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Article . 2020 . Peer-reviewed
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Learning to deal with dual use

Authors: Palmer, Megan J.;

Learning to deal with dual use

Abstract

Biological research is profoundly valuable but can carry profound risks. The coronavirus outbreak reminds us of our vulnerability to biological threats and that research on pathogens is vital to threat mitigation. But such research can lead to catastrophic safety and security incidents. A global proliferation of tools and capabilities, driven by economic and national security interests, is also generating risks that fall outside current governance frameworks. We must learn to manage risks as quickly as we learn to manipulate life, but it remains unclear how well we are doing. One opportunity to learn is found in a new charge to the U.S. National Science Advisory Board for Biosecurity (NSABB), which reconvened in January after a 2-year hiatus, to assess the effectiveness of U.S. dual-use research oversight policies. To meet the charge and suggest improvements, the NSABB must address a neglected need for an evidence base for adaptive risk management. Building this evidence base will require revisiting success criteria, creating data infrastructures, and fostering adaptive policies and testbeds.

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Keywords

Risk Management, Biomedical Research, Multidisciplinary, Data Collection, Health Policy, Pneumonia, Viral, Biomedical Technology, COVID-19, Communicable Diseases, Emerging, Security Measures, United States, Humans, Coronavirus Infections

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    14
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Top 10%
Top 10%
bronze