# The Illusion of Empathy: How AI Chatbots Shape Conversation Perception

arXiv: https://arxiv.org/abs/2411.12877 · HTML: https://mlsanity.com/paper/2411.12877/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 50 references that are in the map.
- First posted on arXiv 19 Nov 2024.

## Builds on (most cited first, 12 of 12)

- [LLM Evaluators Recognize and Favor Their Own Generations](https://mlsanity.com/paper/2404.13076/) (2024)
- [MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer](https://mlsanity.com/paper/2005.00052/) (2020)
- [A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Support](https://mlsanity.com/paper/2009.08441/) (2020)
- [MIME: MIMicking Emotions for Empathetic Response Generation](https://mlsanity.com/paper/2010.01454/) (2020)
- [Recognizing Emotion Cause in Conversations](https://mlsanity.com/paper/2012.11820/) (2020)
- [Harnessing the Power of Large Language Models for Empathetic Response Generation: Empirical Investigations and Improvements](https://mlsanity.com/paper/2310.05140/) (2023)
- [Large Language Models Produce Responses Perceived to be Empathic](https://mlsanity.com/paper/2403.18148/) (2024)
- [Effects of Persuasive Dialogues: Testing Bot Identities and Inquiry Strategies](https://mlsanity.com/paper/2001.04564/) (2020)
- [Empathic Conversations: A Multi-level Dataset of Contextualized Conversations](https://mlsanity.com/paper/2205.12698/) (2022)
- [Are Large Language Models More Empathetic than Humans?](https://mlsanity.com/paper/2406.05063/) (2024)
- [Multi-dimensional Evaluation of Empathetic Dialog Responses](https://mlsanity.com/paper/2402.11409/) (2024)
- [Computer says "No": The Case Against Empathetic Conversational AI](https://mlsanity.com/paper/2212.10983/) (2022)

## Built on by (most cited first, 12 of 12)

- [Humanizing Machines: Rethinking LLM Anthropomorphism Through a Multi-Level Framework of Design](https://mlsanity.com/paper/2508.17573/) (2025)
- [SENSE-7: Taxonomy and Dataset for Measuring User Perceptions of Empathy in Sustained Human-AI Conversations](https://mlsanity.com/paper/2509.16437/) (2025)
- [PERM: Psychology-grounded Empathetic Reward Modeling for Large Language Models](https://mlsanity.com/paper/2601.10532/) (2026)
- [MICA: Multi-granularity Intertemporal Credit Assignment for Long-Horizon Emotional Support Dialogue](https://mlsanity.com/paper/2603.06194/) (2026)
- [Discourse Diversity in Multi-Turn Empathic Dialogue](https://mlsanity.com/paper/2604.11742/) (2026)
- [Dynamic In-Group Persona Generation for Enhancing Human-AI Rapport](https://mlsanity.com/paper/2606.18256/) (2026)
- [RE-LLM: Refining Empathetic Speech-LLM Responses by Integrating Emotion Nuance](https://mlsanity.com/paper/2602.10716/) (2026)
- [EthicMind: A Risk-Aware Framework for Ethical-Emotional Alignment in Multi-Turn Dialogue](https://mlsanity.com/paper/2604.09265/) (2026)
- [Appropriateness of Empathy in AI: A Signal-Cost Perspective](https://mlsanity.com/paper/2605.31340/) (2026)
- [TA-RAG: Tone-Aware Retrieval-Augmented Generation for Peer-Support Health Communication](https://mlsanity.com/paper/2606.06794/) (2026)
- [TA-RAG: Tone Awareness as a Design Imperative for Retrieval-Augmented Generation](https://mlsanity.com/paper/2608.06672/) (2026)
- [How to Run Statistics over LLM Judges and Trust the Results: Calibrated Inference for Small-Sample AI Evaluation with evalstats](https://mlsanity.com/paper/2609.35815/) (2026)

## Abstract (arXiv)

As AI chatbots increasingly incorporate empathy, understanding user-centered perceptions of chatbot empathy and its impact on conversation quality remains essential yet under-explored. This study examines how chatbot identity and perceived empathy influence users' overall conversation experience. Analyzing 155 conversations from two datasets, we found that while GPT-based chatbots were rated significantly higher in conversational quality, they were consistently perceived as less empathetic than human conversational partners. Empathy ratings from GPT-4o annotations aligned with user ratings, reinforcing the perception of lower empathy in chatbots compared to humans. Our findings underscore the critical role of perceived empathy in shaping conversation quality, revealing that achieving high-quality human-AI interactions requires more than simply embedding empathetic language; it necessitates addressing the nuanced ways users interpret and experience empathy in conversations with chatbots.