Work

Individuals and (Synthetic) Data Points: Using Value-Sensitive Design to Foster Ethical Deliberations on Epistemic Transitions

Year: 2023

Type: article

Abstract: Cho & Martinez-Martin (2023) provide a compelling critique of the profound influence that data sourcing for artificial intelligence (AI) has on the healthcare sector.They emphasize the need for meticulous scrutiny of the ethical and epistemological implications that arise from the use of synthetic data or "digital simulacra" (including digital twins, virtual patients, or in silico modeling).They emphasize the growing adoption of synthetic data and a "data-first" approach (whereby data and models can identify useful patterns without context, preconceived notions, or specific factors) and potential biases and conceal inequalities in the design process.This shift of focus from real to simulated patients indeed raises possible concerns.

Source: The American Journal of Bioethics

DOI: 10.1080/15265161.2023.2237436

Authors: Jean-Christophe Bélisle-Pipon, Vardit Ravitsky, Bridge2AI-Voice Consortium, Yael Bensoussan

Institutions: Simon Fraser University, Harvard University, Université de Montréal, University of South Florida

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

Open Access status: hybrid

Funders: Common Fund for Commodities, National Institutes of Health

Awards: Bridge2AI: Cell Maps for AI (CM4AI) Data Generation Project, G4403456761, Bridge2AI: Voice as a Biomarker of Health - Building an ethically sourced, bioaccoustic database to understand disease like never before