How Much Information?

TLDR

The growing use of algorithmic interfaces such as curated news feeds raises new questions for designers, scholars, and media critics. This study investigates how transparent design of algorithmic interfaces can enhance user awareness and foster trust. The authors hypothesize a two‑stage transparency‑trust model grounded in information‑processing and procedural‑justice theory and test it in an online field experiment with three transparency levels during high‑stakes peer assessment. The experiment shows that when expectations are violated, transparency boosts trust, but excessive information erodes it, while satisfied users’ trust is unaffected; overall, balanced transparency is needed to build trust.

Abstract

The rising prevalence of algorithmic interfaces, such as curated feeds in online news, raises new questions for designers, scholars, and critics of media. This work focuses on how transparent design of algorithmic interfaces can promote awareness and foster trust. A two-stage process of how transparency affects trust was hypothesized drawing on theories of information processing and procedural justice. In an online field experiment, three levels of system transparency were tested in the high-stakes context of peer assessment. Individuals whose expectations were violated (by receiving a lower grade than expected) trusted the system less, unless the grading algorithm was made more transparent through explanation. However, providing too much information eroded this trust. Attitudes of individuals whose expectations were met did not vary with transparency. Results are discussed in terms of a dual process model of attitude change and the depth of justification of perceived inconsistency. Designing for trust requires balanced interface transparency - not too little and not too much.