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About this paper
Trond Arne Undheim
Researchers from Stanford University conducted a comprehensive literature review on AI-enabled synthetic biology, identifying the emergent challenges for its governance and proposing an adaptive multi-level, multi-type framework to manage its risks and opportunities. The work conceptualizes the continuous need for adaptive governance as a "whack-a-mole" challenge, highlighting the inadequacy of static regulatory approaches for this rapidly evolving field.
Key insights
- Effective governance for AI-enabled synthetic biology requires an adaptive, interactive "whack-a-mole" approach rather than static command-and-control regulations.
- Governance must be multi-level (global to individual) and multi-type (precautionary, stewardship, bottom-up, laissez-faire) to address the complex and distributed nature of risks.
- Significant terminological confusion and transdisciplinary barriers currently hinder the growth and effective governance of the bioeconomy at the intersection of AI and synthetic biology.
Summary by alphaXiv.
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