mlsanityData to 7 Oct 2026

Large Language Models as Instruments of Power: New Regimes of Autonomous Manipulation and Control

arXiv 2405.03813 ↗First posted 6 May 2024cs.SI cs.CYcited by 10

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Abstract (arXiv)

Large language models (LLMs) can reproduce a wide variety of rhetorical styles and generate text that expresses a broad spectrum of sentiments. This capacity, now available at low cost, makes them powerful tools for manipulation and control. In this paper, we consider a set of underestimated societal harms made possible by the rapid and largely unregulated adoption of LLMs. Rather than consider LLMs as isolated digital artefacts used to displace this or that area of work, we focus on the large-scale computational infrastructure upon which they are instrumentalised across domains. We begin with discussion on how LLMs may be used to both pollute and uniformize information environments and how these modalities may be leveraged as mechanisms of control. We then draw attention to several areas of emerging research, each of which compounds the capabilities of LLMs as instruments of power. These include (i) persuasion through the real-time design of choice architectures in conversational interfaces (e.g., via "AI personas"), (ii) the use of LLM-agents as computational models of human agents (e.g., "silicon subjects"), (iii) the use of LLM-agents as computational models of human agent populations (e.g., "silicon societies") and finally, (iv) the combination of LLMs with reinforcement learning to produce controllable and steerable strategic dialogue models. We draw these strands together to discuss how these areas may be combined to build LLM-based systems that serve as powerful instruments of individual, social and political control via the simulation and disingenuous "prediction" of human behaviour, intent, and action.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 May 2024.

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Citing papers per year: 2024: 2; 2025: 7; 2026: 1.

10 papers.

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  1. 2024Comparing Rationality Between Large Language Models and Humans: Insights and Open Questions
  2. 2026From Tokens To Agents: A Researcher's Guide To Understanding Large Language Models
  3. 2024Systematic Biases in LLM Simulations of Debates
  4. 2025Computational Basis of LLM's Decision Making in Social Simulation
  5. 2025Can (A)I Change Your Mind?
  6. 2026When Agents Persuade: Rhetoric Generation and Mitigation in LLMs
  7. 2025Stop saying LLM: Large Discourse Models (LDM) and Artificial Discursive Agent (ADA)?
  8. 2025From the Fluency Fallacy to the Micro-to-Macro Validity Gap: Opportunities and Pitfalls of LLMs in Social Simulation