Persons or data points? Ethics, artificial intelligence, and the participatory turn in mental health research.

Journal: The American psychologist
PMID:

Abstract

This article identifies and examines a tension in mental health researchers' growing enthusiasm for the use of computational tools powered by advances in artificial intelligence and machine learning (AI/ML). Although there is increasing recognition of the value of participatory methods in science generally and in mental health research specifically, many AI/ML approaches, fueled by an ever-growing number of sensors collecting multimodal data, risk further distancing participants from research processes and rendering them as mere vectors or collections of data points. The imperatives of the "participatory turn" in mental health research may be at odds with the (often unquestioned) assumptions and data collection methods of AI/ML approaches. This article aims to show why this is a problem and how it might be addressed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Authors

  • Joshua August Skorburg
    Duke University, Durham, North Carolina, USA.
  • Kieran O'Doherty
    Department of Psychology, University of Guelph.
  • Phoebe Friesen
    New York University, New York City, USA.