A conceptual framework classifies anthropomorphic deception into four levels using humanlikeness, agency, and selfhood to guide ethical and practical decisions in HCI and HRI.
Characterizing Manipulation from AI Systems, October 2023
3 Pith papers cite this work. Polarity classification is still indexing.
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LLM-based persuasion systems frequently match or exceed human effectiveness across domains, with key influences from interaction style, model scale, prompt design, and personalization, while posing risks to information integrity, fairness, privacy, and autonomy.
TrustLLM defines eight trustworthiness principles, creates a six-dimension benchmark, and evaluates 16 LLMs showing proprietary models generally lead but some open-source ones are close while over-calibration can hurt utility.
citing papers explorer
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Towards A Framework for Levels of Anthropomorphic Deception in Robots and AI
A conceptual framework classifies anthropomorphic deception into four levels using humanlikeness, agency, and selfhood to guide ethical and practical decisions in HCI and HRI.
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Persuasion with Large Language Models: A Survey of Empirical Evidence, Study Methodologies, and Ethical Implications
LLM-based persuasion systems frequently match or exceed human effectiveness across domains, with key influences from interaction style, model scale, prompt design, and personalization, while posing risks to information integrity, fairness, privacy, and autonomy.
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TrustLLM: Trustworthiness in Large Language Models
TrustLLM defines eight trustworthiness principles, creates a six-dimension benchmark, and evaluates 16 LLMs showing proprietary models generally lead but some open-source ones are close while over-calibration can hurt utility.