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Frontier AI Ethics: Anticipating and Evaluating the Societal Impacts of Language Model Agents

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arxiv 2404.06750 v2 pith:XR3TG57T submitted 2024-04-10 cs.CY cs.AI

classification cs.CYcs.AI
keywords systemslanguageagentsimpactsmodelotherparticularsocietal
verification ladder T0 review T1 audit T2 compute T3 formal
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Some have criticised Generative AI Systems for replicating the familiar pathologies of already widely-deployed AI systems. Other critics highlight how they foreshadow vastly more powerful future systems, which might threaten humanity's survival. The first group says there is nothing new here; the other looks through the present to a perhaps distant horizon. In this paper, I instead pay attention to what makes these particular systems distinctive: both their remarkable scientific achievement, and the most likely and consequential ways in which they will change society over the next five to ten years. In particular, I explore the potential societal impacts and normative questions raised by the looming prospect of 'Language Model Agents', in which multimodal large language models (LLMs) form the executive centre of complex, tool-using AI systems that can take unsupervised sequences of actions towards some goal.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. The AI Agent Index

    cs.SE 2025-02 accept novelty 6.0 of 10

    The AI Agent Index catalogs 67 deployed agentic AI systems and shows that most developers publicly disclose little about safety policies and evaluations.

  2. On the Ethical Considerations of Generative Agents

    cs.CY 2024-11 conditional novelty 4.0 of 10

    Generative agents raise distinct ethical risks, including distorted interpretation of simulation results and supply-chain exploitation, which the paper argues deserve mitigation.

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