Artificial Intelligence in mental health and the biases of language based models.

ABSTRACT:

Background

The rapid integration of Artificial Intelligence (AI) into the healthcare field has occurred with little communication between computer scientists and doctors. The impact of AI on health outcomes and inequalities calls for health professionals and data scientists to make a collaborative effort to ensure historic health disparities are not encoded into the future. We present a study that evaluates bias in existing Natural Language Processing (NLP) models used in psychiatry and discuss how these biases may widen health inequalities. Our approach systematically evaluates each stage of model development to explore how biases arise from a clinical, data science and linguistic perspective.

Design/methods

A literature review of the uses of NLP in mental health was carrie

SUBMITTER: Straw I 

PROVIDER: S-EPMC7745984 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature