Understanding Genomics Risks: An Integrated Scenario and Analytic Approach

The Hybrid Vigor Institute, San Francisco CA

Investigators

Abstract

Often a decision maker's first exposure to an innovative technology is a story -- from either a critic or a proponent -- of how the technology will develop. A critic's narrative focuses on what might go wrong if it fails; a proponent's envisions the benefits it will bring. While stories may be a weak form of evidence, they can be useful in the decision-making process, and some of their most disciplined use is found in scenario planning. But the schism between decision analysts and scenarists is a long-standing and historic one, and today there is no credible methodology that can incorporate the subjective, qualitative input provided by the narrative structures of scenarios into a traditional analytic framework -- even though there is a clear need for decision makers to be able to anticipate potential consequences, both scientific and social, in the types of highly fluid and ambiguous circumstances that nascent sciences such as genomics present. The goal of this project is to integrate scenarios and analytical approaches in order to more effectively assess the risks and benefits of genetic interventions and genomic technologies. We begin by screening for problems whose uncertainties seem to require scenario-like thinking -- where there is no historical record that can confidently be projected forward, and no formal analysis that has resolved concerns satisfactorily. (One project member defines these as "things we don't know we don't know, or about which we don't understand what we don't understand.") In these domains, we seek scenarios that have been advanced by some respected agency, organization, process or individual as a plausible representation of a technology's risks and benefits. We then will create a formal analytic model of each domain, based on scenario content and analysis by our domain experts. If successful, the products of this study will be the rudiments of a computable model for problems that previously were impenetrable by such traditional analytic means, as well as a framework for integrating analytic and scenario-based thinking about the risks and benefits produced by complex systems. We believe this new methodology, which will be capable of reflecting the needs and resources of diverse stakeholders, will also be applicable to other complex problems that involve uncertainties as fundamental as those in genomics, such as those posed by nanotechnology.