Toward Community-Based Natural Language Processing (CBNLP): Cocreating With Communities.

Journal: Journal of medical Internet research
Published Date:

Abstract

Rapid development and adoption of natural language processing (NLP) techniques has led to a multitude of exciting and innovative societal and health care applications. These advancements have also generated concerns around perpetuation of historical injustices and that these tools lack cultural considerations. While traditional health care NLP techniques typically include clinical subject matter experts to extract health information or aid in interpretation, few NLP tools involve community stakeholders with lived experiences. In this perspective paper, we draw upon the field of community-based participatory research, which gathers input from community members for development of public health interventions, to identify and examine ways to equitably involve communities in developing health care NLP tools. To realize the potential of community-based NLP (CBNLP), research and development teams must thoughtfully consider mechanisms and resources needed to effectively collaborate with community members for maximal societal and ethical impact of NLP-based tools.

Authors

  • Malvika Pillai
    Carolina Health Informatics Program, University of North Carolina, Chapel Hill, North Carolina.
  • Ashley C Griffin
    University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Clair A Kronk
    Department of Biomedical Informatics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA.
  • Terika McCall
    Center for Medical Informatics, Yale School of Medicine, New Haven, CT, United States.