# Listening to the Voices: Describing Ethical Caveats of Conversational User Interfaces According to Experts and Frequent Users

arXiv: https://arxiv.org/abs/2401.14746 · HTML: https://mlsanity.com/paper/2401.14746/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Jan 2024.

## Built on by (most cited first, 8 of 8)

- [Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight](https://mlsanity.com/paper/2509.10723/) (2025)
- [Building Trustworthy Multimodal AI: A Review of Fairness, Transparency, and Ethics in Vision-Language Tasks](https://mlsanity.com/paper/2504.13199/) (2025)
- [Designing AI Personalities: Enhancing Human-Agent Interaction Through Thoughtful Persona Design](https://mlsanity.com/paper/2410.22744/) (2024)
- [Does My Chatbot Have an Agenda? Understanding Human and AI Agency in Human-Human-like Chatbot Interaction](https://mlsanity.com/paper/2601.22452/) (2026)
- [Personas Evolved: Designing Ethical LLM-Based Conversational Agent Personalities](https://mlsanity.com/paper/2502.20513/) (2025)
- [Beyond PII: How Users Attempt to Estimate and Mitigate Implicit LLM Inference](https://mlsanity.com/paper/2509.12152/) (2025)
- ["I Hadn't Thought About That": Creators of Human-like AI Weigh in on Ethics And Neurodivergence](https://mlsanity.com/paper/2506.12098/) (2025)
- [Can AI be a moral victim? The role of moral patiency and ownership perceptions in ethical judgments of using AI-generated content](https://mlsanity.com/paper/2604.26956/) (2026)

## Abstract (arXiv)

Advances in natural language processing and understanding have led to a rapid growth in the popularity of conversational user interfaces (CUIs). While CUIs introduce novel benefits, they also yield risks that may exploit people's trust. Although research looking at unethical design deployed through graphical user interfaces (GUIs) established a thorough understanding of so-called dark patterns, there is a need to continue this discourse within the CUI community to understand potentially problematic interactions. Addressing this gap, we interviewed 27 participants from three cohorts: researchers, practitioners, and frequent users of CUIs. Applying thematic analysis, we construct five themes reflecting each cohort's insights about ethical design challenges and introduce the CUI Expectation Cycle, bridging system capabilities and user expectations while considering each theme's ethical caveats. This research aims to inform future development of CUIs to consider ethical constraints while adopting a human-centred approach.