Negotiating Privacy with Smart Voice Assistants: Risk-Benefit and Control-Acceptance Tensions

TL;DR

This study introduces a negotiation-based framework with indices to understand how youth balance privacy risks, benefits, and control when using smart voice assistants, revealing that frequent use correlates with more acceptance and perceived benefits.

Contribution

It develops a novel measurement approach using RBTI and CATI indices to capture privacy decision-making tensions among youth in voice assistant environments.

Findings

Both indices are associated with privacy-protective behavior.

Frequent SVA use correlates with benefit-dominant and acceptance-leaning profiles.

Reframes privacy decision-making as negotiation rather than inconsistency.

Abstract

Smart Voice assistants (SVAs) are widely adopted by youth, yet privacy decision-making in these environments is often characterized by competing considerations rather than clear-cut preferences. While our prior research has examined privacy risks, benefits, trust, and self-efficacy as distinct predictors of behavior, less attention has been paid to how these factors combine into higher-level tension that shapes privacy outcomes. This study introduces a negotiation-based framework for understanding youth privacy decision-making with SVAs by operationalizing two composite indices: the Risk-Benefit Tension Index (RBTI) and the Control-Acceptance Tension Index (CATI), using survey data from 469 Canadian youth aged 16-24. We examine the distribution of these indices and their relationship with privacy-protective behavior and SVA usage. Results show that both indices are meaningfully associated with protective action. Frequent SVA usage exhibits more benefit-dominant and acceptance-leaning negotiation profiles, suggesting that convenience-driven engagement may come at the expense of perceived control. By reframing privacy decision-making as a process of negotiation rather than inconsistency, this study offers a complementary perspective on the privacy paradox and provides a compact measurement approach for capturing how youth navigate competing privacy pressures in voice-enabled ecosystems.