Negotiating Privacy with Smart Voice Assistants: Risk-Benefit and Control-Acceptance Tensions
For researchers studying privacy paradox in human-computer interaction, this provides a compact measurement approach to capture competing privacy pressures, though it is incremental as it builds on prior work.
This study introduces a negotiation-based framework for youth privacy decision-making with smart voice assistants, operationalizing Risk-Benefit and Control-Acceptance tension indices. Results show both indices are associated with privacy-protective behavior, and frequent users exhibit benefit-dominant and acceptance-leaning profiles, suggesting convenience may reduce perceived control.
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.