Work

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

Year: 2024

Type: article

Abstract: Digital phenotyping, or personal sensing, is a field of research that seeks to quantify traits and characteristics of people using digital technologies, usually for health care purposes. In this commentary, we discuss emerging ethical issues regarding the use of social media as training data for artificial intelligence (AI) models used for digital phenotyping. In particular, we describe the ethical need for explicit consent from social media users, particularly in cases where sensitive information such as labels related to neurodiversity are scraped. We also advocate for the use of community-based participatory design principles when developing health care AI models using social media data.

Source: JMIR Formative Research

DOI: 10.2196/59794

Authors: Aditi Jaiswal, Aekta Shah, Christopher Harjadi, Erik Windgassen, Peter Washington

Institutions: University of Hawaiʻi at Mānoa, University of Hawaii System, Salesforce (United States), University of California, Berkeley, University of California, Riverside

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $1,900

OpenAlex ID: W4399500684

FWCI: 3.544

Cites: 85

Cited by: 11

Related to: 10