Poster ID
P-52
Poster Title
GA4GH Artificial Intelligence Work Stream (AIWS)
Authors
AIWS Co-leads: Marc Fiume, Susheel Varma
Work Stream Manager: Reggan Thomas
Work Stream Manager: Reggan Thomas
Abstract
Advances open standards and governance for AI-driven genomic discovery, analysis, and model training.
Artificial intelligence (AI) is fundamentally expanding the frontier of genomics and health research: from foundation models that extract novel biological signals from large-scale datasets, to agentic systems capable of autonomous hypothesis generation and testing. This cross-cutting work stream convenes the GA4GH community to coordinate technical, ethical, legal, and security principles for AI in genomics. We will address how AI systems discover, access, and analyse sensitive biomedical data, how authorisation and authentication frameworks must evolve, and how model training can proceed responsibly across federated environments. By working across all GA4GH Work Streams, we aim to ensure AI accelerates rigorous, reproducible, and equitable genomic science globally.
Artificial intelligence (AI) is fundamentally expanding the frontier of genomics and health research: from foundation models that extract novel biological signals from large-scale datasets, to agentic systems capable of autonomous hypothesis generation and testing. This cross-cutting work stream convenes the GA4GH community to coordinate technical, ethical, legal, and security principles for AI in genomics. We will address how AI systems discover, access, and analyse sensitive biomedical data, how authorisation and authentication frameworks must evolve, and how model training can proceed responsibly across federated environments. By working across all GA4GH Work Streams, we aim to ensure AI accelerates rigorous, reproducible, and equitable genomic science globally.
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