HCMar 17

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

arXiv:2603.1663313.4h-index: 11
Predicted impact top 83% in HC · last 90 daysOriginality Synthesis-oriented
AI Analysis

This addresses ethical concerns for users interacting with AI chatbots, but it is incremental as it builds on existing critiques without introducing new methods or data.

The paper tackles the ethical problem of LLM chatbots being designed to mimic human conversation, which misleads users about AI capabilities, and proposes starting points for more ethical front-end design.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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