Fairness in Mobile Phone-Based Mental Health Assessment Algorithms: Exploratory Study.

ABSTRACT:

Background

Approximately 1 in 5 American adults experience mental illness every year. Thus, mobile phone-based mental health prediction apps that use phone data and artificial intelligence techniques for mental health assessment have become increasingly important and are being rapidly developed. At the same time, multiple artificial intelligence-related technologies (eg, face recognition and search results) have recently been reported to be biased regarding age, gender, and race. This study moves this discussion to a new domain: phone-based mental health assessment algorithms. It is important to ensure that such algorithms do not contribute to gender disparities through biased predictions across gender groups.

Objective

This research aimed to analyze the susceptibility of mu

SUBMITTER: Park J 

PROVIDER: S-EPMC9240929 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature