A key challenge for modern genomic research and its potential applications is to understand and ultimately predict how genetic variation between individuals determines complex traits (including predispositions for common diseases). While genome studies have been able to correlate a myriad of genetic variants with such traits, causal relationships are often elusive and the molecular mechanisms by which they determine such traits have been poorly or not at all elucidated. Many hopes for a rapid understanding of how genes control organismal development and traits as well as for applications such as targeted therapies have thus not materialized.
The project aims to analyze the potential of the convergence of artificial intelligence (in particular deep-learning systems) with technological developments in human genomics and genome editing to solve this challenge. Furthermore, the project strives to identify potential social and political implications of the converging developments.
The analysis of the potential knowledge and applications arising from the convergence of artificial intelligence with technological developments in human genomics and genome editing, and of the innovation system that drives and shapes them, will be based on an interdisciplinary, sober, and evidence-based approach. The results will be used to identify realistic applications in the short- to mid-term as well as relevant ethical, social, and political issues linked to them. Based on the analysis of the opportunities and challenges identified, we will delineate and examine policy implications as well as governance options for the responsible development of these converging technologies.