This paper is in the following e-collection/theme issue:

Commentary (1) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1911) Infodemiology and Infoveillance (1558) Infoveillance and Social Listening (313) Autism Spectrum Disorder (ASD) (141) Artificial Intelligence (2117) Machine Learning (2070) Diagnostic Tools in Mental Health (325)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59794, first published .
Ethics of the Use of Social Media as Training Data for AI Models Used for Digital Phenotyping

Ethics of the Use of Social Media as Training Data for AI Models Used for Digital Phenotyping

Ethics of the Use of Social Media as Training Data for AI Models Used for Digital Phenotyping

Authors of this article:

Aditi Jaiswal1 Author Orcid Image ;   Aekta Shah2 Author Orcid Image ;   Christopher Harjadi3 Author Orcid Image ;   Erik Windgassen4 Author Orcid Image ;   Peter Washington1 Author Orcid Image
Article Authors Cited by (6) Tweetations Metrics

Journals

  1. Gardasevic S, Jaiswal A, Lamba M, Funakoshi J, Chu K, Shah A, Sun Y, Pokhrel P, Washington P. Public Health Using Social Network Analysis During the COVID-19 Era: A Systematic Review. Information 2024;15(11):690 View
  2. Zhang Y, Wang J, Zong H, Singla R, Ullah A, Liu X, Wu R, Ren S, Shen B. The comprehensive clinical benefits of digital phenotyping: from broad adoption to full impact. npj Digital Medicine 2025;8(1) View
  3. Otero P, Menéndez-Blázquez J, March D. Challenges of passive citizen science in ecology within a shifting social media landscape. Ecological Informatics 2025;90:103278 View

Books/Policy Documents

  1. Mittal S, Chandel A, Nguyen P. Improving Entrepreneurial Processes Through Advanced AI. View
  2. Chambers S, Kelley M. Artificial Intelligence in Education. View
  3. Chao C, Hsu P, Wei X, See T. Multidisciplinary Social Networks Research. View