# Impact of Voice Fidelity on Decision Making: A Potential Dark Pattern?

arXiv: https://arxiv.org/abs/2402.07010 · HTML: https://mlsanity.com/paper/2402.07010/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Feb 2024.

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

- [GPT-4o System Card](https://mlsanity.com/paper/2410.21276/) (2024)
- [Toward Metaphor-Fluid Conversation Design for Voice User Interfaces](https://mlsanity.com/paper/2502.11554/) (2025)
- [Disclosure By Design: Identity Transparency as a Behavioural Property of Conversational AI Models](https://mlsanity.com/paper/2603.16874/) (2026)
- [The Voice: Lessons on Trustworthy Conversational Agents from "Dune"](https://mlsanity.com/paper/2407.18928/) (2024)
- [RealityTest: How People Probe AI Identity and Whether Models Disclose It](https://mlsanity.com/paper/2606.00168/) (2026)
- [Predicting Biased Human Decision-Making with Large Language Models in Conversational Settings](https://mlsanity.com/paper/2601.11049/) (2026)
- [Emulating Aggregate Human Choice Behavior and Biases with GPT Conversational Agents](https://mlsanity.com/paper/2602.05597/) (2026)
- [A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing](https://mlsanity.com/paper/2606.05330/) (2026)

## Abstract (arXiv)

Manipulative design in user interfaces (conceptualized as dark patterns) has emerged as a significant impediment to the ethical design of technology and a threat to user agency and freedom of choice. While previous research focused on exploring these patterns in the context of graphical user interfaces, the impact of speech has largely been overlooked. We conducted a listening test (N = 50) to elicit participants' preferences regarding different synthetic voices that varied in terms of synthesis method (concatenative vs. neural) and prosodic qualities (speech pace and pitch variance), and then evaluated their impact in an online decision-making study (N = 101). Our results indicate a significant effect of voice qualities on the participant's choices, independently from the content of the available options. Our results also indicate that the voice's perceived engagement, ease of understanding, and domain fit directly translate to its impact on participants' behaviour in decision-making tasks.