Ethical, Legal, and Social Implications of Functional Genomics Data Generation and Downstream AI Uses: An NIH Bridge2AI Initiative Qualitative Study
Year: 2025
Type: report
Abstract: The NIH Bridge2AI (B2AI) program aims to produce AI-ready datasets that adhere to the Findable, Accessible, Interoperable, Reproducible (FAIR) principles and integrate ethical considerations in collecting and preparing the data for computation.1 The program adopts a highly multidisciplinary approach, recruiting experts in biology, standards, computer science, ethics, and team science.One data generation project within this larger program is the Functional Genomics Grand Challenge, Cell Maps for AI (CM4AI), which generates multimodal genomic and proteomic data for integration into large-scale maps of cell structure and function for use in downstream AI/ML systems. 2 For example, these data can enable development of "visible" AI/ML models that allow for the interpretable translation of genetic inputs (e.g., mutations) into phenotypic outputs, such as drug response or disease state, via the underlying molecular pathways.
Authors: Danielle Pacia, Ian Stevens, Vardit Ravitsky, Jillian A. Parker, Trey Ideker, Timothy Clark, Jean-Christophe Bélisle-Pipon
Language: English
Topic: Ethics in Clinical Research
Field: Medicine
Domain: Health Sciences
Open Access status: gold
OpenAlex ID: W4408099282