Mirages: On Anthropomorphism in Dialogue Systems
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Abstract (arXiv)
Automated dialogue or conversational systems are anthropomorphised by developers and personified by users. While a degree of anthropomorphism may be inevitable due to the choice of medium, conscious and unconscious design choices can guide users to personify such systems to varying degrees. Encouraging users to relate to automated systems as if they were human can lead to high risk scenarios caused by over-reliance on their outputs. As a result, natural language processing researchers have investigated the factors that induce personification and develop resources to mitigate such effects. However, these efforts are fragmented, and many aspects of anthropomorphism have yet to be explored. In this paper, we discuss the linguistic factors that contribute to the anthropomorphism of dialogue systems and the harms that can arise, including reinforcing gender stereotypes and notions of acceptable language. We recommend that future efforts towards developing dialogue systems take particular care in their design, development, release, and description; and attend to the many linguistic cues that can elicit personification by users.
Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). Builds on 25 of its 119 references that are in the map. First posted on arXiv 16 May 2023.
Builds on
25 of 119 references.
References · 25
- 2018Personalizing Dialogue Agents: I have a dog, do you have pets too?cited by 820
- 2020The State and Fate of Linguistic Diversity and Inclusion in the NLP Worldcited by 789
- 2018MultiWOZ -- A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modellingcited by 760
- 2022Improving alignment of dialogue agents via targeted human judgementscited by 527
- 2022Neural Theory-of-Mind? On the Limits of Social Intelligence in Large LMscited by 220
- 2020Reducing conversational agents' overconfidence through linguistic calibrationcited by 209
- 2022Talking About Large Language Modelscited by 174
- 2020Recipes for Safety in Open-domain Chatbotscited by 168
- 2023Harms from Increasingly Agentic Algorithmic Systemscited by 134
- 2022ProsocialDialog: A Prosocial Backbone for Conversational Agentscited by 109
- 2022The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systemscited by 92
- 2021On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmarkcited by 73
13 more
- 2021ConvAbuse: Data, Analysis, and Benchmarks for Nuanced Abuse Detection in Conversational AIcited by 46
- 2021Alexa, Google, Siri: What are Your Pronouns? Gender and Anthropomorphism in the Design and Perception of Conversational Assistantscited by 16
- 2021The R-U-A-Robot Dataset: Helping Avoid Chatbot Deception by Detecting User Questions About Human or Non-Human Identitycited by 16
- 2020Living Machines: A study of atypical animacycited by 13
- 2022Report from the NSF Future Directions Workshop on Automatic Evaluation of Dialog: Research Directions and Challengescited by 13
- 2022Risk-graded Safety for Handling Medical Queries in Conversational AIcited by 11
- 2022Computer says "No": The Case Against Empathetic Conversational AIcited by 9
- 2020Developing a Personality Model for Speech-based Conversational Agents Using the Psycholexical Approachcited by 8
- 2022Robots-Dont-Cry: Understanding Falsely Anthropomorphic Utterances in Dialog Systemscited by 8
- 2023"Alexa doesn't have that many feelings": Children's understanding of AI through interactions with smart speakers in their homescited by 8
- 2023ANTONIO: Towards a Systematic Method of Generating NLP Benchmarks for Verificationcited by 6
- 2023Fillers in Spoken Language Understanding: Computational and Psycholinguistic Perspectivescited by 5
- 2015Turing's Red Flagcited by 2
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Citing papers per year: 2023: 4; 2024: 14; 2025: 6; 2026: 6.
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- 2023Evaluating the Social Impact of Generative AI Systems in Systems and Societycited by 91
- 2024"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trustcited by 67
- 2025Creating General User Models from Computer Usecited by 44
- 2025Multi-turn Evaluation of Anthropomorphic Behaviours in Large Language Modelscited by 25
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- 2025A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologiescited by 14
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- 2026Implicit Humanization in Everyday LLM Moral Judgments23 Mar 2026
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- 2025Sycophantic AI Decreases Prosocial Intentions and Promotes Dependence1 Oct 2025
- 2025From Conversation to Orchestration: HCI Challenges and Opportunities in Interactive Multi-Agentic Systems25 Jun 2025
- 2025Creating General User Models from Computer Use16 May 2025
- 2025AI Awareness25 Apr 2025
- 2025A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologies14 Feb 2025
- 2025Multi-turn Evaluation of Anthropomorphic Behaviours in Large Language Models10 Feb 2025
18 more
- 2024Will you donate money to a chatbot? The effect of chatbot anthropomorphic features and persuasion strategies on willingness to donate28 Dec 2024
- 2024Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Models17 Oct 2024
- 2024"I Am the One and Only, Your Cyber BFF": Understanding the Impact of GenAI Requires Understanding the Impact of Anthropomorphic AI11 Oct 2024
- 2024Perceptions of Sentient AI and Other Digital Minds: Evidence from the AI, Morality, and Sentience (AIMS) Survey11 Jul 2024
- 2024Rel-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliance10 Jul 2024
- 2024The Art of Saying No: Contextual Noncompliance in Language Models2 Jul 2024
- 2024Modeling Human Subjectivity in LLMs Using Explicit and Implicit Human Factors in Personas20 Jun 2024
- 2024The Call for Socially Aware Language Technologies3 May 2024
- 2024"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust1 May 2024
- 2024Characterizing and modeling harms from interactions with design patterns in AI interfaces17 Apr 2024
- 2024Behavior Trees Enable Structured Programming of Language Model Agents11 Apr 2024
- 2024From "AI" to Probabilistic Automation: How Does Anthropomorphization of Technical Systems Descriptions Influence Trust?8 Apr 2024
- 2024Towards Goal-oriented Prompt Engineering for Large Language Models: A Survey25 Jan 2024
- 2024Generative Ghosts: Anticipating Benefits and Risks of AI Afterlives14 Jan 2024
- 2023Co-audit: tools to help humans double-check AI-generated content2 Oct 2023
- 2023Evaluating the Social Impact of Generative AI Systems in Systems and Society9 Jun 2023
- 2023AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap2 Jun 2023
- 2023Psychological Metrics for Dialog System Evaluation24 May 2023
- 2025From Conversation to Orchestration: HCI Challenges and Opportunities in Interactive Multi-Agentic Systemscited by 9
- 2026A Scoping Review of the Ethical Perspectives on Anthropomorphising Large Language Model-Based Conversational Agentscited by 2
- 2024Behavior Trees Enable Structured Programming of Language Model Agentscited by 0
- 2026A Scoping Review of the Ethical Perspectives on Anthropomorphising Large Language Model-Based Conversational Agents14 Jan 2026
- 2025From Conversation to Orchestration: HCI Challenges and Opportunities in Interactive Multi-Agentic Systems25 Jun 2025
- 2024Behavior Trees Enable Structured Programming of Language Model Agents11 Apr 2024
- 2023AI Transparency in the Age of LLMs: A Human-Centered Research Roadmapcited by 119
- 2024The Art of Saying No: Contextual Noncompliance in Language Modelscited by 100
- 2023Evaluating the Social Impact of Generative AI Systems in Systems and Societycited by 91
- 2024"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trustcited by 67
- 2025Creating General User Models from Computer Usecited by 44
- 2025Multi-turn Evaluation of Anthropomorphic Behaviours in Large Language Modelscited by 25
- 2024Modeling Human Subjectivity in LLMs Using Explicit and Implicit Human Factors in Personascited by 23
- 2024From "AI" to Probabilistic Automation: How Does Anthropomorphization of Technical Systems Descriptions Influence Trust?cited by 18
- 2024Generative Ghosts: Anticipating Benefits and Risks of AI Afterlivescited by 15
- 2024Rel-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliancecited by 15
- 2024Perceptions of Sentient AI and Other Digital Minds: Evidence from the AI, Morality, and Sentience (AIMS) Surveycited by 15
- 2025A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologiescited by 14
12 most cited of 26 All 26 (JSON)
- 2026Anthropomorphism in the age of Large Language Models: An overview of potential risks and mitigations29 Sep 2026
- 2026Ceci n'est pas une explication: Evaluating Explanation Failures as Explainability Pitfalls in Language Learning Systems28 Apr 2026
- 2026Breaking the Illusion of Identity in LLM Tooling8 Apr 2026
- 2026Implicit Humanization in Everyday LLM Moral Judgments23 Mar 2026
- 2025Sycophantic AI Decreases Prosocial Intentions and Promotes Dependence1 Oct 2025
- 2025Creating General User Models from Computer Use16 May 2025
- 2025AI Awareness25 Apr 2025
- 2025A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologies14 Feb 2025
- 2025Multi-turn Evaluation of Anthropomorphic Behaviours in Large Language Models10 Feb 2025
- 2024Will you donate money to a chatbot? The effect of chatbot anthropomorphic features and persuasion strategies on willingness to donate28 Dec 2024
- 2024Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Models17 Oct 2024
- 2024"I Am the One and Only, Your Cyber BFF": Understanding the Impact of GenAI Requires Understanding the Impact of Anthropomorphic AI11 Oct 2024
12 newest of 26 All 26 (JSON)