Healthcare Informatics & Health Information Technology (SIG Health)

Loading...

Media is loading
 

Paper Type

Complete

Paper Number

1146

Description

Contact-tracing apps are considered one of the core information technologies to help contain the spread of the COVID-19 pandemic. However, they need to be adopted broadly to be effective. In this study, we apply the concept of algorithmic transparency (AT) to contact-tracing apps and hypothesize that users prefer apps with a high level of disclosure of information about the app's inner workings (referred to as transformation AT) and that disclosure increases user comprehension and trust. We empirically validate our hypotheses through an online experiment with 116 participants. We find that the level of transformation AT of a contact-tracing app is positively related to users' adoption behavior, comprehension, and trust.

Share

COinS
Top 25 Percent Paper badge
 
Aug 9th, 12:00 AM

Algorithmic Transparency and Contact-tracing Apps – An Empirical Investigation

Contact-tracing apps are considered one of the core information technologies to help contain the spread of the COVID-19 pandemic. However, they need to be adopted broadly to be effective. In this study, we apply the concept of algorithmic transparency (AT) to contact-tracing apps and hypothesize that users prefer apps with a high level of disclosure of information about the app's inner workings (referred to as transformation AT) and that disclosure increases user comprehension and trust. We empirically validate our hypotheses through an online experiment with 116 participants. We find that the level of transformation AT of a contact-tracing app is positively related to users' adoption behavior, comprehension, and trust.

When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.