State and LLM-Based Decision Policies
LLM action selection approximates but does not reliably preserve a reference first-order Markov policy in OSN simulations and runs several hundred times slower.
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From Democracies to Autocracies: How AI Systems Enable Authoritarianism by Design
A qualitative comparison finds that features such as administrative data centralization, regulatory gaps, weak oversight, and encoding of protected traits appear in AI systems deployed in both democratic and autocratic regimes.