The Impact of Transparency in AI Systems on Users' Data-Sharing Intentions: A Scenario-Based Experiment

TL;DR

The study investigates whether transparency (white-box) versus non-transparency (black-box) in AI data-processing affects users' data-sharing intentions, using a pre-registered scenario-based experiment with $N=240$ participants across three conditions (human, white-box AI, black-box AI). It finds no significant differences in willingness to share data across conditions, challenging the notion that transparency alone boosts data-sharing willingness. However, trust in AI positively influences willingness in AI contexts, particularly for white-box AI, while trust in people has limited impact and privacy concerns do not significantly affect decisions. The results suggest that fostering general trust in AI may be more important than transparency alone for encouraging data sharing and highlight implications for designing AI systems that consider trust dynamics and user privacy without overemphasizing transparency.

Abstract

Artificial Intelligence (AI) systems are frequently employed in online services to provide personalized experiences to users based on large collections of data. However, AI systems can be designed in different ways, with black-box AI systems appearing as complex data-processing engines and white-box AI systems appearing as fully transparent data-processors. As such, it is reasonable to assume that these different design choices also affect user perception and thus their willingness to share data. To this end, we conducted a pre-registered, scenario-based online experiment with 240 participants and investigated how transparent and non-transparent data-processing entities influenced data-sharing intentions. Surprisingly, our results revealed no significant difference in willingness to share data across entities, challenging the notion that transparency increases data-sharing willingness. Furthermore, we found that a general attitude of trust towards AI has a significant positive influence, especially in the transparent AI condition, whereas privacy concerns did not significantly affect data-sharing decisions.

Figures (2)

• Figure 1: Research Model
• Figure 2: Simple slopes plots illustrating the relationship between Trust in AI, Trust in People, and Mean Willingness to Share Data for Human, White-box AI, and Black-box AI groups.