# A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologies

arXiv: https://arxiv.org/abs/2502.09870 · HTML: https://mlsanity.com/paper/2502.09870/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- Builds on 19 of its 121 references that are in the map.
- First posted on arXiv 14 Feb 2025.

## Builds on (most cited first, 19 of 19)

- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://mlsanity.com/paper/2303.12712/) (2023)
- [Improving alignment of dialogue agents via targeted human judgements](https://mlsanity.com/paper/2209.14375/) (2022)
- [The Design and Implementation of XiaoIce, an Empathetic Social Chatbot](https://mlsanity.com/paper/1812.08989/) (2018)
- [The Ethics of Advanced AI Assistants](https://mlsanity.com/paper/2404.16244/) (2024)
- [Could a Large Language Model be Conscious?](https://mlsanity.com/paper/2303.07103/) (2023)
- ["I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust](https://mlsanity.com/paper/2405.00623/) (2024)
- [Believing Anthropomorphism: Examining the Role of Anthropomorphic Cues on Trust in Large Language Models](https://mlsanity.com/paper/2405.06079/) (2024)
- [Mirages: On Anthropomorphism in Dialogue Systems](https://mlsanity.com/paper/2305.09800/) (2023)
- ['Simulacrum of Stories': Examining Large Language Models as Qualitative Research Participants](https://mlsanity.com/paper/2409.19430/) (2024)
- [From "AI" to Probabilistic Automation: How Does Anthropomorphization of Technical Systems Descriptions Influence Trust?](https://mlsanity.com/paper/2404.16047/) (2024)
- [Beyond Behaviorist Representational Harms: A Plan for Measurement and Mitigation](https://mlsanity.com/paper/2402.01705/) (2024)
- [The R-U-A-Robot Dataset: Helping Avoid Chatbot Deception by Detecting User Questions About Human or Non-Human Identity](https://mlsanity.com/paper/2106.02692/) (2021)
- ["Look! It's a Computer Program! It's an Algorithm! It's AI!": Does Terminology Affect Human Perceptions and Evaluations of Algorithmic Decision-Making Systems?](https://mlsanity.com/paper/2108.11486/) (2021)
- ["One-Size-Fits-All"? Examining Expectations around What Constitute "Fair" or "Good" NLG System Behaviors](https://mlsanity.com/paper/2310.15398/) (2023)
- [Characterizing and modeling harms from interactions with design patterns in AI interfaces](https://mlsanity.com/paper/2404.11370/) (2024)
- [Exploring Interactions Between Trust, Anthropomorphism, and Relationship Development in Voice Assistants](https://mlsanity.com/paper/2108.01923/) (2021)
- [Robots-Dont-Cry: Understanding Falsely Anthropomorphic Utterances in Dialog Systems](https://mlsanity.com/paper/2210.12429/) (2022)
- ["I Am the One and Only, Your Cyber BFF": Understanding the Impact of GenAI Requires Understanding the Impact of Anthropomorphic AI](https://mlsanity.com/paper/2410.08526/) (2024)
- [How ChatGPT Changed the Media's Narratives on AI: A Semi-Automated Narrative Analysis Through Frame Semantics](https://mlsanity.com/paper/2408.06120/) (2024)

## Built on by (most cited first, 14 of 14)

- [Inference-Time Scaling for Complex Tasks: Where We Stand and What Lies Ahead](https://mlsanity.com/paper/2504.00294/) (2025)
- [Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is Missing](https://mlsanity.com/paper/2507.10587/) (2025)
- [TALES: A Taxonomy and Analysis of Cultural Representations in LLM-generated Stories](https://mlsanity.com/paper/2511.21322/) (2025)
- [Computational Hermeneutics: Evaluating generative AI as a cultural technology](https://mlsanity.com/paper/2604.16403/) (2026)
- [When AI Gives Advice: Evaluating AI and Human Responses to Online Advice-Seeking for Well-Being](https://mlsanity.com/paper/2512.08937/) (2025)
- [The Psychology of Learning from Machines: Anthropomorphic AI and the Paradox of Automation in Education](https://mlsanity.com/paper/2601.06172/) (2026)
- [Chaplains' Reflections on the Design and Usage of AI for Conversational Care](https://mlsanity.com/paper/2602.04017/) (2026)
- [Human Thinking under Plural LLM Assistance: Mathematical Problem Solving and Open-Ended Writing](https://mlsanity.com/paper/2604.02677/) (2026)
- [Breaking the Illusion of Identity in LLM Tooling](https://mlsanity.com/paper/2604.07398/) (2026)
- [Measuring Successful Cooperation in Human-AI Teamwork: Development and Validation of the Perceived Cooperativity and Teaming Perception Scales](https://mlsanity.com/paper/2604.24461/) (2026)
- [Playing Games with My Heart: An Evaluation of AI Companion Apps](https://mlsanity.com/paper/2605.08093/) (2026)
- [When AI Says "I have been in similar situations": Synthetic Lived Experience in Peer-Like Caregiver Support](https://mlsanity.com/paper/2606.18057/) (2026)
- [Examining Human-Like Behaviors in LLMs: A Multi-Dimensional Analysis of Model Behaviors, User Factors, and System Prompts](https://mlsanity.com/paper/2606.18258/) (2026)
- [Psychological Influences of Conversational AI: Research and Design Directions for Reducing Harm and Promoting Well-Being](https://mlsanity.com/paper/2607.25057/) (2026)

## Abstract (arXiv)

Recent attention to anthropomorphism -- the attribution of human-like qualities to non-human objects or entities -- of language technologies like LLMs has sparked renewed discussions about potential negative impacts of anthropomorphism. To productively discuss the impacts of this anthropomorphism and in what contexts it is appropriate, we need a shared vocabulary for the vast variety of ways that language can be anthropomorphic. In this work, we draw on existing literature and analyze empirical cases of user interactions with language technologies to develop a taxonomy of textual expressions that can contribute to anthropomorphism. We highlight challenges and tensions involved in understanding linguistic anthropomorphism, such as how all language is fundamentally human and how efforts to characterize and shift perceptions of humanness in machines can also dehumanize certain humans. We discuss ways that our taxonomy supports more precise and effective discussions of and decisions about anthropomorphism of language technologies.