Why We Need to Destroy the Illusion of Speaking to A Human: Critical Reflections On Ethics at the Front-End for LLMs

2026-03-17

AI Summary

This study addresses the cognitive biases and ethical risks arising from users’ misattribution of human-like capacities to large language model (LLM)-driven chatbots. Drawing on philosophical inquiry and human-computer interaction theory, the authors develop a critical analytical framework to systematically examine the fundamental differences between human–LLM interactions and genuine interpersonal dialogue. The work argues for proactively dispelling the “anthropomorphic illusion” through intentional front-end design and advocates for ethical interaction principles centered on transparency and honesty. By clarifying the ontological and functional boundaries between human and artificial agents, this research offers theoretical guidance for designing LLM interfaces that foster more responsible and trustworthy AI interactions.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Humans versus LLMs for data annotation and labeling

Abstract

Conversation with chatbots based on Large Language Models (LLMs) such as ChatGPT has become one of the major forms of interaction with Artificial Intelligence (AI) in everyday life. What makes this interaction so convenient is that interacting with LLMs feels so natural, and resembles what we know from real, human conversations. At the same time, this seeming similarity is part of one of the ethical challenges of AI design, since it activates many misleading ideas about AI. We discuss similarities and differences between human-AI-conversations and interpersonal conversation and highlight starting points for more ethical design of AI at the front-end.

Problem

• Large Language Models
• human-AI interaction
• ethical design
• conversational AI
• illusion of humanity

Innovation

• ethical AI design
• human-AI interaction
• LLM front-end
• conversation illusion
• responsible AI